Cooperative mobility maintenance techniques for information extraction from mobile wireless sensor networks

Recent advances in the development of microprocessors, microsensors, ad-hoc wireless networking and information fusion algorithms led to increasingly capable Wireless Sensor Networks (WSNs). Besides severe resource constraints, sensor nodes mobility is considered a fundamental characteristic of WSNs. Information Extraction (IE) is a key research area within WSNs that has been characterised in a variety of ways, ranging from a description of its purposes to reasonably abstract models of its processes and components. The problem of IE is a challenging task in mobile WSNs for several reasons including: the topology changes rapidly; calculation of trajectories and velocities is not a trivial task; increased data loss and data delivery delays; and other context and application specific challenges. These challenges offer fundamentally new research problems. There is a wide body of literature about IE from static WSNs. These approaches are proved to be effective and efficient. However, there are few attempts to address the problem of IE from mobile WSNs. These attempts dealt with mobility as the need arises and do not deal with the fundamental challenges and variations introduced by mobility on the WSNs. The aim of this thesis is to develop a solution for IE from mobile WSNs. This aim is achieved through the development of a middle-layer solution, which enables IE approaches that were designed for the static WSNs to operate in the presence of multiple mobile nodes. This thesis contributes toward the design of a new self-stabilisation algorithm that provides autonomous adaptability against nodes mobility in a transparent manner to both upper network layers and user applications. In addition, this thesis proposes a dynamic network partitioning protocol to achieve high quality of information, scalability and load balancing. The proposed solution is flexible, may be applied to different application domains, and less complex than many existing approaches. The simplicity of the solutions neither demands great computational efforts nor large amounts of energy conservation. Intensive simulation experiments with real-life parameters provide evidence of the efficiency of the proposed solution. Performance experimentations demonstrate that the integrated DNP/SS protocol outperforms its rival in the literature in terms of timeliness (by up to 22%), packet delivery ratio (by up to 13%), network scalability (by up to 25%), network lifetime (by up to 40.6%), and energy consumption (by up to 39.5%). Furthermore, it proves that DNP/SS successfully allows the deployment of static-oriented IE approaches in hybrid networks without any modifications or adaptations

Universal and Dynamic Clustering Scheme for Energy Constrained Cooperative Wireless Sensor Networks

Energy conservation is considered to be one of the key design challenges within resource constrained wireless sensor networks (WSNs) that leads the researchers to investigate energy efficient protocols with some application specific challenges. Dynamic clustering is generally considered as one of the energy conservation techniques; but unbalanced distribution of cluster heads, highly variable number of sensor nodes in the clusters and high number of sensor nodes involved in event reporting tend to drain out the network energy quickly resulting premature decrease in network lifetime. In this paper, a dynamic and cooperative clustering and neighborhood formation scheme is proposed that is expected to evenly distribute energy demand from the cluster heads and optimize the number of sensor nodes involved in event reporting. Assuming multiple sensors will form a cluster, while responding to an event to report to the fusion center. However, all the sensor nodes are assuming to report the sensing parameters to a cluster-head; which are to be summarized and then report it to fusion center. The transmission of the same event data from multiple sensors within the cluster at different distances with single or multiple antennas to the cluster-head with similar antenna characteristics can be realized as multiple-input multiple-output (MIMO) channel set up as found in the literature. Such realization among clusters of MIMO channel and existence of a feedback channel between the clusters and fusion center is the key of the proposed framework. The dynamic behavior has been adopted within the framework with a proposed index derived from the received measure of the channel quality, which has been attained through the feedback channel from the fusion center. The dynamic property of the proposed framework makes it robust against time-varying behavior of the propagation environment. The proposed framework is independent of the nature of the sensing application, providing with universal behavior. From simulation results, it is observed that the proposed clustering scheme enhances network lifetime by 24.5% and 36% as compared to existing schemes e.g. DDEEC and EDDEEC respectively. Furthermore, it is validated by simulation results that the proposed framework provides a trade-off model between network lifetime and transmission reliability

Collaborative Sensing and Communication Schemes for Cooperative Wireless Sensor Networks

Energy conservation is considered to be one of the key design challenges within resource constrained wireless sensor networks (WSNs) that leads the researchers to investigate energy efficient protocols with some application specific challenges. Dynamic clustering scheme within the deployed sensor nodes is generally considered as one of the energy conservation techniques. However, unbalanced distribution of cluster heads, highly variable number of sensor nodes in the clusters and high number of sensor nodes involved in event reporting tend to drain out the network energy quickly, resulting in unplanned decrease in network lifetime. Performing power aware signal processing, defining communication methods that can provide progressive accuracy and, optimising processing and communication for signal transmission are the challenging tasks. In this thesis, energy efficient solutions are proposed for collaborative sensing and cooperative communication within resource constrained WSNs. A dynamic and cooperative clustering as well as neighbourhood formation scheme is proposed that is expected to evenly distribute the energy demand from the cluster heads and optimise the number of sensor nodes involved in event reporting. The distributive and dynamic behaviour of the proposed framework provides an energy efficient self-organising solution for WSNs that results in an improved network lifetime. The proposed framework is independent of the nature of the sensing type to support applications that require either time-driven sensing, event-driven sensing or hybrid of both sensing types. A cooperative resource selection and transmission scheme is also proposed to improve the performance of collaborative WSNs in terms of maintaining link reliability. As a part of the proposed cooperative nature of transmission, the transmitreceive antennae selection scheme and lattice reduction algorithm have also been considered. It is assumed that the channel state information is estimated at the ii receiver and there is a feedback link between the wireless sensing nodes and the fusion centre receiver. For the ease of system design engineer to achieve a predefined capacity or quality of service, a set of analytical frameworks that provide tighter error performance lower bound for zero forcing (ZF), minimum mean square error (MMSE) and maximum likelihood (ML) detection schemes are also presented. The dynamic behaviour has been adopted within the framework with a proposed index derived from the received measure of the channel quality, which has been attained through the feedback channel from the fusion centre. The dynamic property of the proposed framework makes it robust against time-varying behaviour of the propagation environment. Finally, a unified framework of collaborative sensing and communication schemes for cooperative WSNs is proposed to provide energy efficient solutions within resource constrained environments. The proposed unified framework is fully decentralised which reduces the amount of information required to be broadcasted. Such distributive capability accelerates the decision-making process and enhances the energy conservation. Furthermore, it is validated by simulation results that the proposed unified framework provides a trade-off between network lifetime and transmission reliability while maintaining required quality of service