Fuzzy Rule Selection Using Hybrid Artificial Bee Colony with 2-Opt Algorithm for MANET

The Mobile Ad-hoc Networks (MANET) is an independent and self-governing hosts of wireless communication that communicate using wireless links thus forming a dynamic and temporary network without any centralized infrastructure. The MANET nodes will not be stationary and the sender and the receiver ma...

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Bibliographic Details
Published in:Mobile networks and applications 2020-04, Vol.25 (2), p.585-595
Main Authors: Logesh Babu, R., Balasubramanie, P.
Format: Article
Language:English
Subjects:
Algorithms
Communications Engineering
Computer Communication Networks
Computer simulation
Electrical Engineering
Engineering
Fuzzy logic
Fuzzy systems
IT in Business
Mobile ad hoc networks
Networks
Optimization
Route selection
Swarm intelligence
Wireless communications
Wireless networks
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Summary:The Mobile Ad-hoc Networks (MANET) is an independent and self-governing hosts of wireless communication that communicate using wireless links thus forming a dynamic and temporary network without any centralized infrastructure. The MANET nodes will not be stationary and the sender and the receiver may not always take similar paths of routing. This way routing becomes quite complicated. A technique that has emerged recently is known as the Opportunistic Routing (OR) which chooses one set of candidates for the purpose of forwarding packets (being compared to that of conventional forwarding made to an approach with one node). It also takes into consideration the nature of the broadcast. This work proposes fuzzy logic with hybrid optimization approach for optimal route selection in MANET applications. The proposed hybrid optimization is based on 2-Opt algorithm and the Artificial Bee Colony (ABC). A fuzzy rule system depends on the end-to-end delay at a node time tends to leave the network there are several packets that are dropped and many different route requests that are generated. The results of the simulation demonstrated the proposed fuzzy rule selection and its efficiency by using the ABC-2 Opt algorithm on being compared with the selection of rule by using the ABC.
ISSN:1383-469X
1572-8153
DOI:10.1007/s11036-019-01354-z