Multi-channel allocation algorithm based on congestion avoidance in wearable wireless sensor network

Abstract

Wearable Wireless Sensor Network (WWSN) is a hot topic that applying wearable technology and Wireless Sensor Network (WSN) in recent years. Due to the characteristics of wearable devices and that of wireless transmission in WSN, multi-channel allocation is a challenging problem in WWSN. This paper presents a Multi-channel Allocation algorithm based on Congestion Avoidance (MACA) to reduce the interference between nodes and extend the working life of WWSN. The proposed algorithm perceives the congestion degree of different channels by comparing the transmission capacity of each node on different channels so as to select the most suitable channel for data transmission. This algorithm reduces the channel selection conflicts and improves the throughput of the whole network as much as possible. The simulation results show that compared with the Multi-channel Allocation algorithm based on Game Theory (MAGT), the network throughput of proposed algorithm can be increased by up to 50% under the same network structure.