GAER: genetic algorithm-based energy-efficient routing protocol for infrastructure-less opportunistic networks

In this thesis, a history-based energy-efficient routing protocol (called AEHBPR) for opportunistic networks (OppNets) is proposed, which saves the energy consumption by avoiding unnecessary packets transmission in the network and by clearing the buffer of nodes carrying the copies of the already delivered packets. The proposed AEHBPR protocol is evaluated using the Opportunistic NEtwork (ONE) simulator with both synthetic and real mobility traces, showing a superior performance compared to the History-Based Prediction for Routing (HBPR) protocol and AEProphet, in terms of average remaining energy, number of dead nodes, number of delivered messages, and overhead ratio, where AEProphet is the ProPHet routing protocol for OppNets on which the same energy-aware mechanism has been implemented.

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Genetic Algorithm-Based Routing Protocol for Energy Efficient Routing in MANETs

Advances in Intelligent Systems and Computing - Next-Generation Networks ◽

10.1007/978-981-10-6005-2_4 ◽

2017 ◽

pp. 33-40

Author(s):

Pawan ◽

Rajendra K. Sharma ◽

A. K. Sharma ◽

Vinod Jain

Keyword(s):

Genetic Algorithm ◽

Routing Protocol ◽

Energy Efficient ◽

Energy Efficient Routing

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Genetic Algorithm Based Optimized Adaptive Teen Routing for WSN

International Journal of Recent Technology and Engineering - 2 ◽

10.35940/ijrte.f2345.118419 ◽

2019 ◽

Vol 8 (4) ◽

pp. 9838-9843

Keyword(s):

Genetic Algorithm ◽

Routing Protocol ◽

Energy Efficient ◽

Cluster Formation ◽

Energy Levels ◽

Hierarchical Architecture ◽

Energy Efficient Routing ◽

Computing Power ◽

Clustering Approach ◽

Different Levels

A sensor network with wireless communication channel and often termed as WSN comprises of a set of such as nodes with different computing power, and different energy levels. Clustering is an approach to increase the availability of the nodes in the network in terms of lifetime. But an efficient and an optimal to increase the remaining life period of the network is to use an efficient routing approach with hierarchical architecture where at different levels of clusters are formed. Efficient cluster formation in terms of energy and reliable routing are two widely analyzed challenges in WSN. Despite various clustering approaches developed by so many researchers still the design of optimal clustering strategy is remaining as an open challenge. This paper focuses on the design and evaluation of an energy-efficient hierarchical clustering approach of integrating an evolutionary algorithm and the Adaptive Threshold sensitive Energy Efficient routing protocol. Genetic Algorithm (GA) is used to optimize the energy exhaustion in the network.

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A history-based energy-efficient routing protocol for opportunistic networks

10.32920/ryerson.14657526.v1 ◽

2021 ◽

Author(s):

Khuram Khalid

Keyword(s):

Energy Consumption ◽

Routing Protocol ◽

Energy Efficient ◽

Opportunistic Networks ◽

Superior Performance ◽

Opportunistic Network ◽

Energy Aware ◽

Energy Efficient Routing ◽

One Simulator ◽

Overhead Ratio

In this thesis, a history-based energy-efficient routing protocol (called AEHBPR) for opportunistic networks (OppNets) is proposed, which saves the energy consumption by avoiding unnecessary packets transmission in the network and by clearing the buffer of nodes carrying the copies of the already delivered packets. The proposed AEHBPR protocol is evaluated using the Opportunistic NEtwork (ONE) simulator with both synthetic and real mobility traces, showing a superior performance compared to the History-Based Prediction for Routing (HBPR) protocol and AEProphet, in terms of average remaining energy, number of dead nodes, number of delivered messages, and overhead ratio, where AEProphet is the ProPHet routing protocol for OppNets on which the same energy-aware mechanism has been implemented.

Download Full-text