Design of DTS for Clustered Wireless Sensor Networks

The dependability of trust system and resource efficiency are the most fundamental requirements for any Wireless Sensor Network (WSN). However, the existing trust systems developed for WSNs are lacking in satisfying these requirements because of their low dependability and high overhead. In this work, we have proposed a ‘Dependable Trust System’ (DTS) for WSNs, which employ clustering algorithms. First, a dependable trust, decision-making scheme is proposed based on the nodes identity in the clustered WSNs, which is suitable for WSNs because it results in energy saving. Due to deleting of feedback between Cluster Members (CMs) or between Cluster Heads (CHs), this approach can effectively reduce the existence and effects of malicious nodes while significantly improving the system efficiency. More significantly, considering that CHs take on large amounts of data forwarding and communication tasks, a dependability enhanced trust valuating approach is defined for cooperation between CHs. This approach can efficiently reduce network power consumption while malicious, selfish, and faulty CHs, deleted from the network. Moreover, a self-adaptive weighted method is defined for trust calculation at CH level. This approach stands out the limitations of traditional weighting methods for trust factors. Theory as well as simulation results shows that DTS demands less communication overhead and memory compared with the current typical trust systems for WSNs.