LOAD BALANCING IN ANT BASED ALGORITM IN MANET

SEMINAR 

SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENT FOR THE AWARD OF THE DEGREE OF

MASTER OF TECHNOLOGY

(Computer Science and Engineering)

 

 

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Submitted By:- Navish Jindal 1269166 M.Tech(C.S.E) L.L.R.I.E.T. Moga

CONTENTS

What is MANET Ant Based Algorithm Pheromone Pheromone creation Pheromone evaporation Principles of ant colony optimization Phases of ant based optimization Load balancing Performance metrics

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WHAT IS MANET

A mobile ad-hoc network (MANET) is a set of mobile nodes which communicate over radio and do not need any infrastructure.

This kind of networks are very flexible and suitable for several situations and applications.

All the nodes are mobile and connected dynamically. Topology changes rapidly.

Suitable for emergency situations like natural or human-induce disasters, military conflicts,emergency medical situations, etc. 3

MANET

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ANT BASED ALGORITHM

Ant as a single individual has a very limited effectiveness. But as a part of a well-organized colony, it becomes one powerful agent, working for the development of the colony.

Each ant is able to communicate, learn, cooperate, and all together they are capable of develop themselves and colonies a large area.

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PHEROMONE

Pheromones are the chemicals that are excreted by ants of same species when they move.

These are also called alarm pheromones.

Pheromone deposited on ground forms a pheromone

trails which allows the ants to find good sources of food that have be previously identified by other ants.

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PHEROMONE CREATION

Initiate pheromone value for all the nodes route table

calculated by equation

Nh = number of hops for ant to travel from source to next node.

α = constant value parameter 1 > > 0 𝛼

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Pheromone = α/Nh

PHEROMONE EVAPORATION

The benefit is to remove any unused routes that will consume memory space. The evaporation function is calculated by:

All pheromone values in routing table decreases over time.

Pn: New evaporation pheromone value.

P: Pheromone value calculated at each node.

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Pn = P - 0.8* P

PRINCIPLES OF ANT COLONY ALGORITHM

The ability of ants to self organize is based on three principles.

Random and rapid search

Stigmergy

Shortest path

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RANDOM AND RAPID SEARCH

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ANTS AGENTS CAN BE DIVIDED INTO TWO SECTIONS

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STIGMERGY

Stigmergy is defined as method of indirect communication in a self organising system where its individual parts communicate with one another by modifying their local environment.

The implementation of ant algorithms is made possible by the use of so-called stigmergic variables, i.e., variables that contain the information used by artificial ants to indirectly communicate.

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SHORTEST PATH

In a simple case, when two ants leave the colony at the same time and take different paths to a food source, marking their trails with PHEROMONE, the ant that took the shorter path will return first.

As a result of this effect, the shortest path will emerge rapidly because a shorter path will have a higher pheromone concentration. In this way all the ants follow the best and shortest path.

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PHASES OF ANT BASED ALGORITHM

1. Route Discovery Phase

2. Route Maintance Phase

3. Route Failure Handling

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ROUTE DISCOVERY PHASE

Route discovery phase uses control packet to discover route from source to destination. The control packets are mobile agents which walk through the network to establish routes between nodes.

Route Discovery Phase, shows the propagation of Forward ANTS from source to destination.

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A need to send to G

Lookup Cache for route A to G

Route found

?

Start Route Discovery Protocol

Continue normal

processing

Route Discovery finished

Packet in

buffer? Send packet to next-hopdone

Buffer packet

no

Write route in packet header

yes

wait

ROUTE DISCOVERY

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ROUTE MAINTANCE PHASE

It is essential to find the goodness of a route regularly and update the pheromone counts for the different routes at the source nodes.

To accomplish this, when a destination node receives a packet, it probabilistically sends a Congestion Update message to the source. This Congestion Update message also serves an ACK to the source.

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ROUTE FAILURE HANDLING PHASE

This phase is responsible for generating alternative routes in case the existing route fails. Every packet is associated with acknowledgement; hence if a node does not receive an acknowledgement, it indicates that the link is failed.

This helps in load balancing. That is, if the optimal path is heavily loaded, the data packets can follow the next best paths.

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PHEROMONE VALUES :P3> P1 >P5

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PROBLEM IN MANET DUE TO LOAD

There is a Congestion due to broadcasting of Ants in Ant algorithm.

They are unable to provide good performance in large volume of traffic.

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LOAD BALANCING

This load balancing is achieved by calculating the threshold value of each routing table through average number of requests accepted by each node.

The number of packets can be controlled that has been send.

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PERFORMANCE METRICS

Packet Delivery Ratio :- It is calculated by dividing the

number of packets received by the destination over the

packets originated by source.

The better the delivery ration the more accurate routing

protocol.

PDR= Σnumber of all packets received / number of all

packets send

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AVERAGE END TO END DELAY

Average end to end is the average time that a packet takes to reach the destination in seconds.

It is calculated by subtracting time at which first packet was transmitted by source from time at which first data packet arrived to destination.

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PERFORMANCE METRICS

Performance parameters AODV ANT ALGORITHM

Packet delivery ratio low high

End to end delay high low

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CONCLUSION

The algorithm is based on balancing the load among the routes by calculating threshed value of each routing table.

This defines MANET comparison of its better

performance with AODV routing protocol based on ant algorithm is in terms of packet delivery ratio, end to end delay.

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FUTURE WORK

The future work could be to investigate different methods to further limit the traffic or load and compare the ant based algorithm for other proactive and reactive routing protocols.

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REFERENCES

[1] Mesut G¨unes¸,UdoSorges,ImedBouazizi {mesut, udo, imed}@i4.informatik.rwth-aachen.de

Department of Computer Science, Informatik 4 Aachen University of Technology Aachen, Germany

“ARA – The Ant-Colony Based Routing Algorithm for MANETs ”∗

[2] Payman Arabshahi and Andrew Gray, “Adaptive Routing in Wireless Communication Networks

using Swarm Intelligence”.

[3] Kalaavathi B, Madhavi S, VijayaRahavan and Duraiswamy K, “Review of Ant Based Routing

Protocols for MANET” International Conference on Computing, Communication and Networking,

Dec 2008.

[4]. Vinh Dien HOANG. Zhenhai SHAO and Masayunki FUJISE, “Efficient Load balancing in

MANETs to Improve Network Performance”, International Confrence on ITS Telecommunications

Proceedings, 2006.

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REFERENCES

[5] Mamoun Hussein Mamoun “Important Characteristic of Differences between DSR and AODV

Routing Protocol”, MCN 2007 Conference, November 7-10, 2007.

[6] S. Prasad, Y.P.Singh and C.S.Rai , “Swarm Based Intelligent routing for MANET”, International

Journal of Recent trends in Engineering Vol 1,No.1 ,May 2009.

[7] Hamideh Shokrani and Sam Jabbehdari, “A Survey of Ant Based Routing Algorith for Mobile Ad-

Hoc Networks”, International Confrence on Signal Processing Systems, 2009.

[8] Al-Dahoud Ali, Mohamed A. Belal and Moh’d Belal Al-Zoubi, “Load Balancing of Distributed

Systems Based on Multiple Ant Colonies Optimization”, American Journal of Applied Sciences 7

(3): 433-438, 2010.

[9] Shivanajay Marwaha Jadwiga Indulska Marius Portmann “Biologically Inspired Ant-Based Routing

In Mobile Ad hoc Networks (MANET): A Survey” Symposia and Workshops on Ubiquitous,

Autonomic and Trusted Computing, 2009 29