Paper Title
Data Collection through Adaptive Cluster Head Selection Schemein Wireless Body Area Networks

Due to the development in the field of Wireless Sensor Networks (WSNs), its major application, Wireless Body Area Network (WBAN) haspresently become a major area of interest for the developers and researchers. Efficient data collection is the key feature of any effective wireless body area network. Prioritizing nodes and cluster head selection schemes plays an important role in WBAN. Human body exhibits postural mobility which affects distances and connections between different sensor nodes. In this context, we propose maximum consensus based cluster head selection scheme, which allows cluster head selection by using Link State. Nodal priority through transmission poweris also introduced to make WBAN more effective. This scheme results in reduced mean power consumption and also reduces network delay. A comparison with IEEE 802.15.6 based CSMA/CA protocol with different locations of cluster headis presented in this paper. These results show that our proposed scheme outperforms IEEE 802.15.6 based CSMA/CA protocol in terms of mean power consumption, network delay, network throughput and network bandwidth efficiency. Keywords - WBAN, CSMA/CA, LST, Adaptive Cluster head, Nodal Priority