Multicast Scheduling in SDN WISE to Support Mobile Nodes in Industrial Wireless Sensor Networks

Abstract

The growing use of mobile nodes in manufacturing environments is increasing the Quality of Service (QoS) requirements of the communications infrastructures that support them, as is the case with Industrial Wireless Sensor Networks (IWSN). Managing networks using Software Defined Networks (SDN) addresses the challenge of handling multiple sources in a satisfactory manner. The global vision of the topology that the SDN controller has allows a logical segmentation of the network, through the allocation of dedicated resources for each information flow, thus ensuring independent service levels and complete isolation. Mobile nodes produce constant changes in topology, which lead to instability for routing protocols. Traditional routing solutions with protocols such as Routing Protocol for Low-Power and Lossy Networks (RPL) require additional time to make the parent node change. This paper proposes Mobile Multicast Forwarding with Software Defined Network (MMF-SDN), an approach using Software Defined Networking solution for WIreless SEnsor Network (SDN WISE) protocol that exploits the advantages of SDN and Time Slotted Channel Hopping (TSCH) synchronism. The mobile nodes are managed as multicast sources, through a cumulative allocation of resources from the controller. This allows reception states to be synchronized at the parent nodes to provide network stability, avoiding subsequent recalculations in the routing protocol. Parent node changes are transparent and immediate. This proposal improves on other SDN based solutions, reducing energy consumption in reception by up to 50%, 70% end-to-end delay and improving scalability with a 30% reduction in slotframe occupancy.

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Date of publication xxxx 00, 0000, date of current version xxxx 00, 0000.
Digital Object Identifier 10.1109/ACCESS.2017.DOI
Multicast Scheduling in SDN WISE to
Support Mobile Nodes in Industrial
Wireless Sensor Networks.
FEDERICO OROZCO-SANTOS1, VÍCTOR SEMPERE-PAYÁ1,2, (Member, IEEE), JAVIER
SILVESTRE-BLANES1,3, (Member, IEEE) and TERESA ALBERO-ALBERO.1,3
1Instituto Tecnológico de Informática (ITI), 46022 Valencia, Spain
2Departamento de Comunicaciones (DCOM), Universitat Politècnica de València (UPV), 46022 Valencia, Spain
3Departamento de informática de Sistemas y Computadores (DISCA), Universitat Politècnica de València (UPV), 03801 Alcoy, Spain
Corresponding author: Federico Orozco-Santos (e-mail: forozco@iti.es).
This work has been supported by the MCyU (Spanish Ministry of Science and Universities) under the project ATLAS
(PGC2018-094151-B-I00), which is partially funded by AEI, FEDER and EU and has been possible thanks to the collaboration of the
Instituto Tecnológico de Informática (ITI) of Valencia.
ABSTRACT The growing use of mobile nodes in manufacturing environments is increasing the Quality
of Service (QoS) requirements of the communications infrastructures that support them, as is the case
with Industrial Wireless Sensor Networks (IWSN). Managing networks using Software Defined Networks
(SDN) addresses the challenge of handling multiple sources in a satisfactory manner. The global vision
of the topology that the SDN controller has allows a logical segmentation of the network, through the
allocation of dedicated resources for each information flow, thus ensuring independent service levels and
complete isolation. Mobile nodes produce constant changes in topology, which lead to instability for routing
protocols. Traditional routing solutions with protocols such as Routing Protocol for Low-Power and Lossy
Networks (RPL) require additional time to make the parent node change. This paper proposes Mobile
Multicast Forwarding with Software Defined Network (MMF-SDN), an approach using Software Defined
Networking solution for WIreless SEnsor Network (SDN WISE) protocol that exploits the advantages of
SDN and Time Slotted Channel Hopping (TSCH) synchronism. The mobile nodes are managed as multicast
sources, through a cumulative allocation of resources from the controller. This allows reception states to be
synchronized at the parent nodes to provide network stability, avoiding subsequent recalculations in the
routing protocol. Parent node changes are transparent and immediate. This proposal improves on other
SDN based solutions, reducing energy consumption in reception by up to 50%, 70% end-to-end delay and
improving scalability with a 30% reduction in slotframe occupancy.
INDEX TERMS IWSN, Mobility, Multicast, QoS, SDN, TSCH.
I. INTRODUCTION
Nowadays, the industry sector needs to optimize processes
and adapt quickly to technological changes. This has ac-
celerated the evolution towards smart factories [1]. These
incorporate massive measurement elements to simplify the
integration of multiple variables in production lines. This
transformation requires interconnectivity between all rele-
vant systems in order to make decisions based on large
volumes of information. Therefore, a range of elements must
be integrated, which, combined with the dynamism of pro-
duction environments generates the need to provide support
for mobile elements, such as Automated Guided Vehicles
(AGV) that are widely used in logistics tasks.
Industrial Wireless Sensor Networks (IWSN) have a major
role in this transformation, enabling fast, simple and robust
deployment to meet the requirements of industrial environ-
ments [2]. The inclusion of mobile nodes has been exten-
sively researched in Mobile Ad-Hoc Networks (MANETSs),
Flying Ad-hoc Networks (FANETS) and Vehicular Ad-hoc
Networks (VANETS) [3]. However, IWSNs must guarantee
strict QoS requirements to obtain the highest possible de-
terminism. A difficult objective to achieve, considering the
constant changes in the topology produced by the use of mo-
bile nodes, which directly affect network performance. The
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F. Orozco-Santos et al.: Multicast Scheduling in SDN WISE to Support Mobile Nodes in Industrial Wireless Sensor Networks
evolution towards new paradigms such as Software-Defined
Network (SDN) [4] is becoming a better option to address the
complexity of challenges in IWSN. These accept an increase
in control traffic in exchange for additional advantages, such
as: a reduction in the complexity of the processes at the nodes
and a global view of the network elements. An example of
this is the use of the Time Slotted Channel Hopping (TSCH)
protocol for deterministic medium access control and SDN to
integrate the routing process and flow descriptor for enhance
de QoS. This is demonstrated in [5], where it is possible
to guarantee different QoS parameters for different types of
flow dynamically and with low complexity.
This work proposes Mobile Multicast Fordwarding SDN
(MMF-SDN) an SDN-based alternative that allows mobile
nodes to improve determinism and guarantee QoS parameters
with the same level of reliability as fixed nodes. It is based
on the use of the global knowledge provided by SDN and
the synchronization obtained with TSCH, to implement a
centralized TSCH scheduler that performs a cumulative mul-
ticast resource allocation. This consists of centrally assigning
a transmission cell that may have multiple receivers for each
mobile node. These cells will be added to each of the parent
nodes as they are discovered, and will remain active until they
are removed by the controller. Therefore, with each resource
allocation the connectivity of the mobile node is increased
without increasing transmissions. This allocation will elim-
inate the problem of high signalling, because resources are
allocated only the first time a parent node is added. In this
multicast approach, the use of a single input cell for each
mobile node and the reduction of the bandwidth required for
control traffic, allows for more compact slotframes thereby
increasing the maximum number of nodes.
The rest of the paper is organized as follows. Section 2
briefly introduces the TSCH protocol, SDN and the basics
of the Software Defined Networking solution for WIreless
SEnsor Network (SDN WISE). Moreover, there is a brief
literature review highlighting the current approach to sup-
porting mobile nodes using SDN that is Forwarding and
Time-Slotted channel hopping scheduling over SDN (FTS-
SDN). Section 3 presents the proposed methodology, Mobile
Multicast Forwarding SDN (MMF-SDN) and the differences
with FTS-SDN. Section 4 contains the description of the
scenarios used in the tests as well as the results. Conclusions
and future work are shown in Section 5.
II. BACKGROUND AND LITERATURE REVIEW
In this section, the fundamental aspects of Wireless Sensor
Networks (WSN), their evolution towards Software Defined
Networks, and how the implementation of SDN WISE pro-
vides mechanisms that allow the network to adapt to the
constant changes in the topology produced by a mobile node
are discussed.
A. BACKGROUND
WSNs are composed of multiple nodes in charge of collect-
ing information from the environment and sending it to a
common point (Sink), which is responsible for connecting
the nodes with the point where the information is processed.
Communications are carried out over a shared medium,
where a medium access control protocol, such as Carrier
Sense Multiple Access (CSMA), must be used to limit colli-
sions. Wireless links provide great flexibility and scalability,
allowing WSNs to be easily adapted to any scenario and facil-
itating rapid incorporation in industrial scenarios. However,
to achieve the levels of reliability required for industrial-level
applications, more robust nodes and protocols are needed.
For this reason, the IEEE 802.15.4e standard incorporates
medium access protocols to increase determinism in commu-
nications [6]. These are Low Latency Deterministic Network
(LLDN), Deterministic and Synchronous Multi-channel Ex-
tension (DSME) and TSCH. In DSME and TSCH, the perfor-
mance is adapted to industrial requirements by offering high
interference tolerance and deterministic behaviour. However,
the slotframe structure in TSCH is more flexible, as it is
possible to add or remove a single timeslot [7].
1) Time Slotted Channel Hopping
The TSCH medium access control protocol, defined in the
IEEE 802.15.4e standard, is considered a suitable solution
for providing real-time multi-hop transmissions in industrial
environments [8]. TSCH offers guarantees in terms of latency
and data delivery in IWSNs since it allows nodes to have
a guaranteed space for sending their packets. To do this, it
divides the time into a fixed number of timeslots that are
grouped into slotframes. The behavior of the slotframes is
cyclic, which means that when the last timeslot ends, the
slotframe starts again with the first timeslot.
The most common duration of each timeslot is 10 ms,
enough time to be able to transmit a frame of the maximum
size (127 Bytes), wait for the Acknowledgement (ACK) from
the receiver, and process the packet. The frequency division
is done with the assignment of a channel offset, which is
used to determine the physical channel, therefore a timeslot
and a channel offset must be defined for each transmission.
The combination of these two parameters is a cell, which
can be shared or dedicated. In the case of shared, any of the
nodes can transmit if they have packets to send, otherwise
the node goes to receiving mode. Therefore, in the shared
slot the CSMA scheme is followed with backoff exponent to
reduce collisions. On the other hand, if it is dedicated, a uni-
directional link is established between two nodes and only
the source node can transmit during the timeslot and in the
specific offset channel. The TSCH scheduling provides the
action that the node will perform in each timeslot. The node
will be able to receive, transmit, or turn off the radio. Time
division requires that all nodes are correctly synchronized
in order to ensure that the transmission and reception time
slots coincide. This is achieved with the Enhanced Beacon
(EB) packet exchange, which includes information about
the Absolute Sequence Number (ASN) that the nodes take
as a time reference and determines the current timeslot,
also allows the clock drifts to be compensated. The ASN
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F. Orozco-Santos et al.: Multicast Scheduling in SDN WISE to Support Mobile Nodes in Industrial Wireless Sensor Networks
information is used with Channel offset to generate a rotation
of the physical channels in each slotframe using (1). That
helps reduce the points of interference and path fading, thus
increasing reliability. The problem here is that a large number
of channels (Nch) have a longer synchronization time [9].
frequency =F{(AS N +Channeloff set)mod Nch}(1)
To allocate each of the cells in the nodes, there must be
a scheduling process to synchronize the transmission and
reception states. However, the IEEE 802.15.4e standard does
not include any specification on how to do this. For this
reason, there are different types of TSCH schedulers, that can
be classified as: Distributed schedulers such as Decentralized
Traffic Aware Scheduling (DeTAS) [10], and Wave [11];
others are centralized, such as Traffic Aware Scheduling
Algorithm (TASA) [12] and Adaptive MUltihop Scheduling
(AMUS) [13]; and autonomous scheduling algorithms such
as Orchestra [14], as well as some variants of these such as
Escalator [15] and Autonomous Link-based Cell scheduling
(ALICE) [16].
2) Software Defined Networking
The SDN paradigm [17] arose in data centres, where a large
amount of resources needed to be managed and optimized. It
consists of managing the networks by separating the control
plane and the data plane. The control plane is fully software-
controlled by a centralized agent known as a controller. It
is in charge of defining the forwarding rules based on a
total topological knowledge of the network and the policies
established for each of the flows. The data plane is composed
of the physical equipment, operating in plug and play mode.
This equipment receives these rules and stores them as flow
tables. They only need to search within this table and execute
the actions sent by the controller. This approach makes the
network programmable since the controller can modify the
flow tables of each device.
The flexibility achieved by separating the data plane and
the control plane overcomes the limitations of traditional
networks [18]. This is because it provides a global view of
the network, optimizing its use and simplifying the provision
of resources. With SDN it is possible to dynamically manage,
configure and optimize network resources through automated
programs or functions that are integrated into the controller.
For this reason, several studies have been conducted on the
advantages of SDN, especially in QoS where it is possible
to exploit the dynamism and network management with a
higher level of detail. An example of this is [19] where
the controller obtains the best route for each type of traffic
according to the QoS requirements using parameters such as:
Delay, Jitter, Throughput and Loss.
Therefore, in addition to the control plane and the data
plane, there is the application plane that groups together
all the automated functions that modify the behavior of the
network. The application plane is located above the control
plane, as shown in Fig. 1, which allows the global knowledge
of the controller to be reused for specific tasks. The objective
of this is to simplify the development of applications, since
it is not necessary to go into details about the operation
of the network infrastructure, it will be the controller that
communicates with each of the network elements. Hence, the
SDN controller handles a great diversity of protocols, which
are divided into Northbound (NB) and Southbound (SB). The
NB protocols establish communication between the applica-
tion plane and the controller. On the other hand, SB protocols
are used to communicate with the network infrastructure, the
most widespread being OpenFlow developed by the Open
Networking Foundation (ONF) [20].
The flexibility, simplicity of deployment and management
offered by SDN has driven its expansion to all points of the
wired network. According to Cisco® [21], 64% of organiza-
tions had SDN solutions in their data centres, 58% as WAN
technology (SD-WAN) and 40% in access networks. Cur-
rently, all infrastructure equipment manufacturers offer SDN
equipment and controllers. Hence, they are also looking to
incorporate the advantages of SDN into IWSNs, particularly
flexibility. It is possible to generate any type of controller-
oriented application, and new possibilities are opened up to
address the wide range of challenges presented by IWSNs.
Improvements can be added with the implementation of an
SDN such as energy efficiency, routing, mobility, security,
reliability and QoS [22].
3) SDN WISE Protocol
The application of the SDN approach in IWSNs is not
straightforward, due to the large differences in hardware
resources of the equipment that make up the data plane.
SDN WISE is a protocol that extends the SDN paradigm to
WSNs [23]. It is based on the OpenFlow protocol, a protocol
designed for wired networks. This has involved making the
necessary adaptations, as there are many challenges when
it is deployed in wireless environments [24]. To meet these
challenges, a profound change in the OpenFlow protocol was
required, such as being able to make decisions according to
local states without controller intervention (Statefull) or be-
ing able to perform packet aggregation to reduce congestion.
Due to the complexity of the changes, protocols have been
created that allow OpenFlow concepts to operate within the
restrictions of wireless environments such as SDN WISE.
These changes are intended to reduce control traffic and
conserve network bandwidth. Due to the wireless nature of
WSNs, there is no physical isolation between transmissions.
By using the CSMA medium access method, control traffic
has a direct impact on network performance. However, the
versatility, flexibility, and ease of management provided by
an SDN deployment [23], are key elements within WSNs.
In this way, traffic flows in the network can be scheduled
and modified by the controller, simply by modifying the
flow table at each node. The SDN WISE framework is
mainly composed of the following sub-layers: Application,
In-Network Packet Processing (INPP), Topology Discovery
(TD), Forwarding (FWD), Medium Access Control (MAC)
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F. Orozco-Santos et al.: Multicast Scheduling in SDN WISE to Support Mobile Nodes in Industrial Wireless Sensor Networks
and the physical layer that will be 802.15.4. These layers are
shown in Fig. 1 where the layers in the node are detailed,
using the TSCH protocol in the MAC layer.
SDN CONTROLLER
SWITCH SDN
S
N
N
N
N
M
N
TRAFFIC
SOURCES
Control Plane
(Control Layer)
Data Plane
(Infrastructure Layer)
TSCH
Scheduler
Routing
Process
Traffic
Manager
Mobile
Node
Manager
NODE
M
Management Plane
(Application layer)
TSCH
802.15.4
Application
INPP
TD
FWD
Northbound
Southbound
SDN Wise
OpenFLow
API
API
API
API
FIGURE 1. SDN general architecture and SDN WISE node layering
The three sub-layers where the main operation of SDN
WISE is concentrated are described below:
1) In-Network Packet Processing (INPP): Is a layer used
for data aggregation. To minimize network congestion,
small packets with the same destination can be com-
bined. However, it should be noted that the maximum
size of an SDN WISE packet is 116 Bytes and cannot
be exceeded.
2) Topology Discovery (TD): This layer is responsible
for discovering the adjacent nodes and informing the
controller of its neighbours. All nodes generate bea-
con packets, which are sent periodically in broadcast
mode. This packet contains the identity of the node
that generated it, the battery level and the current
distance to the sink, which is updated according to the
beacons received. With the beacon packets, the node
informs the other nodes within its coverage range of its
presence. In this way, each node discovers its adjacent
nodes. When a node receives this type of packet, it
adds the sender to its neighbour table, along with its
current Received Signal Strength Indicator (RSSI) and
battery level. If that node is already in its table, it only
updates the RSSI value and the battery level. Informa-
tion from adjacent nodes is sent via a report packet to
the controller. Each node sends this packet periodically
every two beacon periods. The default beacon period
setting is one second. The packet contains the number
of neighbours and information about each one, such as
the node ID and RSSI. Thanks to the reception of report
packets from each node, the controller builds the global
topology of the network.
3) Forwarding (FWD): Processes outgoing packets ac-
cording to the WISE flow table. This table stores the
flow rules sent by the controller. It is divided into
three sections: matching rule, action and statistics. The
matching rules contain the fields to be compared in
the packets and the matching value. The packet can be
inspected in any of its bytes, not only the header as
is the case with OpenFlow. Up to three matching rules
can be added for each flow rule. When the packet meets
the rules, the action is executed. This action can be of
five types: Drop, Forward, Sleep, Modify or INNP and
is counted in the statistics.
These layers are specifically designed to allow the SDN
controller to modify its behavior according to the network
requirements. SDN WISE includes a simple controller, which
contains all the network information and the Southbound
protocols to communicate with the nodes. To expand the pos-
sibilities of integration with wired networks, the Southbound
protocols can be added to general purpose controllers such
as the ONOS controller which, due to its highly modular
structure, supports the development and integration of spe-
cific protocols and applications [23].
In [5] SDN WISE TSCH is proposed, which extends the
performance of SDN WISE, to guarantee industrial level
requirements with a highly deterministic system. To achieve
this, in the medium access control layer, the CSMA protocol
was replaced by the TSCH protocol. In addition, the Open-
Path packet, which installed the routing rules at each node,
was modified to integrate TSCH scheduling, resulting in the
OpenPathTSCH packet, which allows rapid configuration of
the network by flows, with a minimal increase in control traf-
fic. The packet generation periods are synchronized accord-
ing to the schedule received. To exploit this, a system was
developed in the controller that integrates three application
layer processes: the Traffic Manager, Routing process and
the TSCH Scheduler shown in Fig. 1. This results in a logical
separation of data flows, with a specific allocation of physical
resources (cells) for each type of traffic, called slicing. This
network slicing makes it possible to differentiate flows and
guarantee different qualities of service. The details of how
slicing works and the advantages it brings in terms of quality
of service are explained in depth in [5].
B. LITERATURE REVIEW
The challenge of mobile nodes in IWSN has been addressed
in multiple works, where the effect of mobile nodes in RPL
with Orchestra [25] and TSCH minimal [26] has been evalu-
ated. The results obtained show how the RPL control traffic
increases, due to the disconnections of the mobile nodes.
Each time a mobile node disconnects, it needs to initiate a
discovery process to obtain the new parent node, which takes
a convergence time. Moreover, in this case the nodes depend
on the timers to know that they are disconnected and start a
new discovery process. This also increases packet loss and
latency.
An attempt to overcome this difficulty was made in [27]
with the use of timers that allow the parent nodes that leave
the coverage area to be quickly updated. Also, different
techniques have been tested to optimize the routing process,
such as segmenting the network into circular areas defined
by the Directed Acyclic Graph (DAG) roots [28] or using
Kalman filters to improve RPL decisions with position pre-
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F. Orozco-Santos et al.: Multicast Scheduling in SDN WISE to Support Mobile Nodes in Industrial Wireless Sensor Networks
dictions [29]. In addition, distributed scheduling functions
have been improved, including prediction of position, queue
size and packet generation rate to negotiate the number of
cells required [30]. This negotiation process has limitations
in mobility environments, when a parent change occurs the
node needs time to discover the new neighbours and start
the negotiation process. This can be reduced by reserving
dedicated cells for negotiation and adding multiple control
packets to detect topology changes [31]. However, although
they represent an improvement over traditional RPL, they are
far from offering the same determinism as fixed nodes.
These previous studies show how the support of mobile
nodes considerably increases the complexity of decisions in
the nodes and the amount of signalling packets. Therefore,
the implementation of Software Defined Networks (SDN) in
IWSNs is becoming a better option, as it assumes an increase
in control traffic in exchange for additional advantages, such
as: reducing the complexity of processes at the nodes and
a global view of the network elements. The combination of
SDN and Time Slotted Channel Hopping (TSCH) increases
the reliability, determinism and flexibility of the network.
This is demonstrated in [5], where it is possible to guar-
antee different QoS parameters for different types of flow
dynamically and with low complexity compared to RPL with
Orchestra.
To support nodes that are moving using SDN over TSCH
[32] propose FTS-SDN. The objective is to increase the
frequency and reliability in the exchange of control packets.
In order to decrease the topology update time, the controller
will send the new routing rules with each parent node change.
To adapt to the changes, the controller must update the
topology each time the mobile node changes its parent node.
In this case, the nodes must report their existence through
beacon messages that are broadcast to be received by all
nodes in the coverage range. In addition, they must send the
information of the received beacons to the controller. This is
done by sending report packets, which include all the nodes
from which beacon messages have been received. Therefore,
the greater the number of control packets, the more updated
the topology will be, and the faster it will adapt to changes
in the mobile node. In fact, the speed at which the mobile
node moves is a parameter that can affect this approach. Each
time the controller updates the topology, it must generate
the routes and inform the nodes of the new route with
an OpenPath packet. In FTS-SDN the TSCH scheduling is
fixed and pre-configured, and is performed according to the
following rules:
•Minimum 1 uplink cell for each node.
•Minimum 1 downlink cell for each node.
•1 broadcast cell for each node (Shared Slot).
This solution is highly dependent on control traffic. Higher
frequency and reliability of this traffic increases the perfor-
mance of the protocol. Therefore, in order to guarantee the
forwarding of control traffic, a particular case of shared slots
is used, where a transmission shared slot is assigned exclu-
sively to each node, eliminating the probability of collision.
This means that in each shared slot only one node will be
transmitting and all the others will be receiving. In these
timeslots it is not possible to plan parallel communications.
The result is a significant increase in slotframe length and
occupancy, which is reflected in an increase in energy con-
sumption, a reduction in data bandwidth and more complex
network management due to the need for longer slotframes.
FIGURE 2. Topology and slotframe used in [32].
For example, Fig. 2 shows the first scenario used in [32],
a simple topology with 5 nodes (Sink or S, A, B, C and
the mobile M). The trajectory of M is circular (blue) and
the only node that can communicate with the Sink is B.
The scheduling [32] consists of a slotframe composed of 13
timeslots and 4 channels. The controller has assigned only
the route M->B->S, according to the current coverage range.
In this scheduling shown in Fig. 2, 5 shared slots can be
seen, 1 for each node (red). In addition, multiple inputs from
the Mobile node (M) at different points of the slotframe (6,
9, 12; green) and a single arrival timeslot at the Sink node
(11; yellow). Therefore, this solution uses 5 shared slots in a
slotframe of 13. The end-to-end delay varies depending on
the input node. It will be 150 ms, 120 ms and 50 ms for
inputs A, B and C respectively. These differences are due to
the distribution of the slots in the slotframe made in [32],
which for inputs from nodes A and B need to wait until the
next slotframe to complete the transmission.
III. PROPOSED METHODOLOGY: MOBILE MULTICAST
FORWARDING SDN
This paper proposes Mobile Multicast Forwarding SDN
(MMF-SDN), which exploits the advantages of SDN WISE
and TSCH, to improve support for mobile nodes and bring
them closer to determinism levels that are similar to those
of fixed nodes. MMF-SDN allows a parent node change to
be performed instantaneously and transparently. Because of
this, it has a low dependency on control traffic, so there are
no current limitations due to parent switching or saturation
with control traffic.
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F. Orozco-Santos et al.: Multicast Scheduling in SDN WISE to Support Mobile Nodes in Industrial Wireless Sensor Networks
Due to the global knowledge of the network in SDN,
the extensive resources available at the controller and the
synchronization obtained by the use of the TSCH MAC layer,
mobile nodes can have a high level of determinism. MMF-
SDN involves managing the mobile nodes as a multicast
source, meaning that the mobile node will have multiple
receivers for the same packet. These receiving states for
the mobile node will be synchronized in the same TSCH
scheduling cell for all its parent nodes. Therefore, factors
affecting the topology such as the position and velocity of the
mobile node will be less relevant. Thus, it will be possible
to increase the beacon and report periods, which reduces
control traffic and simplifies the management of the mobile
nodes. To achieve this, the report packets coming from a
mobile node must be differentiated from the report packets
from the fixed nodes. Thus, when the controller receives a
report from a mobile node it will update the topology, but
will not make changes to the routing or TSCH scheduling.
Therefore, the management of these processes is carried out
by implementing a new application Mobile Node Manager
which, being located in the application layer, has direct
communication with the SDN controller as shown in Fig.
1. This application will be in charge of storing the different
parent nodes of a mobile, determining which nodes should be
multicast receivers and requesting that the controller install
the necessary resources (Routing + TSCH) for these nodes.
The resources assigned by request of Mobile Node Manager
are accumulated. This means that, when assigning resources
to the new parent, the resources assigned to the previous
parents are maintained. One of the installed resources is the
multicast receiver cell, which is the same in all the parent
nodes of a mobile node, so that the number of multicast
receivers increases with each resource allocation. With this
approach, it is possible to have all the inputs of the mobile
node scheduled, without generating an overload of frequent
updates and configurations. Therefore, it is possible to have
stable behaviour with mobile nodes, after an initial discovery
phase. This is the time it takes for the controller to know
all the entries of a mobile node and to allocate the routing
and TSCH scheduling resources. The duration of this phase
depends on the length, trajectory and movement speed of the
mobile node. In a defined industrial environment, it corre-
sponds to the first displacement of the mobile node through
the complete trajectory.
Since the topology construction in SDN WISE is done
through the information arriving from the nodes, the update
rate also depends on the capacity and reliability of the net-
work to send the control traffic. Since in FTS-SDN the route
corresponding to each change in the topology is sent, it is
necessary to ensure high reliability in the control packets.
For this reason, MMF-SDN seeks to reduce the dependency
on control traffic through an accumulated multicast resource
allocation.
This reduced dependency on control traffic increases ro-
bustness, which allows the frequency of such traffic to be
reduced. Therefore, in MMF-SDN it is possible to use the
default operation of shared slots, where nodes can transmit
in any of the shared slots if they have packets in queue
or, in the opposite case, are in receive state. This makes
it possible to reduce the number of shared slots that are
assigned. However, there is now one medium per contention,
which increases the probability of collision. To reduce the
number of collisions, the number of shared slots allocated
must be optimized, which depends directly on the amount
of control traffic generated, which makes it necessary to
perform an analysis of this traffic.
A. ANALYSIS OF CONTROL TRAFFIC
Control traffic is essential for the operation of an SDN, since
it is used by the controller to build the topology and send
the flow rules to the nodes. In SDN WISE TSCH [5], this
traffic is composed of periodic packets such as beacon and
report, and aperiodic packets which are the configuration
packets (OpenPathTSCH). The total amount of control traffic
depends mainly on the generation period of the beacon and
report packets. With a higher generation frequency, a more
up-to-date network is obtained, allowing it to be more adapt-
able to changes. However, this type of traffic is a considerable
overhead for the network and can affect data flows. There-
fore, measures must be taken to minimize the impact on the
network. In MMF-SDN the measures used are:
•Reduce: Optimize beacon (Bp) and report periods (Rp)
•Limit: Send this type of traffic only through the shared
slots.
•Optimize: Allocate an optimal number of shared slots to
maintain control traffic reliability.
TABLE 1. Notations
Notation Definition Units
Cpk Control packets packets
CBW Control Bandwidth packets
ShS F Shared slots timeslots
SFsz Slotframe size timeslots
HiHops between Sink and node i Hops
T s Timeslot ms
TEvaluation Period s
BpBeacon Period s
RpReport Period s
In Table 1 the notation used is shown. The total amount of
control traffic (Cpk) for SDN WISE TSCH over a period of
time Tseconds is determined by (2), where nis the number
of nodes in the network; Bp and Rp are beacon and report
periods; and Hidistance in hops to the Sink from each node
i. The first term of (2), T
Bp , is the number of beacon packets
generated by a node. These packets are not forwarded by the
nodes, so there is no factor that depends on the distance to
the Sink, unlike the second term, which are the report packets
that must pass through multiple nodes to reach the controller.
Cpk =nT
Bp +
n
X
i=1
T
Rp Hi(2)
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F. Orozco-Santos et al.: Multicast Scheduling in SDN WISE to Support Mobile Nodes in Industrial Wireless Sensor Networks
Because control packets will be sent through the shared
slots, the number of shared slots allocated per slotframe must
be optimized. A low number of shared slots will create a high
collision rate and prevent the controller from updating the
topology. Conversely, a very high number of shared slots will
increase power consumption and reduce the bandwidth avail-
able for data. To calculate the Control Bandwidth (CBW )
(3) is used, where the bandwidth is obtained as a function
of the number of shared slots in the slotframe (ShS F ) and
the slotframe size (SFsz ) in a period of Tseconds, taking
into account the duration of the timeslot T s. The first term
ShSF
SFsz , is the ratio of slotframe occupancy to shared slots.
An increase in the number of shared slots means a higher
occupancy and a greater bandwidth for control. The same
bandwidth can be achieved with different slotframe lengths
while maintaining the occupancy ratio.
CBW =ShSF
SFsz
·T
T s (3)
The optimum number of shared slots is obtained from
(4), a variation of (3) which guarantees the minimum value
of the control bandwidth. By replacing the total number of
control packets obtained in (2) and the slotframe parameters,
a whole number that corresponds to the number of shared
slots is obtained. Fig. 3 represents the amount of control
traffic that can be sent, varying the length of the slotframe
and the number of shared slots assigned.
ShS F =Cpk ·SFsz ·T s
T(4)
FIGURE 3. Effect of occupancy ratio on the amount of control traffic.
B. SCHEDULE ALLOCATION
In MMF-SDN the scheduling is flow-based, meaning that
cells are mapped from source to destination and the result is
sent for each flow through a single OpenPathTSCH packet.
This allows more control over the cells that are assigned, by
being able to assign or delete specific flows, instead of having
to modify the entire schedule of a node. In MMF-SDN,
multicast cells have been included, which contain multiple
receivers in the same cell for the data packets sent by the
mobile node. For this, a global multicast address has been
added to the nodes, which is used by the mobile nodes to
transmit their data packets and by the receivers to receive in
the same cell. Thus, the transmission of mobile nodes is not
made to a specific node and a dedicated queue is guaranteed
for multicast traffic, which increases determinism. Another
difference with respect to TSCH scheduling in FTS-SDN is
the way in which the number of shared slots is allocated. In
MMF-SDN, an optimal number of shared slots is used, which
is obtained according to (4). This reduces the total number
of shared slots, but increases the number of shared slots in
which a node can transmit. This increase is due to the default
operation of the shared slots, where nodes can transmit in any
of them if they have packets in queue. Thus, as each node has
more transmission opportunities, the bandwidth for control
traffic per node increases, even though the overall bandwidth
is reduced. This operation allows the nodes to dynamically
adapt to the traffic needs of the network. For example, the
nodes farther away from the sink will only send their beacon
and report packets. Therefore, they perform fewer transmis-
sions than the nodes closer to the sink, which must forward
the control traffic received from other nodes. The allocation
of dedicated slots can congest the central nodes, unlike the
optimized allocation where the maximum traffic that can
be generated is taken into account and allows each node to
access the amount of resources it requires. For this reason,
the scheduling of the dedicated cells was calculated based
on the scheduler used in [5]. This scheduler uses the routes
calculated by Dijkstra’s algorithm in the routing manager and
allocates the necessary cells for each hop in the path. The
algorithms presented in [5] have a computational complexity
of quadratic order O(n2), where nis the number of nodes.
This has little impact on the proposed MMF-SDN, as we
are dealing with a typical industrial system as defined in
IEC 62264 (ANSI/ISA 95), where the number of nodes is
generally limited between 10 and 30.
The example of the Fig. 2 generates 85 control packets
(Cpk) every 10 seconds, using beacon and report periods of
1 and 2 seconds respectively. With this, the number of shared
slots obtained with (4) is d1.1e, and therefore 2 shared slots
are used for a slotframe length of 13 timeslots.
With the MMF-SDN approach, there are 2 shared slots
instead of 5, as shown in Fig. 4. In addition, in MMF-SDN
the behaviour of the mobile nodes is stabilized after the
initial discovery phase, where the controller knows all the
input nodes used by the mobile node and has the routing and
TSCH resources assigned for all the routes. In this schedule,
there is no variation of the end-to-end delay, this will be the
minimum (30 ms) regardless of the input node. The number
of allocated cells is reduced from 17 to 10 cells (3 shared slots
and 4 dedicated cells) compared to FTS-SDN. Therefore,
the slotframe occupancy goes from 61% to 31%. This 30%
reduction in occupancy is largely (23%) due to the reduction
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F. Orozco-Santos et al.: Multicast Scheduling in SDN WISE to Support Mobile Nodes in Industrial Wireless Sensor Networks
FIGURE 4. Topology and slotframe using MMF-SDN
in shared slots.
The energy consumption can be estimated using the num-
ber of transmitting and receiving states at each node. For the
transmitter nodes, the worst case is used, which corresponds
to the longest route (M->A->B->S). Fig. 5 shows in blue all
cells used to transmit in the FTS-SDN slotframe, Fig. 5 (a)
and for MMF-SDN, Fig. 5 (b). In both cases there are a total
of 11 transmission states per slotframe.
(a) FTS-SDN
(b) MMF-SDN
FIGURE 5. Number of transmission states
In reception, all the scheduled slots are taken into account,
since, unlike transmission, the nodes must listen whenever
it is planned. In addition, in the shared slots, all the nodes
except the transmitting node (n-1) will listen, so each shared
slot will be multiplied by 4. In Fig. 6 in total there are 32
receive states per slotframe for case (a) and 18 for case (b). If
the shared slots are omitted, there would be 12 and 10 receive
states. In this case, a 40% reduction in power consumption in
reception is achieved. Most of this is due to the reduction
in the number of shared slots, since it is a factor that means
additional consumption in all nodes.
(a) FTS-SDN
(b) MMF-SDN
FIGURE 6. Number of reception states
The analysis of control traffic and the use of multicast
cells illustrate that FTS-SDN can be improved in terms of
quality of service (delay, jitter), energy consumption and
scalability (slotframe length and occupancy). These aspects
were not targeted by [32] which instead focused on having a
low packet loss at the mobile node through a very high update
rate. This means allocating a very high number of shared slots
to ensure that all control packets reach the controller. The
authors of FTS-SDN proposed in [32] the use of clustering
methods to overcome this limitation. Thus, the objective of
MMF-SDN is to limit the constant topology updates due to
the movement of the mobile node. In addition, it is intended
to provide the same deterministic behaviour that fixed nodes
have. In MMF-SDN increasing the size of the slotframe does
not lead to an increase in delays, since the repetition of flows
within the slotframe is implemented. Improvements will be
observed in the following aspects:
1) End-to-End delay: Lower and deterministic.
2) Control traffic independent of mobile topology: The
amount of control traffic does not depend on the num-
ber of mobile nodes or their speed, since it is not based
on constant updates.
3) Reduced control traffic: Scheduling and routing
changes are sent by flow with a single packet to all
nodes in the path, instead of a specific schedule for
each node.
4) Simplified scheduling: Since it does not depend on
control traffic, it is not necessary to assign a shared slot
per node.
5) Greater scalability: Due to the reduction in slotframe
length and the ease of modifying and adding slots.
6) Lower energy consumption: Due to a lower number of
shared slots.
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F. Orozco-Santos et al.: Multicast Scheduling in SDN WISE to Support Mobile Nodes in Industrial Wireless Sensor Networks
IV. PERFORMANCE EVALUATION
This section shows the experimental results for three sce-
narios using the COOJA simulator under the Contiki NG
operating system. The radio medium is setting as Multi-path
Ray-tracer (MRM) medium, with the same parameters used
in FTS-SDN n= 2.04 and σ= 6.7. The hardware used
for simulation is a intel core i7 with 16 GB of RAM and the
nodes are modeled as OpenMote nodes. A summary of the
general parameters used in the simulations is shown in Table
2.
The SDN controller used is the SDN WISE controller
connected with the sink through a serial socket. This con-
troller was modified to handle MAC TSCH and include the
Mobile Node Manager, Traffic Manager, Routing process
and the TSCH Scheduler. The first two scenarios are those
used in FTS-SDN [32]. As a more representative proposal
for an industrial environment, a third scenario has been
used and this is shown in Fig. 16. Results are expressed in
terms of power consumption, end-to-end delay and network
overhead. In the experiments, simulations have been carried
out with the values used in [32], sending 500 data packets
from the mobile node to the sink, sending frequencies of one
packet per second and one packet every three seconds. In
all three cases, these parameters are sufficient to observe the
behaviour of these approaches.
TABLE 2. Summary of parameters used in Cooja
Parameter Value
Radio Medium MRM (n= 2.04,σ= 6.7)
Number of Channels 4 Channels
Timeslot (T s) 10 ms
A. SCENARIO 1.
This is the simplest scenario, the topology of which is shown
in Fig. 2 [32]. The mobile node sends a packet to the sink
every second. It moves at different speeds and follows a
circular trajectory of 16 m radius. Node B is located at
the centre of this trajectory, so that it is always within the
coverage area of node M. A summary of the parameters used
is shown in Table 3.
TABLE 3. Parameters used in scenario 1
Parameter Value
Number of Packets 500
Sending frequency 1 packet/s
Speed 1 m/s, 2 m/s, 4 m/s
Nodes 4 fixed and 1 mobile
Beacon Period (Bp) 1 s, 4 s
Report Period (Rp) 2 s, 8 s
The energy consumption depends on the states contained
in the TSCH scheduling. In Fig. 5 and 6 the number of slots
used in transmission and reception for FTS-SDN and MMF-
SDN is shown. Transmissions do not represent an additional
power consumption, since if a node has no data to transmit,
the radio is not turned on. However, on receptions the radio
must be turned on for a minimum of 2.2 ms, the default time
to determine that there is no traffic to receive. When in a
shared slot no node has data to transmit, all nodes will be
in receiving state during this 2.2 ms, which means additional
power consumption. For the worst case, where all nodes
are receiving, the proposed MMF-SDN schedule will have 5
nodes receiving in each shared slot. In the case of FTS-SDN,
4 nodes will be in receiving state, since one of the nodes is
defined in transmission. In total for control traffic a slotframe
will have 10 receiving states for MMF-SDN scheduling and
20 for FTS-SDN scheduling. This means a 50% decrease in
power consumption in reception in the worst case. To verify
this, the simulation of the topology shown in Fig. 2 was
carried out only with control traffic for the two schedules
using Bp= 1 s and Rp= 2 s. The simulation was run
for one hour, time enough time to observe the long-term
network behavior when collisions effects and buffer issues
affect performance. The result is shown in Fig. 7, where the
power consumption at each node is shown according to CPU,
Radio Tx and Radio Rx usage for the same topology. In Fig.
7 (a) for FTS-SDN 5 shared slots are used, the consumption
in this case is about 2.5 mAh for all nodes and most of this
energy is used in reception. In Fig. 7 (b) MMF-SDN uses
2 shared slots, the total consumption is below 1.5 mAh for
all nodes and there is a clear reduction in the energy used for
reception. This reduction is 62%, and is produced when FTS-
SDN has a consumption of 1.66 mAh and MMF-SDN of 0.63
mAh as is shown in Fig. 7 (a) and in Fig. 7 (b) respectively.
There are no considerable differences in the CPU and Radio
Tx values.
FIGURE 7. Energy consumption Scenario 1
The operation of shared slots in FTS-SDN is very specific,
due to the fact that there is only one transmitter node for each
shared slot. This requires an additional step to configure the
corresponding shared slots on each node. With this method,
transmission is assured, unlike MMF-SDN where multiple
nodes can transmit in the same shared slot, which may
cause collisions. Fig. 8 shows the number of control packets
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F. Orozco-Santos et al.: Multicast Scheduling in SDN WISE to Support Mobile Nodes in Industrial Wireless Sensor Networks
sent during one hour of simulation using Bp= 1 s and
Rp= 2 s in the two protocols. The SDN WISE beacon values
are slightly lower in MMF-SDN and the number of report
packets is higher and does not exactly match the number of
ACKs. This is due to collisions in the shared slots, which
affect all control packets. Since the beacon packets are sent
in broadcast, no retransmissions are made, unlike the report
packets which, as they are unicast, are retransmitted when a
collision is detected. For this reason, in MMF-SDN there are
17% more reports than ACKs. In the case of FTS-SDN, the
lost report packets are due to changes in the parent of the
mobile node and correspond to 5% of the report packets.
FIGURE 8. Number of control packets sent during 1 hour of simulation
FIGURE 9. (a) End-to-End delay FTS-SDN and MMF-SDN. (b) Average
energy consumption.
The collisions that occur in the shared slots do not have
a considerable impact on MMF-SDN performance, since the
MMF-SDN does not require an immediate topology update.
This reduced dependency on control packets also allows
reduction in the frequency of beacon and report packets
without affecting performance. Fig. 9 shows the end-to-end
delay when the speed of movement of the mobile node is
1 m/s, and the schedules in Fig. 5 are used. In Fig. 9 (a)
the end-to-end delay produced by the FTS-SDN algorithm is
observed with Bp= 1 s and Rp= 2 s and by the MMF-SDN
algorithm with Bp= 4 s and Rp= 8 s. In this case, the two
protocols have the expected performance according to TSCH
scheduling and a PDR of 100%. However, the optimization of
the TSCH scheduling used in MMF-SDN reduces the average
end-to-end delay by 70%, from 106 ms in FTS-SDN to 30
ms. The beacon and report periods used in MMF-SDN are 4
times higher than those used in FTS-SDN, so that the same
PDR is obtained with a smaller number of control packets.
The energy consumption is plotted in Fig. 9 (b). At
reception the power consumption has been reduced by 50%
compared to that of FTS-SDN, since the number of shared
slots is lower. Nodes will spend more time in reception,
because they must forward a smaller amount of control traf-
fic. Fewer transmissions reduce the processing load, which
requires less CPU consumption. This proves that it is possible
to use a smaller amount of control traffic and that the loss of
this type of packet does not lead to a loss of performance.
Adapting to topology changes produced by a mobile node
is complex, since the speed and trajectory of the node may
change. Therefore, the effect of speed on MMF-SDN and
FTS-SDN performance has been analyzed. A high depen-
dency on control traffic means that a failure can occur at
any time, unlike the cumulative resource allocation, where
stable behaviour is achieved by keeping the routes assigned,
which limits the amount of configurations to be sent by the
controller. Fig. 10 shows the end-to-end delay obtained with
different travel speeds for the mobile node. In Fig. 10 (a) and
(b) the mobile moves at a speed of 1 m/s, and both FTS-
SDN and MMF-SDN adapt to the movement without any
loss. When increasing the speed to 2 m/s, Fig. 10 (c) and
(d), the FTS-SDN protocol has a high performance in the
transmission of the first packets, but after 100 packets it starts
to have losses. This is because the routes start to become out
of date due to the accumulation of queued packets, unlike
MMF-SDN, which has losses in the first parent change and
then remains stable. With a high movement speed, 4 m/s, the
controller does not manage to update the routes fast enough
and in the case of FTS-SDN Fig. 10 (e), constant losses
occur (around 20%). In contrast, with MMF-SDN, Fig. 10 (f)
the configuration of the routes only affects the first packets.
After this, the behaviour is totally stable as no additional
configurations are required, allowing better performance in
permanent regime.
Fig. 11 summarizes the behaviour of the two protocols for
the three travel speeds of the mobile node. In Fig. 11 (a) the
PDR for FTS-SDN remains at 100% for a velocity of 1 m/s.
For travel speeds of 2 m/s and 4 m/s it is 98.6% and 76.6%.
However, the PDR starts to decrease steadily. Because the
controller cannot adapt to rapid changes in the topology, it is
not possible to achieve a stable system. Therefore, the speeds
of 2 m/s and 4 m/s have a negative trend, the higher the speed
the more noticeable this effect. Fig. 11 (b) shows the PDR
for the MMF-SDN protocol, at the end of sending the 500
packets there is a PDR of 100%, 99.8% and 97% respectively.
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F. Orozco-Santos et al.: Multicast Scheduling in SDN WISE to Support Mobile Nodes in Industrial Wireless Sensor Networks
FIGURE 10. MMF-SDN and FTS-SDN comparison at different mobile node speeds.
With the accumulated resource allocation, there are losses
and delays in the initial discovery phase while the controller
configures the inputs, but after this allocation the throughput
remains stable. Therefore, in all cases the trend is positive.
FIGURE 11. PDR for both protocols with different speeds of the mobile node.
B. SCENARIO 2.
This section shows the results after assessing the scenario
of Fig. 12 [32]. It is composed of 43 nodes, 3 of which are
mobile (Nodes 41, 42 and 43), and which send packets to the
sink every 3 seconds, as they move with a circular trajectory
at 1 m/s. Unlike scenario 1, where the mobile node had a
fixed distance to one of its parents (B), this scenario has
constant changes of parent node and a larger distance to the
sink (Node 1). Therefore, the impact of control traffic will be
more significant. Table 4 shows the parameters used for this
scenario.
TABLE 4. Parameters used in scenario 2
Parameter Value
Number of Packets 500
Sending frequency 1 packet/3s
Speed 1 m/s
Nodes 40 fixed and 3 mobile
Beacon Period (Bp) 3 s, 5 s
Report Period (Rp) 6 s, 10 s
The effect of the beacon and report periods on the amount
of control traffic is shown in Fig. 13. A topology with n
nodes and a maximum of 4 hops to the sink has been used.
The number of nodes in each hop is distributed in a similar
way to that shown in Fig. 12. The dashed line represents
the bandwidth limit, which is achieved by having all slots
as shared according to (3). Therefore, the closer the control
traffic line is to the bandwidth limit, the higher the occupancy
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FIGURE 12. Topology with 43 nodes, 3 mobile nodes [32]
rate of the slotframe with shared slots and the lower the
capacity of the network to send data flows. The FTS-SDN
solution needs a high update frequency, so the authors use
Bp= 1 s and Rp= 2 s. These parameters correspond to the
line (Blue) that approaches the bandwidth limit the fastest.
The proposed MMF-SDN is based on a cumulative resource
allocation, so it is not necessary to update with such a low
period to determine the current parent of the mobile node.
This allows a reduction the control traffic by using longer
beacon and report periods, where the control traffic is reduced
from 50-80% for a configuration of Bp= 5 s and Rp= 10 s.
This reduction in the amount of control traffic also allows the
network to be more scalable. Therefore, it can be seen that the
limit for the values of Bpand Rpused by FTS-SDN is close
to 40 nodes, this can be extended by reducing the amount of
control traffic, with higher Bpand Rpperiods.
In Fig. 14 the number of shared slots used by FTS-SDN
as a function of the number of nodes are compared with
the optimal number of shared slots used by MMF-SDN for
4 different configurations of Bpand Rp. In all cases, the
amount of shared slots is much lower than the 1 shared
slot per node rule used in FTS-SDN, since using a reduced
number of shared slots allows a reduction in the slotframe
size. For example, for 40 nodes FTS-SDN uses 40 shared
slots and a slotframe of 53 timeslots while MMF-SDN can
use 13 shared slots in a slotframe of 23 timeslots. This means
an increase in bandwidth, since due to the cyclic operation
of the slotframes, the distance between the shared slots will
be smaller. Therefore, in MMF-SDN, schedules with better
utilization of network resources are obtained, even in con-
ditions with a high update frequency. Hence, increasing the
number of nodes also increases the performance difference,
since the number of shared slots allocated in FTS-SDN does
FIGURE 13. Total control packets as a function of the number of nodes for
T= 10 s, with different beacon periods (Bp) and report periods (Rp).
FIGURE 14. Number of shared slots to use depending on the control traffic.
not adapt to the bandwidth requirements of the network. For
example, the topology shown in Fig. 12 [32], is composed of
40 fixed nodes (N) and 3 mobile nodes (M) and a maximum
of 4 hops. In the 4th hop there are 3 mobile nodes, in the 3rd
hop there are 27 fixed nodes, in the 2nd hop 9 fixed nodes and
in the first hop 3 fixed nodes. Therefore, for the fixed nodes
the following are needed, N-1 uplink cells and N-1 downlink
cells, which is equivalent to 39 in both cases. In addition, the
mobile nodes need a link to each outside node. This is 27 cells
per mobile node for uplink, plus another 27 cells per mobile
node for downlink, i.e. 54 cells per mobile node. Therefore,
the slotframe must have 162 cells assigned for the mobile
nodes and 78 cells for the fixed nodes, i.e. a total of 240
cells. This value is defined in [32] as the minimum number
of unicast links, which is equal to twice the number of fixed
nodes multiplied by the number of mobile nodes (2·N·M).
For FTS-SDN, a slotframe of 91 timeslots and 4 channels was
used. By removing the 43 timeslots that are assigned to the
shared slots, 48 timeslots remain available. Using 4 channels
there are 192 cells available in total, where it is not possible
to place the required 240 cells. By using the MMF-SDN
multicast approach, it is not necessary to use a different cell
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F. Orozco-Santos et al.: Multicast Scheduling in SDN WISE to Support Mobile Nodes in Industrial Wireless Sensor Networks
for each of the 27 receivers of the mobile node. Hence, the
162 cells used for the unicast links of the mobile nodes can
be reduced to only 6, two per mobile node. Therefore, using
the same parameters, the slotframe would go from 100%
to 70% occupancy. When evaluating the amount of control
traffic generated by the topology of Fig. 12, using (2) with
Bp = 1 s and Rp = 2 s there are 1000 control packets in a
period Tequal to 10 seconds:
Cpk = 43 T
Bp+T
Rp((3 ·4) + (27 ·3) + (9 ·2) + (3 ·1)) = 1000
The bandwidth required to send this number of control
packets is only achieved by using all the slots of the slotframe
as shared slots, i.e., according to (3) S hSF
SFsz = 1. Therefore,
the beacon and report period must be increased. In this
scenario, a slotframe with the same size as in the FTS-
SDN [32] tests is used, 91 timeslots and 4 channels. The
optimal number of shared slots for this slotframe length is
30 timeslots, using Bp= 3 s and Rp= 6 s.
FIGURE 15. End-to-End delay Topology with 43 nodes
Under these conditions MMF-SDN performs better in end-
to-end delay and determinism, as can be seen from Fig. 15
(a). MMF-SDN can guarantee a delay below 200 ms in 99%
of the packets sent during the initial discovery phase. This
coincides with a full rotation of the mobile node, which
for the speed and path length in this scenario is close to
200 packets. In the same scenario for FTS-SDN Fig. 15 (b),
there is a high variability in the delays and losses during the
whole simulation. The results obtained in [32] show delays
greater than 1.5 s, and when this network is segmented into
clusters, the authors manage to reduce these delays to around
500 ms. This significant performance difference is due to
the fact that in FTS-SDN there is a saturation of the central
nodes, since they must forward the control traffic of the leaf
nodes, and having only one shared slot for each slotframe
the bandwidth is reduced by increasing the length of the
slotframe. During the simulation there is an average of 6
packets in the buffer of the central nodes (2, 3 and 4) for
the FTS-SDN implementation with Bp = 1 s and Rp = 2 s.
Therefore, there is a mismatch between the topology of the
controller and the real one, which affects the reliability of the
routes. For this reason, Bp= 3 s and Rp= 6 s are used
where it is reduced to 2 average buffered packets for FTS-
SDN and 1 packet for MMF-SDN. The latter manages to have
a lower amount of buffered packets, because the nodes have
a higher amount of available shared slots per slotframe.
C. SCENARIO 3.
In this case, a typical scenario of the industrial sector is
simulated, where there are two AGVs covering different
routes within the plant. In total there are 27 nodes, 25 fixed
and 2 mobile, all of them with a coverage range of 20 m. The
mobile nodes are located in the AGVs that are in continuous
movement at a speed of 1.5 m/s. These nodes send a data
packet to the sink every second. As shown in Fig. 16 the
mobile nodes move along the two central corridors, one in
the horizontal direction (purple) for 64 m, and the other in the
vertical direction (green), with a distance of 49 m. The sink is
located at the top of the vertical central corridor. According
to the coverage range, the traffic of the entire WSN reaches it
through the 4 nodes located at the top of the central corridor.
The parameters used are shown in Table 5. Compared to the
two previous scenarios, the complexity is increased due to
the displacement of the mobile nodes through the mobile of
the industrial building used as a scenario, which produces
changes in a greater number of nodes simultaneously.
TABLE 5. Parameters used in scenario 3
Parameter Value
Number of Packets 3600
Sending frequency 1 packet/s
Speed 1.5 m/s
Nodes 25 fixed and 2 mobile
Beacon Period (Bp) 1 s
Report Period (Rp) 2 s
Fig. 17 shows the end-to-end delays obtained using the
two approaches during the start-up phase. Fig. 17 (a) shows
how MMF-SDN achieves an end-to-end delay that slightly
exceeds 300 ms for both vertical and horizontal movement.
Between 50 and 150 packets there is a higher delay. This
is due to the fact that in the fixed nodes there is only one
dedicated link to send the data traffic to the sink. Therefore,
the end-to-end delay increases when the routes of the two
mobile nodes coincide and one of the packets must remain
in queue. With MMF-SDN, packet loss occurs only during
the initial discovery phase, when resources are not allocated.
Fig. 17 (b) the results using the FTS-SDN implementation are
shown. For horizontal movement the end-to-end delay can be
kept below 200 ms, however, for vertical movement there are
different levels of end-to-end delay up to a maximum of 800
ms. In FTS-SDN packet loss can occur at any time during the
test. The delays and losses are the effect of the queuing that
occurs.
The packet loss over the entire path is plotted in Fig. 18
(a). MMF-SDN has no losses in the vertical movement, it is
VOLUME 4, 2016 13

This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/
This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI
10.1109/ACCESS.2021.3120917, IEEE Access
F. Orozco-Santos et al.: Multicast Scheduling in SDN WISE to Support Mobile Nodes in Industrial Wireless Sensor Networks
FIGURE 16. Scenario in an industrial environment with 25 fixed nodes and 2 mobile nodes.
FIGURE 17. End-to-End delay for horizontal and vertical movement of
Scenario 3.
in the horizontal movement where losses occur in the initial
discovery phase, specifically during the sending of the first
50 packets. It is during this period that the first path traversal
occurs and the losses are due to the delay in the allocation
of resources. After this, a constant increase in the PDR is
observed. For FTS-SDN the probability of losses is equal
at any instant of time. This is due to the saturation of the
nodes closest to the sink, which send the control traffic of
all leaf nodes. When the bandwidth is exceeded, packets are
buffered and sent when resources become available again.
This increases the lag between the actual topology and the
topology used by the controller to make decisions. Therefore,
the rules sent by the controller to the mobile nodes will
produce losses. Fig. 18 (b) shows the energy consumption
of the two approaches, in this case the difference between the
two is less than that obtained in scenarios 1 and 2. This is
because in MMF-SDN due to the multicast nature, duplicate
traffic is sent when two multicast receivers receive the packet
from the mobile node. It is possible to limit the amount of
duplicate packets with RSSI conditions on multicast packets
to limit the reception area, using sequence numbers for a node
to discard the repeated packets it receives or implementing
applications in the controller that allow debugging on the
routes on which duplicate packets are received. Even so, the
increase in energy consumption produced by these packets is
not enough to overcome the consumption produced in FTS-
SDN.
To validate the effects of the stability obtained in MMF-
SDN, a test was carried out for one hour, where a total
of 3600 packets were sent. Fig. 19 (a) shows the end-to-
end delay for the path types of scenario 3. Two groups are
clearly observed, one below 100 ms and the other below
330 ms with a lower density. These are packets that were
queued because the paths of the two mobile nodes coincided,
therefore, the delay corresponds to one more slotframe. In
each of the groupings there are 4 bands of dots separated by
one timeslot (10 ms). These correspond to each of the nodes
with direct connection to the sink. Fig. 19 (b) shows how
in both cases there are initial packet losses. Afterwards, a
14 VOLUME 4, 2016

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This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI
10.1109/ACCESS.2021.3120917, IEEE Access
F. Orozco-Santos et al.: Multicast Scheduling in SDN WISE to Support Mobile Nodes in Industrial Wireless Sensor Networks
FIGURE 18. MMF-SDN and FTS-SDN comparison Scenario 3.
stability is observed that allows a PDR higher than 95% to
be obtained. The vertical movement has a lower amount of
losses due to the fact that in its displacement it can have two
independent routes to the sink. By sending in multicast, the
traffic arrives duplicated to the sink, which gives a PDR close
to 100%.
FIGURE 19. Stability of MMF-SDN in Scenario 3.
V. CONCLUSIONS
The dynamism of industrial environments requires WSNs to
be able to adapt quickly to physical and logical changes,
while maintaining determinism and quality of service. For
this reason, MMF-SDN, a software-defined WSN manage-
ment protocol, is proposed to efficiently incorporate nodes
in motion. It eliminates the difficulties caused by the lack
of convergence in the routing protocol when the parent node
changes, while maintaining strict QoS parameters. The lower
dependency on control traffic that MMF-SDN has proven to
have, allows this type of traffic to be reduced by 50% with
respect to FTS-SDN. This and the optimized use of shared
slots, reduces energy consumption in reception by up to 50%.
The allocation of accumulated multicast resources used by
MMF-SDN manages to stabilize the network with mobile
nodes, unlike convergence-based approaches such as FTS-
SDN, which must have a response from the controller to each
change in the topology. The use of multicast transmission in
the mobile node eliminates the difficulty of switching parents
that occurs in FTS-SDN, such that switching parents does
not produce an additional delay. This allows a 70% reduction
in the end-to-end delay. In addition, it reduces the slotframe
occupancy and length by more than 30%, since for each
mobile node the same transmit and receive cells are used
in all parent nodes. The collisions that occur in the shared
slots increase the packet loss and the total amount of control
traffic. However, they do not have an impact on MMF-SDN
performance, because MMF-SDN does not need to quickly
update the mobile position, because the resources remain
allocated in each of the possible entries. The allocation of
accumulated multicast resources requires an initial discovery
phase. In industrial environments where the number of nodes
and movement paths are usually operate in clear limits, there
is high determinism after this phase, as resources remain
allocated and there is an immediate and transparent change
of parent node.
As future work, the use of Machine Learning applications
in the controller will be considered, which will allow data
flows to be analysed, in order to improve routing and quality
of service. This application removes cells that are not used
in the nodes or those that produce duplicate data flows.
Furthermore, due to the multicast nature and synchronism
obtained with TSCH, it is possible to implement applications
that exploit the constructive interference that occurs when
transmitting the same data packet from different sources.
This allows the limitations of the initial discovery phase to
be reduced due to a faster information exchange between the
controller and the mobile nodes.
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10.1109/ACCESS.2021.3120917, IEEE Access
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FEDERICO OROZCO-SANTOS received his
master’s degree in Telecommunications engineer-
ing from the Universitat Politècnica de València
(UPV), Spain, in 2019. In January 2020, he joined
at “Advanced Communications and Industrial In-
formatics” group in Informatic Technological In-
situte (ITI). He is currently pursuing his Ph.D.
degree at Universitat Politècnica de València. His
research interests are the application of dynamic
management approaches in wireless sensor net-
works. The focus of this research is mainly on the end-to-end quality of
service, using slicing, virtualized networks functions, cloud computing and
software defined networks.
VÍCTOR SEMPERE-PAYÁ graduated in Indus-
trial Electronics and Computer Engineering and
received his Ph.D. in Telecommunications engi-
neering from the Universitat Politècnica de Valèn-
cia (UPV), Valencia, Spain in 1987, 1993 and
1998 respectively. Currently, he is a associate
professor in the Department of Communications
(UPV), where he teaches Industrial Communica-
tions and Public Access Networks. His current
research interests are Factory Communications,
Real Time Communications and Quality of Service (QoS) in Networks. He
has served as a program committee member for several conferences in the
area of Factory Communications. Since 1996, he has authored or coauthored
more than 60 technical papers in journals and international conferences. He
has managed more than 50 research and technological projects. Currently, he
is also director of “Advanced Communications and Industrial Informatics”
group in Informatic Technological Insitute (ITI).
16 VOLUME 4, 2016

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10.1109/ACCESS.2021.3120917, IEEE Access
F. Orozco-Santos et al.: Multicast Scheduling in SDN WISE to Support Mobile Nodes in Industrial Wireless Sensor Networks
JAVIER SILVESTRE-BLANES was born in Al-
coy, Valencia, Spain in 1965. He received the
M.S and PhD degree in Computer Architecture in
1999 and 2003. In 1999 he joined the Universitat
Politècnica of València as a part-time associate
lecturer in the Department of Computer Architec-
ture, having been promoted to Adjunct professor
in 2001. He was promoted to Assistant Lecturer
in 2004, and since 2010 he has been working as
a associate professor. He joined the ITI in 2009
in the R+D area (industrial computing, communications and image pro-
cessing), participating in R+D projects both individually and in cooperation
with other entities. He has more than 32 papers in international peer review
conferences, 14 articles published in journals of impact JCR and 8 book
chapters, related to the sector of industrial communications, heterogeneous
networks, multimedia networks, image processing and computer vision. He
has carried out research stays abroad, at the University of Aveiro (Portugal)
and at Anglia Ruskin University in Cambridge. (England). He is a member
of the Industrial Electronics Society (IES), belonging to the IEEE, where
he also belongs to the sub-committee FA10 Computer Vision and Human-
Machine Interaction in Industrial and Factory Automation, belonging to the
IES-IEEE Factory Automation Committee. Since 2005 he has participated
as a member of the organizing committee or as a member of the program
committee of numerous international conferences of the IES-IEEE.
TERESA ALBERO-ALBERO graduated and ob-
tained her Ph.D. in Telecommunications engineer-
ing from the Universitat Politècnica de Valèn-
cia (UPV), Valencia, Spain in 2002 and 2011
respectively. In 2002 she joined the UPV as a
scholarship holder and later as research staff. In
2015 she joined as a part-time adjunct professor in
the Department of Communications and currently
belongs to the Department of Computer Architec-
ture. She has teaching experience in the areas of
computer architecture and technology, as well as industrial communications.
Her current research interests are sensor networks, communication networks,
image processing and industrial networks. She currently belongs to the
Institute of Information Technology (ITI).
VOLUME 4, 2016 17