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In this chapter, the state of the art techniques to address the key issues and challenges in the design of WSNs are elaborated. The solutions proposed in the literature to resolve these issues and to overcome the challenges are summarised, and the limitations of the existing works are discussed. Although the existing studies in the literature address several key issues and propose solutions leading to energy efficiency such as collaborative sensing techniques e.g. dynamic cluster formation, cluster head selection, data reduction, dynamic adaptivity etc. and co- operative communication techniques e.g. virtual MIMO, cooperative sensor nodes selection schemes, resource selection, channel quality estimation and link adap- tation. However, the existing scheme does not provide a universal framework to support applications that are required by either time-driven sensing, event-driven

sensing or unification of both scenarios. Moreover, the clustering techniques do not consider all aspects such as the unbalanced distribution of the cluster heads, highly variable number of sensor nodes in the clusters and the high number of sensor nodes involved in the event reporting that can deplete the network energy thus quickly resulting in premature decrease in the network lifetime. Consequently, dynamic and cooperative clustering and a neighbourhood formation framework is needed to evenly distribute the energy demands from the cluster heads and opti- mise the number of sensor nodes involved in event reporting that can support the applications independently of the nature of sensing type.

WSNs are also expected to be optimised by defining cooperation among sensor nodes during data transmission based on channel conditions. There is a need to define energy efficient scheme to select the sensor nodes for cooperation which are least affected from deep fading and interference. Moreover, cooperation among sensor nodes during data transmission are needed to exploit the diversity and spatial multiplexing to provide a trade-off between the transmission reliability and data capacity while maintaining the required QoS. In order to perform ade- quate decisions on the selection of appropriate optimisation schemes adaptively, the transmission quality information is required over the given channel conditions. Such adaptation is expected to be designed in a manner to ensurethe reliability against variable channel conditions and the optimised utilisation of the available resources while maintaining the required QoS. Although, the existing literature provides solutions for the cooperative communication within WSNs. However, there is a need for a framework that can attain transmission reliability by adopt- ing variable channel conditions while optimising the energy consumption. Channel selection schemes for efficient and reliable data transmission as well as selection of intelligent processing based on the channel’s link quality are expected to provide robust solutions against variable channel conditions.

The research studies in the literature consider time-driven and event-driven sce- narios separately and do not provide a universal solution. In this study, a dynamic

clustering and neighbourhood formation scheme is proposed that provides a frame- work which is independent of the nature of sensing application. It is expected that the proposed framework will provide an energy efficient solution by rotating the role of cluster head among all the sensor nodes while trying to keep the size of the clusters uniform and minimising the frequency of re-clustering. Furthermore, considering the residual energy threshold in the cluster heads selection process and their location in the network, the proposed framework is expected to avoid any unbalanced energy consumption and energy holes in the network for time- driven, event-driven as well as unification of both sensing scenarios. In order to attain transmission reliability, the dynamic behaviour is adopted to minimise the effect of variable channel conditions on data transmission. Such adaptation can be achieved by deriving an index from the received measure of channel quality that is attained at the transmitter through a feedback link from the FCR. The dynamic behaviour of the proposed framework is expected to provide a robust solution against variable conditions of the propagation environment. This study is also expected to present a unified framework of collaborative sensing and coop- erative communication schemes to provide energy efficient solutions for resource constrained WSNs.

The next Chapter builds on a collaborative sensing framework that comprises of a universal and dynamic clustering scheme with the aim of evenly distributing the energy demand from the cluster heads and optimising the number of sensor nodes involved in event reporting. A network lifetime model is also derived to evaluate the performance of the proposed framework.

A Universal and Dynamic

Clustering (UDC) Framework for

Collaborative Sensing

3.1

Introduction

Within WSNs, lifetime enhancement is one of the key design issues, regardless of the type of application, without compromising the required QoS. The sensor nodes are expected to collaborate to maximise the energy consumption within the network by involving a minimum number of sensor nodes as well as optimising the network communication required to report events. Moreover, events are generally considered as random and transient which involves the handling of a large amount of sensed data that can lead to uneven energy consumption. To overcome this issue, self-organisation of the network is required to balance the energy consump- tion among the sensor nodes by dynamically rotating the cluster head role and adaptively redefining the cluster boundaries. Also, dynamic clustering is expected to enhance load balancing, fault tolerance and connectivity within the network.

The research studies in the literature consider time-driven and event-driven scenar- ios separately and do not provide a universal solution. In this chapter, a dynamic clustering and neighbourhood formation scheme based on collaborative sensing framework is proposed that provides a universal behaviour to support applica- tions independent of the nature of sensing type. It is expected that the proposed framework will provide an energy efficient solution by dynamically rotating the role of the cluster head among all the sensor nodes while trying to keep the size of the clusters uniform and minimising the frequency of re-clustering. Furthermore, considering the residual energy threshold in the cluster heads election process and their location in the network, the proposed framework is expected to avoid any unbalanced energy consumption and energy holes in the network. The framework for universal and dynamic clustering is presented in the following section.