ﺟﺎﯾﮕﺬاري ﻣﺎﺷﯿﻦ ﻫﺎي ﻣﺠﺎزي آﮔﺎه از اﻧﺮژي ﺑﺎ اﺳﺘﻔﺎده از اﻟﮕﻮرﯾﺘﻢ ﺗﺮﮐﯿﺒﯽ در ﻣﺤﯿﻂ اﺑﺮ

Placement of Energy-Aware Virtual Machines Using Hybrid Algorithm in Cloud Environment

ﻣﺼﺮف زﯾﺎد اﻧﺮژي در ﻣﺮاﮐﺰ داده اﺑﺮ ي، ﭼﺎﻟﺸﯽ ﻣﻬﻢ را از دﯾﺪﮔﺎه اﻗﺘﺼﺎدي و زﯾﺴﺖ ﻣﺤﯿﻄﯽ ﻣﻄﺮح ﻣﯽ ﮐﻨﺪ. ادﻏﺎم ﺳﺮورﻫﺎ ﺑﺎ اﺳﺘﻔﺎده از ﺗﮑﻨﯿﮏ ﻣﺠﺎزي ﺳﺎزي ﺑﻪ ﻃﻮر ﮔﺴﺘﺮده اي ﺑﺮاي ﮐﺎﻫﺶ ﻣﺼﺮف اﻧﺮژي ﻣﺮاﮐﺰ داده ﻫﺎ ﺑﻪ ﮐﺎر ﻣﯽرود. در اﯾﻦ ﻣﻘﺎﻟﻪ، اﻟﮕﻮرﯾﺘﻢ ﺗﺮﮐﯿﺒﯽ ﺟﺎﯾﮕﺬاري ﻣﺎﺷﯿﻦ ﻫﺎي ﻣﺠﺎزي ﺑﺎ اﺳﺘﻔﺎده از اﻟﮕﻮرﯾﺘﻢ ژﻧﺘﯿﮏ ﺑﻬﺒﻮد ﯾﺎﻓﺘﻪ ﻣﺒﺘﻨﯽ ﺑﺮ ﺟﺎﯾﮕﺸﺖ، ﭘﯿﺸﻨﻬﺎد ﺷﺪه و ﻣﻨﺎﺑﻊ ﭼﻨﺪ ﺑﻌﺪي ﮐﻪ ﺑﻬﺘﺮﯾﻦ اﺳﺘﺮاﺗﮋي ﺗﺨﺼﯿﺺ ﻣﻨﺎﺳﺐ را دارﻧﺪ، اراﺋﻪ ﺷﺪه اﺳﺖ. در اﻟﮕﻮرﯾﺘﻢ ﺟﺎﯾﮕﺬاري ﻣﺎﺷﯿﻦ ﻫﺎي ﻣﺠﺎزي ﭘﯿﺸﻨﻬﺎدي، ﻣﯿﺰان اﻧﺮژي ﻣﺼﺮﻓﯽ ﻣﺮاﮐﺰ داده ﻫﺎي اﺑﺮي را از ﻃﺮﯾﻖ ﺑﻪ ﺣﺪاﻗﻞ رﺳﺎﻧﺪن ﺗﻌﺪاد ﺳﺮورﻫﺎي ﻓﻌﺎل ﮐﻪ ﻣﯿﺰﺑﺎن ﻣ ﺎﺷﯿﻦ ﻫﺎي ﻣﺠﺎزي ﻫﺴﺘﻨﺪ، ﮐﺎﻫﺶ ﻣﯽ دﻫﺪ. ﻫﻤﭽﻨﯿﻦ، اﻟﮕﻮرﯾﺘﻢ ﭘﯿﺸﻨﻬﺎدي ﺳﻌﯽ در اﺳﺘﻔﺎده ﻣﺘﻌﺎدل از ﻣﻨﺎﺑﻊ ﭼﻨﺪ ﺑﻌﺪي ﺳﺮورﻫﺎي ﻓﻌﺎل دارد ﮐﻪ ﻣﯽ ﺗﻮاﻧﺪ ﺑﺎﻋﺚ ﮐﺎﻫﺶ ﻫﺪر رﻓﺖ ﻣﻨﺎﺑﻊ ﺷﻮد

The high-energy consumption of cloud data centers presents a significant challenge from both economic and environmental perspectives. Server consolidation using virtualization technology is widely used to reduce the energy consumption rates of data centers. In this paper, a hybrid VMP algorithm is proposed based on another proposed improved permutation-based genetic algorithm and multidimensional resource-aware best fit allocation strategy. The proposed VMP algorithm aims to improve the energy consumption rate of cloud data centers through minimizing the number of active servers that host Virtual Machines (VMs). Additionally, the proposed VMP algorithm attempts to achieve balanced usage of the multidimensional resources of active servers, which in turn, reduces resource wastage