Improving QoS for Ad-Hoc Wireless Networks Using Predictive Preemptive Local Route Repair Strategy

Sharvani, G. S.; Rangaswamy, T. M.; Goel, Aayush; Ajith, B.; Kumar, B. Sarath; Kumar, Manish

doi:10.1007/978-3-642-17878-8_6

Cited by 1 publication

(1 citation statement)

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“…The detection of route failure is predicted through the Lagrange's interpolation methodology. Here a node calculates battery threshold (P) using Lagrange's interpolation methodology, if the battery threshold is reached, then source node preempts the transmission and bypass the packets to the next optimal path [36].…”

Section: Mta Providing Qos and Efficient Route Repair Strategymentioning

confidence: 99%

Efficient Stagnation Avoidance for Manets with Local Repair Strategy Using ant Colony Optimization

G.S¹

2012

IJDPS

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Wireless networks such as Mobile AdHoc Networks (MANETs) have many advantages compared to wired networks. In MANETs the communication is not limited to a certain geometrical region. Swarm Intelligence based ACO algorithms provide interesting solutions to network routing problems. ACO based routing in MANETs will enhance the reliability and efficient packet delivery. They help in reducing control overhead due to their inherent scalable feature. The similarity between ant and nodes, colony and Wireless network helps to use ACO based routing in MANETs. The Termite Algorithms contains several tunable parameters and methods to automate the selection of optimal routes for different network conditions. However, Termite doesn't contain methods for determination of QoS, Route Maintenance; Load balancing etc. The present work focuses on development of an efficient routing algorithm "Modified Termite algorithms" (MTA) for MANETs. The MTA developed by adopting efficient pheromone evaporation technique will address to load balancing problems. By including QoS, efficient route maintenance, local repair strategy by prediction of node failures, the MTA is expected to enhance the performance of the network in terms of throughput, and reduction of End-to-end delay and routing overheads. The results of the analysis are presented in the paper.

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Section: Mta Providing Qos and Efficient Route Repair Strategymentioning

confidence: 99%

Efficient Stagnation Avoidance for Manets with Local Repair Strategy Using ant Colony Optimization

G.S¹

2012

IJDPS

View full text Add to dashboard Cite

show abstract

Improving QoS for Ad-Hoc Wireless Networks Using Predictive Preemptive Local Route Repair Strategy

Cited by 1 publication

References 5 publications

Efficient Stagnation Avoidance for Manets with Local Repair Strategy Using ant Colony Optimization

Efficient Stagnation Avoidance for Manets with Local Repair Strategy Using ant Colony Optimization

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