Updating Neighbour Cell List via Crowdsourced User Reports: A Framework for Measuring Time Performance
In modern wireless networks deployments, each serving node needs to keep its Neighbour Cell List (NCL) constantly up to date to keep track of network changes. The time needed by each serving node to update its NCL is an important parameter of the network’s reliability and performance. An adequate es...
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Series: | Wireless Communications and Mobile Computing |
Online Access: | http://dx.doi.org/10.1155/2018/9028427 |
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doaj-5b04be187c6e4d1e88ce7170b438632e2020-11-25T01:14:46ZengHindawi-WileyWireless Communications and Mobile Computing1530-86691530-86772018-01-01201810.1155/2018/90284279028427Updating Neighbour Cell List via Crowdsourced User Reports: A Framework for Measuring Time PerformanceA. Checco0C. Lancia1D. J. Leith2University of Sheffield, Sheffield, UKLeiden University, Leiden, NetherlandsTrinity College Dublin, Dublin, IrelandIn modern wireless networks deployments, each serving node needs to keep its Neighbour Cell List (NCL) constantly up to date to keep track of network changes. The time needed by each serving node to update its NCL is an important parameter of the network’s reliability and performance. An adequate estimate of such parameter enables a significant improvement of self-configuration functionalities. This paper focuses on the update time of NCLs when an approach of crowdsourced user reports is adopted. In this setting, each user periodically reports to the serving node information about the set of nodes sensed by the user itself. We show that, by mapping the local topological structure of the network onto states of increasing knowledge, a crisp mathematical framework can be obtained, which allows in turn for the use of a variety of user mobility models. Further, using a simplified mobility model we show how to obtain useful upper bounds on the expected time for a serving node to gain Full Knowledge of its local neighbourhood.http://dx.doi.org/10.1155/2018/9028427 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
A. Checco C. Lancia D. J. Leith |
spellingShingle |
A. Checco C. Lancia D. J. Leith Updating Neighbour Cell List via Crowdsourced User Reports: A Framework for Measuring Time Performance Wireless Communications and Mobile Computing |
author_facet |
A. Checco C. Lancia D. J. Leith |
author_sort |
A. Checco |
title |
Updating Neighbour Cell List via Crowdsourced User Reports: A Framework for Measuring Time Performance |
title_short |
Updating Neighbour Cell List via Crowdsourced User Reports: A Framework for Measuring Time Performance |
title_full |
Updating Neighbour Cell List via Crowdsourced User Reports: A Framework for Measuring Time Performance |
title_fullStr |
Updating Neighbour Cell List via Crowdsourced User Reports: A Framework for Measuring Time Performance |
title_full_unstemmed |
Updating Neighbour Cell List via Crowdsourced User Reports: A Framework for Measuring Time Performance |
title_sort |
updating neighbour cell list via crowdsourced user reports: a framework for measuring time performance |
publisher |
Hindawi-Wiley |
series |
Wireless Communications and Mobile Computing |
issn |
1530-8669 1530-8677 |
publishDate |
2018-01-01 |
description |
In modern wireless networks deployments, each serving node needs to keep its Neighbour Cell List (NCL) constantly up to date to keep track of network changes. The time needed by each serving node to update its NCL is an important parameter of the network’s reliability and performance. An adequate estimate of such parameter enables a significant improvement of self-configuration functionalities. This paper focuses on the update time of NCLs when an approach of crowdsourced user reports is adopted. In this setting, each user periodically reports to the serving node information about the set of nodes sensed by the user itself. We show that, by mapping the local topological structure of the network onto states of increasing knowledge, a crisp mathematical framework can be obtained, which allows in turn for the use of a variety of user mobility models. Further, using a simplified mobility model we show how to obtain useful upper bounds on the expected time for a serving node to gain Full Knowledge of its local neighbourhood. |
url |
http://dx.doi.org/10.1155/2018/9028427 |
work_keys_str_mv |
AT achecco updatingneighbourcelllistviacrowdsourceduserreportsaframeworkformeasuringtimeperformance AT clancia updatingneighbourcelllistviacrowdsourceduserreportsaframeworkformeasuringtimeperformance AT djleith updatingneighbourcelllistviacrowdsourceduserreportsaframeworkformeasuringtimeperformance |
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1725156689762582528 |