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RISS 인기검색어
- 검색키워드
- 저자 : Ahmed Eddaoui (검색결과 2 건)
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Load Balancing in Cloud Computing Using Meta-Heuristic Algorithm
Youssef Fahim,Hamza Rahhali,Mohamed Hanine,El-Habib Benlahmar,El-Houssine Labriji,Mostafa Hanoune,Ahmed Eddaoui 한국정보처리학회 2018 Journal of information processing systems Vol.14 No.3
Cloud computing, also known as “country as you go”, is used to turn any computer into a dematerializedarchitecture in which users can access different services. In addition to the daily evolution of stakeholders’number and beneficiaries, the imbalance between the virtual machines of data centers in a cloud environmentimpacts the performance as it decreases the hardware resources and the software’s profitability. Our axis ofresearch is the load balancing between a data center’s virtual machines. It is used for reducing the degree ofload imbalance between those machines in order to solve the problems caused by this technological evolutionand ensure a greater quality of service. Our article focuses on two main phases: the pre-classification of tasks,according to the requested resources; and the classification of tasks into levels (‘odd levels’ or ‘even levels’) inascending order based on the meta-heuristic “Bat-algorithm”. The task allocation is based on levels providedby the bat-algorithm and through our mathematical functions, and we will divide our system into a numberof virtual machines with nearly equal performance. Otherwise, we suggest different classes of virtualmachines, but the condition is that each class should contain machines with similar characteristics comparedto the existing binary search scheme.
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Load Balancing in Cloud Computing Using Meta-Heuristic Algorithm
Fahim, Youssef,Rahhali, Hamza,Hanine, Mohamed,Benlahmar, El-Habib,Labriji, El-Houssine,Hanoune, Mostafa,Eddaoui, Ahmed Korea Information Processing Society 2018 Journal of information processing systems Vol.14 No.3
Cloud computing, also known as "country as you go", is used to turn any computer into a dematerialized architecture in which users can access different services. In addition to the daily evolution of stakeholders' number and beneficiaries, the imbalance between the virtual machines of data centers in a cloud environment impacts the performance as it decreases the hardware resources and the software's profitability. Our axis of research is the load balancing between a data center's virtual machines. It is used for reducing the degree of load imbalance between those machines in order to solve the problems caused by this technological evolution and ensure a greater quality of service. Our article focuses on two main phases: the pre-classification of tasks, according to the requested resources; and the classification of tasks into levels ('odd levels' or 'even levels') in ascending order based on the meta-heuristic "Bat-algorithm". The task allocation is based on levels provided by the bat-algorithm and through our mathematical functions, and we will divide our system into a number of virtual machines with nearly equal performance. Otherwise, we suggest different classes of virtual machines, but the condition is that each class should contain machines with similar characteristics compared to the existing binary search scheme.
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