Showing papers on "Efficient energy use published in 2010"

Energy Efficient Resource Management in Virtualized Cloud Data Centers

Abstract: Rapid growth of the demand for computational power by scientific, business and web-applications has led to the creation of large-scale data centers consuming enormous amounts of electrical power. We propose an energy efficient resource management system for virtualized Cloud data centers that reduces operational costs and provides required Quality of Service (QoS). Energy savings are achieved by continuous consolidation of VMs according to current utilization of resources, virtual network topologies established between VMs and thermal state of computing nodes. We present first results of simulation-driven evaluation of heuristics for dynamic reallocation of VMs using live migration according to current requirements for CPU performance. The results show that the proposed technique brings substantial energy savings, while ensuring reliable QoS. This justifies further investigation and development of the proposed resource management system.

Near-Threshold Computing: Reclaiming Moore's Law Through Energy Efficient Integrated Circuits

Abstract: Power has become the primary design constraint for chip designers today. While Moore's law continues to provide additional transistors, power budgets have begun to prohibit those devices from actually being used. To reduce energy consumption, voltage scaling techniques have proved a popular technique with subthreshold design representing the endpoint of voltage scaling. Although it is extremely energy efficient, subthreshold design has been relegated to niche markets due to its major performance penalties. This paper defines and explores near-threshold computing (NTC), a design space where the supply voltage is approximately equal to the threshold voltage of the transistors. This region retains much of the energy savings of subthreshold operation with more favorable performance and variability characteristics. This makes it applicable to a broad range of power-constrained computing segments from sensors to high performance servers. This paper explores the barriers to the widespread adoption of NTC and describes current work aimed at overcoming these obstacles.

Energy efficiency: economics and policy

Abstract: Energy efficiency and conservation are major factors in the reduction of the environmental impact of the energy sector, particularly with regard to climate change. Energy efficiency also contributes to reducing external dependence and vulnerabilities in the energy domain. In this paper, we discuss the factors that influence energy efficiency and conservation decisions, and the most appropriate policies for their promotion. Although not all public policies seem justified, we argue that specific policies for promoting energy conservation may be required, preferably based on economic instruments or on the provision of information to consumers.

Energy efficiency of mobile clients in cloud computing

Abstract: Energy efficiency is a fundamental consideration for mobile devices. Cloud computing has the potential to save mobile client energy but the savings from offloading the computation need to exceed the energy cost of the additional communication. In this paper we provide an analysis of the critical factors affecting the energy consumption of mobile clients in cloud computing. Further, we present our measurements about the central characteristics of contemporary mobile handheld devices that define the basic balance between local and remote computing. We also describe a concrete example, which demonstrates energy savings. We show that the trade-offs are highly sensitive to the exact characteristics of the workload, data communication patterns and technologies used, and discuss the implications for the design and engineering of energy efficient mobile cloud computing solutions.

Near-Threshold Computing: Reclaiming Moore's Law Through Energy Efficient Integrated Circuits Future computer systems promise to achieve an energy reduction of 100 or more times with memory design, device structure, device fabrication techniques, and clocking, all optimized for low-voltage operation.

Abstract: Power has become the primary design constraint for chip designers today. While Moore's law continues to provide additional transistors, power budgets have begun to prohibit those devices from actually being used. To reduce energy consumption, voltage scaling techniques have proved a popular technique with subthreshold design representing the endpoint of voltage scaling. Although it is extremely energy efficient, subthreshold design has been relegated to niche markets due to its major performance penalties. This paper defines and explores near-threshold computing (NTC), a design space where the supply voltage is approximately equal to the threshold voltage of the transistors. This region retains much of the energy savings of subthreshold operation with more favor- able performance and variability characteristics. This makes it applicable to a broad range of power-constrained computing segments from sensors to high performance servers. This paper explores the barriers to the widespread adoption of NTC and describes current work aimed at overcoming these obstacles.

Power consumption modeling of different base station types in heterogeneous cellular networks

Abstract: In wireless communications micro cells are potentially more energy efficient than conventional macro cells due to the high path loss exponent. Also, heterogeneous deployments of both cell types can be used to optimize the energy efficiency. Energy efficiency of any deployment is impacted by the power consumption of each individual network element and the dependency of transmit power and load. In this paper we developed such power models for macro and micro base stations relying on data sheets of several GSM and UMTS base stations with focus on component level, e.g., power amplifier and cooling equipment. In a first application of the model a traditional macro cell deployment and a heterogeneous deployment are compared.

Energy-Efficient Cloud Computing

Abstract: Energy efficiency is increasingly important for future information and communication technologies (ICT), because the increased usage of ICT, together with increasing energy costs and the need to reduce green house gas emissions call for energy-efficient technologies that decrease the overall energy consumption of computation, storage and communications. Cloud computing has recently received considerable attention, as a promising approach for delivering ICT services by improving the utilization of data centre resources. In principle, cloud computing can be an inherently energy-efficient technology for ICT provided that its potential for significant energy savings that have so far focused on hardware aspects, can be fully explored with respect to system operation and networking aspects. Thus this paper, in the context of cloud computing, reviews the usage of methods and technologies currently used for energy-efficient operation of computer hardware and network infrastructure. After surveying some of the current best practice and relevant literature in this area, this paper identifies some of the remaining key research challenges that arise when such energy-saving techniques are extended for use in cloud computing environments.

Electric, Hybrid, and Fuel-Cell Vehicles: Architectures and Modeling

Abstract: With the advent of more stringent regulations related to emissions, fuel economy, and global warming, as well as energy resource constraints, electric, hybrid, and fuel-cell vehicles have attracted increasing attention from vehicle constructors, governments, and consumers. Research and development efforts have focused on developing advanced powertrains and efficient energy systems. This paper reviews the state of the art for electric, hybrid, and fuel-cell vehicles, with a focus on architectures and modeling for energy management. Although classic modeling approaches have often been used, new systemic approaches that allow better understanding of the interaction between the numerous subsystems have recently been introduced.

Energy-efficient link adaptation in frequency-selective channels

Abstract: Energy efficiency is becoming increasingly important for small form factor mobile devices, as battery technology has not kept up with the growing requirements stemming from ubiquitous multimedia applications. This paper addresses link adaptive transmission for maximizing energy efficiency, as measured by the "throughput per Joule" metric. In contrast to the existing water-filling power allocation schemes that maximize throughput subject to a fixed overall transmit power constraint, our scheme maximizes energy efficiency by adapting both overall transmit power and its allocation, according to the channel states and the circuit power consumed. We demonstrate the existence of a unique globally optimal link adaptation solution and develop iterative algorithms to obtain it. We further consider the special case of flat-fading channels to develop an upper bound on energy efficiency and to characterize its variation with bandwidth, channel gain and circuit power. Our results for OFDM systems demonstrate improved energy savings with energy optimal link adaptation as well as illustrate the fundamental tradeoff between energy-efficient and spectrum-efficient transmission.

Challenges and enabling technologies for energy aware mobile radio networks

Abstract: Mobile communications are increasingly contributing to global energy consumption. In this article, a holistic approach for energy efficient mobile radio networks is presented. The matter of having appropriate metrics and evaluation methods that allow assessing the energy efficiency of the entire system is discussed. The mutual supplementary saving concepts comprise component, link and network levels. At the component level the power amplifier complemented by a transceiver and a digital platform supporting advanced power management are key to efficient radio implementations. Discontinuous transmission by base stations, where hardware components are switched off, facilitate energy efficient operation at the link level. At the network level, the potential for reducing energy consumption is in the layout of networks and their management, that take into account slowly changing daily load patterns, as well as highly dynamic traffic fluctuations. Moreover, research has to analyze new disruptive architectural approaches, including multi-hop transmission, ad-hoc meshed networks, terminal-to-terminal communications, and cooperative multipoint architectures.

Management and Control of Domestic Smart Grid Technology

Abstract: Emerging new technologies like distributed generation, distributed storage, and demand-side load management will change the way we consume and produce energy. These techniques enable the possibility to reduce the greenhouse effect and improve grid stability by optimizing energy streams. By smartly applying future energy production, consumption, and storage techniques, a more energy-efficient electricity supply chain can be achieved. In this paper a three-step control methodology is proposed to manage the cooperation between these technologies, focused on domestic energy streams. In this approach, (global) objectives like peak shaving or forming a virtual power plant can be achieved without harming the comfort of residents. As shown in this work, using good predictions, in advance planning and real-time control of domestic appliances, a better matching of demand and supply can be achieved.

Energy-Efficient Management of Data Center Resources for Cloud Computing: A Vision, Architectural Elements, and Open Challenges

Abstract: Cloud computing is offering utility-oriented IT services to users worldwide. Based on a pay-as-you-go model, it enables hosting of pervasive applications from consumer, scientific, and business domains. However, data centers hosting Cloud applications consume huge amounts of energy, contributing to high operational costs and carbon footprints to the environment. Therefore, we need Green Cloud computing solutions that can not only save energy for the environment but also reduce operational costs. This paper presents vision, challenges, and architectural elements for energy-efficient management of Cloud computing environments. We focus on the development of dynamic resource provisioning and allocation algorithms that consider the synergy between various data center infrastructures (i.e., the hardware, power units, cooling and software), and holistically work to boost data center energy efficiency and performance. In particular, this paper proposes (a) architectural principles for energy-efficient management of Clouds; (b) energy-efficient resource allocation policies and scheduling algorithms considering quality-of-service expectations, and devices power usage characteristics; and (c) a novel software technology for energy-efficient management of Clouds. We have validated our approach by conducting a set of rigorous performance evaluation study using the CloudSim toolkit. The results demonstrate that Cloud computing model has immense potential as it offers significant performance gains as regards to response time and cost saving under dynamic workload scenarios.

[ACM Press the 2nd ACM Workshop - Zurich, Switzerland (2010.11.02-2010.11.02)] Proceedings of the 2nd ACM Workshop on Embedded Sensing Systems for Energy-Efficiency in Building - BuildSys \'10 - Occupancy-driven energy management for smart building automation

Abstract: Buildings are among the largest consumers of electricity in the US. A significant portion of this energy use in buildings can be attributed to HVAC systems used to maintain comfort for occupants. In most cases these building HVAC systems run on fixed schedules and do not employ any fine grained control based on detailed occupancy information. In this paper we present the design and implementation of a presence sensor platform that can be used for accurate occupancy detection at the level of individual offices. Our presence sensor is low-cost, wireless, and incrementally deployable within existing buildings. Using a pilot deployment of our system across ten offices over a two week period we identify significant opportunities for energy savings due to periods of vacancy. Our energy measurements show that our presence node has an estimated battery lifetime of over five years, while detecting occupancy accurately. Furthermore, using a building simulation framework and the occupancy information from our testbed, we show potential energy savings from 10% to 15% using our system.

Energy proportional datacenter networks

Abstract: Numerous studies have shown that datacenter computers rarely operate at full utilization, leading to a number of proposals for creating servers that are energy proportional with respect to the computation that they are performing. In this paper, we show that as servers themselves become more energy proportional, the datacenter network can become a significant fraction (up to 50%) of cluster power. In this paper we propose several ways to design a high-performance datacenter network whose power consumption is more proportional to the amount of traffic it is moving -- that is, we propose energy proportional datacenter networks. We first show that a flattened butterfly topology itself is inherently more power efficient than the other commonly proposed topology for high-performance datacenter networks. We then exploit the characteristics of modern plesiochronous links to adjust their power and performance envelopes dynamically. Using a network simulator, driven by both synthetic workloads and production datacenter traces, we characterize and understand design tradeoffs, and demonstrate an 85% reduction in power --- which approaches the ideal energy-proportionality of the network. Our results also demonstrate two challenges for the designers of future network switches: 1) We show that there is a significant power advantage to having independent control of each unidirectional channel comprising a network link, since many traffic patterns show very asymmetric use, and 2) system designers should work to optimize the high-speed channel designs to be more energy efficient by choosing optimal data rate and equalization technology. Given these assumptions, we demonstrate that energy proportional datacenter communication is indeed possible.

Energy-Efficient Buildings Facilitated by Microgrid

Abstract: Recent research shows that 20%-30% of building energy consumption can be saved through optimized operation and management without changing the building structure and the hardware configuration of the energy supply system. Therefore, there is a huge potential for building energy savings through efficient operation. Microgrid technology provides an opportunity and a desirable infrastructure for improving the efficiency of energy consumption in buildings. The key to improve building energy efficiency in operation is to coordinate and optimize the operation of various energy sources and loads. In this paper, the scheduling problem of building energy supplies is considered with the practical background of a low energy building. The objective function is to minimize the overall cost of electricity and natural gas for a building operation over a time horizon while satisfying the energy balance and complicated operating constraints of individual energy supply equipment and devices. The uncertainties are captured and their impact is analyzed by the scenario tree method. Numerical testing is performed with the data of the pilot low energy building. The testing results show that significant energy cost savings can be achieved through integrated scheduling and control of various building energy supply sources. It is very important to fully utilize solar energy and optimize the operation of electrical storage. It is also shown that precooling is a simple way to achieve energy savings.

Energy efficient building climate control using Stochastic Model Predictive Control and weather predictions

Abstract: One of the most critical challenges facing society today is climate change and thus the need to realize massive energy savings. Since buildings account for about 40% of global final energy use, energy efficient building climate control can have an important contribution. In this paper we develop and analyze a Stochastic Model Predictive Control (SMPC) strategy for building climate control that takes into account weather predictions to increase energy efficiency while respecting constraints resulting from desired occupant comfort. We investigate a bilinear model under stochastic uncertainty with probabilistic, time varying constraints. We report on the assessment of this control strategy in a large-scale simulation study where the control performance with different building variants and under different weather conditions is studied. For selected cases the SMPC approach is analyzed in detail and shown to significantly outperform current control practice.

Global Warming: Energy, Environmental Pollution, and the Impact of Power Electronics

Abstract: Global energy consumption is dramatically increasing due to our quest for a higher standard of living and the increasing world population. Most of our energy comes from fossil fuels, and burning these fuels causes environmental problems, and in particular, the global warming problem. Global warming raises the sea level; brings drought in tropical regions near the equator; increases hurricanes, tornadoes, and floods; and causes the spread of diseases. The consequences are serious and have the potential to bring tremendous unrest in the world. Various measures to solve or mitigate the global warming problem have been outlined in this article. This article particularly highlights the impact of power electronics in solving this problem. Power electronics will play a very important role in clean energy generation, bulk storage of electricity, and efficient energy utilization, and eventually, it will be a key element in the energy policies of nations. It has been estimated that the widespread energy efficiency improvement by power electronics and other methods with the existing technologies can save 20% of the global energy demand, and another 20% can be saved by preventing waste, i.e., by various conservation methods. Finally, the global warming problem is solvable by the united effort of humanity.

Understanding sources of inefficiency in general-purpose chips

Abstract: Due to their high volume, general-purpose processors, and now chip multiprocessors (CMPs), are much more cost effective than ASICs, but lag significantly in terms of performance and energy efficiency. This paper explores the sources of these performance and energy overheads in general-purpose processing systems by quantifying the overheads of a 720p HD H.264 encoder running on a general-purpose CMP system. It then explores methods to eliminate these overheads by transforming the CPU into a specialized system for H.264 encoding. We evaluate the gains from customizations useful to broad classes of algorithms, such as SIMD units, as well as those specific to particular computation, such as customized storage and functional units. The ASIC is 500x more energy efficient than our original four-processor CMP. Broadly applicable optimizations improve performance by 10x and energy by 7x. However, the very low energy costs of actual core ops (100s fJ in 90nm) mean that over 90% of the energy used in these solutions is still "overhead". Achieving ASIC-like performance and efficiency requires algorithm-specific optimizations. For each sub-algorithm of H.264, we create a large, specialized functional unit that is capable of executing 100s of operations per instruction. This improves performance and energy by an additional 25x and the final customized CMP matches an ASIC solution's performance within 3x of its energy and within comparable area.

Energy Efficient Allocation of Virtual Machines in Cloud Data Centers

Abstract: Rapid growth of the demand for computational power has led to the creation of large-scale data centers. They consume enormous amounts of electrical power resulting in high operational costs and carbon dioxide emissions. Moreover, modern Cloud computing environments have to provide high Quality of Service (QoS) for their customers resulting in the necessity to deal with power-performance trade-off. We propose an efficient resource management policy for virtualized Cloud data centers. The objective is to continuously consolidate VMs leveraging live migration and switch off idle nodes to minimize power consumption, while providing required Quality of Service. We present evaluation results showing that dynamic reallocation of VMs brings substantial energy savings, thus justifying further development of the proposed policy.

Adaptive threshold-based approach for energy-efficient consolidation of virtual machines in cloud data centers

Abstract: The rapid growth in demand for computational power driven by modern service applications combined with the shift to the Cloud computing model have led to the establishment of large-scale virtualized data centers. Such data centers consume enormous amounts of electrical energy resulting in high operating costs and carbon dioxide emissions. Dynamic consolidation of virtual machines (VMs) and switching idle nodes off allow Cloud providers to optimize resource usage and reduce energy consumption. However, the obligation of providing high quality of service to customers leads to the necessity in dealing with the energy-performance trade-off. We propose a novel technique for dynamic consolidation of VMs based on adaptive utilization thresholds, which ensures a high level of meeting the Service Level Agreements (SLA). We validate the high efficiency of the proposed technique across different kinds of workloads using workload traces from more than a thousand PlanetLab servers.

Improving energy efficiency of location sensing on smartphones

Abstract: Location-based applications have become increasingly popular on smartphones over the past years. The active use of these applications can however cause device battery drain owing to their power-intensive location-sensing operations. This paper presents an adaptive location sensing framework that significantly improves the energy efficiency of smartphones running location-based applications. The underlying design principles of the proposed framework involve substitution, suppression, piggybacking, and adaptation of applications' location-sensing requests to conserve energy. We implement these design principles on Android-based smartphones as a middleware. Our evaluation results show that the design principles reduce the usage of the power-intensive GPS (Global Positioning System) by up to 98% and improve battery life by up to 75%.

PowerPack: Energy Profiling and Analysis of High-Performance Systems and Applications

Abstract: Energy efficiency is a major concern in modern high-performance computing system design. In the past few years, there has been mounting evidence that power usage limits system scale and computing density, and thus, ultimately system performance. However, despite the impact of power and energy on the computer systems community, few studies provide insight to where and how power is consumed on high-performance systems and applications. In previous work, we designed a framework called PowerPack that was the first tool to isolate the power consumption of devices including disks, memory, NICs, and processors in a high-performance cluster and correlate these measurements to application functions. In this work, we extend our framework to support systems with multicore, multiprocessor-based nodes, and then provide in-depth analyses of the energy consumption of parallel applications on clusters of these systems. These analyses include the impacts of chip multiprocessing on power and energy efficiency, and its interaction with application executions. In addition, we use PowerPack to study the power dynamics and energy efficiencies of dynamic voltage and frequency scaling (DVFS) techniques on clusters. Our experiments reveal conclusively how intelligent DVFS scheduling can enhance system energy efficiency while maintaining performance.

Energy policy and alternative energy in Malaysia: Issues and challenges for sustainable growth

Abstract: Energy is essential to the way we live. Whether it is in the form of oil, gasoline or electricity, a country's prosperity and welfare depends on having access to reliable and secure supplies of energy at affordable prices. However, it is also one of the benefits taken for granted by many people, knowing little about the impact of electricity on their lives. Having dependent mainly on oil and gas for half a century, Malaysia has started to realize the importance to adopt renewable energy in the energy mix and continuously reviewed its energy policy to ensure sustainable energy supply and security. This paper examines and discusses the intricacy of the existing and new energy policies, issues and challenges in Malaysia. The overall approach in addressing the energy issues and challenges will continue to focus on adequacy, quality, security and sustainability of both non-renewable and renewable energy supply in the country's development and the promotion and implementation of its energy efficiency programs. The recently launched National Green Technology Policy is also discussed.