Maximizing lifetime of data-gathering trees with different aggregation modes in WSNs

Fen Zhou, Zhenzhong Chen, Song Guo, Jie Li

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

4 Citations (Scopus)


We study the problem of maximizing the lifetime of data-gathering tree for wireless sensor networks (WSNs). Both data routing and aggregation are considered at the same time to improve the energy efficiency for data collection in WSNs. With different data-aggregation methods, three aggregation modes are studied: full aggregation, non-aggregation, and a hybrid partialaggregation using Compressive Sensing. For each mode, an exact solution based on Mixed-integer linear programming (MIP) is proposed to find the optimal data-gathering tree. Although nonlinear relation exists between the sensor node lifetime and the number of data units that receives or transmits in each time slot, we succeed to express it by a set of linear equations. Performance results demonstrate that the lifetime of data-gathering tree can be increased tenfold with efficient data aggregation methods.
Original languageEnglish
Title of host publication2015 IEEE Global Communications Conference, GLOBECOM 2015
ISBN (Electronic)9781479959525
Publication statusPublished - 1 Jan 2015
Externally publishedYes
Event58th IEEE Global Communications Conference, GLOBECOM 2015 - San Diego, United States
Duration: 6 Dec 201510 Dec 2015


Conference58th IEEE Global Communications Conference, GLOBECOM 2015
Country/TerritoryUnited States
CitySan Diego


  • Compressive Sensing (CS)
  • Data-Gathering Tree
  • Full Aggregation
  • Hybrid Partial- Aggregation
  • Mixed Integer linear Programming (MIP)
  • Non-Aggregation
  • WSNs

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Electrical and Electronic Engineering
  • Communication

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