Green Cloud Computing

The aim of green cloud computing is to achieve a balance between resource consumption and quality of service. This work introduces the distributed system management model, analyses the system’s behavior, describes the operation principles, and presents case study scenarios and some results. We extended CloudSim to simulate the organization model approach and implemented the migration and reallocation policies using this improved version to validate our management solution. In this context, we proposed strategies to optimize the use of the cloud computing resources, introducing two hybrid strategies, describing the base strategies, validating and analyzing them, and presenting the results. The basic principles pointed out in recent works for power management in legacy network equipment are presented, and a model for its use to optimize green cloud approach is proposed.

High energy consumption of cloud data centers is a matter of great concern. Dynamic consolidation of Virtual Machines (VMs) presents a significant opportunity to save energy in data centers. A VM consolidation approach uses live migration of VMs so that some of the under-loaded Physical Machines (PMs) can be switched-off or put into a low-power mode. On the other hand, achieving the desired level of Quality of Service (QoS) between cloud providers and their users is critical. Therefore, the main challenge is to reduce energy consumption of data centers while satisfying QoS requirements. In this paper, we present a distributed system architecture to perform dynamic VM consolidation to reduce energy consumption of cloud data centers while maintaining the desired QoS. Since the VM consolidation problem is strictly NP-hard, we use an online optimization metaheuristic algorithm called Ant Colony System (ACS). The proposed ACS-based VM Consolidation (ACSVMC) approach finds a near-optimal ...

Green computing " represents environmentally responsible way to reduce power and environmental e-waste. Green computing is the practice of using computing resources efficiently. The goals are to reduce the use of hazardous materials, maximize energy efficiency during the product's lifetime, and promote recyclability or biodegradability outdated products and factory waste. It is known that the demand for computing devices rises as the people seek faster way of doing things. The most important issue is the sustainability or sustainable development and it is the key challenge for the environmentalists today. Quite a number of methods have been suggested to ensure sustainability. One important issue is minimum use of papers. Papers are wastage of natural resources. Papers are produced from wood pulp which leads to deforestation. The production of paper releases many by-products which harms the environment. In the present paper the authors have made a systematic study on various issues while producing printed papers which are not good for the environment as well as for the future generations. The authors also propose the negative impacts of paper on the environment can be negated by using E-documentation. Keyword s— green computing, factory waste, sustainability, e-document, energy efficiency I. INTRODUCTION Paper formed from wood pulp or plant fiber, paper is chiefly used for written communication. Paper, whether produced in the modern factory or by the most careful, delicate hand methods, is made up of connected fibers. The fibers can come from a number of sources including cloth rags, cellulose fibers from plants, and, most notably, trees. The use of cloth in the process has always produced high-quality paper. Today, a large proportion of cotton and linen fibers in the mix create many excellent papers for special uses, from wedding invitation paper stock to special paper for pen and ink drawings. The method of making paper is essentially a simple one—mix up vegetable fibers, and cook them in hot water until the fibers are soft but not dissolved. The hot water also contains a base chemical such as lye, which softens the fibers as they are cooking. Then, pass a screen-like material through the mixture, let the water drip off and/or evaporate, and then squeeze or blot out additional water. A layer of paper is left behind. Essential to the process are the fibers, which are never totally destroyed, and, when mixed and softened, form an interlaced pattern within the paper itself. Modern papermaking methods, although significantly more complicated than the older ways, are developmental improvements rather than entirely new methods of making paper. Raw Materials Probably half of the fiber used for paper today comes from wood that has been purposely harvested. The remaining material comes from wood fiber from sawmills, recycled newspaper, some vegetable matter, and recycled cloth. Coniferous trees, such as spruce and fir, used to be preferred for papermaking because the cellulose fibers in the pulp of these species are longer, therefore making for stronger paper. These trees are called "softwood" by the paper industry. Deciduous trees (leafy trees such as poplar and elm) are called "hardwood." Because of increasing demand for paper, and improvements in pulp processing technology, almost any species of tree can now be harvested for paper.

ABSTRACT This paper aims to propose the GreenMACC, an extension of MACC architecture (Metascheduling Architecture To provide QoS in Cloud Computing) aimed at providing QoS in a structure green computing services in a private cloud. To test the new proposed architecture, this paper presents a performance evaluation of policies of the four stages of scheduling with a focus on energy consumption and the average response time. The GreenMACC architecture was consistent in its operation allowing multiple users to run various services on a large scale private cloud and being able to control the energy consumption and quality of services.

Today it is globally accepted that mankind is the major reason for global warming. Data Centres, computers, and other gadgets are the main causes and sources of greenhouse gasses, especially CO2. Data centres use thousands of processors and other computer elements, that generate heat which requires a large amount of cooling equipment, cooling equipment again generate a large amount of heat. Thus, we need such ideas and techniques that reduce the energy consumption and emission of CO2. In this paper, we have compared different techniques of green cloud computing and show the approximate results of each technique.

Internet usage is rapidly increasing in every field of life. Internet coverage is wide either it is textile, pharmaceutical or education sectors. In every sectors where internet envisions are exist, there objects must be connected with each other. When we discussed the objects are connected with each other, a word internet of things (IoT) must exist there. IoT covers iPads, mobile phones, digital camera etc. These devices provide us our basic needs when they connected each other. Sharing of services or concept of virtualization is also part of IoT and also called cloud computing. Cloud computing is said to be sharing of services or resources using internet as a connection. Cloud based resources can be distributed all over the world. It is among most popular technology in developed countries and they are trying to made green solution of its resources. Datacenters of cloud computing systems are wasting a terrific amount of energy, hence emits carbon dioxide. Under developed counties l...

Dynamic consolidation of virtual machines (VMs) is an effective technique, which can lead to improvement of energy efficiency and resource utilization in cloud data centers. However, due to varying workloads in applications, consolidating the virtual machines can cause a violation in Service Level Agreement. The main goal of the dynamic VM consolidation is to optimize the energy-performance trade-off. Detecting when a host is being overloaded or underloaded are two substantial sub-problems of dynamic VM consolidation, which directly affects the utilization of resources, Quality of Service, and energy efficiency as well. In this paper, an adaptive fuzzy threshold-based algorithm has been proposed to detect overloaded and under-loaded hosts. The proposed algorithm generates rules dynamically and updates membership functions to adapt to changes in workload. It is validated with real-world PlanetLab workload. Simulation results demonstrate that the proposed algorithm significantly outperforms the other competitive algorithms.

The concepts proposed by Green IT have changed the priorities in the design of information systems and infrastructure, adding to traditional performance and cost requirements, the need for efficiency in energy consumption. The approach of Green Cloud Computing builds on the concepts of Green IT and Cloud in order to provide a flexible and efficient computing environment, but their strategies have not given much attention to the energy cost of the network equipment. While Green Networking has proposed principles and techniques that are being standardized and implemented in new networking equipment, there is a large amount of legacy equipment without these features in datacenters. In this paper, the basic principles pointed out in recent works for power management in legacy network equipment are presented, and a model for its use to optimize green cloud approach is proposed.

Cloud computing is emerging as a critical information communication technology to heavily impact our daily life in the future. As computing becomes increasingly pervasive, the energy consumption attributable to computing is climbing that marked the foundation of Green Computing. Green Cloud is an Internet Data Canter architecture which aims to reduce data canter power consumption, and at the same time guarantee the performance from users' perspective, leveraging live virtual machine migration technology. Saving energy or reduction of carbon footprints is one of the aspects of Green Computing. Green Cloud Architecture enables comprehensive online monitoring, live virtual machine migration and VM placement optimization. A Green Cloud System responds to peak utilization periods and adjusts availability of resources based on them expanding or shrinking the cloud as needed. The aim of this paper is a literature study of the challenges and various issues in field of Green Computing and discusses the future scope of Green Clouds.

In this paper, we address the problems of massive amount of energy consumption and service level agreements (SLAs) violation in cloud environment. Although most of the existing work proposed solutions regarding energy consumption and SLA violation for cloud data centers (CDCs), while ignoring some important factor: (1) analysing the robustness of upper CPU utilization threshold which maximize utilization of resources; (2) CPU utilization prediction based VM selection from overloaded host which reduce performance degradation time and SLA violation. In this context, we proposed adaptive heuristic algorithms, namely least medial square regression for overloaded host detection and minimum utilization prediction for VM selection from overloaded hosts. These heuristic algorithms reducing CDC energy consumption with minimal SLA. Unlike the existing algorithms, the proposed VM selection algorithm consider the types of application running and it CPU utilization at different time periods over the VMs. The proposed approaches are validated using the CloudSim simulator and through simulations for different days of a real workload trace of PlanetLab.

In this paper, we present a novel multi-objective ant colony system algorithm for virtual machine (VM) consolidation in cloud data centers. The proposed algorithm builds VM migration plans, which are then used to minimize over-provisioning of physical machines (PMs) by consolidating VMs on under-utilized PMs. It optimizes two objectives that are ordered by their importance. The first and foremost objective in the proposed algorithm is to maximize the number of released PMs. Moreover, since VM migration is a resource-intensive operation, it also tries to minimize the number of VM migrations. The proposed algorithm is empirically evaluated in a series of experiments. The experimental results show that the proposed algorithm provides an efficient solution for VM consolidation in cloud data centers. Moreover, it outperforms two existing ant colony optimization based VM consolidation algorithms in terms of number of released PMs and number of VM migrations.

"Nowadays the innovations have turned out to be so quick and advanced that enormous all big enterprises have to go for cloud. Cloud provides wide range of services, from high performance computing to storage. Datacenter consisting of servers, network, wires, cooling systems etc. is very important part of cloud as it carries various business information onto the servers. Cloud computing is widely used for large data centers but it causes very serious issues to environment such as heat emission, heavy consumption of energy, release of toxic gases like methane, nitrous oxide, carbon dioxide, etc. High energy consumption leads to high operational cost as well as low profit. So we required Green cloud computing, which very environment friendly and energy efficient version of the cloud computing. In this paper the major issues related to cloud computing is discussed. And the various techniques used to minimize the power consumption are also discussed. Ruhi D. Viroja | Dharmendra H. Viroja""Energy Saving by Virtual Machine Migration in Green Cloud Computing"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-1 | Issue-1 , December 2016, URL: http://www.ijtsrd.com/papers/ijtsrd104.pdf
Article URL: http://www.ijtsrd.com/engineering/computer-engineering/104/energy-saving-by-virtual-machine-migration-in-green-cloud-computing/ruhi-d-viroja"

Software security is an important aspect that needs to be considered during the entire software development life cycle (SDLC). Integrating software security at each phase of SDLC has become an urgent need. To address software security, various approaches, techniques, methods, practices, and models have been proposed and developed. However, recent research shows that many software development methodologies do not explicitly include methods for incorporating software security during the development of software as it evolves from requirements engineering to its final disposal. The primary objective of this research is to study the state-of-the-art of security in the context of SDLC by following systematic mapping study (SMS). In the second phase, we will identify, through systematic literature review (SLR) and empirical study in the industry, the software security contributions, security challenges and their practices for global software development (GSD) vendors. The ultimate aim is to develop a Software Security Assurance Model (SSAM) to assist GSD vendor organisations in measuring their readiness towards the development of secure software.

Providing real-time cloud services to Vehicular Clients (VCs) must cope with delay and delay-jitter issues. Fog computing is an emerging paradigm that aims at distributing small-size self-powered data centers (e.g., Fog nodes) between remote Clouds and VCs, in order to deliver data-dissemination real-time services to the connected VCs. Motivated by these considerations, in this paper, we propose and test an energy-efficient adaptive resource scheduler for Networked Fog Centers (NetFCs). They operate at the edge of the vehicular network and are connected to the served VCs through Infrastructure-to-Vehicular (I2V) TCP/IP-based single-hop mobile links. The goal is to exploit the locally measured states of the TCP/IP connections, in order to maximize the overall communication-plus-computing energy efficiency, while meeting the application-induced hard QoS requirements on the minimum transmission rates, maximum delays and delay-jitters. The resulting energy-efficient scheduler jointly performs: (i) admission control of the input traffic to be processed by the NetFCs; (ii) minimum-energy dispatching of the admitted traffic; (iii) adaptive reconfiguration and consolidation of the Virtual Machines (VMs) hosted by the NetFCs; and, (iv) adaptive control of the traffic injected into the TCP/IP mobile connections. The salient features of the proposed scheduler are that: (i) it is adaptive and admits distributed and scalable implementation; and, (ii) it is capable to provide hard QoS guarantees, in terms of minimum/maximum instantaneous rates of the traffic delivered to the vehicular clients, instantaneous rate-jitters and total processing delays. Actual performance of the proposed scheduler in the presence of: (i) client mobility; (ii) wireless fading; and, (iii) reconfiguration and consolidation costs of the underlying NetFCs, is numerically tested and compared against the corresponding ones of some state-of-the-art schedulers, under both synthetically generated and measured real-world workload traces.

The increase in energy consumption is the most critical problem worldwide. The growth and development of complex data-intensive applications have promulgated the creation of huge data centers that have heightened the energy demand. In this article, the need for energy efficiency is emphasized by discussing the dual role of cloud computing as a major contributor to increasing energy consumption and as a method to reduce energy wastage. This article comprehensively and comparatively studies existing energy efficiency techniques in cloud computing and provides the taxonomies for the classification and evaluation of the existing studies. The article concludes with a summary providing valuable suggestions for future enhancements.

ABSTRACT The aim of green cloud computing is to achieve a balance between resource consumption and quality of service. This work introduces the distributed system management model, analyses the system’s behavior, describes the operation principles, and presents case study scenarios and some results. We extended CloudSim to simulate the organization model approach and implemented the migration and reallocation policies using this improved version to validate our management solution. In this context, we proposed strategies to optimize the use of the cloud computing resources, introducing two hybrid strategies, describing the base strategies, validating and analyzing them, and presenting the results. The basic principles pointed out in recent works for power management in legacy network equipment are presented, and a model for its use to optimize green cloud approach is proposed.

In this paper, Hybrid of Particle Swarm Optimization (PSO) and Neuro-Fuzzy (NF) has been proposed for improving Vertical Hand-off (VHO) decision for the Ubiquitous Heterogeneous Wireless Network (UHWN). The mobile users have made VHO decision based on data-rate, dwelling time and service type, residue energy and network connection time. To reduce the computational complexity, the pre-decision of VHO is made based on preference of user and number of non-occupied channel. The main aim is the improvement of Quality of Service (QoS) of link and reduction of hand-off frequency. This method is able to reduce call blocking probability, hand-off latency and hand-off call dropping probability, improve the throughput and also balance the load of radio access technologies. The execution of the proposed system has been performed using NS 2 simulator. The numerical results of the proposed algorithm outperforms the state-of-the-art method.

Cloud Computing its a hot topic nowadays, a concept that permits the organizations to access high performance computing and storage infrastructure at reduced cost through internet. With the fast development of cloud computing, the data center is becoming larger in scale and consumes more energy. From this situation comes the immediate need to develop cost-efficient energy saving methods to reduce the huge energy consumption in the cloud data center. The first solution to reduce the power consumption is to plan and test the optimal cloud data center structure before it is in production. We have achieved this goal through intensive testing of various well known cloud simulators (CloudSim, GreenCloud, Cloud Analyst, EMUSIM, GroudSim, DCSim). During this article we take in consideration both software based respectively software and hardware based simulators. Finally, we analyse and compare features of the existing cloud computing simulators and we take in consideration the most effective cloud solution for our project.

The purpose of this paper is to evaluate the interaction of the GreenMACC four stage scheduling using simulation. GreenMACC is an extension of the MACC (Metascheduling Architecture to Provide Quality of Service in Cloud Computing) that provides Quality of Service (QoS) for private clouds considering a green computing structure. In order to evaluate the influence of the scheduling policies in the four stage scheduling, this paper presents the results obtained by simulation that enables to observe the influence of each policy in each evaluated stage, focusing on the energy consumption and the average response time. The operation of GreenMACC is consistent and assures that each scheduling stage works properly, managing several users properly and executing different types of services in a large scale private cloud. GreenMACC is also able to control the energy consumption and the Quality of Services offered to the cloud users.

ABSTRACT The aim of green cloud computing is to achieve a balance between resource consumption and quality of service. This work introduces the distributed system management model, analyses the system’s behavior, describes the operation principles, and presents case study scenarios and some results. We extended CloudSim to simulate the organization model approach and implemented the migration and reallocation policies using this improved version to validate our management solution. In this context, we proposed strategies to optimize the use of the cloud computing resources, introducing two hybrid strategies, describing the base strategies, validating and analyzing them, and presenting the results. The basic principles pointed out in recent works for power management in legacy network equipment are presented, and a model for its use to optimize green cloud approach is proposed.

Green IT is becoming an important concept for the organization since over the last decade, however, not every organization is completely ready to implement Green IT initiatives. Therefore, it is necessary to develop an easy-to-use but comprehensive self-assessment to evaluate organizational readiness to implement Green IT. We have reviewed the literature through systematic literature review (SLR) process to identify motivators in Green IT-outsourcing from vendor"s perspective. Our final sample of publication selection comprises 82 papers in total. We have identified, through the SLR, a list of 9 motivators. Six of these motivators were identified as significant motivators. These significant motivators are "energy efficiency", "development and use of environment-friendly softwares", "overall business cost reduction", "promoting reusability and sustainability both in terms of hardwares and softwares", "improving quality of services&quo...

This paper aims to propose the GreenMACC, an extension of MACC architecture (Metascheduling Architecture To provide QoS in Cloud Computing) aimed at providing QoS in a structure green computing services in a private cloud. To test the new proposed architecture, this paper presents a performance evaluation of policies of the four stages of scheduling with a focus on energy consumption and the average response time. The GreenMACC architecture was consistent in its operation allowing multiple users to run various services on a large scale private cloud and being able to control the energy consumption and quality of services.

In the IT industry’s there is forcefully demand of the technology known as Cloud computing. It is an emerging trend in computing. There are huge data centres are used in big industries. Environmentally, these systems can produce e-wastes, harmful gases with heat. This paper focuses on security in such a power saving data centres in the enterprises we called them as Green Cloud Computers. We have explained and suggested the Virtualization technique for saving energy and the security framework for the Green Cloud that consist of pool of virtual machines. This security framework consists of policy enforcement, trust management and such a security model.

Mobile cloud computing (MCC) provides various cloud computing services to mobile users. The rapid growth of MCC users requires large-scale MCC data centers to provide them with data processing and storage services. The growth of these data centers directly impacts electrical energy consumption, which affects businesses as well as the environment through carbon dioxide (CO2) emissions. Moreover, large amount of energy is wasted to maintain the servers running during low workload. To reduce the energy consumption of mobile cloud data centers, energy-aware host overload detection algorithm and virtual machines (VMs) selection algorithms for VM consolidation are required during detected host underload and overload. After allocating resources to all VMs, underloaded hosts are required to assume energy-saving mode in order to minimize power consumption. To address this issue, we proposed an adaptive heuristics energy-aware algorithm, which creates an upper CPU utilization threshold using ...