An Ant Colony Optimization-Based Multiobjective Service Replicas Placement Strategy for Fog Computing
| Autor: | Weiwei Lin, Jingxuan Huang, Rui Pan, Tiansheng Huang, Chennian Xiong |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Computer science
business.industry Distributed computing Ant colony optimization algorithms Internet of Things Pareto principle 020206 networking & telecommunications Cloud computing 02 engineering and technology Computer Science Applications Scheduling (computing) Human-Computer Interaction Control and Systems Engineering Software deployment 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Electrical and Electronic Engineering business Software Edge computing Algorithms Information Systems |
| Zdroj: | IEEE transactions on cybernetics. 51(11) |
| ISSN: | 2168-2275 |
| Popis: | In recent years, fog computing has emerged as a new paradigm for the future Internet-of-Things (IoT) applications, but at the same time, ensuing new challenges. The geographically vast-distributed architecture in fog computing renders us almost infinite choices in terms of service orchestration. How to properly arrange the service replicas (or service instances) among the nodes remains a critical problem. To be specific, in this article, we investigate a generalized service replicas placement problem that has the potential to be applied to various industrial scenarios. We formulate the problem into a multiobjective model with two scheduling objectives, involving deployment cost and service latency. For problem solving, we propose an ant colony optimization-based solution, called multireplicas Pareto ant colony optimization (MRPACO). We have conducted extensive experiments on MRPACO. The experimental results show that the solutions obtained by our strategy are qualified in terms of both diversity and accuracy, which are the main evaluation metrics of a multiobjective algorithm. |
| Databáze: | OpenAIRE |
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