Imperial College London

ProfessorJulieMcCann

Faculty of EngineeringDepartment of Computing

Professor of Computer Systems
 
 
 
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Contact

 

+44 (0)20 7594 8375j.mccann Website

 
 
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Location

 

258ACE ExtensionSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@inproceedings{Kolcun:2015:10.1109/IOT.2015.7356550,
author = {Kolcun, R and Boyle, D and McCann, JA},
doi = {10.1109/IOT.2015.7356550},
pages = {72--79},
publisher = {IEEE},
title = {Optimal processing node discovery algorithm for distributed computing in IoT},
url = {http://dx.doi.org/10.1109/IOT.2015.7356550},
year = {2015}
}

RIS format (EndNote, RefMan)

TY  - CPAPER
AB - The number of Internet-connected sensing and control devices is growing. Some anticipate them to number in excess of 212 billion by 2020. Inherently, these devices generate continuous data streams, many of which need to be stored and processed. Traditional approaches, whereby all data are shipped to the cloud, may not continue to be effective as cloud infrastructure may not be able to handle myriads of data streams and their associated storage and processing needs. Using cloud infrastructure alone for data processing significantly increases latency, and contributes to unnecessary energy inefficiencies, including potentially unnecessary data transmission in constrained wireless networks, and on cloud computing facilities increasingly known to be significant consumers of energy. In this paper we present a distributed platform for wireless sensor networks which allows computation to be shifted from the cloud into the network. This reduces the traffic in the sensor network, intermediate networks, and cloud infrastructure. The platform is fully distributed, allowing every node in a homogeneous network to accept continuous queries from a user, find all nodes satisfying the user's query, find an optimal node (Fermat-Weber point) in the network upon which to process the query, and provide the result to the user. Our results show that the number of required messages can be decreased up to 49% and processing latency by 42% in comparison with state-of-the-art approaches, including Innet.
AU - Kolcun,R
AU - Boyle,D
AU - McCann,JA
DO - 10.1109/IOT.2015.7356550
EP - 79
PB - IEEE
PY - 2015///
SP - 72
TI - Optimal processing node discovery algorithm for distributed computing in IoT
UR - http://dx.doi.org/10.1109/IOT.2015.7356550
UR - http://hdl.handle.net/10044/1/37002
ER -