Volume 5, Issue 10, October 2019 (ISSN: 2394 – 6598)
COMPARATIVE ANALYSIS OF SWARM BASED ROUTING PROTOCOLS IN
MOBILE AD-HOC NETWORKS
Swapnil Mishra1, Rajendra Purohit2
1M. Tech. Scholar, Department of Computer Science &Engineering, Jodhpur Institute of Engineering and Technology, Jodhpur, India
2Associate Professor, Department of Computer Science&Engineering, Jodhpur Institute of Engineering and Technology, Jodhpur, India
Abstract— A Mobile Ad hoc Network (MANET) is a self-arranging (self-ruling) arrangement of portable switches (and related hosts) associated by remote connections the association of which structure a discretionary topology. The switches are allowed to move haphazardly and compose themselves self-assertively, in this way, the system's remote topology may change quickly and unusually. Such a system may work in an independent manner, or might be associated with the bigger web working as a crossover fixed/specially appointed system.
Swarm Intelligence or SI is a developing field which is recently noticeable by many researchers in the field of network routing. Swarm Intelligence is mainly exhibiting complex behaviors which comes up from simple individual behaviours and interactions, which is commonly observed in nature, mainly among social insects like ants, bees, fishes etc. and they have individual little intelligence and follows basic rules using local information obtained from the surroundings. In this paper, traditional and SI based routing protocols have been discussed and performance comparisons given with is help of different output graphs for routing protocols such as Ant based AODV (AAODV) and Honeybee based AODV (HAODV) using the NS-2 simulation tool.
The performance of routing protocols has been studied in terms of different parameters like throughput and packet delivery ratio (PDR).
Keywords –MANET, SI, AAODV, HAODV.
I.INTRODUCTION
Recently, many network researchers are studying networks based on new communication techniques, more than ever wireless communications. Mobile Ad hoc Network or MANET is a self-configuring system of mobile routers which are wirelessly connected. Such network may work in a separate manner, or may be connected to the larger internet operating as a hybrid fixed/ad hoc network.SI is an Artificial Intelligence technique based on the study of collective behavior in decentralized, self-organized systems. Swarm intelligence is basically the emergent collective intelligence of collection of simple agents. It increases complex and intelligent behavior through simple, unsupervised interactions between a total numbers of independent swarm members.
SWARM INTELLIGENCE
PSO ACO Honeybee Figure 1. Different models of Swarm Intelligence
Swarm Intelligence offers solution for complex optimization problems which are not easily handled by other methods. Swarm is defined as a group of movable agents that jointly resolve problems. Every distinct entity of the group has simple order of action and access to a certain quantity of data through its instantaneous neighbor. The swarms able to complete very tough problems of the computation and optimization even the members in swarm have limited data and simple actions. Swarm Intelligence involves Particle Swarm Optimization or PSO, Ant Colony Optimization or ACO and Honey bee models. The behavior of these models is same as the behavior of real insects for food searching, prearranged living and self-protective styles for computational problems. The SI based techniques are more appropriate for the routing optimization and energy resources optimization.
II.ROUTINGPROTOCOLSANDALGORITHMS In this section, we review selected SI routing protocols for MANETs and highlight their properties with respect to the taxonomy of routing protocols. In the following subsections, we discuss Ant based
AODV (AAODV) and Honeybee based AODV (HAODV) protocols.
A. AAODV
Ant- AODV is a merge of protocols i.e. both reactive with proactive protocols. It has the ability to bear the cost of the friend and defer sand issues, identifying with network all the more effectively, when contrasted with conventional AODV steering convention. The responsive component is performed by means of AODV and the proactive component is done through subterranean ant-based methodology [26].
The goal of the ant-based algorithm right now is to perpetually endeavor to diminish defer hold up in addition the network is season of inertness, developing the likelihood to the disclosure courses speedily, Ant- AODV's steering is for the most part relies upon the check of bounces and its goal is to get familiar with the topology of the system, lacking other exact occupations, as various to the lion's share subterranean ant-based algorithms.
B. Honey Bee Based Protocol
The Honeybees algorithm is fundamentally population-based and nature-inspired method for optimization difficulties that copycats the food foraging nature of swarms of honey bees. This method utilizes the idea of honey bees for food searching, defence and locatable nature of actual honeybees.
According to the work, the artificial bees are separated into three groups like employed bees, onlooker bees and scout bees with performing their corresponding duties. The bee’s algorithm works with the initiation of the settlement of scout bees in the search space and fitness of the scout bees is estimated [27].
The bees which are having greater fitness then a threshold is preferred as selected bees and corresponding visited locations by then are nominated for neighbourhood search.SI based methods are iterative and termination criteria are planned for the termination of the algorithm. The main application of Honeybees based algorithms are in the area of ad hoc and wireless sensor networks.
III.PROPOSEDALGORITHM
This section deals with the Honeybee based AODV with the algorithm steps made for building this novel protocol.
A. Algorithm
Step 1. Initialize the Routing table and the HB parameters for nodes.
Step 2. Randomly allocate bee to every node. Every bee must move to next neighbour node, depending on the probability distribution and depending on destination node.
Step 3. The local Routing table update is performed.
Step 4; Source node Broadcast the Forward scout to all nodes;
Step 5 : For All Node(id):
If (Broadcast already received):
Delete forward scout End
Else:
If (node== Destination node):
Send backward scout to source node.
End Else:
If (is accumulator):
add forward scout to accumulator Else:
Create accumulator
add forward scout to accumulator Broadcast the accumulator.
Step 6. Compute the optimal path and global update of Routing table. Send packet to destination node
Step 7: End
IV. SIMULATION ENVIRONMENT
There are some quantitative metrics that can be used for evaluating the performance of routing protocols in MANET.
A. Performance Matrices
We have used the following parameters for evaluating the performance of two routing protocols AAODV (Ant Based AODV) and HAODV (Honeybee based Ad-hoc On-demand Distance Vector):
1) Throughput: Ratio of the packets delivered to the total number of packets sent.
2) Packet Delivery Fraction: It is the ratio of data packets delivered to the destination to those generated by the sources. It is calculated by dividing the number of packets received by destination through the number packet originated from source.
PDF = (Pr/Ps)*100
Where Pr is total Packet received & Ps is the total Packet sent.
B. Simulation Setup
As already discussed, we have taken routing protocols, specifically AAODVand HAODV. InNS2 simulation, the random way point mobility model were used andnode speed is changedlike1s,2s, 4s, 5s,10s and 30s.The performance investigation is performed on Ubuntu Operating System. NS2 was installed on this platform.In this scenario some parameters with a
certain value are considered. These specific values are given in TABLEI.
TABLE I
Scenario for Implementation of AAODV and HAODV
Platform Ubuntu
Simulator NS2
Protocols AAODV,HAODV
Channel type Wireless channel Traffic type Constant bit rate (CBR) Number of nodes 50
Simulation area size
500 x 400
Mobility model Random way point mobility
Antenna model Antenna/Omnidirectional Packet size 712 Bytes
Max. packet in ifq 50
V. RESULT AND DISCUSSION A. Throughput
1. In Fig. 2, shows that Swarm HAODV have high Throughput than AAODV When as no of node speed increases Throughput for HAODV will increase consistent in comparison with AAODV protocols.
Fig.2 Throughput versus simulation time for AAODV and HAODV
B. Packet Delivery Ratio
Fig.3 Packet Delivery Ratio verses simulation time for AAODV and HAODV
The Fig. 3 shows the relationship between Packet delivery Ratio at y-axis and node speed at x-axis for shows that Swarm HAODV have high PDR than AAODV When as no of node speed increases PDR for HAODV will increase consistent in comparison with AAODV protocol.
VI. CONCLUSION
Here, we compare two different routing methods, one is conventional and other is swarm-based for MANETs.Here, honeybee based AODV algorithm has been made and simulated using NS2 simulator. The outputs denote that the proposed algorithm which is swarm based, is high Throughput and high Packet delivery ratio than Ant based AODV (AAODV) protocol. Further, future opportunity can be mixture of other swarm based techniques and presents hybrid methods for energy efficiency in MANETs.
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