Browsing by Author "Shah, Nazaraf"

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Exception diagnosis for agent-oriented services
(2006)
Shah, Nazaraf
;
Chi-Chun Lo
;
Chun-Lung Huang
;
Kuo-Ming Chao
;
Godwin, Nick
Agent oriented architectures and service oriented architectures (SOA) have many features in common such as loose coupling and provision and consumption of services. Software agent systems have been used in many commercial applications due to their attractive attributes such as autonomy, flexibility and; a rich and complex set of interaction protocols. Agents in such systems provide and consume services on behalf of their owners. These systems are prone to various kinds of runtime exceptions due to the dynamic nature of open environments and the different programming models involved in the provision of a particular service. Diagnosis of underlying causes of these exceptions is critical for the successful and reliable operation of agent oriented services. This paper presents and discusses a sentinel agent based approach for diagnosing the underlying causes of runtime exception for agent-oriented services.
INTELLIGENT HOUSEHOLD ENERGY MANAGEMENT RECOMENDER SYSTEM
(2010)
Shah, Nazaraf
;
Tsai, Chen-Fang
;
Chao, Kuo-Ming
;
Lo, Chi-Chun
;
資訊管理與財務金融系註：原資管所+財金所
Recent years have seen extensive research in home energy management systems to address the issues of rising energy prices and global warming. The focus of these research efforts is to create a smart environment which integrates household energy consumption appliances and devices into a home area network. This home area network collects energy consumption data constantly in real time in order support data analysis, decision making and enable the householders to have a transparent view of their energy consumption. The ultimate goal is to use Information and Communication Technologies (ICT) to help householders to reduce their energy consumption while maintaining level of their comfort. The proposed recommender system is a subsystem of an integrated energy management system which involves innovative technologies to monitor and analyse energy consumption of households in real time and enables them to have more detailed picture of their energy consumption and also provide them advice on efficient energy usage. The recommender system is supported by the monitoring system which consists of a network of energy consumption monitoring sensors. These sensors read energy consumption of household appliances in real time and send the data to a central server for storage, analysis and query purposes. In this paper we present a recommender system which provides advice to householders proactively by taking in account their energy consumption patterns and also provides answers to their queries regarding efficient use of energy.