Green Cloud Computing Research Articles

Green Cloud Computing Using Proactive Virtual Machine Placement: Challenges and Issues

Efficient VM management is very crucial for energy saving, increasing profit, and preventing SLA violations. VM placement schemes can be classified into reactive and proactive/predictive schemes which try to improve the VM placement results, by forecasting future workloads or resource demands using various prediction techniques. This paper puts forward an extensive survey of the proactive VM placement approaches and categorizes them according to their applied forecasting methods. It describes how each scheme has applied the prediction algorithms to conduct more effective and low overhead VM placement. Moreover, in each category, factors such as evaluation parameters, simulation software, workload data, power management method, and prediction factors are compared to illuminate more details about the investigated VM placement approaches. At last, the concluding issues and open future studies trends and area are highlighted.

An Analysis Report on Green Cloud Computing Current Trends and Future Research Challenges

Today cloud computing became an impressive solution to address the challenges in storage and process of high volume data, with low-cost, high-speed, on-demand and pay-per-use characteristics. Although rapid progression has been recorded in the area of cloud computing and its services, attaining the implementation of green clouds is still under development due to lack of research and several barriers in its implementation. Green clouds are committed to design as eco-friendly, energy efficient, max resource utilizable, low carbon emissions, long lasting and recyclable. In order to satisfy the ever growing enterprise data storage and processing needs, the cloud service providers are coming up with cutting edge technologies like Green Cloud Computing in cloud architecture design to reduce, the huge power consumption, water consumption, need of physical hardware peripherals, infrastructure and harmful carbon emissions etc. To protect our environment from cloud negative impacts, the service providers must adopt and update their cloud infrastructure towards green computing. Green computing researches widely focus on designing of efficient clouds with green characteristics like Power Management, Virtualization, High Performance Computing, Load balancing, Green data center, Reusability, Recyclability etc. As part of my research on green clouds, this paper presents an analysis report about the green cloud computing and its characteristics in detailed manner. This paper thoroughly discusses about the former green computing achievements, current trending concepts of green computing and future research challenges as well. This comprehensive green cloud analysis report helps the naive green research fellows to learn about green cloud topics and to understand the green cloud future research challenges.

Towards Green Cloud Computing: Demand Allocation and Pricing Policies for Cloud Service Brokerage

Functioning as an intermediary between tenants and cloud providers, cloud service brokerages (CSBs) can bring about great benefits to the cloud market. As energy costs of cloud computing have been increasing rapidly, there is a need for cloud providers to optimize energy efficiency while maintain high service level performance to tenants, not only for their own benefit but also for social welfares. Thus, for green cloud companies, two questions have arisen: 1) under what pricing policies from the cloud providers to the CSB, a profit-driven CSB is willing to minimize the total energy cost while satisfy tenant demands and 2) how should a CSB distribute tenants demands to achieve this objective? To address question 1), we find a pricing policy for cloud providers such that maximizing CSBs profit is equivalent to minimizing cloud providers energy cost. To address question 2), we first devise a greedy solution, and then propose an approximation algorithm and a decomposition-based solution with a constant approximation ratio. Both simulation and real-world Amazon EC2 experimental results demonstrate the effectiveness of our pricing policy to incentivize CSBs to save energy and the superior performance of our algorithms in energy efficiency and resource utilization over the previous algorithms.

A Study of Energy Conservation Using Green Cloud Computing

Cloud and green computing are rising areas in the IT field, both provide services to users and respond to their needs. Cloud computing is dependent on data whereas, green cloud computing is based on cloud framework. The use of cloud computing is increasing day by day which generates large amount of carbon dioxide because processing each request needs servers which consume high power energy and produce CO 2 . To reduce this some green computing techniques are required. These techniques use computer and memory devices and other devices like network communication devices for constructing a device that helps in reducing the effect of CO 2 on the environment and making it green. This paper discusses some of the green cloud computing techniques and their future use.

Towards Attaining Reliable and Efficient Green Cloud Computing Using Micro-Smart Grids to Power Internet Data Center

Energy generation and consumption are the main aspects of social life due to the fact that modern people’s necessity for energy is a crucial ingredient for existence. Therefore, energy efficiency is regarded as the best economical approach to provide safer and affordable energy for both utilities and consumers, through the enhancement of energy security and reduction of energy emissions. One of the problems of cloud computing service providers is the high rise in the cost of energy, efficiency together with carbon emission with regards to the running of their internet data centres (IDCs). In order to mitigate these issues, smart micro-grid was found to be suitable in increasing the energy efficiency, sustainability together with the reliability of electrical services for the IDCs. Therefore, this paper presents idea on how smart micro-grids can bring down the disturbing cost of energy, carbon emission by the IDCs with some level of energy efficiency all in an effort to attain green cloud computing services from the service providers. In specific term, we aim at achieving green information and communication technology (ICT) in the field of cloud computing in relations to energy efficiency, cost-effectiveness and carbon emission reduction from cloud data center’s perspective.

Towards Green Cloud Computing an Algorithmic Approach for Energy Minimization in Cloud Data Centers

The article presents an efficient energy optimization framework based on dynamic resource scheduling for VM migration in cloud data centers. This increasing number of cloud data centers all over the world are consuming a vast amount of power and thus, exhaling a huge amount of CO2 that has a strong negative impact on the environment. Therefore, implementing Green cloud computing by efficient power reduction is a momentous research area. Live Virtual Machine (VM) migration, and server consolidation technology along with appropriate resource allocation of users' tasks, is particularly useful for reducing power consumption in cloud data centers. In this article, the authors propose algorithms which mainly consider live VM migration techniques for power reduction named “Power_reduction” and “VM_migration.” Moreover, the authors implement dynamic scheduling of servers based on sequential search, random search, and a maximum fairness search for convenient allocation and higher utilization of resources. The authors perform simulation work using CloudSim and the Cloudera simulator to evaluate the performance of the proposed algorithms. Results show that the proposed approaches achieve around 30% energy savings than the existing algorithms.

SLA-Aware Best Fit Decreasing Techniques for Workload Consolidation in Clouds

Cloud computing emerged as one of the leading computational paradigms due to elastic resource provisioning and pay-as-you-go model. Large data centers are used by the service providers to host the various services. These data centers consume enormous energy, which leads to increase in operating costs and carbon footprints. Therefore, green cloud computing is a necessity, which not only reduces energy consumption, but also affects the environment positively. In order to reduce the energy consumption, workload consolidation approach is used that consolidates the tasks in minimum possible servers. However, workload consolidation may lead to service level agreement (SLA) violations due to non-availability of resources on the server. Therefore, workload consolidation techniques should consider the aforementioned problem. In this paper, we present two consolidation based energy-efficient techniques that reduce energy consumption along with resultant SLA violations. In addition to that, we also enhanced the existing Enhanced-Conscious Task Consolidation (ECTC) and Maximum Utilization (MaxUtil) techniques that attempt to reduce energy consumption and SLA violations. Experimental results show that the proposed techniques perform better than the selected heuristic based techniques in terms of energy, SLA, and migrations.

Optimal VM placement in distributed cloud environment using MOEA/D

Virtual machine placement is the concept of hosting the virtual machines to appropriate physical servers so as to meet user computation requirements. An optimal placement is one of the key concerns in green cloud computing. Virtual machine placement in distributed cloud environment also imposes propagation time as a key for effective hosting of VM along with CPU and memory resource constraints. In this paper, MOEA/D a multi-objective evolutionary algorithm is used to find a non-dominated solution w.r.t. minimal wastage, minimal power consumption and less propagation delay. The proposed algorithm has been implemented, tested and compared with the existing multi-objective approaches. The statistical analysis of the simulation results proves that MOEA/D outperforms against the existing algorithms in distributed cloud VM placement.

Smart Configuration and Auto Allocation of Resource in Cloud Data Centers

Cloud computing is one of emerging computing models that has many advantages. The IT industry is keenly aware of the need for Green Cloud computing solutions that save energy for the environment as well as reduce operational costs. This article presents a new green Cloud Computing framework based on multi agent systems for optimizing resource allocation in data centers (DCs). Our framework based on a new cloud computing architecture that benefits from the combination of the Cloud and agent technologies. DCs hosting Cloud applications need energy-aware resource allocation mechanisms that minimize energy costs and other operational costs. This article offers a logical solution to manage physical and virtual resources in smarter data center.

A Review on Fault Tolerance Techniques and Algorithms in Green Cloud Computing

A Review on Fault Tolerance Techniques and Algorithms in Green Cloud Computing

SAVM: A practical secure external approach for automated in‐VM management

SummaryIn‐VM management is usually needed by cloud service providers for cloud management, which includes monitoring the in‐VM application running state, reconfiguring VM system settings, etc. In‐VM management is also very useful in green cloud computing, because it provides the abilities of in‐VM monitoring, VM reconfiguration, performance measurement, etc. Leveraging a shell or an in‐VM agent to manage VMs is faced with generality and security challenges. In this paper, we propose a secure automated in‐VM management approach, ie, SAVM, which likes a hypervisor‐based shell managing the VMs in an out‐of‐box way. To bridge the semantic gap, we reuse the target VM's system calls to process the semantic information automatically. More importantly, we introduce a secure instruction fetch approach to enhance the system security. As a result, SAVM does not rely on the target VM's kernel integrity. In addition, we also present a dummy process selection and a system call injection method to further enhance the system security and transparency. After the implementation, we evaluate the prototype. The experimental results show that SAVM can achieve most of the in‐VM management operations. Furthermore, SAVM can work correctly under the target VM attacked by several popular rootkits.

CCN: A novel energy efficient greedy routing protocol for green computing

SummaryWe proposed a novel Energy Efficient Greedy Routing Protocol (EEGRP) in CCN for MANETs to achieve the gaps in the existing infrastructure of Green Cloud Computing. Initially, the consumer node broadcasts the interest packet; each relay node verifies if it is already satisfied, and then it drops the packet. Otherwise, the provider node selects shortest path to unicast data packet within minimum delay. Each relay node receives a data packet, stores its content in content store, and forwards it to next node according to path mention in the hop‐count field. If the data packet custodian node does not find path mention in the hop‐count field, then it searches the routing table entries to choose the second best path to unicast the data packet. EEGRP is implemented in three scenarios using ns2 and compare its performance with AIRDrop routing protocol on bases of three performance parameters like packet delivery ratio, delay, and energy consumption. EEGRP achieves high PDR with minimum delay and less energy consumption as compared to AIRDrop. Therefore, EEGRP is feasible to use on green computing and cloud technology. This can save energy issue to secure energy for Green Computing and Cloud before moving to full‐scale virtualization and Cloud services.

TOWARDS GREEN COMPUTING, IMPORTANCE, IMPACT AND POSSIBLE SOLUTIONS-A REVIEW

Fresh environment is the key to human life, according to report [8] 25 lack people dead only in India in 2015 due to the polluted atmosphere. Major causes of air pollution are burning of fossil fuels, agricultural activities, exhaust from factories and industries, mining operations, and Indoor air pollution [9]. Unfortunately, our beloved computer is one of them. Datacentres discharge massive amount of CO2 in the air because here in datacentres thousands of servers, and other computer components are continuously in working condition 24/7. It occurs to researchers that they must search some new ways to control this problem. That's why green computing is a trending topic today. In this paper, we will tell the importance of green computing or green cloud computing, the impact of greenhouse gases on nature, also we will suggest some ideas that could be implemented in datacenters.

An energy efficient and SLA compliant approach for resource allocation and consolidation in cloud computing environments

Cloud computing is a promising paradigm that enables a “computing-as-a-service” model, in which a dynamic pool of virtualized computational resources (e.g. CPU) can be leased and released on demand. With the increased demand for cloud computing infrastructures and the explosion in data center sizes, energy efficiency becomes an important issue to consider. Green cloud computing is an area that focuses on the design of energy efficient data centers, in order to achieve cost savings and minimize negative impacts on the environment. One of the main green cloud computing strategies used for the reduction of energy consumption consists in maximizing the utilization of a number of physical machines (PMs) and turning off or suspending unused servers. This strategy is typically achieved using two types of algorithms: Virtual Machines (VMs) placement and VMs consolidation algorithms. VMs’ placement is a process of dynamically placing VMs onto PMs while satisfying specific VM-to-PM mapping rules. VMs’ consolidation optimizes the resource utilization and groups dispersed VMs on a minimal number of active PMs, based on live migration techniques. Both approaches are time and resource consuming, and are categorized as NP-hard optimization problems. Moreover, reducing energy consumption by means of resource consolidation may reduce the system’s availability and reliability, and lead to SLA violations. Therefore, there is a need for multi-objective optimization approaches that can strike a balance between energy consumption and the system’s ability to meet QoS and SLA requirements. In this work, we propose an energy-aware and QoS-aware multi-objective Ant Colony Optimization (MACO) approach for VM placement and consolidation. Our approach aims at achieving a trade-off between energy efficiency, system performance, and SLA-compliance. The proposed approach was implemented and tested in small to mid-size data center settings, simulated using cloudSim, and was compared with a number of heuristic and meta-heuristic approaches, using eight performance metrics. The results show that our approach outperforms the other tested approaches in terms of energy savings, reduction of resource wastage in term of CPU, reduction of communication cost in term of energy induced by traffic load exchanged between VMs, and minimization of the number of VM migrations and SLA violations – thus demonstrating an ability to balance energy efficiency with system performance and QoS requirements.

Energy Saving from Cloud Resources for a Sustainable Green Cloud Computing Environment

Cloud computing services are proliferation. The Cloud computing resources face major pitfall in energy consumes. The prime of energy consumption in cloud computing is by means of client computational devices, server computational devices, network computational devices and power required to cool the IT load. The cloud resources contribute high operational energy cost and emit more carbon emission to the environment. Therefore the cloud services providers need green cloud environment resolution to decrease the operational energy cost along with environmental impact. The most important objective of this effort is to trim down the energy from utilized and unutilized (idle) cloud resources and save the energy in cloud resources efficiently. To achieve the sustainable green cloud environment from an Energy Saving Algorithm used to choose the appropriate virtual services so that the power at the client, server, and network recourses can be reduced.

A Survey of Energy Aware Cloud’s Resource Allocation Techniques for Virtual Machine Consolidation

As the demand for cloud computing environment is increasing, new techniques for making cloud computing more environment-friendly are being proposed with an aim to convert traditional cloud computing into green cloud computing. A standout amongst the most imperative complications in cloud computing is streamlining of energy utilization because its importance is increasing rapidly. There are numerous strategies and algorithms used to limit the energy utilization in the cloud. Methods incorporate DVFS, UP-VMC, Utility based MFF, HCT, AVVMC, ACO, and ESWCT. In this survey, a review of energy-aware techniques is presented for making virtual machines more energy efficient in a cloud computing. Working on each technique is briefly explained. A comparative analysis is also given for comparing multiple efficient techniques with respect to performance metrics.

AHP Aided Decision-Making in Virtual Machine Migration for Green Cloud

In this study, an analytical hierarchy process based model is proposed to perform the decision-making for virtual machine migration towards green cloud computing. The virtual machine migration evaluation index system is established based on the process of constructing hierarchies for evaluation of virtual machine migration, and selection of task usage. A comparative judgment of two hierarchies has been conducted. In the experimental study, five-point rating scale has been adopted to map the raw data to the scaled rating score; this rating method is used to analyze the performance of each virtual machine and its task usage data. The results show a significant improvement in the decision-making process for the virtual machine migration. The deduced results are useful for the system administrators to migrate the exact virtual machine, and then switch on the power of physical machine that the migrated virtual machine resides on. Thus the proposed method contributes to the green cloud computing environment.

Green IOT: Principles, Current Trends, Future Directions

The two trending and popular technologies are Cloud Computing (CC) and the Internet of Things (IoT) are current hot discussions in the field of agriculture and healthcare applications. Motivated by achieving a sustainable world, this paper discusses various technologies and issues regarding green cloud computing and green Internet of Things, further improves the discussion with the reduction in energy consumption of the two techniques (CC and IoT) combination in agriculture and healthcare systems. The history and concept of the hot green information and communications technologies (ICT’s) which are enabling green IoT will be discussed. Green computing introduction first and later focuses on the recent works done regarding the emerging technologies. Finally, lists out the advantages, challenges, and future research directions related to green application design. Our research aims to make green area broad and contribution to sustainable application world.

Green Cloud Computing: Efficient Energy-Aware and Dynamic Resources Management in Data Centers

The uses of Cloud computing over the last years are constantly increasing since it has become a very important technology in the computing landscape. It provides to client decentralized services and a pay-as-you-go model for consuming resources. The growing need for the cloud services oblige the providers to adopt an enlarged sized data center infrastructure which runs thousands of hosts and servers to store and process data. As result, these large servers engender a lot of heat with visual carbon emission in the air, as well as important energy consumption and higher operating cost. This is why researches in energy economics continue to progress including energy saving techniques in servers, in the network, cooling, and renewable energies, etc. In this paper, we tackled the existing energy efficient methods in the green cloud computing fields and we put forward our green cloud solution for data center dynamic resource management. Our proposed approach aims to reduce the infrastructure energy consumption and maintain the required performances.

IEEE Access Special Section Editorial: Green Cloud and Fog Computing: Energy Efficiency and Sustainability Aware Infrastructures, Protocols, and Applications

The evolution of high performance computing architectures has increased the essence of effective utilization of resources. The cloud computing paradigm also incorporates high performance computing architectures with costly resources to provide services to end users. Its pay per use model makes it beneficial for cloud service providers as well as end-users. Through its layered architecture, the cloud computing paradigm offers services pertaining to the infrastructure, platform, and software layers [item 1) in the Appendix],[item 2) in the Appendix]. The fog computing, similar to the cloud computing, is one of the recently evolved paradigms for which the applications and services are set to be provided in proximity to the end-users [item 3) in the Appendix]. Cloud and fog computing are the recently evolved components of Information and Communication Technologies (ICT) which has been effective in reducing energy consumption and gas emissions of the industry [item 4) in the Appendix]. However, management of heavy resources, job processing at computing nodes, and execution costs in these infrastructures require energy efficient and sustainable solutions for successful deployments.