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An infrastructure for embedded systems using task scheduling
Affiliation:1. Faculty of CSE, Department of Computer Science and Engineering, Sathyabama Institute of Science and Technology, Chennai, India;2. Department of IT, RMD Engineering College, Chennai, India;1. Department of Finance, Rongzhi College of Chongqing Technology and Business University, Chongqing, 400067, China;1. Research Scholar, Department of Electrical and Electronics Engineering, Sri Ramakrishna Engineering College, Coimbatore, Tamil Nadu, India;2. Department of Electrical and Electronics Engineering, Sri Ramakrishna Engineering College, Coimbatore, Tamil Nadu, India;1. Department of Electrical Engineering and Computer Science, University of Siegen, Germany;2. Department of Computer Science, Chungbuk National University, South Korea;1. Department of Electrical and Computer Engineering, Kharazmi University, Tehran, Iran;2. Mälardalen University, Sweden
Abstract:Task scheduling in heterogeneous environments such as cloud data centers is considered to be an NP-complete problem. Efficient task scheduling will lead to balance the load on the virtual machines (VMs) thereby achieving effective resource utilization. Hence there is a need for a new scheduling framework to perform load balancing amid considering multiple quality of service (QoS) metrics such as makespan, response time, execution time, and task priority. Multi-core Web server is difficult to achieve dynamic balance in the process of remote dynamic request scheduling, so it is necessary to improve it based on the traditional scheduling algorithm to enhance the actual effect of the algorithm. This article do research on the multi-core Web server, Focusing on multi-core Web server queuing model. On this basis, the author draws the drawbacks of the multi-core Web server in the remote dynamic request scheduling algorithm, and improves the traditional algorithm with the demand analysis. Not only it overcomes the drawbacks of traditional algorithms, but also promotes the system threads carrying the same amount of tasks, and promotes the server being always in a dynamic balance. On the basis of this, it achieves an effective solution to customer requests.
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