An energy-efficient cuckoo search algorithm for virtual machine placement in cloud computing data centers

2021 ◽  
Author(s):  
Hamza Onoruoiza Salami ◽  
Abubakar Bala ◽  
Sadiq M. Sait ◽  
Idris Ismail
Keyword(s):  
Cloud Computing ◽  
Virtual Machine ◽  
Energy Efficient ◽  
Data Centers ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Virtual Machine Placement

Location and Provisioning Problems in Cloud Computing Networks

2013 ◽  
pp. 22-45 ◽  
Author(s):  
Federico Larumbe ◽  
Brunilde Sansò
Keyword(s):  
Cloud Computing ◽  
Energy Consumption ◽  
Virtual Machine ◽  
Data Centers ◽  
Optimization Problems ◽  
Virtual Machine Placement ◽  
Future Research ◽  
Network Efficiency ◽  
Placement Problem ◽  
The Cost

This chapter addresses a set of optimization problems that arise in cloud computing regarding the location and resource allocation of the cloud computing entities: the data centers, servers, software components, and virtual machines. The first problem is the location of new data centers and the selection of current ones since those decisions have a major impact on the network efficiency, energy consumption, Capital Expenditures (CAPEX), Operational Expenditures (OPEX), and pollution. The chapter also addresses the Virtual Machine Placement Problem: which server should host which virtual machine. The number of servers used, the cost, and energy consumption depend strongly on those decisions. Network traffic between VMs and users, and between VMs themselves, is also an important factor in the Virtual Machine Placement Problem. The third problem presented in this chapter is the dynamic provisioning of VMs to clusters, or auto scaling, to minimize the cost and energy consumption while satisfying the Service Level Agreements (SLAs). This important feature of cloud computing requires predictive models that precisely anticipate workload dimensions. For each problem, the authors describe and analyze models that have been proposed in the literature and in the industry, explain advantages and disadvantages, and present challenging future research directions.

scholarly journals Optimal Resource Scheduling for IaaS Cloud Computing using Cuckoo Search Algorithm

2017 ◽  
Vol 9 (1-3) ◽  
Author(s):  
Syed Hamid Hussain Madni ◽  
Muhammad Shafie Abd Latiff ◽  
Shafi’i Muhammad Abdulhamid
Keyword(s):  
Cloud Computing ◽  
Search Algorithm ◽  
Resource Scheduling ◽  
Cuckoo Search ◽  
Computing System ◽  
Cuckoo Search Algorithm ◽  
Cloud Computing System ◽  
Optimal Resource ◽  
System Resource ◽  
Np Hard Problem

Effective resource scheduling is essential for the overall performance of cloud computing system. Resource scheduling problem in IaaS cloud computing is investigated in this paper. It is established to be an NP-hard problem. A recently developed Cuckoo Search (CS) meta-heuristic algorithm is proposed in this paper, to minimize the response time, makespan and throughput for the resource scheduling in IaaS cloud computing. Simulation results show that CS algorithm outperforms that of Ant Colony Optimization (ACO) algorithm based on the considered parameters. 

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