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GIST: Group-Independent Spanning Tree for Data Aggregation in Dense Sensor Networks

  • Lujun Jia
  • Guevara Noubir
  • Rajmohan Rajaraman
  • Ravi Sundaram
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4026)

Abstract

Today, there exist many algorithms and protocols for constructing agregation or dissemination trees for wireless sensor networks that are optimal (for different notions of optimal, i.e. under different cost metrics). However, all these schemes differ from one common failing – they construct an optimal tree for a given fixed subset of the sensors. In most practical scenarios, the sensor group is continuously and dynamically varying – consider for example the set of sensors scattered in a forest that are sensing temperatures above some specified threshold, during a wildfire. Given the limited computational and energy resources of sensor nodes it is impossible to either prestore the optimal tree for every conceivable group or to dynamically generate them on the fly.

In this paper we propose the novel approach of constructing a single group-independent spanning tree (GIST) T for the network and then letting any sensor group S use the subtree induced by S on T, T S as its group aggregation tree. The important question is, how does the quality of the subtree T S compare to the optimal tree, OPT S , across different groups S. We consider two well-accepted measures – aggregation cost (sum over all links) and delay (diameter). We show that in polynomial time we can construct a GIST that simultaneously achieves O(log n)-approximate aggregation cost and O(1)-approximate delay, for all groups S.

To the best of our knowledge GIST is the first construction with a nontrivial and provable performance guarantee that works for all groups. We provide a practical and distributed protocol for realizing GIST that requires only local knowledge. We show an Ω(n) lower bound for commonly accepted solutions such as MST and SPT (i.e. there exists a group for which the induced subtree performs poorly) and demonstrate by simulation that GIST is good not just in the worst case – it outperforms SPT and MST by between 30 and 60 per cent in realistic random scenarios. GIST is an overlay construction and for the special case of grids we present GRID-GIST, a physical tree that uses only grid edges and achieves the same performance bounds.

Keywords

Sensor Network Sensor Node Wireless Sensor Network Span Tree Relay Node 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Lujun Jia
    • 1
  • Guevara Noubir
    • 1
  • Rajmohan Rajaraman
    • 1
  • Ravi Sundaram
    • 1
  1. 1.College of Computer and Information ScienceNortheastern UniversityBostonUSA

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