Showing papers on "Green computing published in 2014"

Adaptive Resource Provisioning for the Cloud Using Online Bin Packing

Abstract: Data center applications present significant opportunities for multiplexing server resources. Virtualization technology makes it easy to move running application across physical machines. In this paper, we present an approach that uses virtualization technology to allocate data center resources dynamically based on application demands and support green computing by optimizing the number of servers actively used. We abstract this as a variant of the relaxed on-line bin packing problem and develop a practical, efficient algorithm that works well in a real system. We adjust the resources available to each VM both within and across physical servers. Extensive simulation and experiment results demonstrate that our system achieves good performance compared to the existing work.

A Novel Deployment Scheme for Green Internet of Things

Abstract: The Internet of Things (IoT) has been realized as one of the most promising networking paradigms that bridge the gap between the cyber and physical world. Developing green deployment schemes for IoT is a challenging issue since IoT achieves a larger scale and becomes more complex so that most of the current schemes for deploying wireless sensor networks (WSNs) cannot be transplanted directly in IoT. This paper addresses this challenging issue by proposing a deployment scheme to achieve green networked IoT. The contributions made in this paper include: 1) a hierarchical system framework for a general IoT deployment, 2) an optimization model on the basis of proposed system framework to realize green IoT, and 3) a minimal energy consumption algorithm for solving the presented optimization model. The numerical results on minimal energy consumption and network lifetime of the system indicate that the deployment scheme proposed in this paper is more flexible and energy efficient compared to typical WSN deployment scheme; thus is applicable to the green IoT deployment.

A survey of techniques for improving energy efficiency in embedded computing systems

Abstract: Recent technological advances have greatly improved the performance and features of embedded systems. With the number of just mobile devices now reaching nearly equal to the population of Earth, embedded systems have truly become ubiquitous. These trends, however, have also made the task of managing their power consumption extremely challenging. In recent years, several techniques have been proposed to address this issue. In this paper, we survey the techniques for managing power consumption of embedded systems. We discuss the need of power management and provide a classification of the techniques on several important parameters to highlight their similarities and differences. This paper is intended to help the researchers and application-developers in gaining insights into the working of power management techniques and designing even more efficient high-performance embedded systems of tomorrow.

Harnessing renewable energy in cloud datacenters: opportunities and challenges

Abstract: The proliferation of cloud computing has promoted the wide deployment of largescale datacenters with tremendous power consumption and high carbon emission. To reduce power cost and carbon footprint, an increasing number of cloud service providers have considered green datacenters with renewable energy sources, such as solar or wind. However, unlike the stable supply of grid energy, it is challenging to utilize and realize renewable energy due to the uncertain, intermittent and variable nature. In this article, we provide a taxonomy of the state-of-the-art research in applying renewable energy in cloud computing datacenters from five key aspects, including generation models and prediction methods of renewable energy, capacity planning of green datacenters, intra-datacenter workload scheduling and load balancing across geographically distributed datacenters. By exploring new research challenges involved in managing the use of renewable energy in datacenters, this article attempts to address why, when, where and how to leverage renewable energy in datacenters, also with a focus on future research avenues.

Power Consumption Estimation Models for Processors, Virtual Machines, and Servers

Abstract: The power consumption of presently available Internet servers and data centers is not proportional to the work they accomplish. The scientific community is attempting to address this problem in a number of ways, for example, by employing dynamic voltage and frequency scaling, selectively switching off idle or underutilized servers, and employing energy-aware task scheduling. Central to these approaches is the accurate estimation of the power consumption of the various subsystems of a server, particularly, the processor. We distinguish between power consumption measurement techniques and power consumption estimation models. The techniques refer to the art of instrumenting a system to measure its actual power consumption whereas the estimation models deal with indirect evidences (such as information pertaining to CPU utilization or events captured by hardware performance counters) to reason about the power consumption of a system under consideration. The paper provides a comprehensive survey of existing or proposed approaches to estimate the power consumption of single-core as well as multicore processors, virtual machines, and an entire server.

ICT Innovations for Sustainability

Abstract: ICT Innovations for Sustainability is an investigation of how information and communication technology can contribute to sustainable development. It presents clear definitions of sustainability, suggesting conceptual frameworks for the positive and negative effects of ICT on sustainable development. It reviews methods of assessing the direct and indirect impact of ICT systems on energy and materials demand, and examines the results of such assessments. In addition, it investigates ICT-based approaches to supporting sustainable patterns of production and consumption, analyzing them at various levels of abstraction from end-user devices, Internet infrastructure, user behavior, and social practices to macro-economic indicators.Combining approaches from Computer Science, Information Systems, Human-Computer Interaction, Economics, and Environmental Sciences, the book presents a new, holistic perspective on ICT for Sustainability (ICT4S). It is an indispensable resource for anyone working in the area of ICT for Energy Efficiency, Life Cycle Assessment of ICT, Green IT, Green Information Systems, Environmental Informatics, Energy Informatics, Sustainable HCI, or Computational Sustainability.

Novel resource allocation algorithms to performance and energy efficiency in cloud computing

Abstract: The rapid growth in demand for computational power has led to a shift to the cloud computing model established by large-scale virtualized data centers. Such data centers consume enormous amounts of electrical energy. Cloud providers must ensure that their service delivery is flexible to meet various consumer requirements. However, to support green computing, cloud providers also need to minimize the cloud infrastructure energy consumption while conducting the service delivery. In this paper, for cloud environments, a novel QoS-aware VMs consolidation approach is proposed that adopts a method based on resource utilization history of virtual machines. Proposed algorithms have been implemented and evaluated using CloudSim simulator. Simulation results show improvement in QoS metrics and energy consumption as well as demonstrate that there is a trade-off between energy consumption and quality of service in the cloud environment.

Power Management Techniques for Data Centers: A Survey

Abstract: With growing use of internet and exponential growth in amount of data to be stored and processed (known as “big data”), the size of data centers has greatly increased. This, however, has resulted in significant increase in the power consumption of the data centers. For this reason, managing power consumption of data centers has become essential. In this paper, we highlight the need of achieving energy efficiency in data centers and survey several recent architectural techniques designed for power management of data centers. We also present a classification of these techniques based on their characteristics. This paper aims to provide insights into the techniques for improving energy efficiency of data centers and encourage the designers to invent novel solutions for managing the large power dissipation of data centers.

Hybrid shuffled frog leaping algorithm for energy-efficient dynamic consolidation of virtual machines in cloud data centers

Abstract: Cloud computing aims to provide dynamic leasing of server capabilities as scalable virtualized services to end users. However, data centers hosting cloud applications consume vast amounts of electrical energy, thereby contributing to high operational costs and carbon footprints. Green cloud computing solutions that can not only minimize the operational costs but also reduce the environmental impact are necessary. This study focuses on the Infrastructure as a Service model, where custom virtual machines (VMs) are launched in appropriate servers available in a data center. A complete data center resource management scheme is presented in this paper. The scheme can not only ensure user quality of service (through service level agreements) but can also achieve maximum energy saving and green computing goals. Considering that the data center host is usually tens of thousands in size and that using an exact algorithm to solve the resource allocation problem is difficult, the modified shuffled frog leaping algorithm and improved extremal optimization are employed in this study to solve the dynamic allocation problem of VMs. Experimental results demonstrate that the proposed resource management scheme exhibits excellent performance in green cloud computing.

Infusing Green: Requirements Engineering for Green In and Through Software Systems.

Abstract: Environmental sustainability can be applied to software systems in two different understandings — either as green in software systems (greening of IT / green IT) or as green through software systems (greening by IT). Currently it is not clear how environmental sustainability can be systematically supported as an objective in requirements engineering for either of these two understandings. This paper presents a checklist and guide word based approach that demonstrates how to include the objective of environmental sustainability from the very early steps in finding the stakeholders and analyzing the domain to the definition of a usage model and specific requirements. The elaboration is illustrated by a case study on a car sharing system. As software systems affect most aspects of our daily lives, enabling software engineers to strategically align the objective of environmental sustainability with the other objectives for the software system under development could considerably decrease the impact of people in the industrialized world on the environment.

Designing and Managing Data centers Powered by Renewable Energy

Abstract: On-site renewable energy has the potential to reduce datacenters' carbon footprint and power and energy costs. The authors built Parasol, a solar-powered datacenter, and GreenSwitch, a system for scheduling workloads, to explore this potential in a controlled research setting.

Detecting Anomalous Energy Consumption in Android Applications

Abstract: The use of powerful mobile devices, like smartphones, tablets and laptops, is changing the way programmers develop software. While in the past the primary goal to optimize software was the run time optimization, nowadays there is a growing awareness of the need to reduce energy consumption.

Building Green Cloud Services at Low Cost

Abstract: Interest in powering data enters at least partially using on-site renewable sources, e.g. solar or wind, has been growing. In fact, researchers have studied distributed services comprising networks of such "green" data centers, and load distribution approaches that "follow the renewables" to maximize their use. However, prior works have not considered where to site such a network for efficient production of renewable energy, while minimizing both data center and renewable plant building costs. Moreover, researchers have not built real load management systems for follow-the-renewables services. Thus, in this paper, we propose a framework, optimization problem, and solution approach for sitting and provisioning green data centers for a follow-the-renewables HPC cloud service. We illustrate the location selection tradeoffs by quantifying the minimum cost of achieving different amounts of renewable energy. Finally, we design and implement a system capable of migrating virtual machines across the green data centers to follow the renewables. Among other interesting results, we demonstrate that one can build green HPC cloud services at a relatively low additional cost compared to existing services.

The adoption of green information technology and information systems: an evidence from corporate social responsibility

Abstract: Over the last decade, an increasing number of firms are undertaking actions to cut their environmental impact. As information technology and information systems have permeated most business activities, they offer an important opportunity to solve the ecological problems. Green information technology and information systems (ITIS) has become one of the latest considerations to reduce energy consuming of IT operation and business operation. Firstly, the paper makes a definition of green IT and green IS based on the prior literature, and concludes the three aspects of green ITIS adoption motivations: regulations, competitiveness and ecological responsibility. Next, the paper looks into the role of business strategy in the process of green ITIS adoption, which can be classified into proactive strategy and reactive strategy. Finally, based on the technology-organization-environment (TOE) framework, the paper proposes a green ITIS adoption model including the factors of business strategy, and three aspects of green ITIS motivations under the instruction of corporate social responsibility (CSR) theoretical perspective.

Green IT segment analysis : an academic literature review

Abstract: Research on Green Information Technology (IT) is becoming a prevalent research theme in Green Information Systems (IS) research. This article provides a review of 98 papers published on Green IT between 2007−2013 to facilitate future research and to provide a retrospective analysis of existing knowledge and gaps thereof. While some researchers have discussed phenomena such as Green IT, motivation of Green IT and the Green IT adoption lifecycle, others have researched the importance of Green IT implementation within the organisational and individual level. Throughout the literature, scholars are trying to portray a constructive relationship between IT and the environment. Through our analysis, we can provide an assessment of the status of information systems literature on Green IT and, we provide taxonomy of segments of Green IT publications. Future research opportunities are identified based on the review.

A research agenda on managerial intention to green it adoption: From norm activation perspective

Abstract: Green IT adoption is a plausible attempt for organizations to tackle the current environmental problem, and can also improve the economic performance of an organization. Therefore, organizational adoption of Green IT is beneficial to the society. Investigating how the decision maker in an organization would come to adopt Green IT is necessary to establish strategies in promoting organizational adoption of Green IT adoption because decision makers make decisions, rather than organizations. However, to our knowledge, studies in Green IT literature seldom investigate this area. In Green IT literature, emphasis has been given on the effects of institutional pressures and organizational resources on organizational adoption of Green IT. The current study adapts a Norm Activation Model in organizational context to investigate on how an intention to Green IT adoption is formed. The decision makers’ personal norm on environmental interpretation is argued to be activated when environmental preservation is interpreted as an opportunity, which may lead to intention to Green IT adoption. Perceived competitive advantage of Green IT will affect how environmental preservation is interpreted, as well as affect intention to Green IT adoption. Moreover, discretionary slack will also affect how environmental preservation is interpreted. All of these should be tested empirically to see if the results support our proposed hypotheses. Empirical data for this study will be collected via a survey.

Energy based Efficient Resource Scheduling: A Step Towards Green Computing

Abstract: Cloud Computing is an evolving area of efficient utilization of computing resources. Data centers accommodating Cloud applications ingest massive quantities of energy, contributing to high functioning expenditures and carbon footprints to the atmosphere. Hence, Green Cloud computing resolutions are required not only to save energy for the environment but also to decrease operating charges. In this paper, we emphasis on the development of energy based resource scheduling framework and present an algorithm that consider the synergy between various data center infrastructures (i.e., software, hardware, etc.), and performance. In specific, this paper proposes (a) architectural principles for energy efficient management of Clouds; (b) energy efficient resource allocation strategies and scheduling algorithm considering Quality of Service (QoS) outlooks. The performance of the proposed algorithm has been evaluated with the existing energy based scheduling algorithms. The experimental results demonstrate that this approach is effective in minimizing the cost and energy consumption of Cloud applications thus moving towards the achievement of Green Clouds.

Green Business Process Management -- A Definition and Research Framework

Abstract: The concepts of both business process management (BPM) and Green IS are on the agenda of IS researchers. BPM has a long-lasting legacy from enterprise resource planning and business process re-engineering. Green IS is still a young topic, although significant research progress has been made in recent years. However, in terms of combining the two aspects, there is still a lack of research. While there are some initial papers, concepts, and thoughts about this subject, a clear definition is missing. In this paper, we examine the literature concerning the research streams of Green IS and BPM and combine it with the initial research on Green BPM. Consequently, we present a definition for Green Business Process Management as well as a multidimensional framework for further research. We argue that research should focus on dimensions we could derive from literature in order to close the gaps in the field of Green BPM.

Energy saving approaches for Green Cloud Computing: A review

Abstract: Cloud Computing is an emerging technology and is being used by more and more IT companies due to its cost saving benefits and ease of use for users. But, it needs to be environment friendly also. Therefore, Green Cloud Computing is the requirement of the today's world. This paper reviews the efforts made by various researchers to make Cloud Computing more energy efficient, to reduce the carbon footprint rate by various approaches and also discusses the concept of virtualization and various approaches which use virtual machines scheduling and migration to show how these can help to make the system more energy efficient. The summary of the main features of the proposed work of different authors that we have reviewed is also presented in it.

Green Software

Abstract: Most studies and regulatory controls focus on hardware-related measurement, analysis, and control for energy consumption. However, all forms of hardware include significant software components. Although software systems don't consume energy directly, they affect hardware utilization, leading to indirect energy consumption. Therefore, it's important to engineer software to optimize its energy consumption. The software engineering research domain has recently been paying attention to sustainability, as the increased number of publications, empirical studies, and conferences on the topic demonstrate. The guest editors of this special issue explain the articles they selected to highlight this important research area. The Web extra at http://youtu.be/h0tQoOH9_aM is an audio interview in which IEEE Software multimedia editor Davide Falessi interviews guest editor Ayse Basar Bener about how green software can help minimize the negative effects of software products and their development.

Evaluation of Software Product Quality Attributes and Environmental Attributes using ANP Decision Framework.

Abstract: Green software development is a relatively new research area within green IT. Software development industry has started getting pressure from regulators to consider green software development. As a result, green attributes of software products are gaining importance as quality attributes. In this study, we evaluate environmental sustainability and software quality criteria using a well-known multi criteria decision making approach: Analytical Network Process (ANP). The aim is to determine the relationships among quality and environmental attributes and relative priorities of attributes. The results are presented as a guide for green software developers. The priority weights of attributes may be used to analyze trade-off between conflicting product quality and environmental requirements.

Cloud computing: a collaborative green platform for the knowledge society

Abstract: Purpose – The main aim of this paper is to investigate the potential of Cloud Computing as a multilayer integrative collaboration space for knowledge acquisition, nurturing and sharing. The paper will pinpoint benefits and challenges of Cloud Computing in satisfying the new techno-sociological requirements of the knowledge society through the provision of information technology (IT) green services. Furthermore, the article calls for the engagement of researchers to generate additional discussion and dialog in this emerging and challenging area. Design/methodology/approach – The paper applies a conceptual analysis to explore the utilization of the Cloud ecosystem as a new platform for knowledge management (KM) technologies characterized by environmental and economic benefits. Findings – This paper reveals the emergence of a new layer in the Cloud stack known as Knowledge Management-as-a-Service. The article discusses how KM has the opportunity to evolve in synergy with Cloud Computing technologies using th...

Virtual Desktop Infrastructure in Higher Education Institution: Energy Efficiency as an Application of Green Computing

Abstract: With the incredible development in computer technology in recent times, the personal computers have become so powerful that most of the users are not using the entire capabilities of a computer for their regular work. Because of this one can utilise the excess capabilities in one computer and share it with many other users. The concept of desktop virtualisation implements this sharing of capabilities with the help of thin client machines which not only reduces the cost of infrastructure but also introduces green computing by limiting energy consumption and e-waste. A similar concept is implemented in St. Xavier's College (Autonomous), Kolkata and is used extensively by the students. The present paper is an effort to establish the green benefits of Virtual Desktop Infrastructure.

A Survey on Energy Efficiency in Information Systems

Abstract: Concerns about energy and sustainability are growing everyday involving a wide range of fields. Even Information Systems (ISs) are being influenced by the issue of reducing pollution and energy consumption and new fields are rising dealing with this topic. One of these fields is Green Information Technology (IT), which deals with energy efficiency with a focus on IT. Researchers have faced this problem according to several points of view. The purpose of this paper is to understand the trends and the future development of Green IT by analyzing the state-of-the-art and classifying existing approaches to understand which are the components that have an impact on energy efficiency in ISs and how this impact can be reduced. At first, we explore some guidelines that can help to understand the efficiency level of an organization and of an IS. Then, we discuss measurement and estimation of energy efficiency and identify which are the components that mainly contribute to energy waste and how it is possible to impr...

Ensemble Learning for Large-Scale Workload Prediction

Abstract: Increasing energy costs of large-scale server systems have led to a demand for innovative methods for optimizing resource utilization in these systems. Such methods aim to reduce server energy consumption, cooling requirements, carbon footprint, and so on, thereby leading to improved holistic sustainability of the overall server infrastructure. At the core of many of these methods lie reliable workload-prediction techniques that guide in identifying servers, time intervals, and other parameters that are needed for building sustainability solutions based on techniques like virtualization and server consolidation for server systems. Many workload prediction methods have been proposed in the recent paper, but unfortunately they do not deal adequately with the issues that arise specifically in large-scale server systems, viz., extensive nonstationarity of server workloads, and massive online streaming data. In this paper, we fill this gap by proposing two online ensemble learning methods for workload prediction, which address these issues in large-scale server systems. The proposed algorithms are motivated from the weighted majority and simulatable experts approaches, which we extend and adapt to the large-scale workload prediction problem. We demonstrate the effectiveness of our algorithms using real and synthetic data sets, and show that using the proposed algorithms, the workloads of 91% of servers in a real data center can be predicted with accuracy > 89%, whereas using baseline approaches, the workloads of only 13%–24% of the servers can be predicted with similar accuracy.