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International Conference on Next Generation Intelligent Systems (ICNGIS)

作者： Priyanka Gupta Kiranbir Kaur Department of computer engineering &technology Guru Nanak Dev University Amritsar India

ISBN: (纸本)9781509008711

Multi-core systems are built on a number of processors and have their own memories. Multi-core processing is like parallel processing because it makes a number of tasks to run at the same time and it enhances the energy efficiency and performance of jobs. The review has shown that if fuzzy rules are combined with multi core computing then power consumption of multi core processors can be further balanced and performance of multi cores can be further increased. Therefore this work has proposed a fuzzy based map reduce technique for multi-core systems. The use of triangular membership function has reduced the potential overheads of Map-reduce technique. Thus proposed technique has quite significant improvement over available techniques.

关键词： Multicore processing Servers scheduling Fuzzy logic Program processors Google scheduling algorithms

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Serving More GPU Jobs, with Low Penalty, Using Remote GPU Execution and Migration

Serving More GPU Jobs, with Low Penalty, Using Remote GPU Ex...

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IEEE International Conference on Cluster Computing

作者： Pak Markthub Akihiro Nomura Satoshi Matsuoka Tokyo Institute of Technology Tokyo Japan

ISBN: (纸本)9781509036547

Remote GPU execution has been proven to increase GPU occupancy and reduce job waiting time in multi-GPU batch-queue systems, by allowing jobs to utilize remote GPUs when there are not enough unoccupied local GPUs available. However, for GPU communication intensive applications, remote GPU communication overhead may account for more than 70% of the applications' execution times. The need for using a remote GPU exists when there are not enough local GPUs available on a node assigned to the job, but a local GPU could become available afterward. We propose mrCUDA, a middleware for migrating execution on a remote GPU to a local GPU on-demand. Our evaluation shows that for long-running jobs mrCUDA overhead accounts for less than 1% of their total execution times. In addition, by applying mrCUDA to the first-come-first-serve (FCFS) job scheduling algorithm, we could reduce job lifetimes (waiting + execution times) as much as 30% on average without changing the scheduling policy.

关键词： Graphics processing units Mathematical model Middleware scheduling algorithms Runtime Bandwidth Libraries

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MTS2: Many task scheduling simulator 29

MTS2: Many task scheduling simulator

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29th European Conference on Modelling and Simulation, ECMS 2015

作者： Stratulat, Adrian Oncioiu, Raluca Pop, Florin Dobre, Ciprian Computer Science Department Faculty of Automatic Control and Computers University Politehnica of Bucharest Romania

ISBN: (纸本)9780993244001

The Many Task Computing paradigm was first introduced by loan Raicu and could be described shortly as solving a large number of tasks with short time executions (i.e. seconds to minutes long) that are data intensive. We propose MTS2: Many Task scheduling Simulator that can be used for a broad range of simulations-after each simulation one can visualize the results. The purpose of MTS2 framework is to simulate events that happen inside a cluster in order to experimentally check or validate various classes of scheduling algorithms. Our event-based simulator provides the building blocks that can be used to implement mathematical models for simulations and it is designed to be extensible, fast and scalable. For the purpose of scheduling algorithm evaluation, the performance is critical: we will study the asymptotic behaviour of some scheduling algorithms under extreme conditions. We will show that MTS2 can be used in various scheduling algorithms and performs better than SimMatrix on a quad core machine, regarding the time per task: 7 microseconds compared to 100 microseconds for simulations with one node and less than 0.5 microseconds with MTS2 for simulations with more than 64 nodes. © ECMS Valen M. Mladenov, Petia Georgieva, Grisha Spasov, Galidiya Petrova (Editors).

关键词： scheduling algorithms

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On optimization of R&D project selection and scheduling 16

On optimization of R&D project selection and scheduling

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16th IFAC Workshop on Control Applications of Optimization, CAO 2015

作者： Latipova, Alina T. Southern Ural State University Chelyabinsk Russia

There is discussed the multi-period problem of project selection and scheduling for research and development (R&D) projects. The problem is a NP-hard RCPSP problem with discrete time periods (weeks), available budget constraints, deadlines, interruption of stages and dynamic change of initial data. Due to this peculiarities and the computational complexity, splitting the problem into series of subproblems for each period is proposed. These subproblems can be solved using GPU programming. © 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： scheduling algorithms

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SLA-based profit optimization for resource management of big data analytics-as-a-service platforms in cloud computing environments

SLA-based profit optimization for resource management of big...

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IEEE International Conference on Big Data

作者： Yali Zhao Rodrigo N. Calheiros James Bailey Richard Sinnott The University of Melbourne Australia Westem Sydney University Australia

ISBN: (纸本)9781467390064

The value that can be extracted from big data greatly motivates organizations to explore data analytics technologies for better decision making and problem solving in a wide range of application domains. Cloud computing greatly eases and benefits big data analytics by offering on-demand and scalable computing infrastructures, platforms, and applications as services. Big data Analytics-as-a-Service (AaaS) platforms aim to deliver data analytics as consumable services in cloud computing environments in a pay as you go model with Service Level Agreement (SLA) guarantees. Resource scheduling for AaaS platforms is significant as big data analytics requires large-scale computing, which can consume huge amounts of resources and incur high resource costs. Our research focuses on proposing automatic and scalable resource scheduling algorithms to maximize the profits for AaaS platforms while delivering AaaS services to users with SLA guarantees on budgets and deadlines to allow timely responses with controllable costs. In this paper, we model and formulate the profit optimization resource scheduling problem and propose an optimization scheduling algorithm that maximizes profits for AaaS platforms and guarantees SLAs for query requests. Experimental evaluations show that the profit optimization scheduling algorithm performs significantly better in cost saving and profit enhancement compared to the state-of-the-art scheduling algorithms.

关键词： Big data Optimization Cloud computing Dynamic scheduling scheduling algorithms Time factors

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Fault detection and correction scheme using RC4 stream cipher

Fault detection and correction scheme using RC4 stream ciphe...

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International Conference on Communications and Signal Processing

作者： S. Kiruba A. Alfred Kirubaraj Applied Electronics Karunya University Coimbatore Tamilnadu India Karunya Institute of Technology and Sciences Coimbatore Tamil Nadu IN

ISBN: (纸本)9781467385497

Cryptography is a method of sending the data to the receiver in a secured manner. This method is used for transferring secured data in various fields like medical, research, hospitals, industrial sites, military applications etc. A Cryptographic attack exists, when the security of cryptosystem gets collapsed. In order to protect the cryptosystem from attack, an attack tolerant method is required. In this paper we have proposed a method to have attack tolerant algorithm by error detection and correction method. The attack tolerant method uses modified RC4 Stream Cipher. The modified RC4 Stream Cipher generates secret keys for encryption with the plain text to form Cipher text. Also, we use modified Matrix code algorithm for error correction in the secret keys generated by the modified RC4 Stream Cipher algorithm. The modified Matrix code algorithm can correct multiple errors in the secret keys generated. Thus the designed attack tolerant algorithm provides robustness to the corruption of secret data in communication standard and protocols.

关键词： Algorithm design and analysis Ciphers Error correction codes scheduling algorithms Signal processing algorithms

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Task Ranking and Allocation Heuristics for Efficient Workflow Schedules

Task Ranking and Allocation Heuristics for Efficient Workflo...

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International Computer Symposium (ICS)

作者： Kuo-Chan Huang Meng-Han Tsai Department of Computer Science National Taichung University of Education Taichung Taiwan

ISBN: (纸本)9781509034390

Task ranking and allocation are two major steps in list-based workflow scheduling. This paper explores various possibilities, evaluates recent approaches in the literature, and proposes several new task ranking and allocation heuristics. A series of simulation experiments have been conducted to evaluate the proposed heuristics. Experimental results indicate that effectiveness of task ranking and allocation heuristics largely depends on the characteristics of workflows to be scheduled, and our new scheduling heuristics can outperform previous methods when dealing with workflows of high CCR (Communication-to-Computation Ratio) values.

关键词： Schedules Resource management scheduling algorithms scheduling Computational complexity Computer science

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Computational Complexity and Speedup Factors Analyses for Self-Suspending Tasks

Computational Complexity and Speedup Factors Analyses for Se...

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Real-Time Systems Symposium (RTSS)

作者： Jian-Jia Chen Department of Informatics TU Dortmund University Germany

In computing systems, an execution entity (job/process/task) may suspend itself when it has to wait for some activities to continue/finish its execution. For real-time embedded systems, such self-suspending behavior has been shown to cause substantial performance/schedulability degradation in the literature. There are two commonly adopted self-suspending sporadic task models in real-time systems: 1) dynamic self-suspension and 2) segmented self-suspension sporadic task models. A dynamic self-suspending sporadic task is specified with an upper bound on the maximum suspension time for a job (task instance), which allows a job to dynamically suspend itself as long as the suspension upper bound is not violated. By contrast, a segmented self-suspending sporadic task has a predefined execution and suspension pattern in an interleaving *** though some seemingly positive results have been reported for self-suspending task systems, the computational complexity and the theoretical quality (with respect to speedup factors) of fixed-priority preemptive scheduling have not been reported. This paper proves that the schedulability analysis for fixed-priority preemptive scheduling even with only one segmented self-suspending task as the lowest-priority task is coNP-hard in the strong sense. For dynamic self-suspending task systems, we show that the speedup factor for any fixed-priority preemptive scheduling, compared to the optimal schedules, is not bounded by a constant or by the number of tasks, if the suspension time cannot be reduced by speeding up. Such a statement of unbounded speedup factors can also be proved for earliest-deadline-first (EDF), least-laxity-first (LLF), and earliest-deadline-zero-laxity (EDZL) scheduling algorithms. However, if the suspension time can be reduced by speeding up coherently or the suspension time of each task is not comparable with (i.e., sufficiently smaller than) its relative deadline, then we successfully show that rate-monotonic sch

关键词： Suspensions Optimal scheduling Dynamic scheduling scheduling algorithms Computational modeling Schedules

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Sensor management in real time and a camera control application for air vehicles

Sensor management in real time and a camera control applicat...

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IEEE Conference on Aerospace

作者： João B. D. Cabrera Philip Haney Patrick Carney Piro Lera Christopher Moss James Metzler BAE Systems MA Rome Research Site Rome Air Force Research Laboratory NY

Camera systems are increasingly utilized in Intelligence, Surveillance and Reconnaissance (ISR) missions on manned and unmanned aircraft. For manned missions, the automatic control of the camera field of view and orientation through pan-tilt-zoom (PTZ) commands frees the pilot to perform higher cognitive functions. For unmanned missions, automatic PTZ commands enable higher degrees of autonomy. This paper addresses the problem of controlling the field of view and orientation of cameras mounted on air vehicles so that the resulting images of commanded areas of interest (AOIs) have specified ground sampling distances (GSDs). The problem is complicated by several factors: First, while the instantaneous positions of the vehicles are assumed to be known, their routes, including their altitude profiles, are not known in advance, which precludes preplanning. Second, the sizes of the AOIs are arbitrary, implying that a single look of the camera may not be sufficient to cover them. Third, the slew times of the cameras may be too slow, and the cameras may not operate while PTZ parameters are changing. Finally, given an AOI, the time intervals when the desired GSDs are achievable varies for different cameras. In the paper, we first show that successful collection of an AOI image (i.e. collection with a prescribed GSD) is only possible if the aircraft lies inside a spherical cap depending on the position of the AOI, and the desired GSD. Given a stream of requested AOIs, with corresponding GSDs and values characterizing their importance to a user, we then develop algorithms to service the most valuable ensemble of requests, while satisfying the requested GSDs. Three algorithms are developed: (1) a scheduling algorithm, for deciding which request to service at a given instant of time, (2) an admission control algorithm, enabling a graceful degradation in case of system overload (more requests than available timeline) and (3) an algorithm for deciding which of the platforms (air v

关键词： Cameras Vehicles Real-time systems Mathematical model Computational modeling scheduling algorithms Admission control

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A Distributed Maximal Link Scheduler for Multi Tx/Rx Wireless Mesh Networks

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2015年第1期14卷 520-531页

作者： Wang, He Chin, Kwan-Wu Soh, Sieteng Raad, Raad Univ Wollongong Sch Elect Comp & Telecommun Engn Wollongong NSW 2522 Australia Curtin Univ Technol Dept Comp Bentley WA 6102 Australia

The capacity of Wireless Mesh Networks (WMNs) has significantly increased with the recent addition of multiple transmit (Tx) and receive (Rx) (MTR) capability or smart antennas. This increase however is predicated on an effective link scheduler. The aim of any scheduler is to derive a superframe comprising the smallest number of slots that affords each link one or more transmission opportunities. In particular, the scheduler is required to solve an instance of the NP-complete, MAX-CUT problem, in each time slot. To this end, there are a number of centralized schedulers, but only a handful of distributed schedulers. However, each of these distributed schedulers has its own drawbacks;either they do not guarantee maximal activated links or do not guarantee all links are activated. Henceforth, in this paper, we add to the state-of-the-art by proposing a novel distributed scheduler, called Algo-d, which approximates the MAX-CUT problem in a distributed manner using only local information. In fact, this is the first distributed solution for MAX-CUT problem. Through theoretical analysis and simulation, we show that Algo-d achieves the following performance: 1) Algo-d schedules on average 12% fewer and 46.5% more links in each time slot than two centralized algorithms, and 2) Algo-d schedules 28% more links than ROMA and 270% more links than JazzyMAC;both state-of-the-art distributed schedulers for MTR WMNs.

关键词： Distributed algorithms scheduling algorithms time division multiplexing wireless mesh networks

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