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Energy-effective Io...
Energy-effective IoT Services in Balanced Edge-Cloud Collaboration Systems
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- Xiang, Zhengzhe (author)
- Zhejiang University City College, China
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- Deng, Shuiguang (author)
- College of Computer Science and Technology, Zhejiang University, China
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- Zheng, Yuhang (author)
- School of Computer and Computing Science, Zhejiang University City College, China
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- Wang, Dongjing (author)
- Hangzhou Dianzi University, China
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- Taheri, Javid (author)
- Karlstads universitet,Institutionen för matematik och datavetenskap (from 2013)
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- Zheng, Zengwei (author)
- School of Computer and Computing Science, Zhejiang University City College, China
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(creator_code:org_t)
- Institute of Electrical and Electronics Engineers Inc. 2021
- 2021
- English.
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In: <em>2021 IEEE International Conference on Web Services (ICWS)</em>. - : Institute of Electrical and Electronics Engineers Inc.. - 9781665416818 ; , s. 219-229
- Related links:
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Subject headings
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- The rapid development of the Internet-of-Things (IoT) makes it convenient to sense and collect real-world information with different kinds of widely distributed sensors. With plenty of web services providing diverse functions on the cloud, the collected information can be sufficiently used to complete complex tasks after being uploaded. However, the latency brought by long-distance communication and network congestion limits the development of IoT platforms. A feasible approach to solve this problem is to establish an edge-cloud collaboration (ECC) system based on the multi-access edge computing (MEC) paradigm where the collected information can be refined with the services deployed on nearby edge servers. However, as the edge servers are resource-limited, we should be more careful in allocating the edge resource to services, as well as designing the traffic scheduling strategy. In this paper, we investigated the edge-cloud cooperation mechanism of service provisioning in ECC systems, and to that end, proposed an energy-consumption model for it; we also proposed a performance model and balancing model to quantify the running state of ECC systems. Based on these, we further formulated the energy-effective ECC system optimization problem as a joint optimization problem whose decision variables are the resource allocation strategy and traffic scheduling strategy. With the convexity of this problem proved, we proposed an algorithm to solve it and conducted a series of experiments to evaluate its performance. The results showed that our approach can improve at least 4.3 % of the performance compared with representative baselines.
Subject headings
- NATURVETENSKAP -- Data- och informationsvetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences (hsv//eng)
Keyword
- Green Computing
- Internet-of-Things
- Multi-access Edge Computing
- Service Management
- Edge computing
- Energy utilization
- Optimization
- Scheduling
- Web services
- Collaboration systems
- Edge clouds
- Edge server
- Energy
- Multiaccess
- Scheduling strategies
- Traffic scheduling
- Internet of things
- Computer Science
- Datavetenskap
Publication and Content Type
- ref (subject category)
- kap (subject category)
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