Clustering-based routing for top-k querying in wireless sensor networks
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RESEARCH
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Clustering-based routing for top-k querying in wireless sensor networks Shangfeng Mo1,2,3, Hong Chen1,2* and Yinglong Li1,2,3
Abstract A large-scale wireless sensor networks (WSNs) can be deployed for top-k querying applications. There are many top-k querying algorithms which are based on traditional routing approaches. In this article, we proposed a clustering-based routing for top-k querying (CRTQ) in WSNs to save the energy consumption and extend the network lifetime. The proposed scheme consists of two parts: one is the cluster formation algorithm; another part is the inter-cluster choosing the relay cluster head algorithm. Moreover, we adopt a corresponding dynamic clustering algorithm. Our experimental result shows that CRTQ substantially outperforms the existing tree-based approaches and clustering-based approaches in terms of both energy consumption and network lifetime. Keywords: WSNs, clustering-based, routing, top-k querying.
1. Introduction Wireless sensor networks (WSNs) are a combination of sensing technology, embedded computing technology, distributed information processing and communication technology [1,2]. All sensor nodes can collaborate with each other to monitor, sense, and collect the information of environment or monitoring object, and to send the needed information to user. The technology of WSNs is considered as one of the most important technologies in the twenty-first century, and it will have a far-reaching impact on the human life in the future. From the logical view of the data, WSNs can be viewed as a distributed database. The data management system of WSNs manages perceptible data from the monitored area and answers queries from users or applications. Continuous top-k querying is defined as the algorithm in which the sink continuously requests the list of k sensor nodes with the highest (or lowest) readings at every sampling period. The characteristics of a top-k querying are to reduce the amount of data transmission and thus save energy consumption. If only parts of nodes forward their readings to the sink, then it can also obtain the top-k result correctly, which can prolong the network lifetime and be used in most of top-k querying algorithms. * Correspondence: [email protected] Full list of author information is available at the end of the article
In recent years, there are many top-k querying algorithms (e.g., FILA [3], POT [4], PRIM [5], PRIM-c [6]), which consider how to reduce the amount of transmission data, thus reducing energy consumption and prolonging network lifetime. These algorithms are based on traditional routing algorithms with little change to the routing algorithms. For example, FILA and PRIM are based on the TAG [7] routing tree; PRIM-c is based on the hierarchical clustering and routing algorithms, such as LEACH [8], and HEED [9]. As shown in Figure 1a, the sink (the base station) node is located at the center, and ordinary nodes selforganize into a tree structure which is called TAG routing tree. Figure 1b shows an example of FILA quer
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