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A Taxonomy and Survey of Energy-Efficient Data Centers and Cloud Computing Systems
"... Traditionally, the development of computing systems has been focused on performance improvements driven by the demand of applications from consumer, scientific and business domains. However, the ever increasing energy consumption of computing systems has started to limit further performance growth d ..."
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Traditionally, the development of computing systems has been focused on performance improvements driven by the demand of applications from consumer, scientific and business domains. However, the ever increasing energy consumption of computing systems has started to limit further performance growth due to overwhelming electricity bills and carbon dioxide footprints. Therefore, the goal of the computer system design has been shifted to power and energy efficiency. To identify open challenges in the area and facilitate future advancements it is essential to synthesize and classify the research on power and energy-efficient design conducted to date. In this work we discuss causes and problems of high power / energy consumption, and present a taxonomy of energy-efficient design of computing systems covering the hardware, operating system, virtualization and data center levels. We survey various key works in the area and map them to our taxonomy to guide future design and development efforts. This chapter is concluded with a discussion of advancements identified in energy-efficient computing and our vision on future
Experimental Analysis of Task-based Energy Consumption
- in Cloud Computing Systems’. in. the 4th ACM/SPEC International Conference on Performance Engineering
, 2013
"... Cloud computing delivers IT solutions as a utility to users. One consequence of this model is that large cloud data centres consume large amounts of energy and produce significant carbon footprints. A common objective of cloud providers is to develop resource provisioning and management solutions th ..."
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Cloud computing delivers IT solutions as a utility to users. One consequence of this model is that large cloud data centres consume large amounts of energy and produce significant carbon footprints. A common objective of cloud providers is to develop resource provisioning and management solutions that minimise energy consumption while guaranteeing Service Level Agreements (SLAs). In order to achieve this objective, a thorough understanding of energy consumption patterns in complex cloud systems is imperative. We have developed an energy consumption model for cloud computing systems. To operationalise this model, we have conducted extensive experiments to profile the energy consumption in cloud computing systems based on three types of tasks: computation-intensive, data-intensive and communication-intensive tasks. We collected fine-grained energy consumption and performance data with varying system configurations and workloads. Our experimental results show the correlation coefficients of energy consumption, system configuration and workload, as well as system performance in cloud systems. These results can be used for designing energy consumption monitors, and static or dynamic system-level energy consumption optimisation strategies for green cloud computing systems.
Renesse, “Toward a reliable, secure and fault tolerant smart grid state estimation
- in the cloud,” in Innovative Smart Grid Technologies. Washington DC, USA: IEEE-PES
, 2013
"... Abstract—The collection and prompt analysis of synchrophasor measurements is a key step towards enabling the future smart power grid, in which grid management applications would be deployed to monitor and react intelligently to changing conditions. The potential exists to slash inefficiencies and to ..."
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Abstract—The collection and prompt analysis of synchrophasor measurements is a key step towards enabling the future smart power grid, in which grid management applications would be deployed to monitor and react intelligently to changing conditions. The potential exists to slash inefficiencies and to adaptively reconfigure the grid to take better advantage of renewables, coordinate and share reactive power, and to reduce the risk of catastrophic large-scale outages. However, to realize this potential, a number of technical challenges must be overcome. We describe a continuously active, timely monitoring framework that we have created, architected to support a wide range of grid-control applications in a standard manner designed to leverage cloud computing. Cloud computing systems bring significant advantages, including an elastic, highly available and cost-effective compute infrastructure well-suited for this application. We believe that by showing how challenges of reliability, timeliness, and security can be addressed while leveraging cloud standards, our work opens the door for wider exploitation of the cloud by the smart grid community. This paper characterizes a PMU-based state-estimation application, explains how the desired system maps to a cloud architecture, identifies limitations in the standard cloud infrastructure relative to the needs of this usecase, and then shows how we adapt the basic cloud platform options with sophisticated technologies of our own to achieve the required levels of usability, fault tolerance, and parallelism. I.
Qiang He “An Energy Consumption Model and Analysis Tool for Cloud Computing Environments”, GREENS 2012
"... Abstract—Cloud computing delivers computing as a utility to users worldwide. A consequence of this model is that cloud data centres have high deployment and operational costs, as well as significant carbon footprints for the environment. We need to develop Green Cloud Computing (GCC) solutions that ..."
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Abstract—Cloud computing delivers computing as a utility to users worldwide. A consequence of this model is that cloud data centres have high deployment and operational costs, as well as significant carbon footprints for the environment. We need to develop Green Cloud Computing (GCC) solutions that reduce these deployment and operational costs and thus save energy and reduce adverse environmental impacts. In order to achieve this objective, a thorough understanding of the energy consumption patterns in complex Cloud environments is needed. We present a new energy consumption model and associated analysis tool for Cloud computing environments. We measure energy consumption in Cloud environments based on different runtime tasks. Empirical analysis of the correlation of energy consumption and Cloud data and computational tasks, as well as system performance, will be investigated based on our energy consumption model and analysis tool. Our research results can be integrated into Cloud systems to monitor energy consumption and support static or dynamic system-level optimisation. Keywords-green computing; Cloud computing; energy consumption; performance analysis
Green Cloud computing and Environmental Sustainability
"... Abstract: Cloud computing is a highly scalable and cost-effective infrastructure for running HPC, enterprise and Web applications. However, the growing demand of Cloud infrastructure has drastically increased the energy consumption of data centers, which has become a critical issue. High energy cons ..."
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Abstract: Cloud computing is a highly scalable and cost-effective infrastructure for running HPC, enterprise and Web applications. However, the growing demand of Cloud infrastructure has drastically increased the energy consumption of data centers, which has become a critical issue. High energy consumption not only translates to high operational cost, which reduces the profit margin of Cloud providers, but also leads to high carbon emissions which is not environmentally friendly. Hence, energy-efficient solutions are required to minimize the impact of Cloud computing on the environment. In order to design such solutions, deep analysis of Cloud is required with respect to their power efficiency. Thus, in this chapter, we discuss various elements of Clouds which contribute to the total energy consumption and how it is addressed in the literature. We also discuss the implication of these solutions for future research directions to enable green Cloud computing. The chapter also explains the role of Cloud users in achieving this goal. 1.
Task and server assignment for reduction of energy consumption in datacenters
- In Proceedings of the IEEE 11-th International Symposium on Network Computing and Applications
"... Abstract-Energy consumption of cloud datacenters accounts for a major operational cost. This paper presents an optimization model for task scheduling to minimize task processing time and energy consumption in datacenters for cloud computing. We formulate an integer programming optimization problem ..."
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Abstract-Energy consumption of cloud datacenters accounts for a major operational cost. This paper presents an optimization model for task scheduling to minimize task processing time and energy consumption in datacenters for cloud computing. We formulate an integer programming optimization problem to minimize the expected energy consumption of homogenous tasks in a datacenter with a large number of servers and propose the most-efficient-server first greedy task scheduling algorithm to minimize energy expenditure. We show that the proposed task scheduling can minimize the energy expenditure while bounding the average task waiting time. We present a simulation of the proposed task scheduling scheme to show an optimum number of servers to achieve small task processing times and to minimize energy consumption.
On-line real-time service allocation and scheduling for distributed data centers
- In Services Computing (SCC), 2011 IEEE International Conference on
, 2011
"... Abstract-With the prosperity of Cluster Computing, Cloud Computing, Grid Computing, and other distributed high performance computing systems, Internet service requests become more and more diverse. The large variety of services plus different Quality of Service (QoS) considerations make it challeng ..."
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Abstract-With the prosperity of Cluster Computing, Cloud Computing, Grid Computing, and other distributed high performance computing systems, Internet service requests become more and more diverse. The large variety of services plus different Quality of Service (QoS) considerations make it challenging to design effective allocate and scheduling algorithms to satisfy the overall service requirements, especially for distributed systems. In addition, energy consumption issue attracts more and more concerns. In this paper, we study a new energy efficient, profit and penalty aware allocation and scheduling approach for distributed data centers in a multi-electricity-market environment. Our approach efficiently manages computing resources to minimize the processing and transferring energy dollar cost in an electricity price varying environment. Our extensive experimental results show the new approach can significantly cut down the energy consumption dollar cost and achieve higher system's retained profit.
Profiling-Based Task Scheduling for Factory-Worker Applications
- in Infrastructure-as-aService Clouds,” in 40th EUROMICRO Conference on Software Engineering and Advanced Applications
, 2014
"... Abstract—With the recent advances of cloud computing, effec-tive resource usage (e.g., CPU, memory or network) becomes an important question as application developers have to continuously pay for rented resources, even if they are not used effectively. In order to maintain required performance level ..."
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Abstract—With the recent advances of cloud computing, effec-tive resource usage (e.g., CPU, memory or network) becomes an important question as application developers have to continuously pay for rented resources, even if they are not used effectively. In order to maintain required performance levels, it is currently common to reserve resources for peak resource usage or possible resource usage overlaps, if more than one task is executed on a host. While this is a reasonable approach for long-running applications or web servers, for some applications with disperse resource usage over time, this strategy causes significant over-provisioning and thus resource wastage and financial loss. In this paper we present a profiling-based task scheduling approach for factory-worker applications that schedules tasks within the defined resource limitations (e.g., existing machine memory size or network quota) and distributes the tasks in the cloud environment in order to use resources effectively. The evaluation of our approach approved the efficiency of the proposed algorithm and minimal performance overhead. In case of the evaluated application, the presented scheduling process leads up to 33% resource savings with only 1 % of performance loss.
Environmental performance of data centres — A case study
- of the Swedish National Insurance Administration,” in EGG’12
"... Abstract There are indications of Data Centres being nodes for environmental impacts in IT solutions, but due to reasons connected to protection of business core assets, few open studies on such centres exist. This LCA case-study of the Swedish National Insurance Agency Data Centre in Sundsvall con ..."
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Abstract There are indications of Data Centres being nodes for environmental impacts in IT solutions, but due to reasons connected to protection of business core assets, few open studies on such centres exist. This LCA case-study of the Swedish National Insurance Agency Data Centre in Sundsvall confirms and quantifies the significance of the environmental load posed by the data centre. The centre increases the IT carbon footprint by more than half (54%) relative to the institutes PC equipment fleet. In the operational phase, climate change contributions are more than double to that of PC use. Environmental impact stemming from embedded emissions in data centre capital infrastructure is significant (33%) given the relative short economic lifetime of the IT hardware. Even within the cold climate geographical zone, about a third (32%) of data centre supplied energy is consumed by air-conditioning thus offering opportunities to further leverage free cooling.