Abstract
With an increase of service users’ demands on high quality of services (QoS), more and more efficient service computing models are proposed. The development of cloud computing, fog computing, and edge computing brings a number of challenges, e.g., QoS optimization and energy saving. We do a comprehensive survey on QoS optimization and energy saving in cloud computing, fog computing, edge computing, and IoT environments. We summarize the main challenges and analyze corresponding solutions proposed by existing works. This survey aims to help readers have a deeper understanding on the concepts of different computing models and study the techniques of QoS optimization and energy saving in these models.
Highlights
With the development of the Internet, more and more computing techniques are developed
Cloud computing cannot play a good role in large-scale or heterogeneous conditions [3]
We point out the problems it aims to solve and introduce the solutions it proposes. e main contribution of this paper is as follows: (1) do a comprehensive survey on the techniques of quality of services (QoS) optimization and energy saving in different computing models, (2) classify papers according to the problems solved by the reviewed works, and (3) compare and summarize the main features of each type of paper. e structure of this paper is Section 2 studies five energy saving techniques under different computing models, and Section 3 concludes this paper
Summary
With the development of the Internet, more and more computing techniques are developed. E main contribution of this paper is as follows: (1) do a comprehensive survey on the techniques of QoS optimization and energy saving in different computing models, (2) classify papers according to the problems solved by the reviewed works, and (3) compare and summarize the main features of each type of paper. E structure of this paper is Section 2 studies five energy saving techniques under different computing models, and Section 3 concludes this paper. We categorize these works in terms of the means they use to achieve the objective of QoS optimization and energy saving, which are (1) quality of service (QoS) guarantee or service-level agreement (SLA) assurance, (2) resource management and allocation, (3) scientific workflow execution, (4) server optimization, and (5) load balancing. Striking a balance between QoS and limited resources can achieve energy saving
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