An energy-efficient mobile sink-based unequal clustering mechanism for WSNs

Network lifetime and energy efficiency are crucial performance metrics used to evaluate wireless sensor networks (WSNs). Decreasing and balancing the energy consumption of nodes can be employed to increase network lifetime. In cluster-based WSNs, one objective of applying clustering is to decrease the energy consumption of the network. In fact, the clustering technique will be considered effective if the energy consumed by sensor nodes decreases after applying clustering, however, this aim will not be achieved if the cluster size is not properly chosen. Therefore, in this paper, the energy consumption of nodes, before clustering, is considered to determine the optimal cluster size. A two-stage Genetic Algorithm (GA) is employed to determine the optimal interval of cluster size and derive the exact value from the interval. Furthermore, the energy hole is an inherent problem which leads to a remarkable decrease in the network’s lifespan. This problem stems from the asynchronous energy depletion of nodes located in different layers of the network. For this reason, we propose Circular Motion of Mobile-Sink with Varied Velocity Algorithm (CM2SV2) to balance the energy consumption ratio of cluster heads (CH). According to the results, these strategies could largely increase the network’s lifetime by decreasing the energy consumption of sensors and balancing the energy consumption among CHs

Mobility in wireless sensor networks : advantages, limitations and effects

The primary aim of this thesis is to study the benefits and limitations of using a mobile base station for data gathering in wireless sensor networks. The case of a single mobile base station and mobile relays are considered. A cluster-based algorithm to determine the trajectory of a mobile base station for data gathering within a specified delay time is presented. The proposed algorithm aims for an equal number of sensors in each cluster in order to achieve load balance among the cluster heads. It is shown that there is a tradeoff between data-gathering delay and balancing energy consumption among sensor nodes. An analytical solution to the problem is provided in terms of the speed of the mobile base station. Simulation is performed to evaluate the performance of the proposed algorithm against the static case and to evaluate the distribution of energy consumption among the cluster heads. It is demonstrated that the use of clustering with a mobile base station can improve the network lifetime and that the proposed algorithm balances energy consumption among cluster heads. The effect of the base station velocity on the number of packet losses is studied and highlights the limitation of using a mobile base station for a large-scale network. We consider a scenario where a number of mobile relays roam through the sensing field and have limited energy resources that cannot reach each other directly. A routing scheme based on the multipath protocol is proposed, and explores how the number of paths and spread of neighbour nodes used by the mobile relays to communicate affects the network overhead. We introduce the idea of allowing the source mobile relay to cache multiple routes to the destination through its neighbour nodes in order to provide redundant paths to destination. An analytical model of network overhead is developed and verified by simulation. It is shown that the desirable number of routes is dependent on the velocity of the mobile relays. In most cases the network overhead is minimized when the source mobile relay caches six paths via appropriately distributed neighbours at the destination. A new technique for estimating routing-path hop count is also proposed. An analytical model is provided to estimate the hop count between source-destination pairs in a wireless network with an arbitrary node degree when the network nodes are uniformly distributed in the sensing field. The proposed model is a significant improvement over existing models, which do not correctly address the low-node density situation