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Dynamic forecasting and adaptation for demand optimization in the Smart Grid

Dynamic forecasting and adaptation for demand optimization i...

引用

International Workshop on software engineering for the Smart Grid (SE4SG)

作者： Eamonn O'Toole Siobhán Clarke Lero-The Irish Software Engineering Research Centre Distributed Systems Group School of Computer Science and Statistics Trinity College Dublin Ireland

The daily peaks and valleys in energy demand create inefficiencies and expense in the operation of the electricity grid. Valley periods force utilities to curtail renewable energy sources such as wind as their unpredictable nature makes it difficult to maintain line frequency across the network within target bounds. Peak periods require additional generators that remain dormant during other periods. Smoothing this demand cycle is one of the fundamental challenges of the Smart Grid, requiring flexibility and coordination between actors throughout the Grid. This paper describes the Smart Grid as a multi-layered system and proposes a cross-layered dynamic adaptation approach to facilitate this flexibility and coordination. This method uses a hierarchical taxonomy to identify appropriate adaptation actions in response to identified mismatches, supported by a run-time predictive statistical framework to predict mismatches, enabling timely adaptations to be triggered.

关键词： Smart grids Generators Electricity Production Renewable energy resources Optimization Wind energy

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KB-CB-N classification: Towards unsupervised approach for supervised learning

KB-CB-N classification: Towards unsupervised approach for su...

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IEEE Symposium on Computational Intelligence and Data Mining (CIDM)

作者： Zahraa Said Abdallah Mohamed Medhat Gaber Centre of Distributed Systems and Software Engineering Monash University Caulfield VIC Australia School of Computing University of Portsmouth Portsmouth Hampshire UK

Data classification has attracted considerable research attention in the field of computational statistics and data mining due to its wide range of applications. K Best Cluster Based Neighbour (KB-CB-N) is our novel classification technique based on the integration of three different similarity measures for cluster based classification. The basic principle is to apply unsupervised learning on the instances of each class in the dataset and then use the output as an input for the classification algorithm to find the K best neighbours of clusters from the density, gravity and distance perspectives. Clustering is applied as an initial step within each class to find the inherent in-class grouping in the dataset. Different data clustering techniques use different similarity measures. Each measure has its own strength and weakness. Thus, combining the three measures can benefit from the strength of each one and eliminate encountered problems of using an individual measure. Extensive experimental results using eight real datasets have evidenced that our new technique typically shows improved or equivalent performance over other existing state-of-the-art classification methods.

关键词： Clustering algorithms Gravity Training Prediction algorithms Density measurement Classification algorithms Euclidean distance

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StreamAR: Incremental and Active Learning with Evolving Sensory Data for Activity Recognition

StreamAR: Incremental and Active Learning with Evolving Sens...

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International Conference on Tools with Artificial Intelligence

作者： Zahraa Said Abdallah Mohamed Medhat Gaber Bala Srinivasan Shonali Krishnaswamy Centre for Distributed Systems and Software Engineering Monash University School of Computing University of Portsmouth Institute for Infocomm Research (I2R)

ISBN: (纸本)9781479902279

Activity recognition focuses on inferring current user activities by leveraging sensory data available on today's sensor rich environment. Supervised learning has been applied pervasively for activity recognition. Typical activity recognition techniques process sensory data based on point-by-point approaches. In this paper, we propose a novel cluster-based classification for activity recognition systems, termed StreamAR. The system incorporates incremental and active learning for mining user activities in data streams. The novel approach processes activities as clusters to build a robust classification framework. StreamAR integrates supervised, unsupervised and active learning and applies hybrid similarity measures technique for recognising activities. Extensive experimental results using real activity recognition datasets have evidenced that our new approach shows improved performance over other existing state-of-the-art learning methods.

关键词： Experiential Learning Activity recognition Incremental Sensation

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Meta object approach to database schema integration

Meta object approach to database schema integration

引用

International Symposium on distributed Objects and Applications

作者： J. Tan A. Zaslavsky A. Bond School of Computer Science and Software Engineering Monash University VIC Australia Distributed Systems Technology Centre University of Queensland Brisbane QLD Australia

Database schema integration is significant not only in building multidatabase systems but also in data warehousing. Meta data, which define schemas, are normally involved in the surrounding issues. And while many of these issues have been addressed in the past, unresolved issues remain. The authors present an approach that not only uses metadata but also uses meta-meta information to make schema integration more possible. Our solution requires a meta object facility that serves not only as a repository but also as a more feasible means of managing meta data. We also advocate the use of such a facility as part of an object oriented middleware environment that provides an open interface standard and several useful services in distributed object management.

关键词： software engineering Computer science Australia Bonding Object oriented databases Database systems distributed databases Warehousing Middleware Environmental management

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Congestion Avoidance Algorithm Using Extended Kalman Filter

Congestion Avoidance Algorithm Using Extended Kalman Filter

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International Conference on Convergence Information Technology

作者： Sung-Soo Kim Yong-Bin Kang Digital Content Research Division Electronics and Telecommunications Research Institute South Korea Centre for Distributed Systems and Software Engineering Monash University Australia

ISBN: (纸本)9781424431779

The prediction of traffic congestion is quite an important issue in vehicle navigation to smoothly control traffic flow, and improve the quality of driver's convenience. However, it is not easy to make accurate predictions since traffic change is highly nonlinear and complex dynamic process. First, we present a new traffic prediction algorithm on the basis of the combined knowledge of both the historical and the real-time traffic information. Based on this traffic prediction result, this paper presents a novel routing technique capable of providing intelligent route services completely adequate to dynamic route guidance systems. In our experiments, we have performed the proposed algorithms on two road networks; one of the complex urban areas and the city. Overall, the results of traffic prediction indicate that our prediction algorithms provide more accurate (nearly 90%) traffic information compared with previous traffic prediction solutions. In addition, our implementation of route determination provides the adaptive routes for traffic conditions, as well as scalable routing services for users' preferences.

关键词： Telecommunication traffic Traffic control Vehicle dynamics Navigation Prediction algorithms Routing Roads Vehicles Prediction methods Shortest path problem

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Mobile Middleware for Wireless Body Area Network

Mobile Middleware for Wireless Body Area Network

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Xiang Chen Agustinus Borgy Waluyo Isaac Pek Wee-Soon Yeoh Institute of Infocomm Research I R Agency for Science Technology and Research Singapore Centre of Distributed Systems and Software Engineering Monash University Australia

This paper presents a flexible, efficient and lightweight Wireless Body Area Network (WBAN) Middleware. The Middleware is developed to bridge the communication between mobile device as a gateway and the sensor nodes, and therefore it shields the underlying sensor and OS/protocol stack away from the WBAN application layer. The middleware is coded in the form of lightweight dynamic link library, which allows the application developer to simply incorporate the middleware resource dynamic link library into their application and call the required functions (i.e. data acquisition, resource management and configurations). A showcase of the middleware deployment is exhibited at the end of the paper.

关键词： Middleware Mobile communication Wireless communication Wireless sensor networks Accelerometers Logic gates Electrocardiography

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Soilse: A decentralized approach to optimization of fluctuating urban traffic using Reinforcement Learning

Soilse: A decentralized approach to optimization of fluctuat...

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International Conference on Intelligent Transportation

作者： As'ad Salkham Vinny Cahill Distributed Systems Group-School of Computer Science and Statistics Trinity College Dublin Ireland Member of Lero - The Irish Software Engineering Research Centre

Increasing traffic congestion is a major problem in urban areas, which incurs heavy economic and environmental costs in both developing and developed countries. Efficient urban traffic control (UTC) can help reduce traffic congestion. However, the increasing volume and the dynamic nature of urban traffic pose particular challenges to UTC. Reinforcement Learning (RL) has been shown to be a promising approach to efficient UTC. However, most existing work on RL-based UTC does not adequately address the fluctuating nature of urban traffic. This paper presents Soilse 1 , a decentralized RL-based UTC optimization scheme that includes a nonparametric pattern change detection mechanism to identify local traffic pattern changes that adversely affect an RL agent's performance. Hence, Soilse is adaptive as agents learn to optimize for different traffic patterns and responsive as agents can detect genuine traffic pattern changes and trigger relearning. We compare the performance of Soilse to two baselines, a fixed-time approach and a saturation balancing algorithm that emulates SCATS, a well-known UTC system. The comparison was performed based on a simulation of traffic in Dublin's inner city centre. Results from using our scheme show an approximate 35%-43% and 40%-54% better performance in terms of average vehicle waiting time and average number of vehicle stops respectively against the best baseline performance in our simulation.

关键词： Optimization Switches

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Knowledge Discovery from Sensor Data 1

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丛书名： Lecture Notes in Computer Science

1000年

作者： Mohamed Medhat Gaber Ranga Raju Vatsavai Olufemi A. Omitaomu Auroop R. Ganguly João Gama Nitesh V. Chawla

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Component-Based software engineering 1

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丛书名： Lecture Notes in Computer Science

1000年

作者： Ian Gorton George T. Heineman Ivica Crnković Heinz W. Schmidt Judith A. Stafford Clemens Szyperski Kurt Wallnau

ISBN: (数字)9783540356295

ISBN: (纸本)9783540356288

On behalf of the Organizing Committee I am pleased to present the proceedings of the 2006 Symposium on Component-Based software engineering (CBSE). CBSE is concerned with the development of software-intensive systems from reusable parts (components), the development of reusable parts, and system maintenance and improvement by means of component replacement and customization. CBSE 2006 was the ninth in a series of events that promote a science and technology foundation for achieving predictable quality in software systems through the use of software component technology and its associated software engineering practices. We were fortunate to have a dedicated Program Committee comprising 27 internationally recognized researchers and industrial practitioners. We received 77 submissions and each paper was reviewed by at least three Program Committee members (four for papers with an author on the Program Committee). The entire reviewing process was supported by Microsoft’s CMT technology. In total, 22 submissions were accepted as full papers and 9 submissions were accepted as short papers. This was the first time CBSE was not held as a co-located event at ICSE. Hence special thanks are due to Ivica Crnkovic for hosting the event. We also wish to thank the ACM Special Interest Group on software engineering (SIGSOFT) for their sponsorship of CBSE 2005. The proceedings you now hold were published by Springer and we are grateful for their support. Finally, we must thank the many authors who contributed the high-quality papers contained within these proceedings.

关键词： software engineering/Programming and Operating systems software engineering Programming Techniques Programming Languages, Compilers, Interpreters Logics and Meanings of Programs Computer Communication Networks

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Grid Economics and Business Models 1

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丛书名： Lecture Notes in Computer Science

1000年

作者： Jörn Altmann Rajkumar Buyya Omer F. Rana

ISBN: (数字)9783642038648

ISBN: (纸本)9783642038631

GECON - Grid Economics and Business Models Cloud computing is seen by many people as the natural evolution of Grid computing concepts. Both, for instance, rely on the use of service-based approaches for pro- sioning compute and data resources. The importance of understanding business m- els and the economics of distributed computing systems and services has generally remained unchanged in the move to Cloud computing. This understanding is nec- sary in order to build sustainable e-infrastructure and businesses around this paradigm of sharing Cloud services. Currently, only a handful of companies have created s- cessful businesses around Cloud services. Among these, Amazon and Salesforce (with their offerings of Elastic Compute Cloud and force. com among other offerings) are the most prominent. Both companies understand how to charge for their services and how to enable commercial transactions on them. However, whether a wide-spread adoption of Cloud services will occur has to seen. One key enabler remains the ability to support suitable business models and charging schemes that appeal to users o- sourcing (part of) their internal business functions. The topics that have been addressed by the authors of accepted papers reflect the above-described situation and the need for a better understanding of Grid economics. The topics range from market mechanisms for trading computing resources, capacity planning, tools for modeling economic aspects of service-oriented systems, archit- tures for handling service level agreements, to models for economically efficient resource allocation.

关键词： Computer Communication Networks e-Commerce/e-business Information systems and Communication Service Computer Appl. in Administrative Data Processing Simulation and Modeling Special Purpose and Application-Based systems

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