Potential of incorporating evolutionary based network coding for information scavenging in intelligent public transportation

• Main Authors: Teo, Kenneth Tze Kin, Chin, Renee, Ka Yin, Chua, Bih Lii, Tan, Shee Eng, Lee, Chun Hoe, Yeo Kiam Beng @ Abdul Noor, Rosalam Sarbatly, Goh, Hui Hwang, Yew, Hoe Tung
• Format: Research Report
• Language: English
• Published: Universiti Malaysia Sabah 2013
• Subjects: TE Highway engineering. Roads and pavements
• Online Access: https://eprints.ums.edu.my/id/eprint/22529/1/Potential%20of%20incorporating%20evolutionary%20based%20network%20coding%20for%20information%20scavenging%20in%20intelligent%20public%20transportation.pdf; https://eprints.ums.edu.my/id/eprint/22529/

Intelligent transportation systems use wireless technology as a communication backbone for disseminating vital traffic information. In conventional store-and-forward of a wireless ad hoc network, data packets disseminated separately and independently with different transmission lows limit the overall network performances. Network coding is implemented to combine several packets from different sources and broadcast the combined packet to respective destinations in single transmission flow. Genetic algorithm (GA) is introduced to further optimise the resources for network coding by searching optimum transmission route. The simulation results show the GA can adapt to various topologies with a better throughput and energy consumption of 22.27 % fewer than store-and-forward and 16.33 % fewer than code based forwarding structure (COPE).