An intelligent routing and CAC framework for large-scale networks based on cooperative agents

Barolli, Leonard; Kôyama, Akio; Yamada, Takako; Yokoyama, Shinya; Suganuma, Takuo; Shiratori, Norio

doi:10.1016/s0140-3664(02)00044-0

Cited by 13 publications

(8 citation statements)

References 16 publications

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“…The work in Ref. [91] uses cooperating agents to perform CAC control in a large-scale networks. The CAC algorithm uses fuzzy logic control based cooperative agents to decide the routes within a domain and between the domains based on traffic estimates information exchange.…”

Section: Qos Managementmentioning

confidence: 99%

Applications of agent technology in communications: a review

Manvi

Venkataram

2004

Computer Communications

103

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Section: Qos Managementmentioning

confidence: 99%

Applications of agent technology in communications: a review

Manvi

Venkataram

2004

Computer Communications

103

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“…To cope with broadband networks the CAC schemes and routing algorithms should give a fast decision and must be adaptive, flexible, and intelligent for efficient network management [5].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of a Network Extraction Topology Algorithm for Reducing Search Space of a GA-based Routing Approach

Ikeda

Barolli

Marco

et al. 2006

26th IEEE International Conference on Distributed Computing Systems Workshops (ICDCSW'06)

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In order to support multimedia communication, it is necessary to develop routing algorithms which use for routing more than one QoS parameters. This is because new services such as video on demand and remote meeting systems require better QoS. Also, for admission control of multimedia applications different QoS parameters should be considered. In our previous work, we proposed an intelligent routing and CAC strategy using cooperative agents. The proposed routing algorithm is a combination of source and distributed routing. However, in the previous research, we only considered the time delay for the routing. Also, QoS and congestion control parameters were considered just as indicators of QoS satisfication and congestion. In this work, we extend our previous work by proposing and implementing new algorithms based on fuzzy logic and genetic algorithm which use for admission control and routing many QoS parameters. Also, we evaluate by simulations the performance of the network extraction topology algorithm which reduces the search space of the proposed GA-based routing approach. Thus, the GA can find a feasible route very fast.

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“…Use of intelligent algorithms based on Fuzzy Logic (FL), Genetic Algorithms (GA) and Neural Networks (NN) can prove to be efficient for telecommunication networks [8][9][10][11][12]. In our previous work, we proposed an intelligent CAC and routing framework using cooperative agents [11].…”

Section: Introductionmentioning

confidence: 99%

“…In our previous work, we proposed an intelligent CAC and routing framework using cooperative agents [11]. The proposed framework is based on Distributed Artificial Intelligence (DAI) approach, which deals with design of artificial agents to develop intelligent systems.…”

Section: Introductionmentioning

confidence: 99%

“…Also, in the GA-based routing algorithm we considered only time delay as the only parameter for routing [9][10][11]. However, in order to support multimedia communication over broadband networks, it is necessary to develop routing algorithms which use for routing more than one QoS parameter such as throughput, delay, and loss probability [12].…”

Section: Introductionmentioning

confidence: 99%

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Performance evaluation of an intelligent CAC and routing framework for multimedia applications in broadband networks

Ikeda

Barolli

Kôyama

et al. 2006

Journal of Computer and System Sciences

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In order to support multimedia communication, it is necessary to develop routing algorithms which use for routing more than one QoS parameters. This is because new services such as video on demand and remote meeting systems require better QoS. Also, for the Call Admission Control (CAC) of multimedia applications different QoS parameters should be considered. In our previous work, we proposed an intelligent routing and CAC strategy using cooperative agents. However, we only considered the time delay for the routing. The QoS and Congestion Control (CC) parameters were considered as indicators of QoS satisfication and congestion. In this work, we extend our previous work by proposing and implementing new algorithms based on Fuzzy Logic (FL) and Genetic Algorithm (GA) which use for CAC and routing many QoS parameters. The simulation results show that proposed framework has a good performance and is a promising method for QoS routing and CAC decision.

show abstract

An intelligent routing and CAC framework for large-scale networks based on cooperative agents

Cited by 13 publications

References 16 publications

Applications of agent technology in communications: a review

Applications of agent technology in communications: a review

Evaluation of a Network Extraction Topology Algorithm for Reducing Search Space of a GA-based Routing Approach

Performance evaluation of an intelligent CAC and routing framework for multimedia applications in broadband networks

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