A Nonuniform Clustering Routing Algorithm Based on an Improved K-Means Algorithm

In a large-scale wireless sensor network(WSN),densely distributed sensor nodes process a large amount of data.The aggregation of data in a network can consume a great amount of energy.To balance and reduce the energy consumption of nodes in a WSN and extend the network life,this paper proposes a nonuniform clustering routing algorithm based on the improved K-means algorithm.The algorithm uses a clustering method to form and optimize clusters,and it selects appropriate cluster heads to balance network energy consumption and extend the life cycle of the WSN.To ensure that the cluster head(CH)selection in the network is fair and that the location of the selected CH is not concentrated within a certain range,we chose the appropriate CH competition radius.Simulation results show that,compared with LEACH,LEACH-C,and the DEEC clustering algorithm,this algorithm can effectively balance the energy consumption of the CH and extend the network life.

Efficient Clustering Routing Algorithm Based on Opportunistic Routing

Based on the analysis of the existing classic clustering routing algorithm HEED, this paper proposes an efficient dynamic clustering routing algorithm ED-HEED. In the cluster selection process, in order to optimize the network topology and select more proper nodes as the cluster head, the proposed clustering algorithm considers the shortest path prediction of the node to the destination sink and the congestion situation. In the data transmission procedure, the high-efficiency CEDOR opportunistic routing algorithm is applied into the ED-HEED as the data transmission mode between cluster headers. A novel adaptive dynamic clustering mechanism is also considered into the algorithm, as well as the data redundancy and security control. Our Simulation demonstrates that the ED-HEED algorithm can reduce the energy consumption, prolong the network life and keep the security and availability of the network compared with the HEED algorithm.

Clustering routing algorithm of self-energized wireless sensor networks based on solar energy harvesting

Aiming at the problems of existing clustering routing algorithm of self-energized wireless sensor networks（WSNs） on fixed threshold for resurrection, incapacitates reappoint cluster head in the next round and lack of election limit, this paper proposes a novel clustering routing algorithm for self-energized WSNs clustering routing algorithm based on solar energy harvesting（CRBS） algorithm. The algorithm puts forward a threshold sensitive resurrection mechanism, reviving the node when harvesting energy reaches the set soft or hard energy threshold. Meanwhile, combined with current energy harvesting level, cluster head node can decide whether to reappoint the cluster head in the next round. What＇s more, CRBS optimizes the cluster head election threshold to limit the incompetent node in election. Combined with the solar energy harvesting simulation, the results show that CRBS algorithm can better keep the default cluster head proportion, and outperforms energy balanced clustering with self-energization（EBCS） algorithm in terms of surviving nodes number and the success ratio of data transmission