Data Collection and Node Counting by Opportunistic Communication

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http://hdl.handle.net/10138/330214

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Li , T , Kouyoumdjieva , S T , Karlsson , G & Hui , P 2019 , Data Collection and Node Counting by Opportunistic Communication . in 2019 IFIP NETWORKING CONFERENCE (IFIP NETWORKING) . , UNSP 1570511170 , International Federation for Information Processing , IEEE , New York , International-Federation-for-Information-Processing (IFIP) Networking Conference (IFIP Networking) , Warsaw , Poland , 20/05/2019 . https://doi.org/10.23919/IFIPNetworking46909.2019.8999476

Title: Data Collection and Node Counting by Opportunistic Communication
Author: Li, Tong; Kouyoumdjieva, Sylvia T.; Karlsson, Gunnar; Hui, Pan
Contributor: University of Helsinki, Hong Kong University of Science and Technology
University of Helsinki, Department of Computer Science
Publisher: IEEE
Date: 2019
Language: eng
Number of pages: 9
Belongs to series: 2019 IFIP NETWORKING CONFERENCE (IFIP NETWORKING)
Belongs to series: International Federation for Information Processing
ISBN: 978-1-7281-3671-4
978-3-903176-16-4
URI: http://hdl.handle.net/10138/330214
Abstract: Ever more powerful mobile devices are nowadays capable of collectively carrying out reasonably demanding computational tasks without offloading the processing to an edge server or a distant cloud-computing service. In this work, we explore such distributed computing and study how it is affected by the mobility as well as the number of nodes that collaborate. We choose distributed counting of a number of nodes in an enclosed area as application. Such application is useful for estimating attendance at events and measuring occupancy for facility management, as needed for monitoring of crowdedness with respect to safety and evacuation, climate control and comfort. For this application, we are interested in determining the time until all nodes know the correct number of nodes in the space where they reside. Our study shows the effect of mobility on the distributed process. We find that the process of collecting data opportunistically from a closed set of nodes is well described by empirical laws that we derive. We discuss the results and suggest further work needed to understand opportunistic computation and to develop it as a new model of computation among collectives of mobile nodes.
Subject: opportunistic computing
distributed computing
data collection
counting
113 Computer and information sciences
213 Electronic, automation and communications engineering, electronics
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