Adaptive Opportunistic Routing for Wireless Ad
Hoc Networks
ABSTRACT
A distributed adaptive opportunistic routing scheme for multihop wireless ad hoc
networks is proposed. The proposed scheme utilizes a reinforcement learning framework to
opportunistically route the packets even in the absence of reliable knowledge about channel
statistics and network model. This scheme is shown to be optimal with respect to an expected
average per-packet reward criterion. The proposed routing scheme jointly addresses the issues of
learning and routing in an opportunistic context, where the network structure is characterized by
the transmission success probabilities. In particular, this learning framework leads to a stochastic
routing scheme that optimally “explores” and “exploits” the opportunities in the network.
Existing System
Motivation by classical routing solutions in the internet, conventional routing in ad hoc networks
attempts to find a fixed path along which the packeta are forwarded. Such fixed-path schems fail
to take advantage of broadcast nature and opportunities provided by the wireless medium and
result in unnecessary packet retransmissions.
Markov decision theoretic formulation for opportunistic routing is developed. It is shown
that the optimal routing decision at any epoch is to select the next relay node based on a distancevector summarizing the expected-cost-to-forward from the neighbors to the destination. This
“distance” is shown to be computable in a distributed manner and with low complexity using the
probabilistic description of wireless links.
A unifying framework for almost all versions of opportunistic routing such as SDF,
Geographic Random Forwarding (GeRaF) , and ExOR , where the variations in are due to the
choices of cost measures to optimize. For instance, an optimal route in the context of ExOR is
Further Details Contact: A Vinay 9030333433, 08772261612
Email: [email protected] | www.takeoffprojects.com
Adaptive Opportunistic Routing for Wireless Ad
Hoc Networks
computed so as to minimize the expected number of transmissions (ETX), while GeRaF uses the
smallest geographical distance from the destination as a criterion for selecting the next-hop.
Disadvantages:
Such fixed path schemes fail to take advantages of broadcast natureand opportunities provided
by the wireless medium and result in necessary packet retransmissions. The opportunistic routing
decisions, in contrast, are made in an online manner by choosing the next relay based on the
actual transmission outcomes as well as a rank ordering of neighboring nodes. Opportunistic
routing mitigates the impact of poor wireless links by exploiting the broadcast nature of wireless
transmissions and the path diversity.
Proposed System
In this paper we propose a distributed adaptive opportunistic routing algorithm (dAdaptOR) that minimizes the expected average per-packet cost for routing a packet from a
source node to a destination. This is achieved by both sufficiently exploring the network using
Further Details Contact: A Vinay 9030333433, 08772261612
Email: [email protected] | www.takeoffprojects.com
Adaptive Opportunistic Routing for Wireless Ad
Hoc Networks
data packets and exploiting the best routing opportunities. Our proposed reinforcement learning
framework
allows
for
a
low-complexity,
low-overhead,
distributed
asynchronous
implementation. The significant characteristics of d-AdaptOR are that it is oblivious to the initial
knowledge about the network, it is distributed, and it is asynchronous.
The main contribution of this paper is to provide an opportunistic routing algorithm that:
1) Assumes no knowledge about the channel statistics and network.
2) Uses a reinforcement learning framework in order to enable the nodes to adapt their
routing strategies,
3) Optimally exploits the statistical opportunities and receiver diversity.
Advantages:
Our proposed reinforcement learning framework allowfor a low complexity, low overhead,
distributed asynchronus implementation. The most significant characteristics of the proposed
solution are:
It is oblivious to the initial knowledge of network.
Further Details Contact: A Vinay 9030333433, 08772261612
Email: [email protected] | www.takeoffprojects.com
Adaptive Opportunistic Routing for Wireless Ad
Hoc Networks
It is distributed; each node makes decisions based on its belief using the information obtained
from its neighbors.
It is asynchronous; at any time any subset of noddes can update their corresponding beliefs.
DISTRIBUTED ALGORITHM
NOTATIONS USED IN THE DESCRIPTION OF THE ALGORITHM
Further Details Contact: A Vinay 9030333433, 08772261612
Email: [email protected] | www.takeoffprojects.com
Adaptive Opportunistic Routing for Wireless Ad
Hoc Networks
Further Details Contact: A Vinay 9030333433, 08772261612
Email: [email protected] | www.takeoffprojects.com
Adaptive Opportunistic Routing for Wireless Ad
Hoc Networks
Detailed Description of d-AdaptOR
The operation of d-AdaptOR can be described in terms of initialization and four stages
of transmission, reception and acknowledgment, relay, and adaptive computation. For
simplicity of presentation, we assume a sequential timing for each of the stages.
1) Transmission Stage:
2) Reception and acknowledgment Stage:
3) Relay Stage
4) Adaptive Computation Stage
System Flow:
Further Details Contact: A Vinay 9030333433, 08772261612
Email: [email protected] | www.takeoffprojects.com
Adaptive Opportunistic Routing for Wireless Ad
Hoc Networks
Flow of the algorithm. The algorithm follows a four-stage procedure: transmission,
acknowledgment, relay, and update.
Modules
1. Network formation
2. Packet Transmission
3. Acknowledgement Module
4. Relay Module
Further Details Contact: A Vinay 9030333433, 08772261612
Email: [email protected] | www.takeoffprojects.com
Adaptive Opportunistic Routing for Wireless Ad
Hoc Networks
5. Update Module
Module Description
1. Network Formation
In this module we can construct a topology to provide communication paths for
wireless adhoc network. Here the node will give the own details such as Node ID through
which the transmission is done and similarly give the neighbor nodes details.
2. Packet Transmission
In this module the node has transmit the packet from source to destination.
Transmission stage occurs at time in which node transmits if it has a packet.
3. Acknowledgement Module
In this module the nodes send acknowledgement details. Set of nodes that have
received the packet transmitted by node. In this module nodes send acknowledgement packet
who received the packet from the source. In the reception and acknowledgment stage,
successful reception of the packet transmitted by node is acknowledged to it by all the nodes.
We assume that the delay for the acknowledgment stage is small enough (not more than the
duration of the time slot) such that node infers by time. The acknowledgment packet of node
includes a control message known as estimated best score (EBS).
Further Details Contact: A Vinay 9030333433, 08772261612
Email: [email protected] | www.takeoffprojects.com
Adaptive Opportunistic Routing for Wireless Ad
Hoc Networks
4. Relay Module
In this module the node select the routing action according to the randomized rule.
Node transmits FO (forwarding), a control packet that contains information about routing
decision at some time strictly between times. If termination action is chosen, i.e. all nodes
in expunge the packet. Upon selection of routing action, the counting variable is updated.
5. Update Module
In this module the node update the following details. After finishing the
transmission and relay the node will update the score Vector. The node updates EBS
Message for future acknowledgements.
Hardware and Software Specification:
Hardware Requirements:
Processor
: Any Processor above 500 Mhz.
Ram
: 1 GB.
Hard Disk
: 10 Gb.
Compact Disk
: 650 Mb.
Input device
: Standard Keyboard and Mouse.
Software requirements:
Operating System
: Windows Xp.
Technology
: NetBeans 7.1
Jdk1.6.0_17
Further Details Contact: A Vinay 9030333433, 08772261612
Email: [email protected] | www.takeoffprojects.com
Adaptive Opportunistic Routing for Wireless Ad
Hoc Networks
UML DIAGRAMS:
Class diagrams:
DISTRIBUTED ALGORITHM
sender
+S_id: int
+S_pwd: string
Absence of channel
+Send packets()
+Acknowledgement()
+packet delivery no channel()
+Routing()
+transmission()
+acknowledgment()
+relay()
+update()
Reciever
+R_id: int
+R_pwd: string
+Receive()
+Send ack()
Further Details Contact: A Vinay 9030333433, 08772261612
Email: [email protected] | www.takeoffprojects.com
Adaptive Opportunistic Routing for Wireless Ad
Hoc Networks
Usecase diagrams:
Further Details Contact: A Vinay 9030333433, 08772261612
Email: [email protected] | www.takeoffprojects.com
Adaptive Opportunistic Routing for Wireless Ad
Hoc Networks
users login
send data
sender
channels not present
Reciever
Distributed algorithm
Packet delivery
Access data
Logout
Further Details Contact: A Vinay 9030333433, 08772261612
Email: [email protected] | www.takeoffprojects.com
Adaptive Opportunistic Routing for Wireless Ad
Hoc Networks
Sequence diagram:
Sender
Channels absent
Distribution algorithm
Reciever
1 : Select data & send to reciever()
2 : send data()
3 : Channels absent()
4 : routing()
5 : Send data without channels()
6 : Transmit packet without any channels()
7 : Access data()
Further Details Contact: A Vinay 9030333433, 08772261612
Email: [email protected] | www.takeoffprojects.com