Abstract
Clustered-based wireless sensor networks have been extensively used in the literature in order to achieve considerable energy consumption reductions. However, two aspects of such systems have been largely overlooked. Namely, the transmission probability used during the cluster formation phase and the way in which cluster heads are selected. Both of these issues have an important impact on the performance of the system. For the former, it is common to consider that sensor nodes in a clustered-based Wireless Sensor Network (WSN) use a fixed transmission probability to send control data in order to build the clusters. However, due to the highly variable conditions experienced by these networks, a fixed transmission probability may lead to extra energy consumption. In view of this, three different transmission probability strategies are studied: optimal, fixed and adaptive. In this context, we also investigate cluster head selection schemes, specifically, we consider two intelligent schemes based on the fuzzy C-means and k-medoids algorithms and a random selection with no intelligence. We show that the use of intelligent schemes greatly improves the performance of the system, but their use entails higher complexity and selection delay. The main performance metrics considered in this work are energy consumption, successful transmission probability and cluster formation latency. As an additional feature of this work, we study the effect of errors in the wireless channel and the impact on the performance of the system under the different transmission probability schemes.
Highlights
Wireless Sensor Networks (WSNs) are deployed over a target area to supervise certain phenomena of interest
One harmful event that can occur due to a noisy channel is when the estimated number of active nodes is low, but there is a higher amount of nodes still active in the cluster formation phase
Energy consumption depends on the principle of the losses by propagation on the free-space described in Equation (23), where D is the distance, f is the frequency used by the WSN and c the speed of light
Summary
Wireless Sensor Networks (WSNs) are deployed over a target area to supervise certain phenomena of interest. The transmission probability (τ) at the beginning of the cluster formation phase should be relatively small, while at the end of the cluster formation, this value should be close to one This behavior is close to that of the optimal strategy, but with the advantage that there is no need to know the number of remaining nodes trying to transmit their control packets. Building from this, we develop a Markov model to consider the effect of errors of the channel in the performance of the system Another important contribution of this work is the study and performance analysis of different CH selections in clustered-based WSNs. we compare the performance of intelligent schemes where multiple iterations are performed in order to find the most appropriate nodes to act as CHs; and direct schemes where CHs are selected at random. The average energy consumption and average cluster formation delay are derived for each transmission strategy
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