Conference PaperPDF Available

Pheromone Termite (PT) Model to Provide Robust Routing over Wireless Sensor Networks


Abstract and Figures

In this paper, a scalable mobility-aware pheromone termite (PT) analytical model is proposed to provide robust and faster routing for improved throughput and minimum latency in Wireless Sensor Networks (WSNs). PT also provides support for the network scalability and mobility of the nodes. The monitoring process of PT analytical model is based on two different parameters: packet generation rate and pheromone sensitivity for single and multiple links. The PT routing model is integrated with Boarder node medium access control (BN-MAC) protocol. Furthermore, we deploy two other known routing protocols with BN-MAC; Sensor Protocols for Information via Negotiation (SPIN) and Energy Aware routing Protocol (EAP). To demonstrate the strength of the PT model, we have used ns-2.35-RC7 to compare its Quality of Service (QoS) features with competing routing protocols. The simulation results demonstrate that the PT model is scalable and mobility-aware protocol that saves energy resources and achieves high throughput.
Content may be subject to copyright.
Abstract the routing in wireless sensor networks (WSNs) is
highly critical that increases the latency and congestion. As a
result, throughput performance of the network reduces. In this
paper, scalable mobility-aware pheromone termite (PT) analytical
model is proposed to provide robust and faster routing for
improved throughput and minimum latency. PT also provides the
support for network scalability and mobility of the nodes. The
monitoring process of PT analytical model is based on two
different parameters: packet generation rate and pheromone
sensitivity for single and multiple links.
PT routing model is integrated with Boarder node medium
access control (BN-MAC) protocol. We here also deploy two other
known routing protocols with BN-MAC: sensor protocols for
information via negotiation (SPIN) and Energy aware routing
protocol (EAP). To demonstrate the strength of the PT model, we
have used ns-2.35-RC7 and compared its Quality of Service (QoS)
features with competing routing protocols. The simulation results
demonstrate that the PT is scalable and mobility-aware protocol
that saves energy resources and achieves high throughput by
reducing number of control packets using the BN-MAC as
compared with other routing protocols.
Index Terms Pheromone Termite (PT) Model, Boarder Node
Medium Access Control (MAC) Protocol, Mobility, Routing,
packet generation rate and pheromone sensitivity.
Wireless Sensor Networks consist of the small size of
sensor nodes. Each sensor node works as a unit with sensing
capabilities to collect and process the data for achieving the
combined goal. The sensors are deployed to observe the
activities of events in the intended areas of interest [1].
Therefore, it is important to be introduced the system that
should be an energy efficient at all the levels of protocol stack.
The efficient MAC protocol substantially improves the WSN
performance because sensor node consumes enough energy for
accessing the channel. The channel access process is performed
by MAC protocol [2]. The MAC protocol inherits its features
from two major mechanisms: contention and scheduled based
[3]. Contention based MAC protocols are simple and easier to
use without synchronization. However, each sensor in
contention MAC protocol keeps its radio on for a longer period
Manuscript received February 12, 2014 for ASEE Conference.
Abdul Razaque is with the Computer Science & Engineering Department,
University of Bridgeport, CT-06604, USA; phone: 917-889-5975; fax: 917-889-5975;
2 Khaled Elleithy is with the Computer Science & Engineering Department,
University of Bridgeport, CT-06604, USA; phone: 203- 576-4703; fax: 203-576-4766;
that causes the energy damage [4]. Alternatively, scheduled
based protocols use time division multiple access (TDMA)
mechanism to decrease the energy waste. From other side,
scheduled based MAC protocols experience the problem due to
Scalability and mobility of the modes [5]. As a result, broken
links occur.
Few cross layer MAC protocols are found in the literature,
which reduce the energy consumption by adjusting the reliable
link and bandwidth constraints [6]. However, these protocols
experience co-channel interference due to long state transitions
[7]. End-to-end delay can be minimized by combining the MAC
and network layer features [8]. Also, end-to-end delay can be
guaranteed while choosing the best least delayed path [9].
The reported MAC protocols in the literature are not fully
capable of supporting mobility and network adaptability. These
are some of the major issues which need to be addressed when
designing a highly robust MAC protocol. To address these
concerns, PT model is integrated BN-MAC to provide the
mobility support [10]. With integration of PT with BN-MAC,
the several WSN applications can be supported using less
energy consumption such as disaster, surveillance, monitoring,
home automation devices and controlling the remote devices.
In this paper, PT routing model provides cross layering support
for BN-MAC to handle the mobility and scalability over WSNs.
BN-MAC protocol is an energy efficient that reduces the
energy consumption while handling idle listening, overhearing
and congestion. It also shortens the latency while guarantying
high reliability in a mobile environment [12].
Let us assume that system model should be composed of
many small nodes, which are organized in ad-hoc fashion. The
nodes should use short range and one-hop communication
rather than long range communication to save the energy. In our
case, we use 1-hop destination search for scheduling and
sending the data. The WSN in system model is divided into
different regions, and each region is controlled by a boarder
node (BN) as shown in Figure 1. The BN plays a role as a
coordinator to forward the data within the region and the
adjacent region.
Pheromone Termite (PT) Model to provide
Robust Routing over Wireless Sensor Networks
1Abdul Razaque, Member IEEE and 2Khaled Elleithy, Senior Member IEEE
The message forwarding process of BN-MAC protocol
involves two types of communications: intra and inter. Intra
communication process is carried within the region while inter
is performed out of the region. The mode of communication
within the region is based on Anycast communication. The
Anycast communication reduces the latency as compared with
multicast communication. The multicast consumes more
energy while forwarding the packets, but larger packet size
severely affects the network performance during the
We preferred to use Anycast to reduce overhead of packet
forwarding from each node. The most of latest WSNs
applications are in the surveillance and monitoring area. For
such applications mobility and packet generation rate of the
network are mandatory constraints. If most of the nodes remain
in an idle state for a longer time, considerable amount of energy
is wasted. In our case, sensor node does not remain in idle state
because node finishes its monitoring process then goes to sleep
state using Automatic active and sleep model explained in [2].
We use BN-MAC with PT for controlling the static and
mobility devices from remote places depicted in Figure 1.
Figure 1. Proposed simulated scenario for handling the devices from a
remote distance over wireless sensor network (WSN)
As, we discussed earlier that BN-MAC protocol leverages
the features of carrier sense multiple access (CSMA) and
TDMA. The CSMA is based on semi synchronous mechanism
supported with low duty cycles. From other side, scheduled
based part uses the PT that provides the cross layering support
for finding the best route to forward and receive the data packets
at one-hop neighbor nodes.
Once the carrier medium is accessed, the sensor nodes fix
to schedule for sending the data based on using pheromone
mobility aware route. Let us assume that ‘Plis the variable
length of packets forwarded to other neighbor nodes. The
distance between the two nodes is ‘r’. Thus, according to
Newton’s law of gravitation, the distance is inversely
proportional to force the [13]. Therefore, we can apply free
space propagation model to measure distance between two
neighbor nodes based on the following parameters.
Dte: Default transmitted energy; Et: Energy gain of the
transmitter (TX); Er: Energy gain of the receiver (RX)
Lt: location of transmitter (Tx); Lr = location of receiver (RX);
pl: Received packet length; LN :Loss in network.
 
The calculated distance is used for updating the trajectory
pheromone of sensor nodes. We hereby deploy the features of
trail pheromone and ant control algorithm.
 
 is the number of pheromones that source sensor
node‘s’ spreads on the link at the one-hop neighbor ‘l’ for node
‘n’. ‘Hpis the previous destined hop of packet, ‘Pa is the
amount of pheromone used in each destined packet. ’rc’ current
distance of neighbor node ‘n’ at link ‘l’ and ‘e’ is the distance
of same neighbor node ‘l’ when last packet received and ‘β’ is
the packet-generation rate. The calculated trail pheromone is
used to determine the forwarding energy power of each
neighbor node. Packet forwarding power of each neighbor node
can be calculated as follows:
 
 
 
Where, P(N)q,r is the energy power of each neighbor node ‘u’ to
forward the packet destination ‘r’ at node ‘n’ and ‘K’ is total
number of neighbor nodes. ‘C’ is a pheromone threshold that is
constant. Ps is the level of pheromone sensitivity. Pheromone
threshold and pheromone sensitivity can also be used to find the
second best alternate path of forwarding the packets to the
We here determine an average predictable amount of
pheromone ‘Pψ’ using different links. Let us assume ‘A’ is the
source node and ‘B’ is the destination node, which are using
two different links:  for sending pheromone.
Each link consists of different attributes that are characterized
by non-negative random operation ‘λo(r)’ with mean value
Each packet the forwards fixed amount of pheromone ‘Pa.
Let us assume that each node generates pheromone at constant
rate ‘β’. Suppose two nodes: ‘A’ and ‘B’ are located at two
different locations with distance ‘r’ which are uniformly
distributed over the network. Thus, Rayleigh Distribution can
be used to find the distance distribution of nodes. If
transmission power of the sensor node is less than WSN area,
then the distribution distance is divided into a range of the 0 to
r that can be calculated as:
U(r) 
This is the probability density function that is used to determine
the density of the WSN [14].
V(r) 
Where, ‘V(r)’ is the node distribution that can be used to
compute the predicted pheromone generation
between the node distribution distance ‘r’ with
respect to the number of arrived packets.
Let us assume ‘Z’ is random variable that is used to describe the
fraction of generation pheromone  between node
distribution distance ‘r’ corresponding to packet arrival rate.
Thus, predicted amount of pheromone can be computed using
For 0 ≤ r ≤ R as follows:
(r) 
, then
Enumeration the order of equalities:
Thus, degenerated predictable pheromone can be calculated as
The predicted generation rate can be used to compute the
average predictable pheromone amount on a single and multiple
links using pheromone update-degeneration function. Let us
assume ‘P’ is the population at a distance ‘h’ and ‘Pi is the
initial population. Thus, the ‘P’ can be derived as follows:
 
The updated pheromone function can also be written as:
This function is used for calculating an average predicted the
pheromone amount on a single and multiple links. Based on the
following assumptions; an average predicted pheromone on the
single link can be determined using pheromone update equation
for the number of ‘n’ packets.
Number of delivered packets for distance’ r’ is Poisson
distribution with an average wavelength
a. The average amount of received pheromone is ‘ω’.
b. Initial pheromone amount ‘Pi’ on a single link.
Thus, the pheromone update equation is used consecutive times
Thus, the predicted pheromone amount on the single link for
node distribution distance ‘r’ for number of ‘n’ arrived packets
PP(r) is expressed with Poisson distribution amount
given as (11):
 
Where, λ: Average number of successfully received packets, Z:
Number of successful attempts. We map and apply the Poisson
distribution ‘ψ’ in our problem, and the details are given as
 
 
An average pheromone performance for a longer time can be
obtained as follows:
If we use only single link for destined the packets, then ‘
is the predicted pheromone amount on a single link. Let us
assume that the forwarded packets on multiple links as depicted
in Figure 2, showing the behavior of a termite when attempting
to find the food. Similarly, the PT works for WSNs for
providing the links on the path. Suppose, P0, P1, P2, ..,Pn be the
multiple links to forward the data over WSN. The amount of
predicted packet degeneration is .
Thus, when a packet is received by node ‘n’, it forwards the
packet to 1-hop neighbor nodes, and pheromone is degenerated
on all the links based on predicted packet degeneration rate.
Thus, the average pheromone for all the multiple links can
calculate as follows:
 
 
 
 
 
 
 
 
Figure 2. Single and multiple links to forward the packets using pheromone-
termite model
We set up simulation scenario for controlling remote devices
over WSN. We use ns-2.35-RC7 that produce results that are
almost similar to real environments. In the experiments, the
WSN is divided into ‘N’ regions to get the information more
We have combined mobility- and static-based scenarios. The
main objectives of the simulation are to determine suitable
routing protocol for BN-MAC. Thus PT, EAP and SPIN are
integrated and simulated with BN-MAC. The simulation
scenarios consist of 300 nodes, which are randomly placed in a
geographical area of 600 × 600 m2. The area is divided into ‘N’
number of 150 × 150 m2 regions. The initial energy of each
sensor node is set to 20 J.
The bandwidth of the nodes is 40 kb/sec, and the maximum
power consumption for each sensor node is set 14 mW. The
sensing capability is 13 mW. Each sensor is capable of
broadcasting the data at a power intensity ranging from -16 to
13 dBm. The size of the packet is fixed to128 bytes. The sink
location in each region is at the distance of (45, 45). The node
mobility is set from 0 m/sec to 18 m/sec. The transmission range
of node is 30 meters with 10 meter sensing capability.
The total simulation time is 20 minutes, and the pause time is
set to 2 sec before start of the simulation. During this phase,
nodes are in warm up phase. The results are an average of 12
simulation runs.
A. Control Packets
The routers consume a substantial amount of energy to send
control packets in WSN applications. The control packets do
not send any data except the handshaking process but consume
network bandwidth. An energy-efficient routing protocol can
minimize the number of control packets that are sent to save
energy and bandwidth. Figure 3 presents the control packet
overhead of PT, SPIN, and EAP with BN-MAC.
The number of control packets is directly proportional to
node mobility. PT outperforms SPIN and EAP. PT is a bio-
inspired protocol that does not vary under different mobility
conditions, whereas the other mobility protocols experience
problems due to changes of mobility. Furthermore, EAP and
SPIN suffer due to frequent link break-up because of high
mobility and thus require more control packets to re-establish
the links.
0 2 4 6 8 10 12 14 16 18
MOBILITY (m/sec)
Figure 3. Control packets for PT, SPIN, and EAP for different
numbers of nodes
B. Throughput
We evaluate the throughput performance of each routing
protocol. PT appears to be compatible with BN-MAC. Figure 4
presents the results of simulations using EAP, SPIN, and PT
with BN-MAC. To check the robustness of three routing
protocols, we simulate a scenario that involves static and
mobile objects. The speeds of the sensor nodes vary from 0 to
18 meters/second.
The simulations validate that BN-MAC with PT produces a
stable throughput, whereas SPIN and EAP with BN-MAC face
the slight problems due to motion. As a result, SPIN and EAP
have reduced the throughputs. The simulation results
demonstrate that PT with BN-MAC is the superior choice for
several WSN applications. BN-MAC-EAP and BN-MAC-
SPIN result in reduced throughput because both lack mobility
features and consume additional time during route discovery
and while maintaining the links.
Figure.4. Throughput of BN-MAC-PT, BN-MAC-SPIN and BN-MAC-EAP
on different mobility rates
In this paper, a scalable and a mobility-aware pheromone
termite (PT) model is presented to provide robust and faster
routing over WSNs. The model supports single and multiple
paths over WSNs. Two important features: packet generation
rate and pheromone sensitivity are analytically discussed. BN-
MAC-PT is compared with BN-MAC-EAP and BN-MAC-
SPIN using ns2 simulator to analyze the strength of PT
analytical model.
The simulation results demonstrate that BN-MAC-PT is the
superior choice for mobility and scalability where it achieves
15-20% higher throughput at different mobility rates. In
addition, PT-BN-MAC sends 22-27% fewer control packets as
compared with other routing protocols. As a result, each node
saves 13-18% energy.
[1] A. Razaque and K,M. Elleithy, “Automatic energy saving (AES) model
to boost ubiquitous wireless sensor networks (WSNs), International
Journal of computers and technology (IJCT),vol.10, no.5 ,pp. 1640-1645,
August, 2013.
[2] A. Razaque and K, M. Elleithy, “Energy-Efficient Boarder Node Medium
Access Control Protocol for Wireless Sensor Networks”, journal Sensors,
Vol-14(3), March, 2014.
[3] J. Lutz et al.,” Apples and oranges: comparing schedule- and contention-
based medium access control” In proceedings of the 13th ACM
international conference on Modeling, analysis, and simulation of
wireless and mobile systems (MSWIM '10), pp. 319-326, 2010.
[4] Pei. H, Li. X, Soroor.S, Matt. W. M and Ning.X,” The Evolution of MAC
Protocols in Wireless Sensor Networks: A Survey”, IEEE Trans. on
communication surveys and tutorials, Vol.15, no.01, pp. 101-120, 2013.
[5] .S.Liqi and O.F.Abraham, “.TDMA Scheduling with Optimized Energy
Efficiency and Minimum Delay in Clustered Wireless Sensor Networks”,
IEEE Trans. Mobile Computing, Vol. 9, No. 7, pp. 927-939, July 2009.
[6] Liqi Shi, and Abraham O. Fapojuwo, ―TDMA Scheduling with
Optimized Energy Efficiency and Minimum Delay in Clustered Wireless
Sensor Networks‖, IEEE Transaction on Mobile Computing, Vol. 9, No.
7, pp. 927-939, July 2009.
[7] K Sumit, C Siddhartha, “A Survey on Scheduling Algorithms for Wireless
Sensor Networks”, International Journal of Computer Applications,
Vol.20, N0.5, 2011.
[8] Zara. H and Faisal.B, XL-WMSN: cross-layer quality of service protocol
for wireless multimedia sensor networks”, EURASIP Journal on Wireless
Communications and Networking, 2013.
[9] E Felemban, C-G Lee, E Ekici, MMSPEED: multipath multi-SPEED
protocol for QoS guarantee of reliability and timeliness in wireless sensor
networks. Mobile Comput. IEEE Trans 5(6), 738754 (2006).
[10] A. Razaque and K. Elleithy, “Least Distance Smart neighboring Search
(LDSNS) over Wireless Sensor Networks” , In proceeding of IEEE
international conference on European Modelling Symposium EMS2013,
Manchester, United Kingdom, 20 22 November 2013.
[11] Ming. L.I et al., “An Energy-Aware Routing Protocol in Wireless Sensor
Networks”, International Journal of sensors, pp.445-462, 2009.
[12] A. Razaque and K M. Elleithy “Mobility-Aware Hybrid Medium Access
Control Protocol for Wireless Sensor Network (WSN)”, In proceedings
of IEEE international conference on Sensors Applications Symposium
(SAS), Rydges Lakeland Resort, New Zealand, 18-20 February, 2014.
[13] A. D. Taskok, “A derivation of Newton’s law of gravitation from
electromagnetic forces”, Bulg. J. Phys. 30, pp. 7–20, 2003.
[14] Wolfram math world from: /http://mathworld. /
Mr. Abdul Razaque is a Phd student of computer
science and Engineering department in the
University of Bridgeport. Mr. Razaque has research
interests in the development of mobile applications
to support mobile collaborative learning (MCL),
congestion mechanism of transmission of control
protocol including various existing variants, and
delivery of multimedia applications. He has
published over 60 research contributions in refereed
conferences, international journals and books.
He presented his work in more than 30 countries. During the last two years he
has been working as a program committee member in IEEE, IET, ICCAIE,
ICOS, ISIEA and Mosharka International conference. Abdul Razaque is
member of the IEEE and ACM.
Dr. Khaled Elleithy is the Associate Dean for
Graduate Studies in the School of Engineering at
the University of Bridgeport. He has research
interests are in the areas of network security,
mobile communications, and formal approaches
for design and verification. He has published more
than two hundred fifty research papers in
international journals and conferences in his areas
of expertise.
Dr. Elleithy is the co-chair of the International Joint Conferences on Computer,
Information, and Systems Sciences, and Engineering (CISSE). CISSE is the
first Engineering/Computing and Systems Research E-Conference in the world
to be completely conducted online in real-time via the internet and was
successfully running for six years. Dr. Elleithy is the editor or co-editor of 12
books published by Springer for advances on Innovations and Advanced
Techniques in Systems, Computing Sciences and Software.
... Each base station further forwards the information to "control room" using the IP network. The LDSNS model [30] is also used to help find the efficient shortest path. As a result, the sensor node uses Anycast communication 3 for maintaining the load balancing to save additional energy. ...
... PT encompasses two important features; packet generation rate and the pheromone sensitivity [30] to handle the task of observing the rescue events and maintaining a faster recovery process. Furthermore, most recent WSN applications in the area of surveillance and monitoring also require mobility and scalability. ...
Full-text available
The need for an efficient medium access control (MAC) protocol is extremely important with the emergence of wireless sensor networks (WSNs). The MAC protocol has increasingly been significant in advancing the performance of WSNs. In this paper, a low duty cycle, energy-efficient and mobility-based Boarder Node Medium Access Control (BNMAC) hybrid protocol is introduced for WSNs that controls overhearing, idle listening and congestion issues by preserving energy over WSNs. Further, the BN-MAC hybrid protocol handles the scalability and mobility of nodes using the pheromone termite (PT) analytical model. BN-MAC leverages the features of contention and schedule-based MAC protocols. The contention encompasses the novel semi synchronous approach that helps obtain faster access to the medium. The schedule-based part helps reduce the collision and overhearing problems. The idle listening control (ILC) model is embedded within the BN-MAC that administers the nodes to go to sleep after performing their tasks to saves additional energy. The least distance smart neighboring search (LDSNS) model is used to determine the shortest and most efficient path in a one-hop neighborhood. Evaluation of the BN-MAC is conducted using network simulator-2 (ns2), then its quality of service (QoS) parameters are compared with other known hybrid MAC protocols including X-MAC, Zebra medium access control (Z-MAC), mobility-aware SMAC (MS-MAC),advertisement-based MAC (A-MAC), Adaptive Duty Cycle SMAC (ADC-SMAC) and Mobile Sensor (MobiSense) MAC protocols.
... Each simulation run lasts for 14 min, and three mobility models are tested: CMM, WMM, and RWMM. We use the pheromone termite routing protocol to handle the packet generation rate and pheromone sensitivity used in [25]. ...
Full-text available
Significant research has been conducted for maintaining a high standard of communication and good coverage in wireless sensor networks (WSNs), but extra power consumption and mobility issues are not yet fully resolved. This paper introduces a memory-less location mobility-aware Lattice Mobility Model (LMM) for WSNs. LMM is capable of concurrently determining the node and sink mobility. LMM has a lower pause time, fewer control packets, and less node dependency (e.g., the energy consumed by each node in each cycle that is independent of the data traffic). LMM accurately determines a node’s moving location, the distance from its previous location to its current location, and the distance from its existing location to its destination. Many existing mobility models only provide a model how nodes move (e.g., to mimic pedestrian behavior), but do not actually control the next position based on properties of the underlying network topology. To determine the strength of LMM, OMNet++ was used to generate the realistic scenario to safeguard the affected area. The operation in affected area comprises searching for, detecting, and saving survivors. Currently, this process involves a time-consuming, manual search of the disaster area. This contribution aims to identify an energy efficient mobility model for a walking pattern in this particular scenario. LMM outperforms other mobility models, including the geographic-based circular mobility model (CMM), the random waypoint mobility model (RWMM) and the wind mobility model (WMM), The simulation results also demonstrate that the LMM requires the least time to change the location, has a lower drop rate, and has more residual energy savings than do the WMM, RWMM, and CMM.
... In [85] a routeing protocol for the purpose to select short path called Pheromone Termite Model (PTM) is designed. To establish a route the proposed protocol uses termite-based concept. ...
Full-text available
Due to distributed nature, dynami topology and resour es onstraints of tiny sensing nodes in WSNs, the QoS support is a hallenging issue. However, satisfying the stringent QoS require- ments is an open problem. QoS aware proto ols for WSNs have gained re ently onsiderable at- tention of the resear hers. In this work we fo us on the QoS satisfa tion in WSNs, basi s of QoS support in WSNs, and more importantly hal- lenge, requirements of QoS at ea h layer. Further- more, we review the QoS proto ols and ategorize the QoS aware proto ols and elaborate their pros and ons. We also dis uss the QoS parameters with respe t to ea h proto ol performan e param- eters. A survey and omprehensive dis ussion on QoS aware proto ols of WSNs are presented in- luding their strengths and limitations. Finally, we also survey some omputational intelligen e (CI) te hniques and nd the basi requirements of su h te hniques. Moreover, we study these CI te hniques in the light of QoS management and tabulate the level of ea h CI te hnique for QoS management. The paper is on luded with open resear h issues.
... The Pheromone Termite (PT) model was introduced in [50,51] and is based on a shortest path mechanism. The protocol uses a termite-based concept to establish the routes. ...
Full-text available
Many routing protocols have been proposed for wireless sensor networks. These routing protocols are almost based on energy efficiency. However, the recent advances in of complementary metal-oxide semiconductor (CMOS) camera and small microphones have led to the development of Wireless Multimedia sensor networks (WMSN) as a class of wireless sensor networks which pose additional challenges. The transmission of imaging and video data needs routing protocol with both energy efficiency and Quality of Service (QoS) characteristics in order to guarantee the efficient use of the sensor nodes and effective access to the collected data. Also, with integration of real time applications in the Wireless Senor Networks (WSNs), the use of QoS routing protocols is not only becoming a significant topic but is also gaining the attention of researches. In designing an efficient QoS routing protocol, the reliability and guarantee of end-to-end delay are critical events while conserving energy. Thus, considerable research has been proposed for designing energy efficient and robust QoS routing protocols. In this paper, we present a state of the art research work based on QoS routing protocols for Wireless Multimedia sensor networks (WMSN) that have already been proposed. This paper categorizes the QoS routing protocols into probabilistic and deterministic protocols. In addition, both categories are classified into soft and hard real time protocols by highlighting the QoS issues including limitations and features of each protocol. Furthermore, we have compared the performance of known routing protocols using network simulator-2 (NS2). This paper also focuses on the design challenges and future research directions as well as highlights the characteristics of each QoS routing protocol.
... Each simulation continues for 20 minutes. We deploy the pheromone termite (PT) routing protocol to route the data to detect the shortest route as explained in [19]. We use different size of packets and consider a sensor application module with a constant bit-rate source that helps maintaining the QoS requirements. ...
Conference Paper
Full-text available
Scalable and efficient Medium Access Control (MAC) protocol has been of the paramount significance for boosting the performance of wireless sensor networks (WSNs). In this paper, scalable and efficient medium access control (SE-MAC) protocol is introduced for WSNs. The Goal of SE-MAC is to reduce the communication delay time, channel delay time and control delays caused by acknowledgment packets, request-to-send (RTS), clear-to-send (CTS) etc. Thus, reducing the delays, SE-MAC incorporates the adaptable application independent aggregation (AAIA) model to achieve the expected goals. Furthermore, SE-MAC is supported with handoff process feature, which helps extend the network lifetime. AAIA model for SE-MAC plays a role of cross-layering that extensively reduces the different delays incurred at MAC sub-layer and network layer. Evaluation of SE-MAC is conducted using network simulator-2 (NS2) then compared with known MAC protocols: Zebra medium access control (Z-MAC), receiver-initiated asynchronous duty cycle MAC (RI-MAC) and an energy-efficient multi-channel mac (Y-MAC). Based on the initial Simulation results, we demonstrate that SE-MAC protocol saves extra 9.8-15% time and energy resources for channel delays as compared with other MAC protocols.
... Wireless Sensor networks are considered as one of the hot research areas in current years [1], [2]. WSNs comprise of a large number of sensor nodes with limited energy constraints that collect the data from interested domain and process to specific domains [3]. ...
Full-text available
Vehicle Routing Problem with Time Windows (VRPTW) involves traversing a coordinated set of vehicular paths such that a set of customers is visited once within a given time-stamped boundary. VRPTW poses a great challenge to logistics distribution and supply chain management systems, due to its characterized stochastic and NP-hard combinatorial properties, which requires that its corresponding optimal path planning and vehicle scheduling solutions be both highly efficient and cost effective even as customers' demands change dynamically. In this paper, a new hybrid metaheuristic scheme, tagged TERMHIGEN, based on the characteristics of the Termite-Hill algorithm and a modified Genetic Algorithm, with its associated adaptive self-learning and tuning schemes, based on is developed and applied to solving a prototype VRPTW specifically with the objective of minimizing overall logistic distribution cost. TERMHIGEN was tested using Solomon's 56 VRPTW instances containing 100 customers. The performance evaluation results of the algorithms reveal that TERMHIGEN produced more optimal and efficient outputs for some problem instances than those produced by some baseline metaheuristic techniques in terms of computational time efficiency and distance travelled.
Wireless sensor networks (WSNs) generally comprise a large number of tiny sensor nodes that perform network processing of the acquired data and then forwarding such data to the sink via multi-hop paths. The sensor nodes are resource constrained in terms of battery life, memory, and processing capability. Hence, a critical aspect in WSNs is power scarcity, which directly affects the network operation lifetime and the performance of applications. Furthermore, large-scale WSNs demand a high level of self-organisation so each node of the system autonomously makes decisions. In this respect, self-organising methods enhancing the network lifetime while achieving balanced energy are highly significant in WSNs. In this study, the authors apply gene regulatory network (GRN) principles to WSN system and design a new GRN-inspired model for autonomous node scheduling in WSNs. GRNs have received considerable attention from computational engineering for their robustness, scalability, and adaptability with simple local interactions and limited information. They apply cellular mechanisms of GRNs to WSNs and establish a metaphor between a multi-cellular system and a WSN system. Then, they propose a new model inspired by GRN so each sensor node autonomously schedules its state with local interaction based on sensor variable signalling while achieving the global object predefined by an application or user. Using control theory, they analyse system stability and derive steady states of the proposed system. They further derive the conditions of system parameters to ensure system convergence to a desired state. Simulation and numerical results are evaluated to provide insights into the effect of various system parameters on energy balancing and system stability.
Conference Paper
Wireless sensor networks consists of a large amount of miniaturized battery-powered wireless networked sensors which are intended to function for years without any human intervention. Because of the large number of sensors and the restrictions on the environment of their deployment, replacing the components cannot be thought of. So the only viable way out is to efficiently use the available resources. Energy efficiency is a major matter of concern in such networks even though energy harvesting techniques exists. Recent times have shown a growing interest on understanding and developing new strategies of wireless sensor network routing especially focussing on the optimal use of the limited and constrained resources like energy, memory and processing capabilities. Routing have to be given due importance as it consumes major part of the energy compared to that of sensing and processing. Adopting the natures self organising system intelligence for the emerging technologies is quite interesting and has proved to be efficient. This article sheds some light on the existing bio inspired routing protocols and explains a new procedure with mobile sinks for energy efficient routing in wireless sensor networks.
Wireless sensor networks (WSNs) are considered as the appealing research area. WSNs require highly robust medium access control (MAC) protocol to enhance the performance in several application areas such as intrusion detection, target detection, industrial automation, environmental monitoring, surveillance system, medical diagnosing system, tactical system and so on. On other hand, there are several factors that affect the performance of these applications particularly selection of weak MAC protocol. In this paper, we provide performance impairing drivers for MAC protocols, which affect the efficiency and robustness of MAC protocols in WSN applications. We classify MAC protocols into six categories, as compared with previous MAC surveys that only focused on classifying the MAC protocols into two, three or four major categories. In addition, we show the link of each category with another based on their existing features. Furthermore, this survey provides a detailed nomenclature in which protocols are categorized based on synchronous and asynchronous communication. This survey also discuss the possible threats and some existing solutions at MAC layer from 2000-2014. Finally, we identify the future research challenges and raise directions for controlling these challenges.
Full-text available
This paper introduces the design, implementation, and performance analysis of the scalable and mobility-aware hybrid protocol named boarder node medium access control (BN-MAC) for wireless sensor networks (WSNs), which leverages the characteristics of scheduled and contention-based MAC protocols. Like contention-based MAC protocols, BN-MAC achieves high channel utilization, network adaptability under heavy traffic and mobility, and low latency and overhead. Like schedule-based MAC protocols, BN-MAC reduces idle listening time, emissions, and collision handling at low cost at one-hop neighbor nodes and achieves high channel utilization under heavy network loads. BN-MAC is particularly designed for region-wise WSNs. Each region is controlled by a boarder node (BN), which is of paramount importance. The BN coordinates with the remaining nodes within and beyond the region. Unlike other hybrid MAC protocols, BN-MAC incorporates three promising models that further reduce the energy consumption, idle listening time, overhearing, and congestion to improve the throughput and reduce the latency. One of the models used with BN-MAC is automatic active and sleep (AAS), which reduces the ideal listening time. When nodes finish their monitoring process, AAS lets them automatically go into the sleep state to avoid the idle listening state. Another model used in BN-MAC is the intelligent decision-making (IDM) model, which helps the nodes sense the nature of the environment. Based on the nature of the environment, the nodes decide whether to use the active or passive mode. This decision power of the nodes further reduces energy consumption because the nodes turn off the radio of the transceiver in the passive mode. The third model is the least-distance smart neighboring search (LDSNS), which determines the shortest efficient path to the one-hop neighbor and also provides cross-layering support to handle the mobility of the nodes. The BN-MAC also incorporates a semi-synchronous feature with a low duty cycle, which is advantageous for reducing the latency and energy consumption for several WSN application areas to improve the throughput. BN-MAC uses a unique window slot size to enhance the contention resolution issue for improved throughput. BN-MAC also prefers to communicate within a one-hop destination using Anycast, which maintains load balancing to maintain network reliability. BN-MAC is introduced with the goal of supporting four major application areas: monitoring and behavioral areas, controlling natural disasters, human-centric applications, and tracking mobility and static home automation devices from remote places. These application areas require a congestion-free mobility-supported MAC protocol to guarantee reliable data delivery. BN-MAC was evaluated using network simulator-2 (ns2) and compared with other hybrid MAC protocols, such as Zebra medium access control (Z-MAC), advertisement-based MAC (A-MAC), Speck-MAC, adaptive duty cycle SMAC (ADC-SMAC), and low-power real-time medium access control (LPR-MAC). The simulation results indicate that BN-MAC is a robust and energy-efficient protocol that outperforms other hybrid MAC protocols in the context of quality of service (QoS) parameters, such as energy consumption, latency, throughput, channel access time, successful delivery rate, coverage efficiency, and average duty cycle.
Conference Paper
Full-text available
Efficient MAC protocol has been paramount importance for improving the performance of WSN. In this paper, Boarder Node Medium Access Control (BN-MAC) mobility aware hybrid protocol is introduced for WSN. BN-MAC controls overhearing, idle listening and congestion problem to save energy. BN-MAC mechanism is based on novel semi synchronous low duty cycle that takes less time for accessing channel and faster delivery of data. The objective of introducing BN-MAC protocol is to support four application areas: monitoring and behavioral areas, controlling natural disasters, tracking and handling home automation devices and human-centric application areas. These application areas need contention free mobility support features with high delivery of data. BN-MAC also provides mobility support for these applications. Evaluation of BN-MAC is conducted using network simulator-2 (ns2) then compared with known low power listening (LPL) and X-MAC low duty cycles MAC protocols. Additionally, we have also compared BN-MAC with MAC hybrid protocols: Zebra medium access control) (Z-MAC), advertisement-based MAC (A-MAC), Speck-MAC, Adaptive Duty Cycle SMAC (ADC-SMAC), low power real time medium access control (LPR-MAC) protocol. On basis of initial Simulation results, we demonstrates that BN-MAC protocol saves extra 18% to 45% energy resources as compared with other MAC protocols.
Conference Paper
Full-text available
In this paper, we introduce a novel least distance smart neighboring search (LDSNS) to determine the mostefficient path at one-hop distance over WSNs. LDSNS helps to reduce the energy consumption and speeds up scheduling for delivery of data. It provides cross layering support and linking MAC layer with network layer to reduce the amount of control messages. LDSNS is a robust and efficient approach that isbased on single-hop communication mechanism. To validate the strength of LDSNS, we incorporate LDSN in Boarder Node Medium AccessControl (BN-MAC) protocol [ 15] to determine the list of neighboring sensor nodes and choosing best 1-hop efficient search to avoid collision and reducing energy consumption. Evaluation of LDSNS is conducted using network simulator-2 (ns2).The performance of LDSNS is compared with minimum energy accumulative routing problem (MEAR) [12], asynchronous quorum-based wakeup scheduling scheme (AQWSS) [14] and Minimum Energy Relay Routing (MERR) [13]. Simulation results show that LDSNS is highly energy efficient and faster as compared with MEAR, AQWSS and MERR. It saves 24% to 62% energy resources and improves12% to 21% search at 1-hop neighboring nodes.
Full-text available
Energy conservation has been the prime motivation behind the design of conventional protocols for wireless sensor networks (WSNs). However, recent trends toward high data rate multimedia communication over WSNs demand traffic- and deadline-aware content delivery with minimum energy expenditure. The basic quality of service requirement in wireless multimedia sensor networks (WMSNs) is time-bound data delivery. The conventional-layered protocol design solutions are inefficient, as real-time content delivery requires interactions between multiple layers like application for traffic categorization, network for real-time delivery, and media access control (MAC) for prioritized medium access with minimum energy expenditure. In this paper a cross-layer solution (XL-WMSN) is proposed for real-time data delivery. The XL-WMSN provides interaction between energy-based admission control, delay- and interference-aware routing, and dynamic duty cycle assignment at MAC layer. Simulation analysis shows that XL-WMSN increases the probability of delivering multimedia content within their allocated deadline and is more efficient than existing solutions.
Full-text available
We deploy BT node (sensor) that offers passive and active sensing capability to save energy. BT node works in passive mode for outdoor communication and active for indoor communication. The BT node is supported with novel automatic energy saving (AES) mathematical model to decide either modes. It provides robust and faster communication with less energy consumption. To validate this approach, network simulator-2 (ns2) simulation is used to simulate the behavior of network with the supporting mathematical model. The main objective of this research is to remotely access different types of servers, laptops, desktops and other static and moving objects. This prototype is initially deployed to control MSCS [13] & [14] from remote place through mobile devices. The prototype can further be enhanced to handle several objects simultaneously consuming less energy and resources.
Wireless Sensor Networks (WSNs) have become a leading solution in many important applications such as intrusion detection, target tracking, industrial automation, smart building and so on. Typically, a WSN consists of a large number of small, low-cost sensor nodes that are distributed in the target area for collecting data of interest. For a WSN to provide high throughput in an energy-efficient way, designing an efficient Medium Access Control (MAC) protocol is of paramount importance because the MAC layer coordinates nodes' access to the shared wireless medium. To show the evolution of WSN MAC protocols, this article surveys the latest progresses in WSN MAC protocol designs over the period 2002-2011. In the early development stages, designers were mostly concerned with energy efficiency because sensor nodes are usually limited in power supply. Recently, new protocols are being developed to provide multi-task support and efficient delivery of bursty traffic. Therefore, research attention has turned back to throughput and delay. This article details the evolution of WSN MAC protocols in four categories: asynchronous, synchronous, frame-slotted, and multichannel. These designs are evaluated in terms of energy efficiency, data delivery performance, and overhead needed to maintain a protocol's mechanisms. With extensive analysis of the protocols many future directions are stated at the end of this survey. The performance of different classes of protocols could be substantially improved in future designs by taking into consideration the recent advances in technologies and application demands.
With the Strong Law of Large Numbers, induced polarisation is used to show that electromagnetic forces obey Newton's Law of Gravitation; and experimentally verified to suggest that it may be the only cause.
Wireless sensor networks(WSN) have wide range of application such as traffic analysis, environmental monitoring, industrial process monitoring, and tactical systems. Large-scale wireless sensor networks are expected to play increasingly important role in future civilian and military application. Designing of MAC layer protocol for wireless sensor network is a challenging task due to limited battery power and limited bandwidth. Time Division Multiple Access Protocol solves both problems at the level of MAC layer. Various scheduling method for TDMA protocol with different objective have been proposed for wireless sensor networks. In this paper, we first outline the sensor network properties that are crucial for the design of TDMA protocols and then, we describe several TDMA protocols which are proposed for sensor networks. Finally, we point out open research issue with regard to TDMA protocols.
In recent years, wireless sensor networks (WSNs) have been an interesting and important research area. Many routing protocols for WSNs have been designed for various objectives. In this paper, a novel energy-aware routing protocol in WSNs is proposed for achieving high energy-efficiency which prolongs the network lifetime and is one of the most important requirements for applications of WSNs. Additionally, communication delay is fully considered. Performance analyses and simulation results show that our proposed protocol has much better performance than directed diffusion and rumor routing in terms of both network lifetime and communication delay.
Conference Paper
Comparison of schedule and contention based MAC protocols is made difficult by their fundamental differences in approach to medium access control. This paper provides a way in which to analyze and compare MAC protocols regardless of their underlying allocation strategy. To that end a framework is developed in which the persistence of any protocol, contention- or schedule-based, can be measured. The framework is used to measure and compare the persistence levels of two prototypical contention- and schedule-based MACs, IEEE 802.11 and Scheduled p-Persistence. An ideal persistence that provides lexicographically max-min fair access to the channel is characterized, and used as a bandwidth allocation scheme. In addition to reducing the unfairness, simulations employing the ideal persistence values show increased throughput and decreased delay and drop rate when compared to either Scheduled p-Persistence or IEEE 802.11.