scholarly journals Context Aware VM Placement Optimization Technique for Heterogeneous IaaS Cloud

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 89702-89713 ◽  
Author(s):  
Ashwin Kumar Kulkarni ◽  
B. Annappa
Keyword(s):  
Optimization Technique ◽  
Context Aware ◽  
Vm Placement ◽  
Placement Optimization

scholarly journals Deep-submicron Placement Minimizing Crosstalk

VLSI Design ◽  
2001 ◽  
Vol 12 (1) ◽  
pp. 1-12
Author(s):  
Jun Dong Cho ◽  
Jin Youn Cho
Keyword(s):  
High Performance ◽  
Optimization Technique ◽  
Deep Submicron ◽  
Multi Objective Optimization ◽  
Crosstalk Noise ◽  
Performance Constraints ◽  
Placement Optimization ◽  
Number Of Layers ◽  
Physical Attributes ◽  
Performance Issues

Placement of multiple dies on an MCM or high-performance VLSI substrate is a nontrivial task in which multiple criteria need to be considered simultaneously to obtain a true multi-objective optimization. Unfortunately, the exact physical attributes of a design are not known in the placement step until the entire design process is carried out. When the performance issues are considered, crosstalk noise constraints in the form of net separation and via constraint become important. In this paper, for better performance and wirability estimation during placement for MCMs, several performance constraints are taken into account simultaneously. A graph-based wirability estimation along with the Genetic placement optimization technique is proposed to minimize crosstalk, crossings, wirelength and the number of layers. Our work is significant since it is the first attempt at bringing the crosstalk and other performance issues into the placement domain.

Resource Management Mechanisms to Support SLAs in IaaS Clouds

2012 ◽  
pp. 288-307 ◽  
Author(s):  
David Breitgand ◽  
Amir Epstein ◽  
Benny Rochwerger
Keyword(s):  
Service Level Agreement ◽  
Service Level ◽  
Capacity Management ◽  
Resource Provisioning ◽  
Cloud Provider ◽  
Vm Placement ◽  
Placement Problem ◽  
Efficient Manner ◽  
Placement Optimization ◽  
And Performance

The authors consider elastic multi-VM workloads corresponding to multi-tier application and study the fundamental problems of VM placement optimization, subject to policy constraints, elasticity requirements, and performance SLAs. Numerous algorithmic and architecture proposals appeared recently in the area of resource provisioning in IaaS. The chapter provides a comprehensive review of related work in this field and presents the authors’ recent scientific findings in this area obtained in the framework of an EU funded project, RESERVOIR. The chapter discusses horizontal elasticity support in IaaS, its relationship to SLA protection, VM placement optimization and efficient capacity management to improve cost-efficiency of cloud providers. Elastic services comprise multiple virtualized resources that can be added and deleted on demand to match variability in the workload. A Service owner profiles the service to determine its most appropriate sizing under different workload conditions. This variable sizing is formalized through a service level agreement (SLA) between the service owner and the cloud provider. The Cloud provider obtains maximum benefit when it succeeds to fully allocate the resource set demanded by the elastic service subject to its SLA. Failure to do so may result in SLA breach and financial losses to the provider. The chapter defines a novel combinatorial optimization problem called elastic services placement problem to maximize the provider’s benefit from SLA compliant placement. It demonstrates the feasibility of our approach through a simulation study, showing that we are capable of consistently obtaining good solutions in a time efficient manner. In addition, we discuss how resource utilization level can be improved through an advanced capacity management leveraging elastic workload resource consumption variability.

Optimized Energy Aware VM Provisioning in Green Cloud Based on Cuckoo Search with Levy Flight

2016 ◽  
pp. 449-474
Author(s):  
Md. Ashifuddin Mondal ◽  
Tamal Deb
Keyword(s):  
Cloud Computing ◽  
Power Consumption ◽  
Optimization Technique ◽  
Electrical Energy ◽  
Cuckoo Search ◽  
Vm Placement ◽  
Energy Aware ◽  
Green Cloud ◽  
Vm Provisioning

This chapter proposed a nature inspired energy aware VM provisioning technique in cloud computing to minimize the power consumption by the resources while providing negotiable Quality of Services (QoS). Data centers hosting different cloud application consume huge amount electrical energy which leads to a higher operational cost for service provider and makes an adverse effect in environment in terms of co2 emission. Green cloud computing can provide the solutions by optimum use of electrical energy in data center without degrading the Quality of Service (QoS). The proposed technique works in three phases: firstly consumer's service request validation is done with respect to Service Level Agreement. Then move to VM placement phase. Lastly VM placement optimization is done in order to minimize the power consumption by physical host. This chapter use Cuckoo search for optimization technique. The performance of proposed approach is validates by conducting series of evaluation using CloudSim framework

The New Commutation Theory to the Optimization Technique of the Large DC Machine Commutation Design

2011 ◽  
Vol 131 (4) ◽  
pp. 654-666
Author(s):  
Qingliang Zhang ◽  
Takahiro Ueno ◽  
Noboru Morita
Keyword(s):  
Optimization Technique

Array Design for the Synthesis of Stair Step Patterns Using Firefly Optimization Technique

2019 ◽  
Vol 9 (4) ◽  
pp. 285
Author(s):  
Krishna Rudraraju Chaitanya ◽  
P. Mallikarjuna Rao ◽  
K. V. S. N. Raju ◽  
G. S. N. Raju
Keyword(s):  
Optimization Technique ◽  
Array Design ◽  
Firefly Optimization
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