Energy efficient resource provisioning with dynamic VM placement using energy aware load balancer in cloud

Pavithra, B.; Ranjana, R.

doi:10.1109/icices.2016.7518919

Cited by 8 publications

(8 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It is a procedure to use computing resources environmentally and user friendly while maintain overall computing performance. To reduce the use of hazardous materials, minimize energy consumption, less heat generation and resource wastage are problematic issues in computing [12,36,43,44,55,62,67,75,91,98,102,105,112]. • Dynamic resource allocation: is applied for increase or decrease allocation of resources according to the fluctuating demands of the cloud users.…”

Section: Future Workmentioning

confidence: 99%

“…Furthermore, Dynamic VM placement emphasis on the mapping of VMs to PMs, with maximum utilization and no disturbance occur at the time of execution. Pavithra and Ranjana [105] present a weighted first-come-first-served (WFCFS) algorithm for developing an energy efficient resource provisioning framework with dynamic VM placement. The simulations results based on CloudSim show that the better performance by reducing the energy consumption, cost and execution time as compared to static environment.…”

Section: Power Aware Resource Allocationmentioning

confidence: 99%

See 1 more Smart Citation

Recent advancements in resource allocation techniques for cloud computing environment: a systematic review

et al. 2016

View full text Add to dashboard Cite

There are two actors in cloud computing environment cloud providers and cloud users. On one hand cloud providers hold enormous computing resources in the cloud large data centers that rent the resources out to the cloud users on a pay-per-use basis to maximize the profit by achieving high resource utilization. On the other hand cloud users who have applications with loads variation and lease the resources from the providers they run their applications within minimum expenses. One of the most critical issues of cloud computing is resource management in infrastructure as a service (IaaS). Resource management related problems include resource allocation, resource adaptation, resource brokering, resource discovery, resource mapping, resource modeling, resource provisioning and resource scheduling. In this review we investigated resource allocation schemes and algorithms used by different researchers and categorized these approaches according to the problems addressed schemes and the parameters used in evaluating different approaches. Based on different studies considered, it is observed that different schemes did not consider some important parameters and enhancement is required to improve the performance of the existing schemes. This review contributes to the existing body of research and will help the researchers to gain more insight into resource allocation techniques for IaaS in cloud computing in the future.

show abstract

Section: Future Workmentioning

confidence: 99%

Section: Power Aware Resource Allocationmentioning

confidence: 99%

Recent advancements in resource allocation techniques for cloud computing environment: a systematic review

et al. 2016

View full text Add to dashboard Cite

show abstract

“…These metrics aid in analyzing the performance of cloud data center networks. The load of data center, due to large number of servers, is also taken into consideration for effective utilization of bandwidth, proper load balancing and thereby aid in energy savings of data center [11]. These metrics are analyzed to get efficient DCN with less packet loss, over-subscription ratio and less cost.…”

Section: Tools and Metricsmentioning

confidence: 99%

“…These metrics are analyzed to get efficient DCN with less packet loss, over-subscription ratio and less cost. The energy efficiency in cloud data center networks can be improved with the aid of efficient load balancers such as MODA algorithm as stated in [11] [12], which provides better performance in terms of overall cost, time taken and energy efficiency. The existing techniques make use of various simulation tools like OpenFlow, POX controller and Mininet for implementing the test-bed environment.…”

Section: Tools and Metricsmentioning

confidence: 99%

SDN Based Energy Efficient Cloud Data Center Networks

Pavithra*¹,

Suchitra²,

Sophia³

et al. 2019

IJITEE

View full text Add to dashboard Cite

Abstract: Cloud computing has led to the tremendous growth of IT organizations, which serves as the means of delivering services to large number of consumers globally, by providing anywhere, anytime easy access to resources and services. The primary concern over the increasing energy consumption by cloud data centers is mainly due to the massive emission of greenhouse gases, which contaminate the atmosphere and tend to worsen the environmental conditions. The major part of huge energy consumption comes from large servers, high speed storage devices and cooling equipment, present in cloud data centers. These serve as the basis for fulfilling the increasing need for computing resources. These in turn bestow additional cost of resources. The goal is to focus on energy savings through effective utilization of resources. This necessitates the need for developing a green-aware, energy-efficient framework for cloud data center networks. The Software Defined Networking (SDN) are chosen as they aid in studying the behaviour of networks from the overall perspective of software layer, rather than decisions from each individual device, as in case of conventional networks. The central objective of this paper is dedicated to survey on various existing SDN based energy efficient cloud data center networks.

show abstract

“…However, building more DCs will increase the operational costs due to increased energy consumption [6]- [8]. Extensive research has been conducted to ensure energy efficient operation of DCs [7], [9]- [11], taking into consideration various, energy-intensive DC systems, such as the cooling installation, for instance [5], [6]. Researchers have proposed the use of renewable energy sources to power DCs [6], [12], [13].…”

Section: Introductionmentioning

confidence: 99%

Optimized Energy Aware Resource Allocation Algorithm Using Software Deﬁned Network Technology

Al-Musawi¹,

Al-Khatib²

2019

JTIT

View full text Add to dashboard Cite

The number of data centers (DCs) used for storing and processing data has evolved rapidly in recent years. However, the operations held by DCs may relate to a number of disadvantages, primarily presuming in excessive energy and power consumption due to the poor management standards applied. This may lead to a situation in which many devices within the DC operate at full capacity without any tasks assigned for actual execution. A Software Deﬁned Network (SDN) is a network architecture where the control plane is an independent entity from the data plane, yielding to a higher controllability and ﬂexibility over the network. Through the utilization of SDN architecture, a highly functional energy aware network may be established. In this paper, we propose a heuristic algorithm that monitors the current status of an SDN network (in addition to all ingoing and outgoing trafﬁc), in order to dynamically and eﬃciently allocate network resources by ensuring that only the necessary network devices are active and by turning the idle ones oﬀ. The results show that the proposed algorithm reduces energy consumption of the network compared to existing solutions.

show abstract

Energy efficient resource provisioning with dynamic VM placement using energy aware load balancer in cloud

Cited by 8 publications

References 2 publications

Recent advancements in resource allocation techniques for cloud computing environment: a systematic review

Recent advancements in resource allocation techniques for cloud computing environment: a systematic review

SDN Based Energy Efficient Cloud Data Center Networks

Optimized Energy Aware Resource Allocation Algorithm Using Software Deﬁned Network Technology

Contact Info

Product

Resources

About