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Sphere: Simulator of edge infrastructures for the optimization of performance and resources energy consumption

Authors :
Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos
Universidad de Sevilla. TIC134: Sistemas Informáticos
Ministerio de Ciencia, Innovación y Universidades (MICINN). España
Fernández Cerero, Damián
Fernández Montes González, Alejandro
Ortega Rodríguez, Francisco Javier
Jakóbik, Agnieszka
Widlak, Adrian
Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos
Universidad de Sevilla. TIC134: Sistemas Informáticos
Ministerio de Ciencia, Innovación y Universidades (MICINN). España
Fernández Cerero, Damián
Fernández Montes González, Alejandro
Ortega Rodríguez, Francisco Javier
Jakóbik, Agnieszka
Widlak, Adrian
Publication Year :
2020

Abstract

Edge computing constitutes a key paradigm to address the new requirements of areas such as smart cars, industry 4.0, and health care, where massive amounts of heterogeneous data from continuous geographically-distributed sources have to be processed and computed near real-time. To this end, new distributed infrastructures consisting on small computing clusters close to data sources, also known as Cloudlets have emerged. In order to evaluate the performance of these solutions we present Sphere, a simulation tool that enables researchers to establish various scenarios, including: (a) topology and orchestration model of the infrastructure; (b) incoming workload patterns; (c) resource-managing models; and (d) scheduling policies. Moreover, Sphere allows researchers to apply efficiency and performance policies both at infrastructure and cluster levels. The simulator presents the following benefits: (a) Evaluation of various orchestration models; (b) Analysis of resource-efficiency and performance strategies at Edge-infrastructure and cluster (Cloudlet/Cloud) level; (c) Execution of diverse workload generation patterns; (d) Evaluation of strategies for the infrastructure communication, as well as the impact on tasks completion time (makespan); and (e) Simulation of each cluster (Cloudlet/Cloud) independently, including resource-managing, scheduling and resource-efficiency models. Finally, we performed a deep evaluation based on realistic Edge-Computing use cases. The results of the experiments confirm that it is a performant and reliable tool for the analysis of orchestration, graph-resolving, energy-efficiency, resource-managing and scheduling strategies in Edge-computing environments.

Details

Database :
OAIster
Notes :
English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1333664986
Document Type :
Electronic Resource