Proceedings Article10.1109/CITS.2017.8035288
Genetic algorithm and probability based routing protocol for Opportunistic Networks
Deepak Kr. Sharma,Sanjay Kumar Dhurandher,Mohammad S. Obaidat,Aman Bansal,Apoorv Gupta +4 more
- 01 Jul 2017
- pp 58-62
8
TL;DR: Simulation results show that the GAP routing protocol outperforms Prophet, Spray and Wait and GAER protocol in terms of message delivery ratio, overhead ratio and average latency.
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Abstract: The random nature of network topology is a major challenge while developing new routing protocol for Opportunistic Networks (OppNets). Additionally, other factors like intermittent connections, limited bandwidth etc. further restrict the performance of existing routing protocols. In this paper, an advanced context aware routing protocol called GAP is proposed. The proposed protocol efficiently combines the benefits of Genetic Algorithm and Probabilistic Routing to route the message from the source to destination. The protocol uses the Genetic algorithm to predict the path a message would take if it is transferred to the neighbouring node. A Fitness function is defined to evaluate the efficiency of this predicted path. The message is transferred to the neighbouring node only if the fitness value of the predicted path is greater than a threshold value, which is calculated by implementing the concepts of probabilistic routing. Simulation results show that the GAP routing protocol outperforms Prophet, Spray and Wait and GAER protocol in terms of message delivery ratio, overhead ratio and average latency.
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Citations
FCNS: A Fuzzy Routing-Forwarding Algorithm Exploiting Comprehensive Node Similarity in Opportunistic Social Networks
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55
Probability-based path discovery protocol for electromagnetic nano-networks
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Neural network‐based routing protocol for opportunistic networks with intelligent water drop optimization
TL;DR: The proposed protocol Intelligent Water Drop Neural Network (IWDNN) is shown to outperform all other protocols with an average message delivery ratio of 60%, which is a significant improvement of over 10% in comparison to other similarly conceived algorithms.
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Content-Aware Personalized Sharing Based on Cooperative User Selection and Attention in Mobile Internet of Things
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Predicted Encounter Probability Based on Dynamic Programming Proposed Probability Algorithm in Opportunistic Social Network
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