Energy Efficient VM Migration in Cloud Datacenter Using Dolphin Echolocation Optimization with Tchebycheff Algorithm
Rajesh P. Patel
Rajesh Patel, Ph.D Research Scholar, C. U. Shah University, Wadhwan, Gujarat, India.
Manuscript received on 13 March 2019 | Revised Manuscript received on 20 March 2019 | Manuscript published on 30 July 2019 | PP: 86-94 | Volume-8 Issue-2, July 2019 | Retrieval Number: A1379058119/19©BEIESP | DOI: 10.35940/ijrte.A1379.078219
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© 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: The workload in cloud computing surroundings changes progressively delivering unwanted circumstances, for example, load unbalancing and minor usage. Virtual machine migration is an impressive plan in such circumstances inorder to improve system performance. With a specific end goal to give productive energy virtual machine migration is essential that migrates a running virtual machine without disconnecting the client or application. In any case, an algorithm in view of a single objective is generally familiar with to coordinate the migration process. Unexpectedly, there stay alive unconsidered variables affecting the migration process, for example, burden capacity, power utilization and resource wastage. We offer a multi-objective algorithm for obtaining VM migration by evaluating the multi objectives that are responsible for migration overhead. In this manner, we suggest a narrative relocation approach united by a Multi objective Dolphin Echolocation Optimization Algorithm (MO-DEOA) to assess several objectives. The aim is to efficiently obtain improved migration that concurrently diminishes power consumption by guaranteeing the performance of the system.
Index Terms: Multi Objective Dolphin Echolocation Algorithm, Tchebycheff Algorithm, VM migration
Scope of the Article: Discrete Optimization