Routing in Opportunistic Networks

1 |School of Software Engineering(南昌航空大學)
Survey on Routing in Opportunistic Networks
Auwal Tijjani Amshi
Email: auwalamshi@gmail.com
School of Software Engineering, Nanchang Hang Kong University (南昌航空大學).
Abstract - In Opportunistic Networks one of the most important issues relies on the selection
of the best intermediate node to forward the messages towards the destination. These issues of
selection make opportunistic network a challenging research field. In this paper we survey the
existing routing algorithms in opportunistic network. The routing algorithms are classified based
on their routing behaviour and comparisons among these algorithms are also presented in this
paper. Suitable message forwarders are selection using Forwarding Decision Based on either
floating, Randomness, or Probability obtained previous meetings. So this paper basically
overview and disused those potential method and Techniques to select next hop to forward the
packets (message) to destination.
Keyword:Opportunistic Networks, store-carry forward, flooding, Prediction, routing techniques.
1. INTRODUCTION
By definition A Network has nodes that are interconnected to each other these nodes are usually
static. However, in an Opportunistic Network nodes are dynamic in nature. Communication
possible even if no connecting route exists between nodes, and routes are built dynamically- i.e.,
communication path not predetermined. Opportunistic network [1]
is a new network frame
developing from ad hoc networks. It can transfer the packets by hops while nodes moving around
and finally reaching the destination node on condition of split network. Contact refer to
connection between two nodes. When node are in the same communication domain then link is
establish and communication occurs. Likewise when leaving the communication domain the
communication end or disrupted.
Opportunistic networks perform a store-carry-forward model to carry services by
multiple hops [1] [2]. If the current node fails to obtain the next hop leading to destination, it stores
the message and waits for forwarding opportunity while moving around. Fig. 1 illustrate the
store-carry-forward model.

… …
Fig. 1 store-carry-forward model in opportunistic networks
In Fig. 1 There is no direct path from the source node S to the destination node D. So node S
delivers the message to node 3.Node 3 stores and carries the message till the time of t2 then
deliver the message to the node 4. Finally, until time of t3, node 4 and the destination node D
move to the same communication domain.
Opportunistic networks is used as a network frame in many application areas such as
vehicular Ad Hoc network (VANET), mobile computing sharing, mobile data offloading [4][5][6]
etc.All the above listed are possible because of the easy to deploy and low cost characteristics of
Opportunistic networks. With Opportunistic networks frame, massage sharing, content
distribution, resources sharing and other function can be realized regardless of the infrastructure.
The dynamic nature of Opportunistic network make it difficult to determine the
forwarding path. [1] Improve the performance of transmission by using multiple copies of
message and choose suitable next hop according to the criteria of transmission utility. [3] Survey
the existing routing algorithms in opportunistic network. The routing algorithms are classified
based on their routing behaviour and compare these algorithms in other to improve routing in
Opportunistic network. [7]Proposing a multi-agent system where each node of network runs an
embedded instance of an agent. The main tasks of such agent are to collect context data about
current node, predict future values of context parameters and make decisions about routing.[21]
Focus on the deployment of Native Ferries in regions which takes the responsibility for
collecting data from the nodes in those regions and to deliver to the External Ferry. Native
Ferries are special mobile nodes which take the responsibility for collecting data from nodes in
its region and have fewer constraints in resources, equipped with renewable power, large
memory and powerful processors.[20]Incorporate a concept to develop an adaptive, reactive
routing protocol foropportunistic networks which can predict the future contactopportunities with
certain levels of confidence and showthat the adaptive routing protocol outperforms existing
routingalgorithms.Routing in opportunistic network is composed of two factors:
1. To find a path to destination: There is no fixed path between source and destination in the
opportunistic network. Intermediate nodes are used to form paths dynamically.
2. Selection of next hop forwarder: Finding a helper node which can forward data to
destination as earlier as possible.

So messages may have to be buffered for a long time by intermediate nodes, and the
mobility of those nodes must be exploited to bring messages closer to their destination by
exchanging messages between nodes as they meet. Researchers have developed some routing
algorithms for opportunistic network based on store-carry- and forward mechanism. These
algorithms are shortly discussed and comparison is presented in the following section.
2. ROUTING TECHNIQUES
In this section we discussed possible routing techniques in opportunistic network and at the end
of the section we compare those techniques based on their Forwarding Decision, Mobility Model
and No. Of replication of massage (packets).
DirectTransmission
In direct transmission routing, the source node generates message and stores it in its
buffer until it meets the destination directly. To achieve data forwarding in opportunistic
network, Spyropoulos et al [8] have proposed a single copy routing based on hop by hop fashion.
A single copy of the message is forwarded from source to destination.The figure below show an
example.
Fig. 2 Example of a direct transmission routing.
Flooding Based
In flooding based routing, the source node generates multiple copies of the message and
injects those into the network. This injection of replicated message is continued until destination
receives the message.[9][10] Fig. 2 illustrate the routing behavior of flooding based routing.

Fig. 2 Flooding based routing.
The flooding at source can be classified into two categories as uncontrolled and controlled [8].
a. Uncontrolled
In this type of routing, replication of source data is not restricted with any limits.To
reduce long delivery delay, Vahdat et al [11] have proposed epidemic routing. It utilizes the
epidemic algorithm which was originally proposed for synchronizing replicated databases. The
epidemic algorithm ensures that a sufficient number of random exchanges of data in the network
and guarantees that all nodes will eventually receive all messages. The epidemic routing is
similar to the flooding because it tries to send each message to all nodes in the network. For this
reason, Epidemic Routing incurs significant demand on both bandwidth and buffer.
b. Controlled
The uncontrolled approach is refined to limit the number of packets to be replicated to
reduce the network contention.To bound the overhead of delivering a message, Spyropoulos et al
[12] proposed a technique called Spray and Wait to control the level of flooding. In the spray
phase, there are L (Limit) number of copies that are initially spread over the network by the
source node or other nodes to L distinct relays. In the wait phase, if the destination was not found
during the spray phase, each node who has a copy of message will perform direct
transmission.When it is only one copy left, it switches to direct transmission.
Prediction Based
In prediction base routing massage are forward by predicting the behavior of the neighbor
nodes for taking some forwarding decisions. It forwards a message to its neighbor node if and
only if that neighbor node has a higher delivery predictability value.Lindgren et al have proposed
a probabilistic routing protocol, called PROPHET (Probabilistic Routing Protocol using History
of Encounters and Transitivity) and lebrunet al [5]have proposed a method using the motion
vector (move).

a. PROPHET
PROPHET estimates a probabilistic metric called delivery predictability. This metric
indicates the probability of successfully delivering a message to the destination from the local
node. To achieve this,[13] “delivery predictability” is defined at a node for every other contacted
node. The delivery predictability of node A to node B is denoted by PA,Band the range of delivery
predictability value is defined as 0≤ PA,B≤ 1. If node A with a message to a destination node D
contacts with node B, node A and node B exchange summary vectors and delivery predictability.
Then, node A compares PA,D and PB,D. If PB,D> PA,Dthe message to destination node D is copied
to node B. Otherwise, the message is not copied to node B.
Fig. 3 nodes encountes in PROPHET
Given Fig. (3) As set of in time t(i)which is represented as {a, b, c and d }.In [14] explain, if two
nodes n(i) and n(j) are often encountered, they have high delivery predictability to each other. On
the other hand, if a pair of nodes n(i) and n(j)does not encounter each other in a while, they are
intuitively not good forwarders of messages to each other.
b. MoVe
The move scheme uses the knowledge of relative velocities of a node and its
neighbouring nodes to predict the closest distance between two nodes [15] [16].After the nodes
future locations are calculated, messages are passed through the nodes that are moving closer to
the destination.

Fig. 4 A Time evolving with relative velocities
In Fig. 4 the source can first send its data to his neighbor 1, then 1 will carry the data while
moving until it meets another node 3 and relays this data to node 3. Node 3 will carry this data
until it meets destination D. In the end the source node S can send data to the destination node D
successfully.
MessageFerry
In these techniques, additional mobile nodes are used. These nodes are known as ferries
and used for message delivery in the network[17][18].The route of these ferries are controlled to
increase the delivery performance by using the store-and-carry mechanism.These message ferries
allow nodes to communicate when the network is disconnected and when nodes do not have
global knowledge of the network.
Fig. 5 message ferries routing.
Fig. 5: At the start the ferry F follows a selected default route and sporadically broadcasts its
location to nodes employing a long vary radio [5]. Once a node S finds the ferry is close and

needs to send or receive messages via the ferry, it sends a Service Request message to the ferry
mistreatment its long vary radio. This message contains the node’s location info. Upon reception
of asking message, the ferry adjusts its mechanical phenomenon to fulfil the node. To guide the
ferry movement, the node sometimes transmits Location Update messages to apprize the ferry of
its new location. Once the ferry and therefore the node square measure shut enough, they
exchange messages via short vary radios.
Table 1: Comparison of Routing Techniques
Algorithm No. Of replications Mobility Model used Forwarding Decision
Based on
Single copy routing Single Random Way point Node willingness
Move Algorithm Single Randomize d Model Node’s motion vector
Spray and Wait Limited (L) Random way point,
Random walk, Real
data
Randomness
PROPHET Single Random way point Probability obtained
previous meetings
Epidemic Routing Multiple Random way point Flooding
3. SUMMARY
The inherent dynamic nature of Opportunistic Network makes it a challenging research field. It
is difficult to determine a routing path to destination in advance. Aiming at improving the
performance of delivery, multiple copies of one message are delivered simultaneously. However,
suitable forwarders are chosen according to some utility-based criteria [8]. But there are still
some problems caused by the dynamic nature: (1) high delivery latency; (2) low delivery ratio;
(3) too much storage and energy consumption; (4) bad user experience etc. A lot of studies has
been made in other to solve those problems some succeeded but some are still facing problems
with dynamic nature of Opportunistic Networks.
Flooding based approaches provides better delivery ratio but introduces network congestion
[8].So prediction based mechanisms were proposed to route data by predicting whether the data
could be delivered to destination or not. This type of algorithms has reduced network congestion
but delivery ratio was affected as compared with flooding based approaches.

Prediction and flooding based approaches are combined to take advantages of those methods.
This performs better than flooding and prediction based schemes. But still there is a need for
research in improving data delivery ratio with reduced resource consumption.
4. CONCLUSION
Opportunistic network is formed by devices with short range communication interfaces. Routing
in such network is a big issue. In order to increase delivery ratio and to reduce overhead in the
network.The existing routing algorithms or techniques in opportunistic network are discussed
and compared in this study. Routing algorithms are classified based on their routing behaviour.
This studyfurtherdiscusseddynamic nature of Opportunistic Networkand some problems caused
by the dynamic nature.
5. REFERENCE
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Routing in Opportunistic Networks

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