A Trust Based Congestion Aware Hybrid Ant Colony Optimization Algorithm for Energy Efficient Routing in Wireless Sensor Networks (TC-ACO)

Congestion is a problem of paramount importance in resource constrained Wireless Sensor Networks, especially for large networks, where the traffic loads exceed the available capacity of the resources. Sensor nodes are prone to failure and the misbehavior of these faulty nodes creates further congestion. The resulting effect is a degradation in network performance, additional computation and increased energy consumption, which in turn decreases network lifetime. Hence, the data packet routing algorithm should consider congestion as one of the parameters, in addition to the role of the faulty nodes and not merely energy efficient protocols. Unfortunately most of the researchers have tried to make the routing schemes energy efficient without considering congestion factor and the effect of the faulty nodes. In this paper we have proposed a congestion aware, energy efficient, routing approach that utilizes Ant Colony Optimization algorithm, in which faulty nodes are isolated by means of the concept of trust. The merits of the proposed scheme are verified through simulations where they are compared with other protocols.Comment: 6 pages, 5 figures and 2 tables (Conference Paper

A Trust Based Fuzzy Algorithm for Congestion Control in Wireless Multimedia Sensor Networks (TFCC)

Network congestion has become a critical issue for resource constrained Wireless Sensor Networks (WSNs), especially for Wireless Multimedia Sensor Networks (WMSNs)where large volume of multimedia data is transmitted through the network. If the traffic load is greater than the available capacity of the sensor network, congestion occurs and it causes buffer overflow, packet drop, deterioration of network throughput and quality of service (QoS). Again, the faulty nodes of the network also aggravate congestion by diffusing useless packets or retransmitting the same packet several times. This results in the wastage of energy and decrease in network lifetime. To address this challenge, a new congestion control algorithm is proposed in which the faulty nodes are identified and blocked from data communication by using the concept of trust. The trust metric of all the nodes in the WMSN is derived by using a two-stage Fuzzy inferencing scheme. The traffic flow from source to sink is optimized by implementing the Link State Routing Protocol. The congestion of the sensor nodes is controlled by regulating the rate of traffic flow on the basis of the priority of the traffic. Finally we compare our protocol with other existing congestion control protocols to show the merit of the work.Comment: 6 pages, 5 figures, conference pape

Development of FIGA: a Novel Trust-Based Algorithm for Securing Autonomous Interactions in WSN

Attempts at securing wireless sensor networks (WSN) and making them more resilient and self-healing after attacks demand that services rendered by the network be secured on individual basis. The fact that a node is malfunctioning and/or has been compromised does not necessarily warrant its elimination from the network. Albeit, services such as routing, sensor readings, key distribution schemes, and others are handled in isolation and individually, due to the fact that an attack or malfunction may only be temporary. Moreover, an attack aimed at routing, or a particular application service does not invalidate nodes or the entire network. Consequently, Fuzzy Inference Gatekeeper Algorithm (FIGA); the algorithm presented in this paper proposes a piecemeal approach to WSN security. FIGA secures interactions in autonomous WSN by using a contextualized fuzzy inference system to combine trust scores from individual node interactions, reputation scores gotten from consultations and time dependent exponential trust scores. By so doing, we argue that autonomous WSNs can be better secured. We further illustrate the effectiveness of the FIGA against a simulated Sybil attack and discuss how the network recovers following such an attack