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Effects of Heterogeneity on the Performance of
Pocket Switched Networks
Barun Kumar Saha and Sudip Misra, Senior Member, IEEE
School of Information Technology,
Indian Institute of Technology Kharagpur, India
Email: {barun.kumar.saha, smisra}@sit.iitkgp.ernet.in
Abstract
Pocket Switched Networks (PSNs), which are formed by mobile devices carried by their users, present an interesting
communication paradigm especially in the absence of access to global network connectivity. This work explores the effect of
nodes’ heterogeneity on the performance of PSNs that use opportunistic communication mechanisms. The focus is on the diversities
reflected by the hardware (specifically, buffer size and network interfaces) and software (specifically, routing protocol) of the nodes.
Further, the effects of the asymmetric (unidirectional) connections among the devices have also been studied. While there could
be other forms of diversities, for example, different MAC layer protocols, the ones considered here are among the fundamental,
and have the potential to render available communication opportunities useless. We use time-varying graphs to represent a PSN
with heterogeneous routing protocols and capture its effect. To address the interactions among diverse routing protocols, the use
of special nodes, Protocol Translation Units (PTUs), is proposed. Each PTU runs a hybrid routing protocol, which encapsulates
the functionality of two or more routing protocols. The results of performance evaluations reflect that deploying PTUs promotes
the delivery ratio of the messages by about 15 −50%, compared to the levels obtained in, otherwise, homogeneous PSNs.
I. INTRODUCTION
PSN [1] is a category of Delay-Tolerant Networks (DTNs) where the portable devices carried by the human beings, for
example, mobile phones and PDAs, form a network among themselves. These devices use global network connectivities, when
available, for communications. PSNs, however, present an interesting and useful mechanism supporting communication in the
absence of any network infrastructure. Under such a scenario, the devices in PSNs engage in opportunistic communications
with the other devices when they are in the transmission range of one another.
A. Motivation
Various aspects – such as, routing [2]–[4], security [5] and cooperation [6] – related to the PSNs, or DTNs in general,
have been explored by the research community. The existing works, however, have addressed scenarios where the network
compositions are homogeneous. Such an assumption, however, may not hold true in real life. To illustrate, two end devices
cannot communicate with each other using incompatible network interfaces, such as Bluetooth and Wi-Fi adapters. Further,
communication between two devices in a PSN running different routing protocols may fail due to incompatibility of the
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routing protocols. These issues, if not addressed, would affect the performance of spontaneously formed PSNs. Moreover,
such heterogeneity would adversely affect the performance in MOONs [7] – an extension of the PSNs considering the mission
objectives and influence of the human onwers upon the network communication process. In [7], the authors considered how
intuitive for of human intelligence increases zone visits in a post-disaster rescue scenario. A MOON formed in such a scenario
with the objective of maximizing message transfer would be affected due to heterogeneity.
In this work, the effects of nodes’ heterogeneity, reflected by their hardware and software, on the performance of PSNs using
opportunistic communications have been considered. On the hardware aspects, specifically, the asymmetric (unidirectional)
connections, buffer sizes, and incompatible network interfaces of the mobile devices have been considered. The work also
explores the diversity in the software of the devices by considering them running different routing protocols. To address such
diversity, the use of special nodes, Protocol Translation Units (PTUs), have been proposed. Each PTU runs a hybrid routing
protocol, which encapsulates the functionalities of two or more routing protocols. The question about the availability of the
PTUs in real-life PSNs can be addressed by considering that a certain fraction of the users already possess such devices. This
is possible either when the users purchase such devices, or are promoted by some person/organization.
B. Contributions
The specific contributions of this work are summarized as follows:
•Acquiring insights on – and evaluating – the effect of diversity in hardware (specifically, buffer size and network interfaces)
of the devices on the network performance.
•Investigating the interaction of different routing protocols and the resulting performance degradation in the network.
•Using time-varying graphs (TVGs) [8] to represent a heterogeneous PSN, and defining communication degree to capture
the effects of diverse routing protocols.
•Proposing the use of PTUs, which use hybrid routing protocols, to counter such degradation.
II. RELATED WORK
The issue of heterogeneity in the context of ubiquitous and pervasive computing has been widely addressed in the literature.
Schmohl and Baumgarten [9] noted that heterogeneity arises in mobile computing environments due to the hardware and
software of the devices, and the architecture of the network. Bromberg et al. [10] proposed the Starlink framework – a
middleware for run-time bridging of heterogeneous protocols. The proposed framework can address heterogeneity related
to the different message formats and protocol’s behaviour. Heterogeneity often arises due to diverse link layer protocols for
example, MAC protocols based on/or not cognitive radio [11]. Stuedi and Alonso [12] explored the integration of heterogeneous
MAC protocols in mobile ad hoc networks, with specific focus on 802.11 and Bluetooth. The authors proposed the use of
software-based virtual interface to integrate the devices with different MAC layers. The proposed approach, although novel,
is suitable for traditional networks using end-to-end communication paradigms. Moreover, the assumption of the use of such
bridging software may further lead towards heterogeneity.
The unlayered architecture of Haggle [13] was developed for the PSNs. Haggle’s focus is on data-centric networks, and
is located in between the application layer and the hardware interfaces. Petz et al. [14] presented MaDMAN, a middleware
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for dynamic switching between MANET and DTN protocols. In their proposed architecture, the network stack consisted
of a collection of different possible transport, network and link layer protocols. The network stack could be switched with
another even while the application is running, which enabled communications with asymmetric protocols. While no comparative
performance of the two models are available, MaDMAN supports more extensibility. However, unlike Haggle, MaDMAN does
not support data transfer with user-level naming.
Lee and Eun [15] and Tian and Li [16] considered the heterogeneity in the contact process of the mobile nodes and diversity
in the pairwise contact patterns. Such factors, however, do not reflect the heterogeneity in the composition of the concerned
networks. Li et al. [17] explored deploying defense mechanisms in PSNs to prevent malware attacks. The authors considered a
network of heterogeneous devices, where different types of malware can only attack the systems they are targeted for. Manam
et al. [18] presented the performance modeling of two routing protocols (two-hop and Epidemic) by considering the nodes
to have heterogeneous transmission ranges. The delivery latency of the messages was found to decrease with the increasing
transmission ranges of the nodes.
It may be noted that, apart from the diversities in the mobility patterns and contact dynamics, there are several other factors
that lead to a heterogeneous network. A walk through of the existing works reveal that there is a lack of comprehensive approach
to address the heterogeneity, and its impacts, on PSNs, or DTNs, in general. Besides, while works in [15], [16], [18] focus
on the reduction of communication opportunities in the network, heterogeneity of certain aspects (e.g., incompatible network
devices – in absence of any bridging [12], and routing protocols) turn available communication opportunities useless. Further,
the existing works do not present any insight, in terms of quantitative values, on how performance degrades in heterogeneous
PSNs. In this work, through extensive simulations, such degradation in the PSNs, and the improvements obtained in the presence
of interoperability mechanisms, have been quantified.
III. HETEROGENEITY IN PSNS
This Section presents the various aspects that contribute to heterogeneity in a PSN.
A. Heterogeneity in Connection Dynamics
Heterogeneity in the connection dynamics of the devices arises due to one or more of the following reasons: 1) Asymmetric
transmission ranges and/or speeds, 2) Diversity in the link-layer protocols of the devices, and 3) Asymmetric device scanning
intervals.
Diverse transmission ranges could result in one-way connectivity between a pair of devices. Further, each device scans for
its neighbours periodically after a certain time interval. Devices with variable scan intervals would affect the frequency of
neighbour discovery, and, hence, possibly decreased number of connection establishment events. Such issues, however, could
be induced by the underlying link-layer protocol of the devices, and their further consideration have been scoped out in this
work.
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B. Diverse Hardware of the Devices
Users’ devices have a fixed buffer size, which determines how many messages could be stored by a device at any given
time. Another potential hardware related issue is the presence of incompatible devices in the network. For example, let us
consider two devices where the first has a Bluetooth interface, while the other has a Wi-Fi interface. Such devices, although
may be within the transmission range of each other, cannot communicate due to their differences in the network interfaces.
C. Routing Protocols in DTN and their Compatibility
To discount the effects of intermittent connectivities, several routing schemes based on message replication have been adopted.
The simplest scheme in this case is the Epidemic routing [19], where every node replicates and forwards the messages they are
carrying to the nodes not having the messages’ copies. SnW [3], on the other hand, limits the maximum number of replication
possible in the network. For each message generated, SnW assigns a count L > 1. Any node having a copy of the message
forwards a copy to another node as long as L > 1. After forwarding, it reduces its own count of copies to L/2or L−1,
depending on whether the protocol is run under binary mode or not.
In PROPHET [2], a node forwards a replica of a message to another node only if the other node has greater chances of
encountering the destination of the message than itself. The following equations govern the functionality of PROPHET:
P(a,b)=P(a,b)old + (1 −P(a,b)old)×Pinit (1)
P(a,b)=P(a,b)old ×γk(2)
P(a,c)=P(a,c)old + (1 −P(a,c)old)×P(a,b)×P(b,c)×β(3)
Here, P(a,b)and P(a,b)old, respectively, indicate the current and previous delivery predictabilities, i.e., the likelihood that any
node awould meet with another node b;P(a,b)∈[0,1];Pinit ∈[0,1] is an initialization constant. The delivery predictabilities
are aged with time when two nodes do not encounter for long. The parameter γ∈[0,1) is the aging constant, and kdenotes
the number of time units expired since the last update of this predictability. The scaling parameter β∈[0,1] controls extent
to which transitivity should affect the delivery predictability.
Although these routing protocols help in enhancing the message delivery ratio, most of the protocols are not compatible
with one another primarily due to two reasons:
•The protocol-specific headers added to the messages while they are created, and
•The operation modes of the protocols, for example, single- or multi-copy routing and message forwarding/replication
criteria.
Further, routing in content-centric DTNs often do not have a particular destination address [20], unlike the traditional routing
protocols.
D. Effects of Incompatibilities
Lack of interoperability among the devices results in the following adverse effects in PSNs:
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•Loss of communication opportunities: Devices cannot communicate even when they are near to each other, i.e., commu-
nication opportunities are lost.
•Undelivered messages: Certain messages in the network always remain undelivered, no matter what resource and time
are provided.
•Increased delivery latencies: Nodes have less communication opportunities, which affects, on an average, the time required
to deliver the messages.
Thus, it is desirable that such issues are addressed to achieve better performance in the network.
IV. REPRESENTATION OF HETEROGENEOUS PSNS
Casteigts et al. [8] presented the concept of TVGs as G= (V, E , τ, ρ, ζ), where Vis the set of nodes, Eis the set of edges,
and τis the lifetime of the system. ρis called the presence function indicating the existence of a particular edge at a given
time, and is represented as ρ:E×τ→ {0,1}. The function ζrepresents the (possibly time-varying) latency involved to travel
an edge from one end point to the other.
The above TVG model could be used to represent a heterogeneous PSN. In particular, ρaccounts for multiple scenarios of
heterogeneity, for example, devices with incompatible network interfaces and asymmetric connection events. However, since
ρindicates the temporal presence of the links, it cannot capture the scenarios when a link exists, but no communication is
possible, such as when diverse routing protocols are used.
Let, Eτbe the set of the edges that exists over the entire network lifetime, i.e., Eτ={e|e∈E∧ρ(e, t) = 1, t ∈τ}.
Let us define a function φsuch that φ(e∈Eτ) = 1, if the nodes at the two end points of the edge have compatible routing
protocol, and 0, otherwise. Therefore, EC=∪e∈Eτφ(e)⊆Eτgives the set of potentially communicable edges in the network
i.e., the edges through which messages could be exchanged. A measure of α=|EC|
|Eτ|indicates the communication degree of a
PSN resulting due to the diverse routing protocols, and depends on the number of nodes in the PSN, routing protocols used
by them, as well as their mobility patterns.
A logical question that arises here is – what role, if any, do the nodes play in a heterogeneous PSN when there is apparently
a possibility of communication? By apparently, we mean that the link layer of a device indicates that it can communicate with
another device. Even if such a link layer connectivity exists, several factors, for example, energy levels and routing protocols
could prevent the actual communication. Let us consider the scenario when the messages sent by one node could not be
interpreted by the other due to the difference in their protocols. In this case, however, both the nodes consume energy during
transmission/reception of the messages. Such an issue could be circumvented if the link layers of the devices advertise the
routing protocols used by them, and, therefore, do not engage in further communication if the other device is not found to use
a compatible protocol.
V. OVERCOMING THE ADVERSE EFFECTS OF NETWORK HETEROGENEITY
This Section explores how the adverse affects of heterogeneity could be mitigated. The approach presented here derives
from the general concept of bridges discussed in [9].
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A. Hardware Incompatibility
The capacity of existing PSNs with differing network interfaces could be easily augmented in the presence of devices that
are accompanied with multiple types of network interfaces. For example, a group of devices having only Bluetooth adapters
could be bridged to a group of devices having only Wi-Fi capabilities if they come in contact with one or more devices having
both types of network interfaces.
This work considers two network interfaces – if1 and if2 – that are assumed to be incompatible with each other. It is
considered that certain devices in the PSN have only either if1 or if2, and the remaining have both. Any device having if1 (if2)
could communicate with other devices having if2 (if1) or both. Communication is not possible otherwise.
B. Protocol Translation Units
We addresses the incompatibility issues between two specific routing protocols: PROPHET and SnW. They are representative
of two different categories of routing protocols used with PSNs/DTNs – routing with 1) Fixed number, and 2) Unlimited copies
of the messages. Moreover, while SnW maintains the state of a message (L), PROPHET considers the state of connectivity
among the nodes (P(a,b)). Although variations of these protocols have been proposed, the principles described here holds good
for them as well.
To overcome the communication impairments caused due to heterogeneous routing protocols, the use of PTUs is proposed.
PTUs are “special devices” that can interact with two or more routing protocols both in terms of interpretation of protocol-
specific headers and sequence of interactions. The PTUs run a hybrid routing protocol, encapsulating the syntax and semantics
of both PROPHET and SnW protocols. This enables a PTU to communicate with both types of routers. This could be further
extended to encapsulate the logic of multiple other protocols.
1) How the PTUs Help?: To understand how the PTUs handle the dynamic scenarios arising in the PSNs, let us consider
two devices Xand Yusing the routing protocols SnW and PROPHET, respectively. Although Xcannot successfully send a
message to Y, it can do so to a PTU device. The latter, in turn, helps in forwarding the message to Ydirectly or through
other intermediate nodes using the PROPHET routing protocol.
It is considered that the devices periodically emit beacon signals, which also provides information about the routing protocol
used by the respective devices. The PTUs are assumed to advertise both the routing protocols in their beacon messages. Thus,
any device that is running PROPHET (SnW) initiates communication with other devices if the received beacons advertise
the use of PROPHET (SnW). Figure 1 shows the interaction among the different routers and the PTUs. In the Figure, the
PTU identifies the routing protocol of the other device, and behaves accordingly. The Figure also shows the failed interaction
between a SnW and a PROPHET router.
Algorithm 1 presents the interaction logic between a PTU and any other device using the PROPHET routing protocol. At
the beginning, all the deliverable messages (i.e., the messages destined for the other device) are transferred. In case any such
message was received from a SnW router, the corresponding SnW headers are removed, and PROPHET headers are added
before forwarding. Replication of the remaining messages take place in the following two phases:
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1) In the first phase, all the messages received from the other PROPHET routers are replicated depending on the delivery
predictabilities as shown in (1), (2) and (3).
2) Subsequently, any message received from the SnW routers are replicated, provided L > 1. This ensures that the last
copy of the message is directly delivered to the destination node.
Algorithm 1 Interaction of the PTUs with PROPHET routers
Require:
•All messages carried by the device
Ensure:
•Exchange new messages with the other device
1: for each directly deliverable message do:
2: if message has SnW or PTU header then
3: Remove the header.
4: Add PROPHET header.
5: end if
6: Forward the message.
7: end for
8: for msg in remaining messages do:⊲PROPHET messages
9: if msg does not have SnW header then:
10: Replicate and send according to the (1), (2), and (3).
11: end if
12: end for
13: for msg in messages do:⊲SnW messages
14: if msg has SnW header with L > 1then:
15: Update header with L=L/2.
16: Replicate, remove header and send.
17: end if
18: end for
Algorithm 2 presents a similar logic of interaction between the PTUs and the SnW routers.
Algorithm 2 Interaction of the PTUs with SnW routers
Require:
•All messages carried by the device
Ensure:
•Exchange new messages with the other device
1: for each directly deliverable message do:
2: if message has PROPHET or PTU header then
3: Remove the header.
4: Add SnW header with L= 1.
5: end if
6: Forward the message.
7: end for
8: for msg in remaining messages do:⊲SnW messages
9: if msg has SnW header with L > 1then:
10: Set L=L/2, replicate and send.
11: end if
12: end for
13: for msg in messages do:⊲PROPHET messages
14: if msg does not have SnW header then:
15: Replicate msg, add SnW header with L, and send.
16: end if
17: end for
2) Time Complexity: Let us assume that nmessages are generated in the concerned PSN. Thus, a PTU can have at most
nmessages in its buffer. It may be noted that in the Algorithm 1, a PTU can identify the directly deliverable messages in
O(n)time. Moreover, the actions such as, removing/updating message header and replicating/forwarding a message can be
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performed in constant time. Therefore, the time complexity of the proposed algorithm becomes O(n), which is true for the
Algorithm 2 as well.
VI. SIMULATION
This Section discusses the experimental setup used to simulate the effects of the above discussed diversities in PSNs.
A. Experimental Setup
The effects of heterogeneity in PSNs were evaluated using the ONE simulator [21]. Real-life connection traces of 78 nodes
from the Infocom’06 data set [22] were used.
The first scenario explored the possible impacts of asymmetry in the connection dynamics of the devices. The connection
“Up” events were considered to be uni-directional. The scenario was contrasted with the case when such events were bi-
directional.
In the second scenario, the effect of the buffer sizes on the delivery ratio of the messages was considered while using
the SnW, Random forwarding (single copy), PROPHET and Epidemic routing protocols. Next, the effects of limited energy
of the devices on the performance of PSNs were analyzed. The typical energy consumption rates for Motorola Milestone
(http://www.gsmarena.com/motorola milestone-3001.php) were considered. In particular, the initial energy was taken to be
1400 mAh, 3.5V, and transmission and scanning energies as 0.7Joule and 2Joule, respectively.
We investigated the effects of incompatible network interface of the devices. A fraction of nodes with two network interfaces,
if1 and if2, were considered. Half of the other nodes used if1, while the remaining nodes had if2.
Next, we explored the interactions of two different routing protocols – PROPHET and SnW. A group of nodes were considered
running as the PTUs, and varied their count from 0% to 50% in steps of 10%. In each case, half of the remaining nodes used
PROPHET, while the other half used the SnW protocol.
In the final scenario, the variation in communication degree was explored. In the first case, we divided the 78 nodes into
two groups. The first group contained the 10 −50% of the nodes incremented in steps of 10%; the other group contained the
remaining nodes. In the two other cases, we considered 5and 10 nodes, respectively, to be the PTUs. The remaining 68 nodes
were divided into two groups in a similar way.
Table I summarizes the other parameters.
TABLE I: Simulation Parameters
Parameter Value
Number of messages, size 400,50 KB to 1MB
Message creation time 5hour
Transmission speed, range 2Mbps, 10 m
SnW settings Binary mode, L= 16
PROPHET settings [2]
Duration 12,18,24 hours
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B. Performance Metrics
The performance was evaluated based on the following metrics:
•Delivery ratio of the messages (γ),
•Delivery ratio versus delivery latencies, and
•Overhead ratio (ω).
The delivery ratio gives the fraction of the created messages that were delivered to the respective destinations. A measure of
this metric evaluates the effectiveness of any message forwarding scheme. Let, Mand Md, respectively, denote the number
of messages created and delivered in the PSN. Further, let Mfdenote the number of messages forwarded in the network,
Mf≥Md. Then, the delivery ratio of the messages is defined as: γ=Md
M.
The overhead ratio is computed as: ω=Mf−Md
Md. It determines the efficiency of any routing protocol.
A plot of the delivery ratio of the messages versus delivery latencies provides insights in understanding the different
components of the delay associated with the delivered messages.
VII. RESULTS
This Section presents the results of the simulations, and related analysis.
A. Effects of Heterogeneous Connection Events
Figure 2 shows the impact on message delivery ratio when (all) the nodes used the SnW and PROPHET routing protocols.
The “true” and “false” cases indicate the scenarios whether the connection events were considered to be symmetric or not. It
can be observed that, for the lesser durations of simulation (or low message density per unit time), the asymmetry in connection
among the devices reduces the delivery ratio of the messages by 30 −40%. When sufficient time is given (the 24-hour case),
the ratio improves significantly.
B. Effects of Buffer Size
Figure 3 shows the message delivery ratio with different buffer sizes when SnW (L= 32), Random, PROPHET and Epidemic
routing protocols were used. In Random routing, a node forwards any message it has to the first node that it comes in contact
with. Figure 3 (a) & (b) indicates that with a fixed limit on message replication, excess buffer space does not help. Otherwise,
larger buffers enhance the delivery ratio (Figure 3 (c) & (d)) due to the reason that during each communication opportunity,
more number of nodes get a copy of a message.
Figure 4 plots the delivery ratio of the messages versus the delivery latencies. Figure 4 (a) presents the base case when
devices had unlimited energy, while Figure 4 (b) corresponds to the case when the devices had limited energy. It could be
observed that limited energy budgets significantly degrade the performance in, otherwise, homogeneous PSNs. Further, the
diversity in initial energies of the devices worsens the delivery ratio (Figure 4 (b)) compared to the scenario when all the nodes
had the same initial energies (indicated by “Same” in the graph).
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C. Impact of Incompatible Networking Devices
Figure 5 (a) shows how the delivery ratio of the messages is affected when a fraction of the devices have network interface
if2, while the others use if1. The 0% case represents the scenario when all the nodes had if1. It could be observed that the
delivery ratio steadily decreases as long as 20% of the devices have incompatible network interfaces. This could be explained by
considering the fact that all the nodes could be partitioned into two mutually exclusive groups based on their network interfaces.
As the size of each such group increases, more number of the nodes fail to exchange the messages among themselves, which
reduces the delivery ratio.
The impact on the message delivery ratio in the presence of the nodes with dual network interfaces is shown in Figure 5
(b). A steady increase could be observed till 20% presence of such nodes. This is due to the reason that the remaining nodes
with either if1 or if2 gets opportunities to transfer their messages to each other through the nodes with dual network interfaces.
D. Effects of Heterogeneous Routing Protocols
Figures 6 (a) and (b) present the delivery ratio of the messages when different routing protocols were considered. In Figure
6 (a), the plots labeled with “SnW (khour)” denote the base case performances when all the nodes used the SnW routing
protocol and the simulation duration was khour. The plots with labels “PROPHET (khour)” represent the scenarios when
different fraction of the population (shown along the x−axis) used the PROPHET protocol. It could be observed that, in
comparison to the base cases, when the fraction of the nodes using PROPHET protocol increases, the delivery ratio drastically
decreases. Finally, the delivery ratio obtained with equivalent fraction of PTU nodes are shown. It could be observed that,
while varying the fraction of PTUs from 10% to 50% in the network, the delivery ratio obtained is almost the same as the
best cases considered. Further, the Figure indicates that a mere presence of 20% PTUs in the network greatly enhances the
delivery ratio as compared to the scenarios when PROPHET protocol was used.
Figure 6 (b) shows the performance when the nodes used the PROPHET routing protocol together with the nodes using
different fractions of SNW and PTUs.
Figures 6 (c) and (d) show the overhead while using different types of routing protocols together for simulation durations
of 12 and 24 hours. It could be observed that, when all the nodes used the SnW routing protocol, the overhead ratio was the
least (around 15%). This is due to the reason that SnW assigns a fixed upper limit on the number of possible replications of
any message.
It could be further observed that the overhead largely increases in the presence of the PTUs. This behaviour could be
explained from Algorithm 2, where the PTU replicates a message from a PROPHET router with Lcopies to a SnW router.
In Figure 6 (d), it could be observed that the overhead ratio remains the same when all the nodes use PROPHET or a mix of
PROPHET and PTUs. This is accounted for the reason that the PTUs interact “normally” with the PROPHET routers without
increasing any overhead.
The variation in the communication degree (α) of the PSN is shown in Figure 7. It shows that with the increasing group
sizes, αsharply decreases. However, in the worst case when both the groups had equal number of nodes, the presence of 10
PTUs enhances αby 12%.
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VIII. OBSERVATIONS
The observations from Section VII are summarized in the following points:
•When the time window considered is small, for multi-copy message forwarding, the buffer size plays a significant role.
•Heterogeneous connection dynamics (the simplest case due to different transmission ranges) substantially reduces the
delivery ratio of the messages.
•Hardware incompatibility arising due to incompatible network interfaces is hard to address particularly because, one may
opt for software upgrade, but not for purchasing a new phone. Therefore, any contact opportunity with devices with
multiple interfaces should be used to the best. This may require the routing protocols to use information available from
the link-layer of the devices.
•For approaching reality, any new protocol or mechanism proposed should take energy consumption of the nodes into
consideration.
•The performance degradation due to software-based incompatibility among the routing protocols is severe, but could be
prevented. This does not require all the users to update their software. Rather, the presence of few “special” devices (for
example, devices with middlewares, or the PTUs as proposed here) could boost the performance.
IX. CONCLUSION
PSNs present an interesting communication paradigm, especially in the absence of global network connectivities. The
performance of the PSNs, however, could heavily degrade in the face of various diversities manifested by the hardware and
software of the devices. In this work, the effects of such degradation have been quantified through extensive simulations. To
counter the negative impacts of the heterogeneous routing protocols used by the devices, the use of PTUs has been proposed.
The results of performance evaluation showed that the use of PTUs can elevate the message delivery ratio to the value obtained
in a homogeneous network.
In future, it is intended to the consider the other forms of diversities, including the interactions among the diverse PTUs.
While multiple middleware architectures promise of universal interoperability, it is not clear whether deployment of such a
“single platform” to all the devices is feasible. Under such a scenario, the use of devices supporting two or more protocols,
which attempts to address heterogeneity in incremental steps, could be considered.
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SnW PTU PROPHET
routerInfo
sendMessages
sendMessages
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sendPredictables
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sendMessages
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Fig. 1: Interactions among different types of routing protocols.
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Messages delivered (%)
Simulation time (hour)
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SnW (false)
Fig. 2: Effects of (a)symmetric connection events on the delivery ratio of the messages.
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% of messages delivered
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Fig. 3: Impact of buffer sizes using (a) SnW (L= 32), (b) Random, (c) PROPHET and (d) Epidemic routing.
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Fig. 4: Delivery ratio versus delivery latencies of the delivered messages (a) without and (b) with energy constraints.
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Fig. 5: Effect of different networking interfaces when: (a) Different percentage of the nodes had incompatible network interface
if2, and (b) The nodes had dual network interfaces.
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Fig. 6: Percentage of messages delivered in presence of different types of routing protocols together with (a) SnW and (b)
PROPHET. Overhead ratio in presence of different types of routing protocols together with (c) SnW and (d) PROPHET.
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Fig. 7: Communication degree with different percentage of nodes in the first group.
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