Intelligent SLA-Aware VM Allocation and Energy Minimization Approach with EPO Algorithm for Cloud Computing Environment

Cloud computing is the most prominent established framework; it offers access to resources and services based on large-scale distributed processing. An intensive management system is required for the cloud environment, and it should gather information about all phases of task processing and ensuring fair resource provisioning through the levels of Quality of Service (QoS). Virtual machine allocation is a major issue in the cloud environment that contributes to energy consumption and asset utilization in distributed cloud computing. Subsequently, in this paper, a multiobjective Emperor Penguin Optimization (EPO) algorithm is proposed to allocate the virtual machines with power utilization in a heterogeneous cloud environment. The proposed method is analyzed to make it suitable for virtual machines in the data center through Binary Gravity Search Algorithm (BGSA), Ant Colony Optimization (ACO), and Particle Swarm Optimization (PSO). To compare with other strategies, EPO is energy-efficient and there are significant differences. The results of the proposed system have been evaluated through the JAVA simulation platform. The exploratory outcome presents that the proposed EPO-based system is very effective in limiting energy consumption, SLA violation (SLAV), and enlarging QoS requirements for giving capable cloud service.

Download Full-text

An Enhanced Discrete Symbiotic Organism Search Algorithm for Optimal Task Scheduling in the Cloud

Algorithms ◽

10.3390/a14070200 ◽

2021 ◽

Vol 14 (7) ◽

pp. 200

Author(s):

Suleiman Sa’ad ◽

Abdullah Muhammed ◽

Mohammed Abdullahi ◽

Azizol Abdullah ◽

Fahrul Hakim Ayob

Keyword(s):

Cloud Computing ◽

Response Time ◽

Task Scheduling ◽

Large Scale ◽

Virtual Machines ◽

Search Algorithm ◽

Search Space ◽

Cloud Environment ◽

Nature Inspired Algorithm ◽

Symbiotic Organism Search

Recently, cloud computing has begun to experience tremendous growth because government agencies and private organisations are migrating to the cloud environment. Hence, having a task scheduling strategy that is efficient is paramount for effectively improving the prospects of cloud computing. Typically, a certain number of tasks are scheduled to use diverse resources (virtual machines) to minimise the makespan and achieve the optimum utilisation of the system by reducing the response time within the cloud environment. The task scheduling problem is NP-complete; as such, obtaining a precise solution is difficult, particularly for large-scale tasks. Therefore, in this paper, we propose a metaheuristic enhanced discrete symbiotic organism search (eDSOS) algorithm for optimal task scheduling in the cloud computing setting. Our proposed algorithm is an extension of the standard symbiotic organism search (SOS), a nature-inspired algorithm that has been implemented to solve various numerical optimisation problems. This algorithm imitates the symbiotic associations (mutualism, commensalism, and parasitism stages) displayed by organisms in an ecosystem. Despite the improvements made with the discrete symbiotic organism search (DSOS) algorithm, it still becomes trapped in local optima due to the large size of the values of the makespan and response time. The local search space of the DSOS is diversified by substituting the best value with any candidate in the population at the mutualism phase of the DSOS algorithm, which makes it worthy for use in task scheduling problems in the cloud. Thus, the eDSOS strategy converges faster when the search space is larger or more prominent due to diversification. The CloudSim simulator was used to conduct the experiment, and the simulation results show that the proposed eDSOS was able to produce a solution with a good quality when compared with that of the DSOS. Lastly, we analysed the proposed strategy by using a two-sample t-test, which revealed that the performance of eDSOS was of significance compared to the benchmark strategy (DSOS), particularly for large search spaces. The percentage improvements were 26.23% for the makespan and 63.34% for the response time.

Download Full-text

Research on Energy-Saving Algorithms with Migration Energy Consumption in Heterogeneous Cloud Environment

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.986-987.1383 ◽

2014 ◽

Vol 986-987 ◽

pp. 1383-1386

Author(s):

Zhen Xing Yang ◽

He Guo ◽

Yu Long Yu ◽

Yu Xin Wang

Keyword(s):

Cloud Computing ◽

Energy Consumption ◽

Energy Saving ◽

Large Scale ◽

Electrical Energy ◽

Cloud Environment ◽

Migration Energy ◽

Live Migration ◽

Large Scale Data ◽

Heterogeneous Cloud

Cloud computing is a new emerging paradigm which delivers an infrastructure, platform and software as services in a pay-as-you-go model. However, with the development of cloud computing, the large-scale data centers consume huge amounts of electrical energy resulting in high operational costs and environment problem. Nevertheless, existing energy-saving algorithms based on live migration don’t consider the migration energy consumption, and most of which are designed for homogeneous cloud environment. In this paper, we take the first step to model energy consumption in heterogeneous cloud environment with migration energy consumption. Based on this energy model, we design energy-saving Best fit decreasing (ESBFD) algorithm and energy-saving first fit decreasing (ESFFD) algorithm. We further provide results of several experiments using traces from PlanetLab in CloudSim. The experiments show that the proposed algorithms can effectively reduce the energy consumption of data center in the heterogeneous cloud environment compared to existing algorithms like NEA, DVFS, ST (Single Threshold) and DT (Double Threshold).

Download Full-text

ALGORITHM FOR TASK CONSOLIDATION IN CLOUD COMPUTING: A COMPARATIVE SURVEY

International Journal of Research -GRANTHAALAYAH ◽

10.29121/granthaalayah.v6.i5.2018.1479 ◽

2018 ◽

Vol 6 (5) ◽

pp. 340-345

Author(s):

Rajat Pugaliya ◽

Madhu B R

Keyword(s):

Cloud Computing ◽

Energy Consumption ◽

Resource Utilization ◽

Service Provider ◽

Virtual Machines ◽

Cloud Service ◽

Cloud Service Provider ◽

Dynamic Task ◽

Main Challenge ◽

High Level

Cloud Computing is an emerging field in the IT industry. Cloud computing provides computing services over the Internet. Cloud Computing demand increasing drastically, which has enforced cloud service provider to ensure proper resource utilization with less cost and less energy consumption. In recent time various consolidation problems found in cloud computing like the task, VM, and server consolidation. These consolidation problems become challenging for resource utilization in cloud computing. We found in the literature review that there is a high level of coupling in resource utilization, cost, and energy consumption. The main challenge for cloud service provider is to maximize the resource utilization, reduce the cost and minimize the energy consumption. The dynamic task consolidation of virtual machines can be a way to solve the problem. This paper presents the comparative study of various task consolidation algorithms.

Download Full-text

An analysis of software aging in cloud environment

International Journal of Electrical and Computer Engineering (IJECE) ◽

10.11591/ijece.v10i6.pp5985-5991 ◽

2020 ◽

Vol 10 (6) ◽

pp. 5985

Author(s):

Shruthi P. ◽

Nagaraj G. Cholli

Keyword(s):

Cloud Computing ◽

Large Scale ◽

Virtual Machines ◽

Cloud Service ◽

Software Systems ◽

System Failure ◽

Dynamic Nature ◽

Software Aging ◽

Software Rejuvenation ◽

The Impact

Cloud Computing is the environment in which several virtual machines (VM) run concurrently on physical machines. The cloud computing infrastructure hosts multiple cloud service segments that communicate with each other using the interfaces. This creates distributed computing environment. During operation, the software systems accumulate errors or garbage that leads to system failure and other hazardous consequences. This status is called software aging. Software aging happens because of memory fragmentation, resource consumption in large scale and accumulation of numerical error. Software aging degrads the performance that may result in system failure. This happens because of premature resource exhaustion. This issue cannot be determined during software testing phase because of the dynamic nature of operation. The errors that cause software aging are of special types. These errors do not disturb the software functionality but target the response time and its environment. This issue is to be resolved only during run time as it occurs because of the dynamic nature of the problem. To alleviate the impact of software aging, software rejuvenation technique is being used. Rejuvenation process reboots the system or re-initiates the softwares. This avoids faults or failure. Software rejuvenation removes accumulated error conditions, frees up deadlocks and defragments operating system resources like memory. Hence, it avoids future failures of system that may happen due to software aging. As service availability is crucial, software rejuvenation is to be carried out at defined schedules without disrupting the service. The presence of Software rejuvenation techniques can make software systems more trustworthy. Software designers are using this concept to improve the quality and reliability of the software. Software aging and rejuvenation has generated a lot of research interest in recent years. This work reviews some of the research works related to detection of software aging and identifies research gaps.

Download Full-text

Cloud-Based Platforms and Infrastructures

Advances in Data Mining and Database Management - Advancing Cloud Database Systems and Capacity Planning With Dynamic Applications ◽

10.4018/978-1-5225-2013-9.ch003 ◽

2017 ◽

pp. 47-90

Author(s):

Marcus Tanque

Keyword(s):

Cloud Computing ◽

Virtual Machines ◽

Cloud Service ◽

Resource Provisioning ◽

Virtual Networks ◽

Network Resources ◽

Computing Services ◽

Service Models ◽

Cloud Computing Services ◽

Shared Network

Cloud computing consists of three fundamental service models: infrastructure-as-a-service, platform-as-a service and software-as-a-service. The technology “cloud computing” comprises four deployment models: public cloud, private cloud, hybrid cloud and community cloud. This chapter describes the six cloud service and deployment models, the association each of these services and models have with physical/virtual networks. Cloud service models are designed to power storage platforms, infrastructure solutions, provisioning and virtualization. Cloud computing services are developed to support shared network resources, provisioned between physical and virtual networks. These solutions are offered to organizations and consumers as utilities, to support dynamic, static, network and database provisioning processes. Vendors offer these resources to support day-to-day resource provisioning amid physical and virtual machines.

Download Full-text

Energy-Efficient Resource Provisioning Using Adaptive Harmony Search Algorithm for Compute-Intensive Workloads with Load Balancing in Datacenters

Applied Sciences ◽

10.3390/app10072323 ◽

2020 ◽

Vol 10 (7) ◽

pp. 2323

Author(s):

T. Renugadevi ◽

K. Geetha ◽

K. Muthukumar ◽

Zong Woo Geem

Keyword(s):

Energy Consumption ◽

Load Balancing ◽

Power Consumption ◽

Virtual Machine ◽

Virtual Machines ◽

Search Algorithm ◽

Harmony Search ◽

Harmony Search Algorithm ◽

Resource Provisioning ◽

Total Power

Drastic variations in high-performance computing workloads lead to the commencement of large number of datacenters. To revolutionize themselves as green datacenters, these data centers are assured to reduce their energy consumption without compromising the performance. The energy consumption of the processor is considered as an important metric for power reduction in servers as it accounts to 60% of the total power consumption. In this research work, a power-aware algorithm (PA) and an adaptive harmony search algorithm (AHSA) are proposed for the placement of reserved virtual machines in the datacenters to reduce the power consumption of servers. Modification of the standard harmony search algorithm is inevitable to suit this specific problem with varying global search space in each allocation interval. A task distribution algorithm is also proposed to distribute and balance the workload among the servers to evade over-utilization of servers which is unique of its kind against traditional virtual machine consolidation approaches that intend to restrain the number of powered on servers to the minimum as possible. Different policies for overload host selection and virtual machine selection are discussed for load balancing. The observations endorse that the AHSA outperforms, and yields better results towards the objective than, the PA algorithm and the existing counterparts.

Download Full-text

Resource Provisioning Analysis in Virtual Machines Using Statistical Performance of Workloads for Business Applications

Journal of Computational and Theoretical Nanoscience ◽

10.1166/jctn.2020.9037 ◽

2020 ◽

Vol 17 (9) ◽

pp. 4156-4161

Author(s):

Jeny Varghese ◽

S. Jagannatha

Keyword(s):

Cloud Computing ◽

Large Scale ◽

Virtual Machines ◽

Resource Provisioning ◽

Business Applications ◽

Cloud Federation ◽

Cloud Datacenter

Cloud Federation is the interconnection of two or more cloud computing settings in order to share configurable processing components such as networks, servers, apps that can be dynamically delivered to customers. Virtualization has been an integral part of cloud computing which provides manageability and utilization of resources. This paper analyses on how jobs of business applications demand and efficiently use the capacity of the resources that are provisioned by the VMs, thereby managing the performance of the applications. The in-depth assessment is based on two large-scale and constant performance traces gathered in a cloud datacenter that host company tools for running distinct apps with regard to requested and used resources.

Download Full-text

Efficient utilization of energy consumption in cloud environment

International Journal of Engineering & Technology ◽

10.14419/ijet.v7i1.7.10649 ◽

2018 ◽

Vol 7 (1.7) ◽

pp. 189

Author(s):

G Soniya Priyatharsini ◽

N Malarvizhi

Keyword(s):

Cloud Computing ◽

Energy Consumption ◽

Data Center ◽

Virtual Machines ◽

Vital Role ◽

Cloud Environment ◽

Efficient Utilization ◽

Server Consolidation ◽

Resource Request

In the tremendous growth of the cloud computing, server consolidation plays a vital role. It gives more benefits also it gives the pollution towards the nature. Inspite of avoiding this, saving of energy in the data center or the cluster is more important. In this regard this paper proposes a method of which reduces the energy consumption. This is done by identifying the active physical machines and the remaining machines were kept in the sleep or off mode according to the user’s availability. Here Virtual Machines (VMs) are grouped under the particular types. Based on this type the customer’s resource request can be maintained.

Download Full-text

A Review on Secure Storage Using Bidirectional Verification Techniques in Cloud Computing

International Journal of Engineering & Technology ◽

10.14419/ijet.v7i4.36.24128 ◽

2018 ◽

Vol 7 (4.36) ◽

pp. 511

Author(s):

Mr. Girish kumar d ◽

Dr. Rajashree v biradar ◽

Dr. V c patil

Keyword(s):

Cloud Computing ◽

Data Privacy ◽

Virtual Machines ◽

Cloud Service ◽

Sensitive Information ◽

Cloud Environment ◽

It Industry ◽

Cloud Data ◽

Secure Storage ◽

Verification Techniques

Cloud computing increases the capacity or capabilities vigorously without devoting new infrastructure, training new personnel, or licensing the new software . In the past few years, cloud computing has grown from being a promising business concept to one of the fast-growing sectors of IT industry. As the more sensitive information and data are moved into the cloud data centers, they run on virtual computing resources in the form of virtual machines. Security has become one of the major issue in cloud computing which reduces the growth of cloud environment with complications in data privacy and data protection continue to outbreak the market. A new model created for the advancement should not result as a threat to the existing model. The architecture of cloud poses such a threat to the security of existing models when deployed in a cloud environment. The different cloud service users need to be attentive in considerate,about the risk of data breaks in the new environment. In this paper, advanced survey of the various secured storage in cloud computing using bidirectional protocols is presented.

Download Full-text