present s GRACE-OS, an energy-e#cient soft real-t-e CPU scheduler for mobile devicestvi primarily run multD]A1D applicatD4D[ The major goal of GR CE-OS is t support applicatDD qualit y of service and save energy. To achievet his goal, GR CE-OS int egrat] dynamic volt]% scaling int osoft real-t1D scheduling and decides howfast t execut applicat37: inaddit]] t when and how longt executt hem. GR CE-OS makes such scheduling decisions based ont heprobabilit y distD[A1%M3 of applicat%M cycle demands, andobt23] t he demanddistA3:772A via online profiling and est]:A1%]2 We have implementl GR CE-OS in tA Linux kernel and evaluat: it on an HPlapt7 wit a variable-speed CPU and mult37MA1 codecs. Our experiment alresult showt hat (1) tA demand dist2DA1%%M oft he stA7M7 codecs isst373 or changes smoot73 . ThisstsA74[ y impliest hat it is feasiblet o perform st chast: scheduling and volt]3 scaling wit low overhead; (2) GR CE-OS deliverssoft performance guarant ees by boundingtn deadline miss rat4 under applicat7:]7M ecific requirementu and (3) GR CE-OS reduces CPU idlet ime and spends more busyt ime in lower-power speeds. Our measurement indicati t hat comparedt o det::2A1744M scheduling and volt age scaling, GR CE-OS saves energy by 7% t 72% while delivering stMD%A17%D performance guarant ees.

This paper presents the design and implementation of a compiler algorithm that effectively optimizes programs for energy usage using dynamic voltage scaling (DVS). The algorithm identifies program regions where the CPU can be slowed down with negligible performance loss. It is implemented as a source-to-source level transformation using the SUIF2 compiler infrastructure. Physical measurements on a high-performance laptop show that total system (i.e., laptop) energy savings of up to 28% can be achieved with performance degradation of less than 5% for the SPECfp95 benchmarks. On average, the system energy and energydelay product are reduced by 11% and 9%, respectively, with a performance slowdown of 2%. It was also discovered that the energy usage of the programs using our DVS algorithm is within 6% from the theoretical lower bound. To the best of our knowledge, this is one of the first work that evaluates DVS algorithms by physical measurements.

Abstract not found

Traditional disk management strategies---prefetching and caching in particular---are designed to maximize performance. In mobile systems they conflict with strategies that attempt to save energy by powering down the disk when it is idle. We present new rules for prefetching and caching that maximize power-down opportunities (without performance loss) by creating an access pattern characterized by intense bursts of activity separated by long idle times. We also describe an automatic system that monitors past application behavior in order to generate appropriate prefetching hints, and a general system of kernel enhancements that coordinate I/O activity across all running applications. We have

Energy consumption in hosting Internet services is becoming a pressing issue as these services scale up. Dynamic server provisioning techniques are effective in turning off unnecessary servers to save energy. Such techniques, mostly studied for request-response services, face challenges in the context of connection servers that host a large number of long-lived TCP connections. In this paper, we characterize unique properties, performance, and power models of connection servers, based on a real data trace collected from the deployed Windows Live Messenger. Using the models, we design server provisioning and load dispatching algorithms and study subtle interactions between them. We show that our algorithms can save a significant amount of energy without sacrificing user experiences. 1

OS resource management policies traditionally employ buffering to “smooth out ” fluctuations in resource demand. By minimizing the length of idle periods and the level of contention during non-idle periods, such smoothing tends to maximize overall throughput and minimize the latency of individual requests. For certain important devices, however (disks, network interfaces, or even computational elements), smoothing eliminates opportunities to save energy using low-power modes. As devices with such modes proliferate, and as energy efficiency becomes an increasingly important design consideration, we argue that OS policies should be redesigned to increase burstiness for energysensitive devices. We are currently experimenting with techniques to increase the disk access pattern burstiness of the Linux operating system. Our results indicate that the deliberate creation of bursty activity can save up to 78.5 % of the energy consumed by a Hitachi DK23DA disk (in comparison with current policies), while simultaneously decreasing the negative impact of disk congestion and spin-up latency on application performance. 1.

We introduce external synchrony, a new model for local file I/O that provides the reliability and simplicity of synchronous I/O, yet also closely approximates the performance of asynchronous I/O. An external observer cannot distinguish the output of a computer with an externally synchronous file system from the output of a computer with a synchronous file system. No application modification is required to use an externally synchronous file system: in fact, application developers can program to the simpler synchronous I/O abstraction and still receive excellent performance. We have implemented an externally synchronous file system for Linux, called xsyncfs. Xsyncfs provides the same durability and ordering guarantees as those provided by a synchronously mounted ext3 file system. Yet, even for I/O-intensive benchmarks, xsyncfs performance is within 7 % of ext3 mounted asynchronously. Compared to ext3 mounted synchronously, xsyncfs is up to two orders of magnitude faster. 1

With increasing costs of energy consumption and cooling, power management in server clusters has become an increasingly important design issue. Current clusters for real-time applications are designed to handle peak loads, where all servers are fully utilized. In practice, peak load conditions rarely happen and clusters are most of the time underutilized. This creates the opportunity for using slower frequencies, and thus smaller energy consumption, with little or no impact on the Quality of Service (QoS), for example, performance and timeliness. In this work we present a cluster-wide QoS-aware technique that dynamically reconfigures the cluster to reduce energy consumption during periods of reduced load. Moreover, we also investigate the effects of local QoS-aware power management using Dynamic Voltage Scaling (DVS). Since most real-world clusters consist of machines of different kind (in terms of both performance and energy consumption) we focus on heterogeneous clusters. For validation, we describe and evaluate an implementation of the proposed scheme using the Apache Webserver in a small realistic cluster. Our experimental results show that using our scheme it is possible to save up to 45 % of the total energy consumed by the servers, maintaining average response times within the specified deadlines and number of dropped requests within the required amount. 1

Dynamic voltage scaling (DVS) is a popular approach for energy reduction of integrated circuits. Current processors that use DVS typically have an operating voltage range from full to half of the maximum Vdd. However, it is possible to construct designs that operate over a much larger voltage range: from full Vdd to subthreshold voltages. This possibility raises the question of whether a larger voltage range improves the energy efficiency of DVS. First, from a theoretical point of view, we show that for subthreshold supply voltages leakage energy becomes dominant, making “just in time completion” energy inefficient. We derive an analytical model for the minimum energy optimal voltage and study its trends with technology scaling. Second, we use the proposed model to study the workload activity of an actual processor and analyze the energy efficiency as a function of the lower limit of voltage scaling. Based on this study, we show that extending the voltage range below 1/2 Vdd will improve the energy efficiency for most processor designs, while extending this range to subthreshold operation is beneficial only for very specific applications. Finally, we show that operation deep in the subthreshold voltage range is never energy-efficient.

Current approaches to power management are based on operating systems with full knowledge of and full control over the underlying hardware; the distributed nature of multi-layered virtual machine environments renders such approaches insufficient. In this paper, we present a novel framework for energy management in modular, multi-layered operating system structures. The framework provides a unified model to partition and distribute energy, and mechanisms for energy-aware resource accounting and allocation. As a key property, the framework explicitly takes the recursive energy consumption into account, which is spent, e.g., in the virtualization layer or subsequent driver components. Our prototypical implementation targets hypervisor-based virtual machine systems and comprises two components: a host-level subsystem, which controls machine-wide energy constraints and enforces them among all guest OSes and service components, and, complementary, an energy-aware guest operating system, capable of fine-grained applicationspecific energy management. Guest level energy management thereby relies on effective virtualization of physical energy effects provided by the virtual machine monitor. Experiments with CPU and disk devices and an external data acquisition system demonstrate that our framework accurately controls and stipulates the power consumption of individual hardware devices, both for energy-aware and energyunaware guest operating systems. 1