Multi agent system based service architectures for service level agreement in cellular networks

Giri, Nupur; Mundle, Siddharth; Ray, Arpita; Bodhe, S. K.

doi:10.1145/1517303.1517309

Cited by 8 publications

(3 citation statements)

References 6 publications

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“…There is a large body of work focusing on how multiagent systems are used in negotiating the service-level agreements (SLA) [ 6 – 10 ]. Giri et al [ 6 ], Ouelhadj et al [ 7 ], He et al [ 8 ], and Chhetri et al [ 9 ] have all applied multiagent systems to SLA negotiations. Further, SLA negotiations in cloud computing are currently also under investigation [ 10 ].…”

Section: Previous Workmentioning

confidence: 99%

Smart Grid as a Service: A Discussion on Design Issues

Chao

Tsai

Hsiung

et al. 2014

The Scientific World Journal

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Smart grid allows the integration of distributed renewable energy resources into the conventional electricity distribution power grid such that the goals of reduction in power cost and in environment pollution can be met through an intelligent and efficient matching between power generators and power loads. Currently, this rapidly developing infrastructure is not as “smart” as it should be because of the lack of a flexible, scalable, and adaptive structure. As a solution, this work proposes smart grid as a service (SGaaS), which not only allows a smart grid to be composed out of basic services, but also allows power users to choose between different services based on their own requirements. The two important issues of service-level agreements and composition of services are also addressed in this work. Finally, we give the details of how SGaaS can be implemented using a FIPA-compliant JADE multiagent system.

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Section: Previous Workmentioning

confidence: 99%

Smart Grid as a Service: A Discussion on Design Issues

Chao

Tsai

Hsiung

et al. 2014

The Scientific World Journal

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“…Our work proposes two MAS based Service Architectures depending on the degree of distribution of agents and the type of interaction, in Connection Plane: Network Provider Resource Agent (NPRA-based) Centralized Service Architecture and Network Provider Cell Agent (NPCA-based) Distributed Service Architecture. These service architectures use Foundation for Intelligent Physical Agent compliant message 'performatives' [9]. These performatives have been modeled using open source Java Agent DEvelopment framework, JADE 3.1 [10].…”

Section: The Workmentioning

confidence: 99%

Role of Multi Agent System for Qos Guarantee in Cellular Networks

Giri¹

2012

IJDPS

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The paper highlights the benefits of Multi Agent System for maintaining QoS in cellular network by evaluating various multi agent based call admission control strategies for different traffic conditions. It establishes the effect of degree of distribution of agents on system performance by comparing the two service architectures, namely centralized and distributed, for reactivity, responsiveness, utilization of resources, communication overhead, sustainability, scalability, robustness and modifiability. It also establishes the relationship between the social attitude of an agent towards the other agents and fairness of resource distribution in distributed architecture. This evaluation helps in building knowledge for choosing the optimal multi agent based call admission and channel borrowing schemes, along with the most suitable service architecture for the required QoS and traffic conditions.

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“…Giri [10] presents this extended model and proposes two Multi agent System based service architectures, Centralized (NPRA-based) and Distributed (NPCA-based). It also compares Static or Dynamic Call Admission schemes for Agent and Non agent based architectures.…”

Section: Review Of Previous Workmentioning

confidence: 99%

JADE based Multi Agent system for mobile computing for cellular networks

Mundle¹,

Giri²,

Ray³

et al. 2009

Proceedings of the International Conference on Advances in Computing, Communication and Control

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Multi Agent System extends the intelligent agent paradigm to improve upon the conceptual model of designing problems through agent interaction. This interaction could be of the form of collaboration, cooperation or even negotiation through Agent Communication Languages. Our paper models Call Admission Control in Cellular networks as Multi Agent resource provisioning problem, where agents interact with each other to find the optimal threshold for call admission using Distributed Service Architectures. It evaluates connection level performance characteristics of Dynamic and Mobility based call admission control schemes using agents. The Multi Agent architecture is designed and simulated using open source Java Agent DEvelopment Framework (JADE). Finally the papers compares performance of the CAC schemes in Non Agent based and Multi agent based environments.

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Multi agent system based service architectures for service level agreement in cellular networks

Cited by 8 publications

References 6 publications

Smart Grid as a Service: A Discussion on Design Issues

Smart Grid as a Service: A Discussion on Design Issues

Role of Multi Agent System for Qos Guarantee in Cellular Networks

JADE based Multi Agent system for mobile computing for cellular networks

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