An Experimental Simulation of Addressing Auto-Configuration Issues for Wireless Sensor Networks

Applications of Wireless Sensor devices are widely used by various monitoring sections such as environmental monitoring, industrial sensing, habitat modeling, healthcare and enemy movement detection systems. Researchers were found that 16 bytes packet size (payload) requires Media Access Control (MAC) and globally unique network addresses overheads as more as the payload itself which is not reasonable in most situations. The approach of using a unique address isn't preferable for most Wireless Sensor Networks (WSNs) applications as well. Based on the mentioned drawbacks, the current work aims to fill the existing gap in the field area by providing two strategies. First, name/address solutions that assign unique addresses locally to clustered topology-based sensor devices, reutilized in a spatial manner, and reduce name/address size by a noticeable amount of 2.9 based on conducted simulation test. Second, name/address solutions that assign reutilizing of names/addresses to location-unaware spanning-tree topology in an event-driven WSNs case (that is providing minimal low latencies and delivering addressing packet in an efficient manner). Also, to decline the approach of needing both addresses (MAC and network) separately, it discloses how in a spatial manner to reutilize locally unique sensor device name approach and could be utilized in both contexts and providing an energy-efficient protocol for location unawareness clustered based WSNs. In comparison, an experimental simulation test performed and given the addresses solution with less overhead in the header and 62 percent fair payload efficiency that outperforms 34 percent less effective globally unique addresses. Furthermore, the proposed work provides addresses uniqueness for network-level without using network-wide Duplicate Address Detection (DAD) algorithm. Consequently, the current study provides a roadmap for addressing/naming scheme to help researchers in this field of study. In general, some assumptions were taken during the work phases of this study such as number of Cluster Head (CH) nodes is 6% of entire sensor nodes, location unawareness for entire sensor network and 4 bits per node address space which considered as the limitation of the study.