One of the major problems in wireless sensor networks (WSNs) is that resource-constrained sensor nodes consume their limited batteries quickly due to long-distance data communications. The communication distance of the nodes can be decreased using clustering architectures and multi-hop data transmissions; hence, the lifetime of the network can be increased. In this study, two-level intra-cluster and multi-level inter-cluster communication are proposed. The coverage area of the second-level clusters is dynamically determined according to the distance of cluster heads to the BS. Self-organized nodes in the network designate the clustering ranges, the clusters, and the cluster heads without a central control mechanism using a fully distributed approach. Moreover, with the help of static clustering, the control messages generated by the system are decreased. The proposed approach, FDEAM, is compared with recent approaches in terms of the network lifetime, network energy consumption, cluster head alteration frequency, dead parent statistics, and data collection.The results show that FDEAM outperforms state-of-the-art approaches for all performance metrics.
Due to the positioning in hostile environment, wireless sensor networks (WSNs) are prone to various attacks. Hence, security is one of the most important issues in these networks. Therefore, detecting and preventing several kinds of attacks on WSNs is a popular subject in literature. However, handling these attacks on WSNs requires realistic modeling of these attacks since most of WSNs are application specific. In this paper, two kinds of serious attacks called the sinkhole and the black hole attack are modelled on the LEACH, which is a common clusterbased WSN. Three models are designed for these attacks and the results are evaluated under different performance metrics for different number of nodes. The results show that the black hole attack with a black hole region, which damages the network more than the other attacks, inclines 38% of the packets to be dropped. Index Terms-black hole, LEACH, sinkhole, wireless sensor network
Abstract-Due to the resource limitations of the sensor nodes, the most important issue in Wireless Sensor Networks (WSNs) is prolonging overall network lifetime by using energy-efficient routing algorithms. Cluster-based routing protocols have proven to be effective in network topology management, energy minimization and data aggregation. Clustering process can be conducted by a distributed or a centralized manner. In this paper, a distributed and a centralized clustering algorithms are scrutinized under different network parameters, including the size of the network and the location of the base station. The results are evaluated by using the death of the first node and the death of the last node since they are the indicators of the quality and the lifetime of the network. The results show that the distributed approach performs better than the centralized equivalent up to 24.5% for small scale networks when the BS is inside the network. However, as the size of the network increases or as the BS moves away from the network, the centralized approach gets the advantage.
The position of the base station (BS) in wireless sensor networks (WSNs) has a significant impact on network lifetime. This paper suggests a mobile BS positioning algorithm for clusterbased WSNs, which considers both the location and the remaining energy level of the cluster heads in the network and evaluate the performance of the algorithm under different values of network sizes, including 100m x 100m, 200m x 200m and 300m x 300m. Simulations are conducted by using OMNeT++ and proposed method is compared with two different static BS positions, including central and external, on HEED protocol. The results show that mobile BS performs better than both central and external BS positions under all network sizes. Besides, the performance difference between the proposed method and the others increases as the size of the network increases, which demonstrates that the proposed mobile BS positioning also provides scalability.
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