Proactive vs reactive failure recovery assessment in combined fog-to-cloud (F2C) systems
Document typeConference report
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Rights accessOpen Access
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ProjectmF2C - Towards an Open, Secure, Decentralized and Coordinated Fog-to-Cloud Management Ecosystem (EC-H2020-730929)
The increasing number of end user devices at the edge of the network, along with their ever increasing computing capacity, as well as the advances in Data Center technologies, paved the way for the generation of Internet of Things (IoT). Several IoT services have been deployed leveraging Cloud Computing and, more recently, Fog Computing. In order to enable efficient control of cloud and fog premises, Fog-to-Cloud (F2C) has been recently proposed as a distributed architecture for coordinated management of both fog and cloud resources. Certainly, many challenges remain unsolved in combined Fog-to-Cloud systems, mostly driven by the dynamicity and volatility imposed by edge devices, such as the recovery of failures at the edge of the network. Indeed, possible failures in computing commodities may be prohibitive for the achievement of the envisioned performance in F2C systems. In this work, we assess proactive and reactive strategies for failure recovery of network elements by modelling them as a Multidimensional Knapsack Problem (MKP) and study the impact of each one on several aspects such as service allocation time, recovery delay and computing resources load. The obtained results show the effect each strategy brings, thus concluding with some analysis on the recovery strategy best suiting distinct IoT scenarios.
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CitationSouza, V., Masip, X., Marin, E., Ramirez, W., Sanchez, S. Proactive vs reactive failure recovery assessment in combined fog-to-cloud (F2C) systems. A: IEEE International Workshop on Computer-aided Modeling Analysis and Design of Communication Links and Networks. "2017 IEEE 22nd International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD 2017): Lund, Sweden: 19-21 June 2017". Lund: Institute of Electrical and Electronics Engineers (IEEE), 2017, p. 1-5.