Secrecy outage performance analysis for energy harvesting sensor networks with a jammer using relay selection strategy

In this paper, we study radio frequency energy harvesting (EH) in a wireless sensor network in the presence of multiple eavesdroppers (EAVs). Specifically, the sensor source and multiple sensor relays harvest energy from multiple power transfer stations (PTSs), and then, the source uses this harvested energy to transmit information to the base station (BS) with the help of the relays. During the transmission of information, the BS typically faces a risk of losing information due to the EAVs. Thus, to enhance the secrecy of the considered system, one of the relays acts as a jammer, using harvested energy to generate interference with the EAVs. We propose a best-relay-and-best-jammer scheme for this purpose and compare this scheme with other previous schemes. The exact closed-form expression for the secrecy outage probability (SOP) is obtained and is validated through Monte Carlo simulations. A near-optimal EH time algorithm is also proposed. In addition, the effects on the SOP of key system parameters such as the EH efficiency coefficient, the EH time, the distance between the relay and BS, the number of PTSs, the number of relays, and the number of EAVs are investigated. The results indicate that the proposed scheme generally outperforms both the best-relay-and-random-jammer scheme and the random-relay-and-best-jammer scheme in terms of the secrecy capacity

A Comparison of Alternative Distributed Dynamic Cluster Formation Techniques for Industrial Wireless Sensor Networks

In this paper, we investigate alternative distributed clustering techniques for wireless sensor node tracking in an industrial environment. The research builds on extant work on wireless sensor node clustering by reporting on: (1) the development of a novel distributed management approach for tracking mobile nodes in an industrial wireless sensor network; and (2) an objective comparison of alternative cluster management approaches for wireless sensor networks. To perform this comparison, we focus on two main clustering approaches proposed in the literature: pre-defined clusters and ad hoc clusters. These approaches are compared in the context of their reconfigurability: more specifically, we investigate the trade-off between the cost and the effectiveness of competing strategies aimed at adapting to changes in the sensing environment. To support this work, we introduce three new metrics: a cost/efficiency measure, a performance measure, and a resource consumption measure. The results of our experiments show that ad hoc clusters adapt more readily to changes in the sensing environment, but this higher level of adaptability is at the cost of overall efficiency

A Comparison of Alternative Distributed Dynamic Cluster Formation Techniques for Industrial Wireless Sensor Networks

In this paper, we investigate alternative distributed clustering techniques for wireless sensor node tracking in an industrial environment. The research builds on extant work on wireless sensor node clustering by reporting on: (1) the development of a novel distributed management approach for tracking mobile nodes in an industrial wireless sensor network; and (2) an objective comparison of alternative cluster management approaches for wireless sensor networks. To perform this comparison, we focus on two main clustering approaches proposed in the literature: pre-defined clusters and ad hoc clusters. These approaches are compared in the context of their reconfigurability: more specifically, we investigate the trade-off between the cost and the effectiveness of competing strategies aimed at adapting to changes in the sensing environment. To support this work, we introduce three new metrics: a cost/efficiency measure, a performance measure, and a resource consumption measure. The results of our experiments show that ad hoc clusters adapt more readily to changes in the sensing environment, but this higher level of adaptability is at the cost of overall efficiency