Ant Colony Based Node Disjoint Hybrid Multi-path Routing for Mobile Ad Hoc Network

Kalaavathi, B.; Duraiswamy, K.

doi:10.3844/jcssp.2008.80.86

Cited by 7 publications

(3 citation statements)

References 10 publications

(7 reference statements)

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“…Routing overhead is actually meant to add number of routing packets observed from the AntHoc-TBN. The route load in AntHoc-TBN model is comparatively depicts lower result than the existing technique of AODV [21], AntNet [22] and AntHoc Net [23]. In this model, the routing packages arise to compute the routing overhead is route request (RREQ), route response (RREP) and route error (RRER) [19].…”

Section:  Routing Overheadmentioning

confidence: 99%

Anthoc Based Trust Behavioural Network (Anthoc-tbn) Assist to Detect Blackhole Attack by Discover Secure Route

Rajkumar¹,

Karthika

2021

Preprint

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MANET is a wireless topology mainly used to grouping several mobile nodes as network. This wireless network is highly vulnerable by several security threads. Blackhole attack, a severe thread that voluntarily disrupts the healthy nodes and turn it as malicious node. So, introducing security mechanism can forcefully work together to defeat the black hole attack. In this paper, a new approach of AntHoc based trust behavioural network (AntHoc-TBN) model is introduced. This model effectively discovers the route with trust based packet transmission take place. Here, the forward ant agent performs shortest distance computation to discover the route. So that, Dijikstra algorithm is employed to detect the shortest route of all other nodes from source. Then, trust procedure is applied to find that corresponding node is trustable or not. Based on trust threshold, the respective intermediate node is computed and stored the updated value in extended data routing information (EDRI) table. Once the condition is not satisfied, then updated value in EDRI table tends to be distrust node and the concerned node is eliminated from the routing table. Now, the trusted node becomes an active path after that the packet has to be sent. Likewise, the same process is repeated for backward ant agent to transfer the Ack message from destination to source. To simulate the process, the result reveals that the AntHoc-TBN model improves its efficiency by lowest delay, packet loss and routing overhead. And also, the technique gets highest value of packet delivery ratio. The performance measures of our proposed model achieves better outcome when compared to existing techniques such as AODV, AntNet and AntHoc Net.

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Section:  Routing Overheadmentioning

confidence: 99%

Anthoc Based Trust Behavioural Network (Anthoc-tbn) Assist to Detect Blackhole Attack by Discover Secure Route

Rajkumar¹,

Karthika

2021

Preprint

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“…AntHocNet was shown to outperform AODV and other state-of-the-art algorithms in a wide range of different open space and urban scenarios. In [57], a mechanism is added to AntHocNet in order to favor the establishment of node-disjoint multiple paths. A little improvement in performance has been observed in a set of experiments with 30 personal digital assistants (PDAs).…”

Section: Reactive and Hybrid Si Routing Algorithmsmentioning

confidence: 99%

Principles and applications of swarm intelligence for adaptive routing in telecommunications networks

Ducatelle

Gambardella

2010

Swarm Intell

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In the past few years there has been a lot of research on the application of swarm intelligence to the problem of adaptive routing in telecommunications networks. A large number of algorithms have been proposed for different types of networks, including wired networks and wireless ad hoc networks. In this paper we give an overview of this research area. We address both the principles underlying the research and the practical applications that have been proposed. We start by giving a detailed description of the challenges in this problem domain, and we investigate how swarm intelligence can be used to address them. We identify typical building blocks of swarm intelligence systems and we show how they are used to solve routing problems. Then, we present Ant Colony Routing, a general framework in which most swarm intelligence routing algorithms can be placed. After that, we give an extensive overview of existing algorithms, discussing for each of them their contributions and their relative place in this research area. We conclude with an overview of future research directions that we consider important for the further development of this field.

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“…Because of its infrastructure-less nature it is easy to deploy and instantly finds extensive applications in military, business and academia (Kalaavathi and Duraiswamy, 2008). In a MANET each and every individual node has the additional task of a router by which it can forward packets between two or more nodes.…”

Section: Introductionmentioning

confidence: 99%

Varying Overhead Ad Hoc on Demand Vector Routing in Highly Mobile Ad Hoc Network

Balaji¹

2011

Journal of Computer Science

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Problem statement: An inherent feature of mobile ad hoc networks is the frequent change of network topology leading to stability and reliability problems of the network. Highly dynamic and dense network have to maintain acceptable level of service to data packets and limit the network control overheads. This capability is closely related as how quickly the network protocol control overhead is managed as a function of increased link changes. Dynamically limiting the routing control overheads based on the network topology improves the throughput of the network. Approach: In this study we propose Varying Overhead -Ad hoc on Demand Vector routing protocol (VO-AODV) for highly dynamic mobile Ad hoc network. The VO-AODV routing protocol proposed dynamically modifies the active route time based on the network topology. Results and Conclusion: Simulation results prove that the proposed model decreases the control overheads without decreasing the QOS of the network.

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Ant Colony Based Node Disjoint Hybrid Multi-path Routing for Mobile Ad Hoc Network

Cited by 7 publications

References 10 publications

Anthoc Based Trust Behavioural Network (Anthoc-tbn) Assist to Detect Blackhole Attack by Discover Secure Route

Anthoc Based Trust Behavioural Network (Anthoc-tbn) Assist to Detect Blackhole Attack by Discover Secure Route

Principles and applications of swarm intelligence for adaptive routing in telecommunications networks

Varying Overhead Ad Hoc on Demand Vector Routing in Highly Mobile Ad Hoc Network

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