In wireless sensor networks, sensor nodes are usually powered by battery and thus have very limited energy. Saving energy is an important goal in designing a WSN. It is known that clustering is an effective method to prolong network lifetime. Due to the development of big data, there are more sensor nodes and data needed to process. So how to cluster sensor nodes cooperatively and achieve an optimal number of clusters in a big data WSN is an open issue. In this paper, we first propose an analytical model to give the optimal number of clusters in a wireless sensor network. We then propose a centralized cluster algorithm based on spectral partitioning method. After that, we present a distributed implementation of the clustering algorithm based on fuzzy C-means method. Finally, we conduct extensive simulations, and the results show that the proposed algorithms outperform the hybrid energy-efficient distributed (HEED) clustering algorithm in terms of energy cost and network lifetime.
In this paper, we propose a joint subcarrier pairing and power allocation (JS2PA) scheme with fairness based on the Intelligent Water Drop (IWD) optimization method for Orthogonal Frequency Division Multiple Access (OFDMA) cooperative relay networks. The proposed scheme consists of a subcarrier pairing and selection algorithm and a power allocation algorithm. We first formulate the JS2PA problem as a mixed integer programming problem aiming to maximize the total network utility under the constraints of the total and individual power, subcarrier fairness requirement and pairing. To solve the non-convex JS2PA problem, firstly, we propose a subcarrier pairing and selection algorithm based on Hungarian method so as to select the appropriate subcarrier pairs for relaying. Secondly, we provide a power allocation algorithm based on the IWD method (PA-MIWD) in which water drops act as the agents to find the optimal power allocation for each node. Finally, we conduct simulations to validate the proposed algorithms and the results show that the proposed JS2PA scheme outperforms the existing methods in terms of convergence and total network utility.
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