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