A combinatorial algorithm for the maximum lifetime data gathering with aggregation problem in sensor networks

  • Authors:
  • Konstantinos Kalpakis;Shilang Tang

  • Affiliations:
  • Computer Science & Electrical Engineering Department, University of Maryland Baltimore County, 1000 Hilltop Circle, Baltimore, MD 21250, USA;Computer Science & Electrical Engineering Department, University of Maryland Baltimore County, 1000 Hilltop Circle, Baltimore, MD 21250, USA

  • Venue:
  • Computer Communications
  • Year:
  • 2009

Quantified Score

Hi-index 0.24

Visualization

Abstract

Performing tasks energy efficiently in a wireless sensor network (WSN) is a critical issue for the successful deployment and operation of such networks. Gathering data from all the sensors to a base station, especially with in-network aggregation, is an important problem that has received a lot of attention recently. The Maximum Lifetime Data Gathering with Aggregation (MLDA) problem deals with maximizing the system lifetime T so that we can perform T rounds of data gathering with in-network aggregation, given the initial available energy of the sensors. A solution of value T to the MLDA problem consists of a collection of aggregation trees together with the number of rounds each such tree should be used in order to achieve lifetime T. We describe a combinatorial iterative algorithm for finding an optimal continuous solution to the MLDA problem that consists of up to n-1 aggregation trees and achieves lifetime T"o, which depends on the network topology and initial energy available at the sensors. We obtain an @a-approximate optimal integral solution by simply rounding down the optimal continuous solution, where @a=(T"o-n+1)/T"o. Since in practice T"o@?n,@a~1. We get asymptotically optimal integral solutions to the MLDA problem whenever the optimal continuous solution is @w(n). Furthermore, we demonstrate the efficiency and effectiveness of the proposed algorithm via extensive experimental results.