Title :
A bias routing tree avoiding technique based on population-based incremental learning algorithm
Author :
Liu Ri-Xian; Yuan Li-Yong
Author_Institution :
College of Information Engineering, Jinhua Polytechnic, Zhejiang, 321017, China
Abstract :
6LoWPAN is a technique which enables wireless sensor networks to support IPv6 protocol. Hilow, a hierarchical routing protocol for 6LoWPAN, is a lightweight address assignment and routing method, which uses the distinct feature of IEEE802.15.4-based devices that supports dynamic configuring the 16-bit MAC address. However, HiLow mainly introduces the address assignment, routing method and packet format. The problem of bias routing tree is not dealt with in the HiLow specification. In our paper, in order to avoid bias routing tree, we propose a method that each node uses population-based incremental learning algorithm to selects those nodes that have most unassociated neighbor nodes as its child nodes, which ensures balance in the growth direction of the tree as much as possible. The simulation result shows that our method is better than existing ones on the average number of hops from the sink to each node.
Keywords :
"Routing","Wireless sensor networks","Robot sensing systems","Optimization","Routing protocols","Linear programming"
Conference_Titel :
Fuzzy Systems and Knowledge Discovery (FSKD), 2015 12th International Conference on
DOI :
10.1109/FSKD.2015.7382258