Genetic algorithm based network coding in wireless ad hoc networks

Tan, Shee Eng (2013) Genetic algorithm based network coding in wireless ad hoc networks. Masters thesis, Universiti Malaysia Sabah.


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The main objective of this research is to maximize the throughput and minimize the energy consumption in wireless ad hoc networks with network coding by selecting a suitable route to destination. Packet's forwarding of the conventional store-and forward in an intermediate node is just storing the received packets and then forwarding the same packet without doing any additional processing to the packets. In the intermediate node of network coding (NC), instead of store then forward data packets, the nodes in NC can perform additional function by encoding several packets into a single coded packet, and then transmit the coded packet to respective destinations simultaneously. Wireless network simulation is used to demonstrate and assess the implementation of network coding in wireless ad hoc networks. Every destination node will decode the coded packet to get the intended packet. Results show that the network coding transfers the packets 13.64% faster than store-and-forward method. However, the chances to perform network coding in wireless ad hoc networks are limited if the path of packet does not flow through potential network coding nodes. Therefore, coding-aware routing is important to explore the data traffic flows with more network coding opportunities. Genetic algorithm based coding-aware routing (GACAR) is embedded in the wireless ad hoc network with network coding capabilities to search for coding opportunities for unicast sessions. In this work, an adaptive genetic algorithm based coding-aware routing (AGACAR) is also proposed to improve the solution on the GACAR. Evaluation and assessments have been carried out through various simulations under different network topologies, and it shows that AGACAR provides better coding opportunities and reduces energy consumption in the network. The expected transmissions count metric (ETX) for AGACAR is 22.27% fewer than store-and-forward and 16.33% fewer than network coding in wireless network transmission and forwarding structure COPE).

Item Type: Thesis (Masters)
Uncontrolled Keywords: Wireless ad hoc network, network coding, genetic algorithm
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: SCHOOL > School of Engineering and Information Technology
Depositing User: ADMIN ADMIN
Date Deposited: 07 Oct 2015 08:10
Last Modified: 07 Nov 2017 07:14

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