LECC: Location, energy, carbon and cost-aware VM placement model in geo-distributed DCs

2021 ◽  
pp. 100649
Author(s):  
Soha Rawas ◽  
Ahmed Zekri ◽  
Ali El Zaart
Keyword(s):  
Vm Placement

A Study for VM Placement Schemes in Cloud

2017 ◽  
Vol 7 (8) ◽  
pp. 208
Author(s):  
Ramandeep Kaur ◽  
Navpreet Kaur
Keyword(s):  
Cloud Computing ◽  
Reaction Time ◽  
Task Scheduling ◽  
Specific Time ◽  
Due Date ◽  
Vm Placement ◽  
Time Task ◽  
Wide Range ◽  
The Web

The cloud computing can be essentially expressed as aconveyance of computing condition where distinctive assets are conveyed as a support of the client or different occupants over the web. The task scheduling basically concentrates on improving the productive use of assets and henceforth decrease in task fruition time. Task scheduling is utilized to allot certain tasks to specific assets at a specific time occurrence. A wide range of systems has been exhibited to take care of the issues of scheduling of various tasks. Task scheduling enhances the productive use of asset and yields less reaction time with the goal that the execution of submitted tasks happens inside a conceivable least time. This paper talks about the investigation of need, length and due date based task scheduling calculations utilized as a part of cloud computing.

A memetic grouping genetic algorithm for cost efficient VM placement in multi-cloud environment

2019 ◽  
Vol 23 (2) ◽  
pp. 797-836 ◽  
Author(s):  
Seyedeh Yasaman Rashida ◽  
Masoud Sabaei ◽  
Mohammad Mehdi Ebadzadeh ◽  
Amir Masoud Rahmani
Keyword(s):  
Genetic Algorithm ◽  
Cloud Environment ◽  
Vm Placement ◽  
Grouping Genetic Algorithm ◽  
Cost Efficient ◽  
Multi Cloud

A Game Theoretic Approach to Estimate Fair Cost of VM Placement in Cloud Data Center

2018 ◽  
Vol 12 (4) ◽  
pp. 3509-3518
Author(s):  
Sourav Kanti Addya ◽  
Ashok Kumar Turuk ◽  
Bibhudatta Sahoo ◽  
Anurag Satpathy ◽  
Mahasweta Sarkar
Keyword(s):  
Data Center ◽  
Theoretic Approach ◽  
Vm Placement ◽  
Cloud Data Center ◽  
Cloud Data ◽  
Game Theoretic ◽  
Game Theoretic Approach

scholarly journals Virtual Machine Placement via Bin Packing in Cloud Data Centers

Electronics ◽  
2018 ◽  
Vol 7 (12) ◽  
pp. 389 ◽  
Author(s):  
Aisha Fatima ◽  
Nadeem Javaid ◽  
Tanzeela Sultana ◽  
Waqar Hussain ◽  
Muhammad Bilal ◽  
...  
Keyword(s):  
Particle Swarm Optimization ◽  
Data Centers ◽  
Bin Packing ◽  
Virtual Machines ◽  
Particle Swarm ◽  
Vm Placement ◽  
Swarm Optimization ◽  
Cloud Data ◽  
Cloud Data Centers ◽  
Vm Consolidation

With the increasing size of cloud data centers, the number of users and virtual machines (VMs) increases rapidly. The requests of users are entertained by VMs residing on physical servers. The dramatic growth of internet services results in unbalanced network resources. Resource management is an important factor for the performance of a cloud. Various techniques are used to manage the resources of a cloud efficiently. VM-consolidation is an intelligent and efficient strategy to balance the load of cloud data centers. VM-placement is an important subproblem of the VM-consolidation problem that needs to be resolved. The basic objective of VM-placement is to minimize the utilization rate of physical machines (PMs). VM-placement is used to save energy and cost. An enhanced levy-based particle swarm optimization algorithm with variable sized bin packing (PSOLBP) is proposed for solving the VM-placement problem. Moreover, the best-fit strategy is also used with the variable sized bin packing problem (VSBPP). Simulations are done to authenticate the adaptivity of the proposed algorithm. Three algorithms are implemented in Matlab. The given algorithm is compared with simple particle swarm optimization (PSO) and a hybrid of levy flight and particle swarm optimization (LFPSO). The proposed algorithm efficiently minimized the number of running PMs. VM-consolidation is an NP-hard problem, however, the proposed algorithm outperformed the other two algorithms.

scholarly journals A Access of MBFD, Percentage Util, Absolute Capacity and BSP VM Placement Algorithm on Cloud Datacenter

2019 ◽  
Vol 8 (2S8) ◽  
pp. 1782-1786
Keyword(s):  
Virtual Machine ◽  
Vm Placement ◽  
Dynamic Provisioning ◽  
Works Of Art ◽  
Cloud Datacenter ◽  
Placement Algorithm

The datacenter control admission is expanding hurriedly because of the versatility and dynamic provisioning of benefits. The debasement in like manner generally execution, effect of surroundings are the vital inconveniences in datacenter for the blast in power utilization. The power benefited from by method for unused host device to be turned off, through combining the virtual gadget powerfully to keep control in datacenter. on this paper we have conversely 4 specific virtual machine situation set of rules for the quality utilization, amount of VM movement, SLA infringement (SLAV), in general execution debasement in view of Migration (PDM), SLA infringement Time in accordance with vigorous host (SLATAH) and power SLA infringement (ESV). to assess the arrangement of guidelines we have utilized the CloudSim recreation toolbox and true works of art burden lines of planet lab VMs for our examination.

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