Priori information and sliding window based prediction algorithm for energy-efficient storage systems in cloud

One of the major challenges in cloud computing and data centers is the energy conservation and emission reduction. Accurate prediction algorithms are essential for building energy efficient storage systems in cloud computing. In this paper, we first propose a Three-State Disk Model (3SDM), which can describe the service quality and energy consumption states of a storage system accurately. Based on this model, we develop a method for achieving energy conservation without losing quality by skewing the workload among the disks to transmit the disk states of a storage system. The efficiency of this method is highly dependent on the accuracy of the information predicting the blocks to be accessed and the blocks not be accessed in the near future. We develop a priori information and sliding window based prediction (PISWP) algorithm by taking advantage of the priori information about human behavior and selecting suitable size of sliding window. The PISWP method targets at streaming media applications, but we also check its efficiency on other two applications, news in webpage and new tool released. Disksim, an established storage system simulator, is applied in our experiments to verify the effect of our method for various users’ traces. The results show that this prediction method can bring a high degree energy saving for storage systems in cloud computing environment

Comprehensive characterization of an open source document search engine

This work performs a thorough characterization and analysis of the open source Lucene search library. The article describes in detail the architecture, functionality, and micro-architectural behavior of the search engine, and investigates prominent online document search research issues. In particular, we study how intra-server index partitioning affects the response time and throughput, explore the potential use of low power servers for document search, and examine the sources of performance degradation ands the causes of tail latencies. Some of our main conclusions are the following: (a) intra-server index partitioning can reduce tail latencies but with diminishing benefits as incoming query traffic increases, (b) low power servers given enough partitioning can provide same average and tail response times as conventional high performance servers, (c) index search is a CPU-intensive cache-friendly application, and (d) C-states are the main culprits for performance degradation in document search.Web of Science162art. no. 1

Cloud computing: survey on energy efficiency

International audienceCloud computing is today’s most emphasized Information and Communications Technology (ICT) paradigm that is directly or indirectly used by almost every online user. However, such great significance comes with the support of a great infrastructure that includes large data centers comprising thousands of server units and other supporting equipment. Their share in power consumption generates between 1.1% and 1.5% of the total electricity use worldwide and is projected to rise even more. Such alarming numbers demand rethinking the energy efficiency of such infrastructures. However, before making any changes to infrastructure, an analysis of the current status is required. In this article, we perform a comprehensive analysis of an infrastructure supporting the cloud computing paradigm with regards to energy efficiency. First, we define a systematic approach for analyzing the energy efficiency of most important data center domains, including server and network equipment, as well as cloud management systems and appliances consisting of a software utilized by end users. Second, we utilize this approach for analyzing available scientific and industrial literature on state-of-the-art practices in data centers and their equipment. Finally, we extract existing challenges and highlight future research directions

Energy-Efficient Streaming Using Non-volatile Memory

The disk and the DRAM in a typical mobile system consume a significant fraction (up to 30%) of the total system energy. To save on storage energy, the DRAM should be small and the disk should be spun down for long periods of time. We show that this can be achieved for predominantly streaming workloads by connecting the disk to the DRAM via a large non-volatile memory (NVM). We refer to this as the NVM-based architecture (NVMBA); the conventional architecture with only a DRAM and a disk is referred to as DRAMBA. The NVM in the NVMBA acts as a traffic reshaper from the disk to the DRAM. The total system costs are balanced, since the cost increase due to adding the NVM is compensated by the decrease in DRAM cost. We analyze the energy saving of NVMBA, with NAND flash memory serving as NVM, relative to DRAMBA with respect to (1) the streaming demand, (2) the disk form factor, (3) the best-effort provision, and (4) the stream location on the disk. We present a worst-case analysis of the reliability of the disk drive and the flash memory, and show that a small flash capacity is sufficient to operate the system over a year at negligible cost. Disk lifetime is superior to flash, so that is of no concern

Performance of information discovery and message relaying in mobile ad hoc networks

This paper presents 7DS, a novel peer-to-peer resource sharing system. 7DS is an architecture, a set of protocols and an implementation enabling the exchange of data among peers that are not necessarily connected to the Internet. Peers can be either mobile or stationary. We focus on three different facets of cooperation, namely, data sharing, message relaying and network connection sharing. 7DS enables wireless devices to discover, disseminate, relay information among each other to increase the data access. We evaluate via extensive simulations the effectiveness of our system for data dissemination and message relaying among mobile devices with a large number of user mobility scenarios. We model several general data dissemination approaches and investigate the effect of the wireless coverage range, 7DS host density, and cooperation strategy among the mobile hosts as a function of time. We also present a power conservation mechanism that is beneficial, since it increases the power savings, without degrading the data dissemination. Using theory from random walks, random environments and diffusion of controlled processes, we model one of these data dissemination schemes and show that the analysis confirms the simulation results for this scheme

Adaptive Resource Management Schemes for Web Services

Web cluster systems provide cost-effective solutions when scalable and reliable web services are required. However, as the number of servers in web cluster systems increase, web cluster systems incur long and unpredictable delays to manage servers. This study presents the efficient management schemes for web cluster systems. First of all, we propose an efficient request distribution scheme in web cluster systems. Distributor-based systems forward user requests to a balanced set of waiting servers in complete transparency to the users. The policy employed in forwarding requests from the frontend distributor to the backend servers plays an important role in the overall system performance. In this study, we present a proactive request distribution (ProRD) to provide an intelligent distribution at the distributor. Second, we propose the heuristic memory management schemes through a web prefetching scheme. For this study, we design a Double Prediction-by-Partial-Match Scheme (DPS) that can be adapted to the modern web frameworks. In addition, we present an Adaptive Rate Controller (ARC) to determine the prefetch rate depending on the memory status dynamically. For evaluating the prefetch gain in a server node, we implement an Apache module. Lastly, we design an adaptive web streaming system in wireless networks. The rapid growth of new wireless and mobile devices accessing the internet has contributed to a whole new level of heterogeneity in web streaming systems. Particularly, in-home networks have also increased in heterogeneity by using various devices such as laptops, cell phone and PDAs. In our study, a set-top box(STB) is the access pointer between the internet and a home network. We design an ActiveSTB which has a capability of buffering and quality adaptation based on the estimation for the available bandwidth in the wireless LAN

ViPEr-HiSS: A Case for Storage Design Tools

The viability of large-scale multimedia applications, depends on the performance of storage systems. Providing cost-effective access to vast amounts of video, image, audio, and text data, requires (a) proper configuration of storage hierarchies as well as (b) efficient resource management techniques at all levels of the storage hierarchy. The resulting complexities of the hardware/software co-design in turn contribute to difficulties in making accurate predictions about performance, scalability, and cost-effectiveness of a storage system. Moreover, poor decisions at design time can be costly and problematic to correct in later stages of development. Hence, measurement of systems after they have been developed is not a desirable approach to predicting their performance. What is needed is the ability to evaluate the system's design while there are still opportunities to make corrections to fundamental design flaws. In this paper we describe the framework of ViPEr-HiSS, a tool which facilitates design, development, and subsequent performance evaluation of designs of multimedia storage hierarchies by providing mechanisms for relatively easy experimentation with (a) system configurations as well as (b) application- and media-aware resource management techniques. (Also cross-referenced as UMIACS-TR-99-69

On improving performance and conserving power in cluster-based web servers

Efficiency and power conservation are critical issues in the design of cluster systems because these two parameters have direct implications on the user experience and the global need to conserve power. Widely adopted, distributor-based systems forward client requests to a balanced set of waiting servers in complete transparency to the clients. The policy employed in forwarding requests from the front-end distributor to the backend servers plays an important role in the overall system performance. Existing research separately addresses server performance and power conservation. The locality-aware request distribution (LARD) scheme improves the system response time by having the requests served by web servers which have the data in their cache. The power-aware request distribution aims at reducing the power consumption by turning the web servers OFF and ON according to the load. This research tries to achieve power conservation while preserving the performance of the system. First, we prove that using both power-aware and locality-aware request distribution together provides optimum power conservation, while still maintaining the required QoS of the system. We apply the usage of pinned memory in the backend servers to boost performance along with a request distributor design based on power and locality considerations. Secondly, we employ an intelligent-proactive-distribution policy at the front-end to improve the distribution scheme and complementary pre-fetching at the backend server nodes. The proactive distribution depends on both online and offline analysis of the website log files, which capture user navigation patterns on the website. The prefetching scheme pre-fetches the web pages into the memory based on a confidence value of the web page predicted by backend using the log file analysis. Designed to work with the prevailing web technologies, such as HTTP 1.1, our scheme provides reduced response time to the clients and improved power conservation at the backend server cluster. Simulations carried out with traces derived from the log files of real web servers witness performance boost of 15-45% and 10-40% power conservation in comparison to the existing distribution policies