Performability Analysis Methods for Clustered WSNs as Enabling Technology for IoT

The Internet of Things (IoT) where sensors are used to couple the physical infrastructure with information and communication technologies is the main concept enabling applications such as smart homes, smart cities and intelligent transportation. The distributed sensor networks are used for interconnecting devices to transmit measured information, and control instructions. Therefore, energy efficiency and performability of wireless sensor networks (WSNs) are critical for IoT applications. It is possible to combine WSN nodes into smaller groups and set one of the nodes as cluster head (CH) in order to increase the energy efficiency and decrease transmission delay. This approach of combining sensor nodes is known as clustering. Clustering is a technique that has been widely applied for achieving goals such as prolonging the network lifetime, improving scalability and balancing the residual energy of all nodes. Development of algorithms using equal and unequal clustering techniques has been a popular topic in recent studies. Most of these techniques use residual energy of nodes and distance to base station as parameters for selecting cluster heads. This chapter considers analytical modelling approaches of homogeneous clustered WSNs with a centrally located CH responsible for coordinating cluster communication. Unlike most of the existing studies, the performance and energy efficiency of the cluster head are considered together. Furthermore, potential failure of WSN nodes is considered and performance and availability models are integrated as well as the potential repair or replacement of sensor nodes. Existing techniques used in performance evaluation of multiserver systems in general are investigated and analysed in detail. Similarly, pure availability modelling approaches are also analysed. Pure performance modelling techniques, pure availability models and performability models are considered critically for WSN configurations. Since the pure performance models tend to be too optimistic and pure availability models are too conservative, performability models are used in turn for the evaluation. The two-dimensional continuous-time Markov chains (CTMC) which are popularly used in performability analysis are considered together with queuing theory, in order to merge the performance and reliability processes which are relatively mutually independent. The possible use of open queuing networks to model the behaviour of the CH which is expecting intra-cluster as well as inter-cluster traffic while in various operative states is discussed. Among the possible operative conditions, we have states where the servers are broken, fully operational states, states with degraded service facilities and states where sleep scheduling mechanisms are also incorporated to extend the proposed energy models