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  • CCNC2017_crc_MLResil

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Multi-level resilience in networked environments: concepts and principles

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Published
Publication date20/07/2017
Host publication2017 14th IEEE Annual Consumer Communications & Networking Conference (CCNC)
PublisherIEEE
Pages272-275
Number of pages4
ISBN (electronic)9781509061969
ISBN (print)9781509061976
<mark>Original language</mark>English
EventIEEE CCNC 2017: The 14th Annual IEEE Consumer Communications & Networking Conference - Las Vegas, Las Vegas, NV, United States
Duration: 8/01/201711/01/2017
http://ccnc2017.ieee-ccnc.org/

Conference

ConferenceIEEE CCNC 2017: The 14th Annual IEEE Consumer Communications & Networking Conference
Abbreviated titleIEEE CCNC 2017
Country/TerritoryUnited States
CityLas Vegas, NV
Period8/01/1711/01/17
Internet address

Conference

ConferenceIEEE CCNC 2017: The 14th Annual IEEE Consumer Communications & Networking Conference
Abbreviated titleIEEE CCNC 2017
Country/TerritoryUnited States
CityLas Vegas, NV
Period8/01/1711/01/17
Internet address

Abstract

Resilience is an essential property for critical networked environments such as utility networks (e.g. gas, water and electricity grids), industrial control systems, and communication networks. Due to the complexity of such networked environments achieving resilience is multi-dimensional since it involves a range of factors such as redundancy and connectivity of different system components as well as availability, security, dependability and fault tolerance. Hence, it is of importance to address resilience within a unified framework that considers such factors and further enables the practical composition of resilience mechanisms. In this paper we firstly introduce the concepts and principles of Multi-Level Resilience (MLR) and then demonstrate its applicability in a particular cloud-based scenario.

Bibliographic note

©2017 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.