R-bUCRP: A Novel Reputation-Based Uneven Clustering Routing Protocol for Cognitive Wireless Sensor Networks

Energy of nodes is an important factor that affects the performance of Wireless Sensor Networks (WSNs), especially in the case of existing selfish nodes, which attracted many researchers’ attention recently. In this paper, we present a reputation-based uneven clustering routing protocol (R-bUCRP) considering both energy saving and reputation assessment. In the cluster establishment phase, we adopt an uneven clustering mechanism which controls the competitive scope of cluster head candidates to save the energy of WSNs. In the cluster heads election phase, the residual energy and reputation value are used as the indexes to select the optimal cluster head, where the reputation mechanism is introduced to support reputation assessment. Simulation results show that the proposed R-bUCRP can save node energy consumption, balance network energy distribution, and prolong network lifetime

A critical analysis of mobility management related issues of wireless sensor networks in cyber physical systems

Mobility management has been a long-standing issue in mobile wireless sensor networks and especially in the context of cyber physical systems; its implications are immense. This paper presents a critical analysis of the current approaches to mobility management by evaluating them against a set of criteria which are essentially inherent characteristics of such systems on which these approaches are expected to provide acceptable performance. We summarize these characteristics by using a quadruple set of metrics. Additionally, using this set we classify the various approaches to mobility management that are discussed in this paper. Finally, the paper concludes by reviewing the main findings and providing suggestions that will be helpful to guide future research efforts in the area