Optimistic virtual machine placement in cloud data centers using queuing approach

Ponraj, Anitha

doi:10.1016/j.future.2018.10.022

Cited by 51 publications

(14 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Ponraj 48 presented a VMP strategy that considers both compute and data transmission time to minimize the total task completion time. Dynamic and static workloads were used to test the suggested optimum VMP algorithm.…”

Section: Vmp In Cloud Computingmentioning

confidence: 99%

See 1 more Smart Citation

Nature‐inspired virtual machine placement mechanisms: A systematic review

Kong

He²,

Abnoosian

2022

Concurrency and Computation

View full text Add to dashboard Cite

Cloud data centers do not completely use their resources, resulting in resource underutilization. Cloud computing companies primarily leverage virtualization technologies to supply cost-effective service provision. In order to optimize cloud performance, virtual machines (VMs) must be placed among physical machines (PMs). When it comes to concentrating on the issues in the cloud computing environment, effective VM placement (VMP) is one of the primary difficulties that might cost suppliers money. VMP may be applied in a variety of ways in cloud computing. In terms of lowering related processing overhead, consolidating the cloud environment to become a highly on-demand method, balancing the load among PMs, power usage, and refining performance, VMP techniques still require improvement in the computing environment. This study aims to provide a comprehensive overview of VMP approaches. This article provides an up-to-date survey of the most related VMP literature to highlight study possibilities in cloud settings utilizing nature-inspired metaheuristic algorithms. The findings suggest that placing VMs in the most efficient place saves power usage substantially. The key problem is to minimize data center energy usage without compromising performance or breaking service level agreements. Finally, we will discuss and look at what further may be accomplished in this line of science.

show abstract

Section: Vmp In Cloud Computingmentioning

confidence: 99%

“…Ponraj 48 presented a VMP strategy that considers both compute and data transmission time to minimize the total task completion time.…”

Section: Hybrid Vmpmentioning

confidence: 99%

Nature‐inspired virtual machine placement mechanisms: A systematic review

Kong

He²,

Abnoosian

2022

Concurrency and Computation

View full text Add to dashboard Cite

show abstract

“…A novel novel energy efficient flow scheduling and routing algorithm for SDN-enabled DC networks is proposed in [148]. By bringing in programmability features to control management interface, OpenStack Neat [74] can help DC administrators to reduce energy consumption in conventional as well as pure SDDCs prototypes. It is an extended version of OpenStack that helps in reducing energy consumption by reallocating VMs using live migration schemes.…”

Section: A Programmabilitymentioning

confidence: 99%

“…10. Power management models: Power management techniques for reducing DC energy consumption can deliver significant opportunities for operational cost savings and other business values [38], [42], [74]. In many areas, energy reduction initiatives can actually be used for generating revenue.…”

Section: Policy Enforcement and Validation: Floodlight [90]mentioning

confidence: 99%

Software-Defined Cloud Computing: A Systematic Review on Latest Trends and Developments

Abbasi

Shamshirband

et al. 2019

IEEE Access

View full text Add to dashboard Cite

Cloud computing concepts offer effective and efficient tools for addressing resource-hungry computational problems. While conventional methods, architectures, and processing techniques may limit cloud data center performance, software-defined cloud computing (SDCC) is an approach where virtualization services to all network resources in a dc are software-defined and where software-defined networking (SDN) and cloud computing go hand in hand. SDCC-related concepts change the previous state of affairs by promoting the centralized control of networking functions in a data center. A key objective of developing software-driven cloud infrastructure is that the networking hardware, software, storage, security, and network traffic management is open and interoperable. This facilitates easy installation and management of networking functions in the cloud infrastructure. Employing SDCC concepts to cloud data centers can improve resource administration challenges to a greater extent. This paper presents a survey on SDCC. We begin by introducing SDCC environments and explain its main architectural components. We identify the essential contributions of various developments to this field and discuss the implementation challenges and limitations faced in their adoption. We also explore the potential of SDCC in two domains, namely, resource orchestration and application development, as case studies of specific interest. In an attempt to anticipate the future evolution, we discuss the important research opportunities and challenges in this promising field.

show abstract

“…A. Selvaraj et al presented an optimizing VM selection solution called analogous particle swarm optimization (APSO) under a cloud computing environment, which implemented a swarm intelligence approach [15]. A. Ponraj proposed a VM placement algorithm to minimize the computing time and data transferring time, which considered computation resources, quality of service (QoS) metrics, virtual machine status, and I/O data with priority-based probability queuing model [16]. W. Shi et al proposed an efficient online auction mechanism to address virtual cluster (VC) allocation and designed a novel online algorithm for dynamic VC provisioning and pricing, achieving truthfulness, individual rationality, and computational efficiency in social welfare [4].…”

Section: A Resource Allocation Of Cloud Computingmentioning

confidence: 99%

A Dynamic Virtual Datacenter Selection Strategy for Integrated Cloud Service Platform Construction With Multiclouds

Huang

Sun

et al. 2019

IEEE Access

View full text Add to dashboard Cite

The pay-as-you-go model and network virtualization of cloud computing allow micro and small content businesses (MSCBs) who construct their integrated cloud service platforms (ICSPs) with virtual datacenters (VDCs) to serve their end users with low service latency and construction cost. However, designing a flexible VDC selection strategy to meet the demands of MSCBs is a challenging task. To address this problem, a dynamic VDC selection strategy is designed for MSCBs to construct their ICSPs flexibly with the VDCs from different clouds. To this end, three dynamic landmark selection metrics are proposed and applied to construct the network coordinates. Then, a dynamic VDC selection algorithm is presented to determine the locations and service resources of VDCs, which are purchased from different clouds by MSCBs to construct their ICSPs. Based on our VDC selection strategy, a simulator is developed based on our designed experimental framework to evaluate our VDC selection strategy. The experimental results show that compared with previous server placement strategies, our strategy can actively and effectively determine VDCs' locations and allocate service resources for each VDC with less computing consumption and is a practical VDC selection strategy for cloud construction in a multicloud environment.

show abstract

Optimistic virtual machine placement in cloud data centers using queuing approach

Cited by 51 publications

References 6 publications

Nature‐inspired virtual machine placement mechanisms: A systematic review

Nature‐inspired virtual machine placement mechanisms: A systematic review

Software-Defined Cloud Computing: A Systematic Review on Latest Trends and Developments

A Dynamic Virtual Datacenter Selection Strategy for Integrated Cloud Service Platform Construction With Multiclouds

Contact Info

Product

Resources

About