A QoS-aware barrier coverage scheduling scheme for WSN-based surveillance applications

Wireless sensor networks (WSNs) have been utilized for various mission-critical surveillance (or intrusion detection) applications such as military, environmental, agricultural, and critical infrastructure. One of the inherent challenges of WSNs is their limited network lifetime due to severe energy constraints. To guarantee a reliable and secure operation of these applications, WSNs should also meet other key quality of service (QoS) such as coverage, connectivity, fault-tolerance, and security along with extended network lifetime. This thesis primarily aims at developing a unified energy conservation scheme that can extend the network lifetime simultaneously guaranteeing other key QoS requirements.

In this thesis, we develop a barrier coverage scheduling scheme, which is an energy conservation scheme capable of meeting key QoS requirements. In the barrier coverage scheduling scheme, subsets (also called barriers) of sensor nodes in the network are selected and activated in different time slots of the communication cycle to extend the network lifetime. We investigate state-of-the-art barrier coverage scheduling schemes and examine their effectiveness in meeting the required QoS in a densely deployed network. We aim to harness the potential of a graph-based barrier scheduling scheme. To this effect, we propose a novel fully weighted graph model and a graph-based barrier coverage scheduling scheme based on a greedy heuristic. The proposed graph model is scalable and can efficiently model a dense network. The designed greedy heuristic complements the graph model and intelligently exploits the graph weights to construct more barriers resulting in extended network lifetime.

In order to guarantee better connectivity and energy-efficient network management, we propose a novel handshaking-based clustering scheme that incorporates an energy-saving cluster head selection scheme. The proposed graph model is modified to capture the network dynamics to meet the fault-tolerance requirement. We modify the greedy heuristic to fairly exploit the dynamic graph for the efficacious identification of barriers. A threshold-based fault identification technique and a barrier recovery heuristic are also developed for the reliable operation of barriers.

The proposed scheme is also systematically designed (following the proposed security framework) to incorporate a graph-based anomaly detection module to detect the Depletion-of-Battery (DoB) attack. The anomaly detection module is based on a cluster ensemble scheme, which exploits the graph features to detect malicious sensor nodes that may launch such attacks. The detection of such attacks is paramount for guaranteeing QoS at all times.

The proposed graph model and schemes have been implemented, tested, and evaluated through necessary simulations and experiments that are backed up by theoretical analysis and insights. The results show that the proposed scheme outperforms other similar schemes in meeting the key QoS requirements. The contributions of this thesis show that it is feasible to extend the network lifetime while meeting other key QoS requirements through a systematically designed graph model and graph-based barrier coverage scheduling scheme.