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A Review on Computational Intelligence Techniques in Cloud and Edge Computing

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Document pages: 22 pages

Abstract: Cloud computing (CC) is a centralized computing paradigm that accumulatesresources centrally and provides these resources to users through Internet.Although CC holds a large number of resources, it may not be acceptable byreal-time mobile applications, as it is usually far away from usersgeographically. On the other hand, edge computing (EC), which distributesresources to the network edge, enjoys increasing popularity in the applicationswith low-latency and high-reliability requirements. EC provides resources in adecentralized manner, which can respond to users requirements faster than thenormal CC, but with limited computing capacities. As both CC and EC areresource-sensitive, several big issues arise, such as how to conduct jobscheduling, resource allocation, and task offloading, which significantlyinfluence the performance of the whole system. To tackle these issues, manyoptimization problems have been formulated. These optimization problems usuallyhave complex properties, such as non-convexity and NP-hardness, which may notbe addressed by the traditional convex optimization-based solutions.Computational intelligence (CI), consisting of a set of nature-inspiredcomputational approaches, recently exhibits great potential in addressing theseoptimization problems in CC and EC. This paper provides an overview of researchproblems in CC and EC and recent progresses in addressing them with the help ofCI techniques. Informative discussions and future research trends are alsopresented, with the aim of offering insights to the readers and motivating newresearch directions.

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