A novel cloud information agent system with Web service techniques: Example of an energy-saving multi-agent system

Yang, Sheng-Yuan

doi:10.1016/j.eswa.2012.09.025

Cited by 33 publications

(23 citation statements)

References 26 publications

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“…Several other work in the same aspect is been presented by researchers using different techniques like: energy saving based on Web service and ontology techniques in a cloud environment by Yang (2013), gARTMAP; a multi-agent system for building heat management system by Mokhtar & Howe (Mokhtar, et al 2014), and a multi-agent system by Davidsson and Boman to control an office building (Davidsson & Boman, 2005).…”

Section: Literature Reviewmentioning

confidence: 99%

Agent-Based Adaptive Cooling Optimising Systems for Homes in KSA

Malibari¹,

Gamlo²

2017

CIS

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Energy saving has been a global concern since the last few years. Due to the massive growth of population in Saudi Arabia and its extremely hot climate, electricity consumption, and costs are expected to increase every year. This work presents an intelligent and efficient technology to create a balance between the need of energy consumption minimization and standards regarding the comfort of people in Saudi Arabia. Thermal Modelling and Optimization of Cooling Systems have been considered to generate the outcomes of study. The sample size comprised of 10 houses, which have been selected randomly from Royal Commission for Yanbu province. It has been revealed through testing that there is a reduction by 20% in cooling consumption. This reduction reflects in 31% reduction in expected cooling costs without affecting the comfort of householders.

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Section: Literature Reviewmentioning

confidence: 99%

Agent-Based Adaptive Cooling Optimising Systems for Homes in KSA

Malibari¹,

Gamlo²

2017

CIS

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“…Bonanno et al proposed a cloud-based distributed toolbox to optimally manage the energy dispatch from renewable resources utilizing Graphics Processing Unit (GPU) and Wavelet Recurrent Neural Networks (WRNN) predictors [35]. Yang et al implemented cloud-based energy serving a multi-agent system using web service techniques with backend information agents involved [36]. Napoli et al developed a neural-network-driven forecasting setup to manage the power production and dispatch systems of smart grids applying cloud computing [37].…”

Section: Related Workmentioning

confidence: 99%

“…-A cloud-based distributed toolbox to optimally manage the energy dispatch from renewable resources utilizing the GPU and WRNN predictors [35]. -Cloud-based energy serving a multi-agent system using web service techniques with backend information agents involved [36]. -A neural-network-driven forecasting setup to manage the power production and dispatch in a smart grid [37] -A user wants to run their own application over the cloud to process their own data utilizing encrypted computation [47] …”

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confidence: 99%

A Secure, Scalable and Elastic Autonomic Computing Systems Paradigm: Supporting Dynamic Adaptation of Self-* Services from an Autonomic Cloud

2018

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Abstract:Autonomic computing embeds self-management features in software systems using external feedback control loops, i.e., autonomic managers. In existing models of autonomic computing, adaptive behaviors are defined at the design time, autonomic managers are statically configured, and the running system has a fixed set of self-* capabilities. An autonomic computing design should accommodate autonomic capability growth by allowing the dynamic configuration of self-* services, but this causes security and integrity issues. A secure, scalable and elastic autonomic computing system (SSE-ACS) paradigm is proposed to address the runtime inclusion of autonomic managers, ensuring secure communication between autonomic managers and managed resources. Applying the SSE-ACS concept, a layered approach for the dynamic adaptation of self-* services is presented with an online 'Autonomic_Cloud' working as the middleware between Autonomic Managers (offering the self-* services) and Autonomic Computing System (requiring the self-* services). A stock trading and forecasting system is used for simulation purposes. The security impact of the SSE-ACS paradigm is verified by testing possible attack cases over the autonomic computing system with single and multiple autonomic managers running on the same and different machines. The common vulnerability scoring system (CVSS metric) shows a decrease in the vulnerability severity score from high (8.8) for existing ACS to low (3.9) for SSE-ACS. Autonomic managers are introduced into the system at runtime from the Autonomic_Cloud to test the scalability and elasticity. With elastic AMs, the system optimizes the Central Processing Unit (CPU) share resulting in an improved execution time for business logic. For computing systems requiring the continuous support of self-management services, the proposed system achieves a significant improvement in security, scalability, elasticity, autonomic efficiency, and issue resolving time, compared to the state-of-the-art approaches.

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“…DPAWSC is based on the distributed decision making of the autonomous service agents and addresses the distributed nature of Web service composition. From a different perspective, Yang [9] proposed a cloud information agent system with Web service techniques, one of the relevant results of which is the energy-saving multi-agent system.…”

Section: Service Paradigmmentioning

confidence: 99%

Towards Intelligent Distributed Computing: Cell-Oriented Computing

Karawash

Mcheick

Dbouk

2014

Studies in Computational Intelligence

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Distributed computing systems are of huge importance in a number of recently established and future functions in computer science. For example, they are vital to banking applications, communication of electronic systems, air traffic control, manufacturing automation, biomedical operation works, space monitoring systems and robotics information systems. As the nature of computing comes to be increasingly directed towards intelligence and autonomy, intelligent computations will be the key for all future applications. Intelligent distributed computing will become the base for the growth of an innovative generation of intelligent distributed systems. Nowadays, research centres require the development of architectures of intelligent and collaborated systems; these systems must be capable of solving problems by themselves to save processing time and reduce costs. Building an intelligent style of distributed computing that controls the whole distributed system requires communications that must be based on a completely consistent system. The model of the ideal system to be adopted in building an intelligent distributed computing structure is the human body system, specifically the body's cells. As an artificial and virtual simulation of the high degree of intelligence that controls the body's cells, this chapter proposes a Cell-Oriented Computing model as a solution to accomplish the desired Intelligent Distributed Computing system.

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A novel cloud information agent system with Web service techniques: Example of an energy-saving multi-agent system

Cited by 33 publications

References 26 publications

Agent-Based Adaptive Cooling Optimising Systems for Homes in KSA

Agent-Based Adaptive Cooling Optimising Systems for Homes in KSA

A Secure, Scalable and Elastic Autonomic Computing Systems Paradigm: Supporting Dynamic Adaptation of Self-* Services from an Autonomic Cloud

Towards Intelligent Distributed Computing: Cell-Oriented Computing

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