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A generalized approach for practical task allocation using a MAPE-K control loop

Book Contribution - Book Abstract Conference Contribution

Fog and edge computing paradigms were adopted to enable Internet of Things (IoT) applications, improving response time and reducing network load. Task allocation algorithms are used on IoT-enabled networks to determine the optimal software placement. However, managing such a network is considerably more complex than allocating the tasks. To simplify management, we propose a general Monitor - Analyze - Plan - Execute over a Knowledge base (MAPE-K) framework in which all requirements for task allocation are fulfilled, and where components can easily be adapted to the use case at hand. This research identifies several pitfalls and proposes solutions. Additionally, we apply this approach to a distributed testbed, comparing it to traditional cloud approaches.
Book: 2021 International Conference on Information and Communication Technology Convergence (ICTC), 20-22 October, 2021
Pages: 779 - 784
Publication year:2021
Keywords:P1 Proceeding