Biblio

Opportunistic routing (OR) is gaining popularity in low-duty wireless sensor network (WSN), so the need for efficient and reliable data transmission is becoming more essential. Reliable transmission is only feasible if the routing protocols are secure and efficient. Due to high energy consumption, current cryptographic schemes for WSN are not suitable. Trust-based OR will ensure security and reliability with fewer resources and minimum energy consumption. OR selects the set of potential candidates for each sensor node using a prioritized metric by load balancing among the nodes. This paper introduces a trust-based load-balanced OR for duty-cycled wireless sensor networks. The candidates are prioritized on the basis of a trusted OR metric that is divided into two parts. First, the OR metric is based on the average of four probability distributions: the distance from node to sink distribution, the expected number of hops distribution, the node degree distribution, and the residual energy distribution. Second, the trust metric is based on the average of two probability distributions: the direct trust distribution and the recommended trust distribution. Finally, the trusted OR metric is calculated by multiplying the average of two metrics distributions in order to direct more traffic through the higher priority nodes. The simulation results show that our proposed protocol provides a significant improvement in the performance of the network compared to the benchmarks in terms of energy consumption, end to end delay, throughput, and packet delivery ratio.

This paper discusses two issues with multi-channel multi-radio Wireless Mesh Networks (WMN): gateway placement and gateway selection. To address these issues, a method will be proposed that places gateways at strategic locations to avoid congestion and adaptively learns to select a more efficient gateway for each wireless router by using learning automata. This method, called the N-queen Inspired Gateway Placement and Learning Automata-based Selection (NQ-GPLS), considers multiple metrics such as loss ratio, throughput, load at the gateways and delay. Simulation results from NS-2 simulator demonstrate that NQ-GPLS can significantly improve the overall network performance compared to a standard WMN.