Exploiting Spatiotemporal Correlation for Wireless Networks under Interference

Song Min Kim, Shuai Wang, Tian He

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


This paper starts from an empirical observation on the existence of spatiotemporal correlation among nearby wireless links within short time intervals. The phenomenon due to correlated interference has become pervasive with densely deployed wireless devices, causing potential errors in existing popular metrics built upon the assumption of link independence. To this end, we propose correlated ETX (cETX), which generalizes the widely-adopted ETX to maintain the accuracy under correlated links. To the best of our knowledge, this is the first work to introduce a unified metric embracing both temporal and spatiotemporal correlations. As a generalized metric, the highlight of our work is the broad applicability and effectiveness-extensive evaluations on ZigBee (802.15.4) and Wi-Fi (802.11b/g/n) testbeds deployed in a lab, corridor, and on a bridge reveal that: simply replacing ETX with cETX: 1) cuts down the error by 62.1%-70.2% and 2) saves averages of 22% and 37% communication cost in three unicast and nine broadcast protocols, respectively, under only 0.7% additional overhead.

Original languageEnglish (US)
Article number8008814
Pages (from-to)3132-3145
Number of pages14
JournalIEEE/ACM Transactions on Networking
Issue number5
StatePublished - Oct 2017

Bibliographical note

Funding Information:
Manuscript received July 19, 2016; revised May 9, 2017; accepted June 24, 2017; approved by IEEE/ACM TRANSACTIONS ON NETWORKING Editor J. Xie. Date of publication August 11, 2017; date of current version October 13, 2017. This work was supported in part by the National Science Foundation under Grant CNS-1525235, Grant CNS-1444021, Grant CNS-1717059, and Grant CNS-1718456. A conference paper [25] containing preliminary results of this paper appeared in ACM SenSys 2015. (Corresponding author: Tian He.) S. M. Kim is with the Department of Computer Science, George Mason University, Fairfax, VA 22030 USA (e-mail: song@gmu.edu).


  • Wireless routing
  • energy efficiency
  • route metrics

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