Wireless Networks

, Volume 24, Issue 4, pp 1313–1325 | Cite as

A unified delay analysis framework for opportunistic data collection

  • Dong Zhao
  • Huadong Ma
  • Qi Li
  • Shaojie Tang


The opportunistic data collection paradigm leverages human mobility to improve sensing coverage and data transmission for collecting data from a number of Points of Interest scattered across a large sensing field, enabling many large-scale mobile crowd sensing applications at lower cost. Sensing delay and transmission delay are two critical Quality of Service (QoS) metrics for such applications. However, the existing works only study them separately, and do not fully consider the effects of various sink deployment schemes (i.e., single sink or multiple sinks, and sinks are static or mobile) and transmission schemes (i.e., direct transmission, epidemic transmission or other schemes). In contrast, we provide a unified delay analysis framework for opportunistic data collection, by integrating both the sensing and transmission delays, to describe the QoS more comprehensively. We analyze how the three delays (sensing delay, transmission delay, and a novel metric called data collection delay) vary with several parameters considering the effects of various sink deployment schemes and transmission schemes. Validity of the theoretic analysis is verified by simulations.


Mobile crowd sensing Delay analysis Opportunistic sensing Opportunistic data collection 



This work is supported by the National Natural Science Foundation of China under Grant Nos. 61332005, 61502051, and 61302087, the Funds for Creative Research Groups of China under Grant No. 61421061, the Cosponsored Project of Beijing Committee of Education, and the Beijing Training Project for the Leading Talents in S&T (ljrc201502).


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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.Beijing Key Lab of Intelligent Telecommunication Software and MultimediaBeijing University of Posts and TelecommunicationsBeijingChina
  2. 2.School of Computer ScienceBeijing University of Posts and TelecommunicationsBeijingChina
  3. 3.Naveen Jindal School of ManagementUniversity of Texas at DallasRichardsonUSA

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