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Decomposition based algorithm for state prediction in large scale distributed systems

Decomposition based algorithm for state prediction in large ...

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9th international Symposium on parallel and distributed Computing, ISPDC 2010

作者： Istin, Mihai Vişan, Andreea Pop, Florin Cristea, Valentin Faculty of Automatic Control and Computers Computer Science Department University Politehnica of Bucharest Romania

ISBN: (纸本)9780769541204

Prediction represents an important component of resource management, providing information about the future state, utilization and availability of resources. We propose a new prediction algorithm inspired from the decomposition of a complex wave into simpler waves with fixed frequencies (similar to Fourier decomposition). The partial results obtained from this decomposition stage are combined using approaches inspired from artificial intelligence models. The experimental results for different system parameters, used in Alice experiment, highlight the great improvement, discussed in terms of error reduction, offered by this new prediction algorithm. The tests were made using real-time monitoring data provided by a system monitoring tool, in the case of one-step and multi-step ahead prediction. The prediction's results can be used by the resource management systems in order to improve the scheduling decisions, assuring the load balancing and optimizing the resource utilization. © 2010 IEEE.

关键词： Forecasting

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A cooperative intrusion detection system framework for cloud computing networks

A cooperative intrusion detection system framework for cloud...

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international workshop on scheduling and resource management for parallel and distributed systems

作者： Lo, Chi-Chun Huang, Chun-Chieh Ku, Joy Institute of Information Management National Chiao Tung University Hsinchu Taiwan

ISBN: (纸本)9780769541570

Cloud computing provides a framework for supporting end users easily attaching powerful services and applications through Internet. To provide secure and reliable services in cloud computing environment is an important issue. One of the security issues is how to reduce the impact of denial-of-service (DoS) attack or distributed denial-of-service (DDoS) in this environment. To counter these kinds of attacks, a framework of cooperative intrusion detection system (IDS) is proposed. The proposed system could reduce the impact of these kinds of attacks. To provide such ability, IDSs in the cloud computing regions exchange their alerts with each other. In the system, each of IDSs has a cooperative agent used to compute and determine whether to accept the alerts sent from other IDSs or not. By this way, IDSs could avoid the same type of attack happening. The implementation results indicate that the proposed system could resist DoS attack. Moreover, by comparison, the proposed cooperative IDS system only increases little computation effort compared with pure Snort based IDS but prevents the system from single point of failure attack. © 2010 IEEE.

关键词： Denial-of-service attack

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Proceedings of the 2010 IEEE international Symposium on parallel and distributed Processing, workshops and Phd Forum, IPDPSW 2010

Proceedings of the 2010 IEEE International Symposium on Para...

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2010 IEEE international Symposium on parallel and distributed Processing, workshops and Phd Forum, IPDPSW 2010

ISBN: (纸本)9781424465347

The proceedings contain 239 papers. The topics discussed include: characterizing heterogeneous computing environments using singular value decomposition;statistical predictors of computing power in heterogeneous clusters;a first step to the evaluation of SimGrid in the context of a real application;dynamic adaptation of DAGs with uncertain execution times in heterogeneous computing systems;robust resource allocation of DAGs in a heterogeneous multicore system;decentralized dynamic scheduling across heterogeneous multi-core desktop grids;a configurable-hardware document-similarity classifier to detect web attacks;a configurable high-throughput linear sorter system;hardware implementation for scalable lookahead regular expression detection;reducing grid energy consumption through choice of resource allocation method;and scheduling parallel tasks on multiprocessor computers with efficient power management.

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CAP-OS: Operating system for runtime scheduling, task mapping and resource management on reconfigurable multiprocessor architectures

CAP-OS: Operating system for runtime scheduling, task mappin...

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2010 IEEE international Symposium on parallel and distributed Processing, workshops and Phd Forum, IPDPSW 2010

作者： Göhringer, Diana Hübner, Michael Zeutebouo, Etienne Nguepi Becker, Jürgen Fraunhofer IOSB Germany Germany

ISBN: (纸本)9781424465347

Operating systems traditionally handle the task scheduling of one or more application instances on a processor like hardware architecture. Novel runtime adaptive hardware exploits the dynamic reconfiguration on FPGAs, where hardware blocks are generated, started and terminated. This is similar to software tasks in well established operating system approaches. The hardware counterparts to the software tasks have to be transferred to the reconfigurable hardware via a configuration access port. This port enables the allocation of hardware blocks on the FPGA. Current reconfigurable hardware, like e.g. Xilinx Virtex 5 provide two internal configuration access ports (ICAPs), where only one of these ports can be accessed at one point of time. In e.g. a multiprocessor system on an FPGA, it can happen that multiple instances try to access these ports simultaneously. To prevent conflicts, the access to these ports as well as the hardware resource management needs to be controlled by a special purpose operating system running on an embedded processor. This special purpose operating system, called CAP-OS (Configuration Access Port-Operating System), which will be presented in this paper, supports the clients using the configuration port with the service of priority-based access scheduling, hardware task mapping and resource management.© 2010 IEEE.

关键词： Field programmable gate arrays (FPGA)

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2010 1st international Conference on parallel, distributed and Grid Computing, PDGC - 2010

2010 1st International Conference on Parallel, Distributed a...

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2010 1st international Conference on parallel, distributed and Grid Computing, PDGC - 2010

ISBN: (纸本)9781424476725

The proceedings contain 68 papers. The topics discussed include: optimizing resources in real-time scheduling for fault tolerant processors;grid based real time collaborative system;scheduling tasks in mobile grid environment using mobility based resource prediction;an efficient negotiation based algorithm for resources advanced reservation using hill climbing in grid computing system;optimized grid scheduling using two level decision algorithm (TLDA);scalable link analysis algorithm for a distributed memory environment;a scalable parallel wavelet transform based finite element solver;query slicing with pipeline processing: an effective approach towards improving application performance in a multicore environment;several approaches to parallel computing in the Boolean domain;an efficient key management scheme for mobile agents in distributed networks;and a fast genetic algorithm based static heuristic for scheduling independent tasks on heterogeneous systems.

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On performance and energy management in High Performance Computing systems

On performance and energy management in High Performance Com...

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international workshop on scheduling and resource management for parallel and distributed systems

作者： Evans, Jeffrey J. Electrical and Computer Engineering Technology Purdue University West Lafayette IN United States

ISBN: (纸本)9780769541570

Large-scale High Performance Computing (HPC) systems continue to be designed and constructed to extend performance beyond Petascales using monolithic, cluster, and distributed architectures and emerging multi-core Central Processing Unit (CPU) technologies. As these machines grow so too does the size and variety of applications that run on them. Yet power management and interconnection performance are of great and mounting concern, and to date, the understanding of HPC subsystem interactions and their relationships to power efficiency remains less than desirable. Furthermore, Executive Order 13423 was issued in January of 2007 in an effort to ensure that Federal agencies operate in an environmentally, economically, and fiscally sound manner. It mandates a 30% reduction in energy intensity (MBTUs per square foot) of government facilities in the FY06-15 timeframe using FY03 as a baseline. Two major drawbacks hinder their ability to sustain consistent run time and energy efficient performance: (1) major subsystems interact with each other, often at the expense of unpredictable application run time and energy consumption, and (2) increased power density of these machines complicates the space, power, and cooling problem, resulting in partial or full system down time, further exacerbating run time unpredictability. We believe that one fundamental reason for the above limitations is the operational isolation of loosely coupled subsystems. While the development of subsystems in isolation has been the dominant model for decades, it is inherently unsuitable for ensuring consistent and sustainable systemic performance. We propose that the collection of HPC sub-systems, including the set of running applications must be collaborative in nature, and as such the HPC systems full potential is limited by subsystem isolation and autonomous actions to improve their individual subsystem performance. This paper describes an approach for using "Application-Level Behavioral Attribute Dri

关键词： Program processors

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Improving the effectiveness of context-based prefetching with multi-order analysis

Improving the effectiveness of context-based prefetching wit...

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international workshop on scheduling and resource management for parallel and distributed systems

作者： Chen, Yong Zhu, Huaiyu Jin, Hui Sun, Xian-He Computer Science and Mathematics Division Oak Ridge National Laboratory Oak Ridge TN United States Department of Computer Science Illinois Institute of Technology Chicago IL United States

ISBN: (纸本)9780769541570

Data prefetching is an effective way to accelerate data access in high-end computing systems and to bridge the increasing performance gap between processor and memory. In recent years, the contextbased data prefetching has received intensive attention because of its general applicability. In this study, we provide a preliminary analysis of the impact of orders on the effectiveness of the context-based prefetching. Motivated by the observations from the analytical results, we propose a new context-based prefetching method named Multi-Order Context-based (MOC) prefetching to adopt multi-order context analysis to increase the context-based prefetching effectiveness. We have carried out simulation testing with the SPECCPU2006 benchmarks via an enhanced CMP$im simulator. The simulation results show that the proposed MOC prefetching method outperforms the existing single-order prefetching and reduces the data-access latency effectively. © 2010 IEEE.

关键词： CMP$im simulator context-based prefetching context-based prefetching method data prefetching data prefetching data-access latency high-end computing high-end computing systems information retrieval memory access performance multiorder analysis multiorder context-based prefetching simulation testing single-order prefetching storage management

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Smartphone evolution and reuse: Establishing a more sustainable model

Smartphone evolution and reuse: Establishing a more sustaina...

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international workshop on scheduling and resource management for parallel and distributed systems

作者： Li, Xun Ortiz, Pablo J. Browne, Jeffrey Franklin, Diana Oliver, John Y. Geyerz, Roland Zhou, Yuanyuan Chong, Frederic T. Department of Computer Science University of California Santa Barbara United States Department of Computer Science and Engineering University of California San Diego United States Department of Electrical Engineering Cal Poly San Luis Obispo United States Donald Bren School of Environmental Science and Management University of California Santa Barbara United States

ISBN: (纸本)9780769541570

The dark side of Moore's Law is our society's insatiable need to constantly upgrade our computing devices. The high cost in manufacturing energy, materials and disposal is more worrisome the increasing number of smartphones. Repurposing smartphones for educational purpose is a promising idea and shown success in recent years. Our previous work has shown that although different components in smartphones degrade from use, their functionalities, available resources and power supplies are still able to satisfy the requirement of educational applications. In this study, we demonstrate the potential benefits of reusing smartphones by analyzing their manufacturing and life-time energy. The key challenge is the design of software that can adapt to extreme heterogeneity of devices. We also characterize different types of heterogeneities among different generations of smartphones from HTC and Apple, including processing capability, storage resource and various features. We propose insights to aid establishing a sustainable model of designing mobile applications for phone reuse. © 2010 IEEE.

关键词： Smartphones

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Optimizing service level agreements for autonomic cloud bursting schedulers

Optimizing service level agreements for autonomic cloud burs...

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international workshop on scheduling and resource management for parallel and distributed systems

作者： Kailasam, Sriram Gnanasambandam, Nathan Dharanipragada, Janakiram Sharma, Naveen Distributed and Object Systems Lab Dept. of Comp. Sci. and Engg. IIT Madras Chennai 600036 India Xerox Research Center Webster Xerox Corporation Webster NY 14580 United States

ISBN: (纸本)9780769541570

The practice of computing across two or more data centers separated by the Internet is growing in popularity due to an explosion in scalable computing demands and payas- you-go schemes offered on the cloud. While cloud-bursting is addressing this process of scaling up and down across data centers (i.e. between private and public clouds), offering service level guarantees, is a challenge for inter-cloud computation, particularly for best-effort traffic and large files. The parallel workload we address is real-time and involves inter-cloud processing and analysis of images and documents. In our production printing domain, dedicated processing/network resources are cost-prohibitive. Further, the problem is exacerbated by data intensive computing - we encounter huge file sizes atypical of intercloud parallel processing. To address these problems we propose three flavors of autonomic cloud-bursting schedulers that offer probabilistic guarantees on service levels required by customers (such as speed-up and queue sequence preservation) by adapting to changing workload characteristics, variation in bandwidth and available resources. In particular, these opportunistic schedulers use a quadratic response surface model for processing time in concert with a time-of-day dependent bandwidth predictor to increase the throughput and utilization while simultaneously reducing out-of-sequence completions for a document processing workload. © 2010 IEEE.

关键词： Bandwidth

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A distributed and Energy efficient algorithm for data collection in sensor networks

A Distributed and Energy efficient algorithm for data collec...

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international workshop on scheduling and resource management for parallel and distributed systems

作者： Sharafkandi, Sarah Du, David H.C. Razavi, Alireza Department of Computer Science and Engineering University of Minnesota Twin cities MN United States

ISBN: (纸本)9780769541570

In wireless sensor networks, collection of raw sensor data at a base station provides the flexibility to perform offline detailed analysis on the data which may not be possible with innetwork data aggregation. However, lossless data collection consumes considerable amount of energy for communication while sensors usually have limited energy. In this paper, we propose a distributed and Energy efficient algorithm for Collection of Raw data in sensor networks called DECOR. DECOR exploits spatial correlation to reduce the communication energy in sensor networks with highly correlated data. In our approach, at each neighborhood, one sensor shares its raw data as a reference with the rest of sensors without any suppression or compression. Other sensors use this reference data to compress their observations by representing them in the forms of mutual differences. In a highly correlated network, transmission of reference data consumes significantly more energy than transmission of compressed data. Thus, we first attempt to minimize the number of reference transmissions. Then, we try to minimize the size of mutual differences. We derive analytical lower bounds for both these phases and based on our theoretical results, we propose a twostep distributed data collection algorithm which reduces the communication energy significantly compared to existing methods. In addition, we modify our algorithm for lossy communication channels and we evaluate its performance through simulation. © 2010 IEEE.

关键词： Wireless sensor networks

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