Top-K with Diversity-M Data Retrieval in WSNs

Alternative Title

Top-K with Diversity-M Data Retrieval in Wireless Sensor Networks


In applications of Wireless Sensor Networks (WSNs) such as monitoring chemical leaks in case of a disaster, a user may be interested in getting top-k with diversity-m (referred as Top (k, m)), that is, top-k data should come from m different sub-regions (clusters) to simultaneously monitor critical areas. In addition, one may also monitor values for persistency, how long the top-k values remain unchanged. In this paper, we have introduced the new problem of continuous top-k query with diversity-m, i.e., we want to find the k highest values from at least m different clusters over a period of time in a WSN. In this context, we introduce an energy efficient scheme Top (k, m) to utilize the Gaussian's probability function to estimate the probability of a sensor node value being in the final top-k set. Based on the probability, the node decides whether to forward data values to the base station or not. Moreover, we make sure that top-k data items are not only collected from m-clusters, but they are also persistency, which is helpful in real-time monitoring applications. We have shown the improved performance of our scheme with respect to recent schemes EXTOK and Grid in terms of communication, energy usage and network life-time.

Meeting Name

17th IEEE International Conference on Mobile Data Management, MDM (2016: Jun. 13-16, Porto, Portugal)


Computer Science

Research Center/Lab(s)

Intelligent Systems Center

Keywords and Phrases

Base stations; Standards; Monitoring; Wireless sensor networks; Clustering algorithms; Approximation algorithms; Temperature sensors

International Standard Book Number (ISBN)


International Standard Serial Number (ISSN)


Document Type

Article - Conference proceedings

Document Version


File Type





© 2016 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.

Publication Date

16 Jul 2016