Efficient Encoding Scheme in Genetic Algorithm for Requirement Optimization
Rajesh Kumar1, Rakesh Kumar2
1Rajesh Kumar, Dept. of Computer Science & Applications, K.U., Kurukshetra, Haryana, India.
2Prof. Rakesh Kumar, Dept. of Computer Science & Applications, K.U., Kurukshetra, Haryana, India.
Manuscript received on 09 June 2019 | Revised Manuscript received on 14 June 2019 | Manuscript Published on 08 July 2019 | PP: 489-493 | Volume-8 Issue-8S3 June 2019 | Retrieval Number: H11120688S319/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In the era of cloud computing and Big Data, millions of records are managed by cloud and gazillions of requests are handled in every piece of time. Because of this large amount of data, sometimes it becomes impossible for the servers to execute multiple requests simultaneously. There can be two types of request sent to the cloud including the one that requires no time bound or little delay is feasible and the other one is real-time or time-bound in nature. These services fall under the category of deadline-based services. For providing these services, cloud has to be configured in a manner such that these services can be executed within the required time frame. In this paper, a novel approach named Deadline Based VM optimization (DBVO), has been proposed for optimization of VMs (Virtual Machines). In this proposed approach, time factor i.e. the execution time and deadline are taken as primary parameters. With the passage of time, deadline is reduced as well. Therefore, in proposed approach, forthcoming deadline is considered and only required VMs are initialized. This causes minimum VM initialization and maximum resource optimization. The obtained results are compared with some of the existing approaches
Keywords: Chromosome, Encoding, Genetic Algorithm Requirement, Optimization.
Scope of the Article: Algorithm Engineering