2018 · 17 citations · 14 references
ComputingComputer ScienceComputer SystemsCloud ArchitectureCloud InfrastructureCloud Performance OptimizationCloud Resource ManagementPerformance OptimizationResource ProvisioningResource SchedulingThroughput OptimizationWorkload PlacementMicroservice DeploymentMicroservice PlacementMicroservices DeploymentNetwork ResourcesNp-hardnessParticle Swarm OptimizationResponse TimeService Placement
It is now feasible for consumers to buy inexpensive devices that can be installed at home and accessed remotely thanks to an Internet connection. Such a simple "self-hosting" can be an alternative to traditional cloud providers, especially for privacy-conscious users. We discuss how a community of users can pool their devices in order to host microservices-based applications, where each microservice is deployed on a different device. The performance of such an application depends heavily on the computing and network resources that are available and on the placement of each microservice. Finding the placement that minimizes the application response time is an NP-hard problem. We show that, thanks to well known optimization techniques (Particle Swarm Optimization), it is possible to quickly find a service placement resulting in a response time close to the optimal one. Thanks to an emulation platform, we evaluate the robustness of this solution to changes in the Quality of Service under conditions typical of a residential access network.
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A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy · 2002 · 14.9K citations
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David P. Anderson, Gilles Fedak · 2006 · 322 citations