Presented By:ARYA.B.SRoll. No: 32S7 CSMACE

ABSTRACTABSTRACTAnt colony optimization (ACO)

◦ Stochastic approach for solving combinatorial optimization problems like routing in computer networks

Food accumulation methodology Position based routing algorithms (POSANT) DrawbackThis paper presents

◦ A new routing algorithm for MANET by combining the concept of Ant Colony approach and Zone based routing approach

◦ Using clustering to get shortest path with small number of control messages to minimize the overhead.

INTRODUCTIONINTRODUCTION

Wireless Sensor Network RoutingAnt colony optimizationZone based routing algorithms

OVERVIEW OF ANT COLONY OVERVIEW OF ANT COLONY ROUTING ALGORITHMROUTING ALGORITHMAnt colony algorithm (ACO)

◦ It is a stochastic approach for solving combinatorial optimization problems like routing in computer networks.

To find the shortest paths from source to destination nodes

The idea of this optimization is based on the observation of how ants optimize food gathering in the nature

The Shortest Path Problem In The Shortest Path Problem In A Real Ant ColonyA Real Ant ColonyA real ant colony is able to find

food and follow the shortest path from the nest to the food.

POSANT ROUTING ALGORITHMPOSANT ROUTING ALGORITHMPOSANT is ant colony optimization based

routing algorithm which uses location information to improve its efficiency

Zones In Posant

Zone Selection Algorithm of POSANT

if (abs(θH) >= z5)θH = abs(θH) - z5;if(((abs(θH) < z1) && (abs(θH) >= 0.0)) || ((abs(θH) > z4) &&(abs(θH) <= z5)))ret = 1;elseif (((abs(θH) < z2) && (abs(θH) >= z1)) || ((abs(θH) > z3)&& (abs(θH) <= z4)))ret = 2;elseif((abs(θH) <= z3) && (abs(θH) >= z2))ret = 3;return ret;Where, z5 = 2π, z4 = 7π/4, z3 = 5π/4, z2 = 3π/4, z1 = π/4.

Route Establishment In Posant

ZONE BASED ANT ROUTING USING ZONE BASED ANT ROUTING USING CLUSTERCLUSTER

ClusteringPhases Of Zone Based Clustering

Algorithm◦Phase I :Cluster Formation ◦Phase II : Zone Formation ◦Phase III : Mobility Management of

Cluster Heads through Selection of Surrogate Heads

Max-Min D-Cluster Formation Algorithm

The heuristic has four logical stages: ◦ Propagation of larger node ids via floodmax, ◦ Propagation of smaller node ids via floodmin, ◦ Determination of clusterheads,◦ The linking of clusters.

Initial Cluster formationData StructuresBasic Idea

◦Floodmax◦Floodmin

Algorithm:Algorithm:Step I: At some common epoch each node initiates 2d

rounds of flooding of information exchange (node id) where d is the given heuristic. In this algorithm, flooding occurs once, at the time of initial cluster formation. Each node maintains a logged entry of two arrays, WINNER and SENDER to store the results of each flooding round.

Step II: Initially each node sets its winner to be equal to its own node id.

Step III: This is the phase for FLOODMAX where a node chooses the largest value among its own WINNER array and this process continues for d rounds.

Step IV: This FLOODMIN phase follows FLOODMAX where a node chooses the smallest rather than the largest value as its new WINNER.

Step V: After these two d rounds of information exchange a node is able to determine its cluster-head .

Cluster formation in a network of 25 nodes.

Zone Formation algorithmZone Formation algorithmStep I: The cluster head broadcasts get_Position_forAll (

) request message along with its own GPS to get percolated within d hop.

Step II: All member nodes in turn unicast back the message node_GPS ( ) to the cluster-head using geographical routing.

Step III: Cluster-head receives all the GPS values of its members and calculates the maximum limiting coordinates for Left, Right, Up and Down values to define its boundary.

Step IV: The cluster head then broadcasts the message get_Boundary_values ( ) within the d hop transmission range to notify all the member nodes about the cluster boundary.

Step IV: All the member nodes become alerted about the rectangular cluster boundary information, which can be verified while changing their positions and these geographical formed boundaries are considered as zones.

◦Cluster Maintenance protocol using GPS technology

Route Establishment Procedure of Zone based ANT Colony

Route establishment Algorithm of Zone Route establishment Algorithm of Zone based ANT Colonybased ANT Colony S unicast data-packet DP to ClusterHead(S) [Data Packet DP

consists of Destination Node address + Message M which need to be delivered to D].

CH(S) searches its Member List Table to see if D is a member of CH(S)

If CH(S) finds that D is its own member, send feedback to S and deliver the message M to D

If CH(S) finds that D is not its own member, CH(S) generates (n-1) forward ants with unique sequence numbers to send them to (n-1) reachable Cluster heads through multi-hop paths.

Each forward Ant, is forwarded towards boundary nodes of Cluster(S).

From these boundary nodes, forward Ants are sent to those neighbour nodes, which are boundary nodes of other clusters.

From this boundary nodes of other clusters, forward ants travels to the Cluster head of other Clusters.

Route establishment Algorithm of Zone Route establishment Algorithm of Zone based ANT Colony (Cont….)based ANT Colony (Cont….) When forward Ant comes to a Cluster head, sequence

number of this forward ant is stored in this Cluster head to keep track of duplicate entry.

Each Cluster head checks the sequence number of the forward ant and see if it already has the sequence stored in it.If no, it searches its Member List Table to see if D is its member. Otherwise it kills the forward and as it has already searches for this ant. Thus this algorithm avoids loops.

When any of the Cluster heads finds that D is its member, it kills the forward Ant and generates Backward Ant with same sequence number.

Cluster head which has D as its member node,delivers the message M to D.

Then sends back the Backward Ant to the Source node S as a feedback.

When a Cluster head finds that D is not its member,it sends the forward ant to its neighbour cluster to search.

Route Route establishment establishment Flow Chart of Zone Flow Chart of Zone based ANT Colonybased ANT Colony

COMPARATIVE STUDY OF OVERHEAD OF COMPARATIVE STUDY OF OVERHEAD OF POSANT WITH THAT OF ZONE BASED ANT POSANT WITH THAT OF ZONE BASED ANT COLONY ROUTINGCOLONY ROUTING

Overhead Comparison◦By varying Zone size

COMPARATIVE STUDY OF OVERHEAD OF COMPARATIVE STUDY OF OVERHEAD OF POSANT WITH THAT OF ZONE BASED ANT POSANT WITH THAT OF ZONE BASED ANT COLONY ROUTING (Cont..)COLONY ROUTING (Cont..)

◦By varying Node Number

COMPARATIVE STUDY OF OVERHEAD OF COMPARATIVE STUDY OF OVERHEAD OF POSANT WITH THAT OF ZONE BASED ANT POSANT WITH THAT OF ZONE BASED ANT COLONY ROUTING (Cont..)COLONY ROUTING (Cont..)

◦By varying Mobility

COMPARATIVE STUDY OF OVERHEAD OF COMPARATIVE STUDY OF OVERHEAD OF POSANT WITH THAT OF ZONE BASED ANT POSANT WITH THAT OF ZONE BASED ANT COLONY ROUTING (Cont..)COLONY ROUTING (Cont..)

◦HOP Count Comparison By varying number of nodes

COMPARATIVE STUDY OF OVERHEAD OF COMPARATIVE STUDY OF OVERHEAD OF POSANT WITH THAT OF ZONE BASED ANT POSANT WITH THAT OF ZONE BASED ANT COLONY ROUTING (Cont..)COLONY ROUTING (Cont..)

By varying mobility

COMPARATIVE STUDY OF OVERHEAD OF COMPARATIVE STUDY OF OVERHEAD OF POSANT WITH THAT OF ZONE BASED ANT POSANT WITH THAT OF ZONE BASED ANT COLONY ROUTING (Cont..)COLONY ROUTING (Cont..)

◦Delay Comparison ◦Throughput Comparison

By varying number of nodes

COMPARATIVE STUDY OF OVERHEAD OF COMPARATIVE STUDY OF OVERHEAD OF POSANT WITH THAT OF ZONE BASED ANT POSANT WITH THAT OF ZONE BASED ANT COLONY ROUTING (Cont..)COLONY ROUTING (Cont..)

By varying Mobility:

Advantage of Zone based Advantage of Zone based ANT colony over POSANTANT colony over POSANTOverheadHOP CountThroughput

CONCLUSION CONCLUSION Zone based routing using ant colony optimization

aims to support zone based routing with minimum routing overhead for mobile ad hoc networks.

The idea behind this zone based routing is to allow the nodes within each zone to get referred with the zone boundaries and control the node.

Ant Colony technique merged with Zone based technique to optimize memory utilization, overhead and throughput.

In zone based routing, each zone member is aware of its mobility using the zone boundary values.

It allows the node to inform about their mobility and thereby enabling the protocol to find the mobile destination quickly with minimum overhead.

Future WorkFuture Work It always uses shortest path for routing the data packets. Ants always traverse the shortest path from source to

destination through the source cluster head and destination cluster head using geographical shortest path forwarding technique.

So here always the shortest path is selected for routing and load balancing concept has not been incorporated in this routing algorithm.

Load balancing can be introduced by selecting second shortest path sometimes in case we have large number of data packets to send so that the same set of nodes should not remain selected in the route path always.

Thus load balancing can also be handled in Zone based Ant colony algorithm.

This can be implemented as a future work.

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