Abstract
Due to significant environmental changes in the telecommunications market, network failures affect socioeconomic activities more than ever before. In this paper, we investigate the statistical characteristics of interval, duration, and number of users affected for serious network failures, which are defined as network failures that last for more than two hours and affect more than 30,000 users, that occurred in Japan during Japanese fiscal years 2008-2013 (April 2008 to March 2014). The results show that (i) the interval follows a Poisson process, (ii) the duration follows a Pareto distribution, (iii) the number of users affected follows a piecewise Pareto distribution, (iv) the product of duration and number of users affected roughly follows a distribution that can be derived from a convolution of two distributions of duration and number of users affected, (v) the relationship between duration and number of users affected differs from service to service, and (vi) the impact of recent serious network failures is getting more severe.
Original language | English |
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Title of host publication | Proceedings - 2015 International Conference on Intelligent Networking and Collaborative Systems, IEEE INCoS 2015 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 478-485 |
Number of pages | 8 |
ISBN (Electronic) | 9781467376945 |
DOIs | |
Publication status | Published - 2015 Oct 28 |
Externally published | Yes |
Event | 7th International Conference on Intelligent Networking and Collaborative Systems, IEEE INCoS 2015 - Taipei, Taiwan, Province of China Duration: 2015 Sep 2 → 2015 Sep 4 |
Other
Other | 7th International Conference on Intelligent Networking and Collaborative Systems, IEEE INCoS 2015 |
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Country/Territory | Taiwan, Province of China |
City | Taipei |
Period | 15/9/2 → 15/9/4 |
Keywords
- failure duration
- failure interval
- Network failure
- Number of users affected
ASJC Scopus subject areas
- Computer Networks and Communications
- Computer Science Applications
- Hardware and Architecture
- Artificial Intelligence