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International Conference on Tools for Artificial Intelligence (ICTAI)

作者： F. Dehne A.G. Ferreira A. Rau-Chaplin Center for Parallel and Distributed Computing School of Computer Science Carleton University Ottawa Canada Laboratoire de I'lnformatique du Parallelisme-IMAG Ecole Normale Superieure Lyon France Center for Parallel and Distributed Computing. School of Computer Science Carleton University Ottawa Canada

An efficient branch and bound algorithm for fine-grained hypercube multiprocessors is presented. The method uses a global storage allocation scheme where all processors collectively store all back-up paths such that each processor needs to store only a constant amount of information. At each iteration of the algorithm, all nodes of the current back-up tree may decide whether they need to create new children, be pruned, or remain unchanged. An algorithm that, on the basis of these decisions, updates the current back-up tree and distributes global information in O(log m) steps, where m is the current number of nodes, is described. This method also provides a dynamic allocation mechanism that obtains optimal load balancing. Another important property of the method is that, even if very drastic changes in the current back-up tree occur, the performance of the load balancing mechanism remains constant. The method is currently being implemented on the Connection Machine.< >

关键词： Hypercubes Load management distributed computing computer science Search methods Linear programming Artificial intelligence Operations research High definition video Concurrent computing

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HCW 2020 Keynote Speaker Edge Intelligence Empowering IoT Data Analytics

HCW 2020 Keynote Speaker Edge Intelligence Empowering IoT Da...

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IEEE International Symposium on parallel and distributed Processing Workshops and Phd Forum (IPDPSW)

作者： Albert Y. Zomaya Centre for Distributed & High Performance Computing School of Computer Science University of Sydney Australia

ISBN: (数字)9781728174457

ISBN: (纸本)9781728174570

Along with the many developments in computing and communication technologies and the surge of mobile devices, a brand new paradigm, Edge computing (EC), has gained a lot of momentum in recent times. In parallel, Artificial Intelligence (AI) applications have been thriving fuelled by breakthroughs in deep learning and the emergence of new hardware architectures. Billions of bytes of data, generated at the network edge which is composed of a multitude of heterogeneous devices, put great demands on data processing and structural optimization which led to a genuine demand for the integration of EC and AI leading to what is known today as Edge Intelligence (EI). n this talk, I will discuss how EI is rapidly increasing the convergence between humans, things, and Al. I will briefly review some of our designs for the development of EI and present how to rethink decisions that are made by "black box" Al approaches when implementing analytics on data generated by the Internet of Things (IoT). This does not provide a clear explanation of how a method works and why it behaves in a certain way. Lack of explanation might not be an issue for those IoT applications which have less privacy constraints, but it can be a barrier to the adoption of such systems in highly regulated domains. I will argue that explainable Edge Al is the key to social acceptance of an even wider deployment of IoT applications.

关键词： Artificial intelligence High performance computing computer science Internet of Things distributed processing Conferences Data analysis

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Domain Generalization for Time-Series Forecasting via Extended Domain-Invariant Representations

Domain Generalization for Time-Series Forecasting via Extend...

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Artificial Intelligence of Things (AIoT), IEEE Annual Congress on

作者： Yunchuan Shi Wei Li Albert Y. Zomaya Centre for Distributed and High Performance Computing School of Computer Science The University of Sydney Australia

ISBN: (数字)9798350392296

ISBN: (纸本)9798350392302

Time-series forecasting is crucial for IoT applications, but generalizing across domains is challenging due to distinct data distributions and dynamics. Most domain generalization methods work well for image processing and classification, but they struggle with time-series forecasting. This is because they solely learn domain-invariant representations of input data, ignoring variations in the output space across domains. This oversight can lead to inaccurate forecasts when outputs in new domains exhibit different distributions or temporal patterns. In this work, we present a new approach to improve the time-series forecasting model generalization by extracting domain-invariant representations from both input and output data. Experiments demonstrate the effectiveness of our approach, achieving significant improvements in forecasting accuracy across multiple test domains. Compared to state-of-the-art methods, our approach delivers up to an 8% increase in accuracy.

关键词： Bridges Accuracy Image processing Time series analysis Predictive models Data models Internet of Things

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distributed Online Resource Scheduling for Mobile Edge Servers

Distributed Online Resource Scheduling for Mobile Edge Serve...

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IEEE International Conference on Edge computing (EDGE)

作者： Ziwen Zhou Tianming Zhao Wei Li Albert Y. Zomaya Centre for Distributed and High Performance Computing School of Computer Science The University of Sydney Australia

ISBN: (纸本)9781665400633

Due to the flexibility and scalability, the increasing number of mobile edge computing applications involves Mobile Edge Servers (MES). MES introduces the new challenge of online resource scheduling to serve different requests under limited energy to offer similar functionalities of the immobile edge servers. The previous studies consider the case of the identical server, which has poor scalability and is hard to apply to real-world applications. This work proposes a novel model named the distributed k-server problem that formulates the MES resource scheduling to address the heterogeneity issues in both servers and requests. We design an algorithm named DWFA based on the efficient network flow-based Work Function Algorithm (WFA) to the classic k-server problem as an immediate solution to the proposed problem. DWFA inher-its the competitiveness of WFA but has high computational complexity. To further increase scalability via the computing power of MES, we parallelise DWFA to design a distributed algorithm named FD-WFA as a distributed execution of DWFA, which significantly reduces the computational complexity and increases the practicality. Extensive simulations have been con-ducted to verify the theoretical results and show the advantages of FD-WFA over the benchmarks.

关键词： Multi-access edge computing Processor scheduling Power supplies Scalability Computational modeling Benchmark testing Servers

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Grid and Cooperative computing - GCC 2004 Workshops 1

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丛书名： Lecture Notes in computer science

1000年

作者： Hai Jin Yi Pan Nong Xiao Jianhua Sun

ISBN: (数字)9783540302070

ISBN: (纸本)9783540235781

Welcome to the proceedings of GCC2004 and the city of Wuhan. Grid computing has become a mainstream research area in computer science and the GCC conference has become one of the premier forums for presentation of new and exciting research in all aspectsofgridandcooperativecomputing. Theprogramcommitteeispleasedtopresent the proceedings of the 3rd International Conference on Grid and Cooperative Comp- ing (GCC2004), which comprises a collection of excellent technical papers, posters, workshops, and keynote speeches. The papers accepted cover a wide range of exciting topics, including resource grid and service grid, information grid and knowledge grid, grid monitoring,managementand organizationtools, grid portal, grid service, Web s- vices and their QoS, service orchestration, grid middleware and toolkits, software glue technologies, grid security, innovative grid applications, advanced resource reservation andscheduling,performanceevaluationandmodeling,computer-supportedcooperative work, P2P computing, automatic computing, and meta-information management. The conference continues to grow and this year a record total of 581 manuscripts (including workshop submissions) were submitted for consideration. Expecting this growth, the size of the program committee was increased from 50 members for GCC 2003 for 70 in GCC 2004. Relevant differences from previous editions of the conf- ence: it is worth mentioning a signi?cant increase in the number of papers submitted by authors from outside China; and the acceptance rate was much lower than for p- vious GCC conferences. From the 427 papers submitted to the main conference, the program committee selected only 96 regular papers for oral presentation and 62 short papers for poster presentation in the program.

关键词： Theory of Computation computer Communication Networks Operating Systems Information Systems Applications (incl. Internet) Information Storage and Retrieval User Interfaces and Human computer Interaction

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Robust task scheduling for volunteer computing systems

Robust task scheduling for volunteer computing systems

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作者： Lee, Young Choon Zomaya, Albert Y. Siegel, Howard Jay Centre for Distributed and High Performance Computing School of Information Technologies University of Sydney Sydney NSW 2006 Australia Department of Electrical and Computer Engineering Department of Computer Science Colorado State University Fort Collins CO 80523-1373 United States

Performance perturbations are a natural phenomenon in volunteer computing systems. Scheduling parallel applications with precedence-constraints is emerging as a new challenge in these systems. In this paper, we propose two novel robust task scheduling heuristics, which identify best task-resource matches in terms of makespan and robustness. Our approach for both heuristics is based on a proactive reallocation (or schedule expansion) scheme enabling output schedules to tolerate a certain degree of performance degradation. Schedules are initially generated by focusing on their makespan. These schedules are scrutinized for possible rescheduling using additional volunteer computing resources to increase their robustness. Specifically, their robustness is improved by maximizing either the total allowable delay time or the minimum relative allowable delay time over all allocated volunteer resources. Allowable delay times may occur due to precedence constraints. In this paper, two proposed heuristics are evaluated with an extensive set of simulations. Based on simulation results, our approach significantly contributes to improving the robustness of the resulting schedules. © 2009 Springer science+Business Media, LLC.

关键词： Resource allocation

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Scientific workflow makespan reduction through cloud augmented Desktop Grids

Scientific workflow makespan reduction through cloud augment...

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2011 3rd IEEE International Conference on Cloud computing Technology and science, CloudCom 2011

作者： Reynolds, Christopher J. Winter, Stephen Terstyanszky, Gabor Z. Kiss, Tamas Greenwell, Pamela Acs, Sandor Kacsuk, Peter Centre for Parallel Computing School of Electronics and Computer Science University of Westminster London United Kingdom Dept. of Biomedical Sciences University of Westminster London United Kingdom MTA SZTAKI Computer and Automation Research Institute Hungarian Academy of Sciences Budapest Hungary

ISBN: (纸本)9780769546223

Scientific workflows are common in biomedical research, particularly for molecular docking simulations such as those used in drug discovery. Such workflows typically involve data distribution between computationally demanding stages which are usually mapped onto large scale compute resources. Volunteer or Desktop Grid (DG) computing can provide such infrastructure but has limitations resulting from the heterogeneous nature of the compute nodes. These constraints mean that reducing the makespan of a given workflow stage submitted to a DG becomes problematic. Late jobs can significantly affect the makespan, often completing long after the bulk of the computation has finished. In this paper we present a system capable of significantly reducing the makespan of a scientific workflow. Our system comprises a DG which is dynamically augmented with an infrastructure as a service (IaaS) Cloud. Using this solution, the Cloud resources are used to process replicated late jobs. Our system comprises a core component termed the scheduler, which implements an algorithm to perform late job detection, Cloud resource management (instantiation and reuse), and job monitoring. We offer a formal definition of this algorithm, whilst we also provide an evaluation of our prototype using a production scientific workflow. © 2011 IEEE.

关键词： Infrastructure as a service (IaaS)

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Grid and Cooperative computing - GCC 2004 1

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丛书名： Lecture Notes in computer science

1000年

作者： Hai Jin Yi Pan Nong Xiao Jianhua Sun

ISBN: (数字)9783540302087

ISBN: (纸本)9783540235644

关键词： Theory of Computation computer Communication Networks Operating Systems Software Engineering Information Systems Applications (incl. Internet) Information Storage and Retrieval

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A general and scalable solution for heterogeneous workflow invocation and nesting

A general and scalable solution for heterogeneous workflow i...

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Workshop on Workflows in Support of Large-Scale science, WORKS

作者： Tamas Kukla Tamas Kiss Gabor Terstyanszky Peter Kacsuk Centre for Parallel Computing School of Informatics University of Westminster London UK Laboratory of the Parallel and Distributed Systems Computer and Automation Research Institute Hungarian Academy of Sciences (ATOMKI) Budapest Hungary

Several widely utilized, grid workflow management systems emerged in the last decade. These systems were developed by different scientific communities for various purposes. Enhancing these systems with the capability of invoking and nesting the workflows of other systems within their native workflows makes these communities to be able to carry out cross-organizational experiments and share non-native workflows. The novel solution described in this paper allows the integration of different workflow engines and makes them accessible for workflow systems in order to achieve this goal. The solution is based on an application repository and submitter, which exposes different workflow engines and executes them using the computational resources of the grid. In contrast with other approaches, our solution is scalable in terms of both number of workflows and amount of data, easily extendable in the sense that the integration of a new workflow engine does not require code re-engineering, and general, since it can be adopted by numerous workflow systems.

关键词： Engines Workflow management software Risk management Petri nets parallel processing Informatics Laboratories Concurrent computing distributed computing Automation

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Non-functional Oriented Dynamic Integration Of distributed Components

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Electronic Notes in Theoretical computer science 2003年第3期68卷 405-418页

作者： Ahmed Saleh George R.R. Justo Stephen C. Winter Centre For Parallel Computing Computing University of Westminster London UK Cap Gemini Ernst & Young London UK Cavendish School of Computer Science University of Westminster London UK

Building distributed systems from scratch is known as one of the most difficult and time consuming process in software engineering. A great deal of progress has been made in the development of middleware and techniques to facilitate the process of distributed systems through integrating reusable components and customizing middleware. However, most of these solutions tend to focus on the functional aspects of the components and how to adapt their behavior according to their needs. Although the non-functional properties of the services are equally important, because of the difficulties in representing and controlling them, they are usually neglected. This paper investigates the problem of distributed systems' non-functional properties and describes a framework that presents a solution to the problem. The framework is based on the idea of defining the non-functional properties of the services at the early stages of the design and incorporating such properties within the architecture to ease the process of managing the system at run time.

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