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

Ikeda, Makoto; Barolli, Leonard; Kôyama, Akio; Durresi, Arjan; Marco, Giuseppe De; Iwashige, Jiro

doi:10.1016/j.jcss.2005.12.007

Cited by 26 publications

(9 citation statements)

References 16 publications

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“…Algorithm 1 (Branke, Deb, Miettinen, & Slowinski, 2008;Deb, 2001;Ikeda et al, 2006) can be used to get the non-dominated set of the feasible solutions.…”

Section: Pareto-optimal Solutionmentioning

confidence: 99%

Applying Ant Colony System algorithm in multi-objective resource allocation for virtual services

Pham¹,

2017

Journal of Information and Telecommunication

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Over the past few years, using cloud computing technology has become popular. With the cloud computing service providers, reducing the number of physical machines providing resources for virtual services in cloud computing is one of the efficient ways to reduce the amount of energy consumption which in turn enhance the performance of data centres. However, using a minimum of physical machines to allocate resources for virtual services can result in system overload and break the SLA of service. Consequently, providing resources for virtual services which do not only satisfy the constraint of reducing the energy consumption but also ensure the load balancing of the whole system is necessary. In this study, we present the multi-objective resource allocation problem for virtual services. This problem aims at both reducing the energy consumption and balancing the load of physical machines. The MORA-ACS algorithm is proposed to resolve the problem by the Ant Colony System method. The experimental results show that in the CloudSim environment, the MORA-ACS algorithm could balance the load as well as reduce the energy consumption better than the Round Robin algorithm. ARTICLE HISTORY

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“…Algorithm 1 (Branke, Deb, Miettinen, & Slowinski, 2008;Deb, 2001;Ikeda et al, 2006) can be used to get the non-dominated set of the feasible solutions.…”

Section: Pareto-optimal Solutionmentioning

confidence: 99%

Applying Ant Colony System algorithm in multi-objective resource allocation for virtual services

Pham¹,

2017

Journal of Information and Telecommunication

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“…Use of intelligent methods based on Fuzzy Logic (FL), Neural Networks (NN) and Genetic Algorithms (GA) can prove to be efficient for traffic control in telecommunication networks [4][5][6][7][8][9][10][11][12][13].…”

Section: Introductionmentioning

confidence: 99%

Performance Evaluation and Comparison of Fuzzy-Based Intelligent CAC Systems for Wireless Cellular Networks

Barolli

Mino

Ikebata

et al. 2010

2010 International Conference on Intelligent Networking and Collaborative Systems

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The mobile cellular systems are expected to support multiple services with guaranteed Quality of Service (QoS). But, the ability of wireless systems to accommodate expected growth of traffic load and broadband services is limited by available radio frequency spectrum. Call Admission Control (CAC) is one of the resource management functions, which regulates network access to ensure QoS provisioning. However, the decision for CAC is very challenging issue due to user mobility, limited radio spectrum, and multimedia traffic characteristics. To deal with these problems, we implemented a Fuzzy Admission Control System (FACS). We compared the performance of FACS with Shadow Cluster Concept (SCC). In another work, we extended FACS by considering the priority of the on-going connections. We called this system FACS-P. As priority parameter, we considered only one parameter (service request). In this work, we improve our previous system by adding different priorities. We call this system FACS-MP. We evaluate and compare the performance of implemented systems by simulations. From the simulations results, we conclude that the FACS-MP can differentiate better different services compared with previous systems.

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“…For instance, Ikeda et al proposed new algorithms based on fuzzy logic and genetic algorithm applications to call admission control (CAC) and routing many QoS parameters for video and multimedia data. The simulation results show that the proposed framework has a good performance and is a promising method for QoS routing and CAC decision making [9]. Yuang and Tien presented a new intelligent multiple access control system (IMACS) which included a versatile MAC scheme augmented with dynamic bandwidth allocation for wireless ATM networks, supporting CBR, VBR and available bit rate (ABR) data.…”

Section: Introductionmentioning

confidence: 99%

An intelligent MPEG rate control in 2.4 GHz frequency

Kazemian

Chantaraskul

2009

Adaptive Control & Signal

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Transmitting Moving Picture Expert Group (MPEG) Variable Bit Rate (VBR) video stream over 2.4 GHz wireless frequency demands a large bandwidth and may result in data loss and delay, because of excessive fluctuation in bit rate. Transmission over 2.4 GHz frequency further causes uncertainty due to interferences by other wireless devices in the same frequency band and/or common dynamic channel noises. As a result, an intelligent system has been developed for MPEG video transmission over 2.4 GHz frequency band. A novel fuzzy controller automatically determines the quantization scale for each Group Of Picture (GOP) of the encoder during the transmission period. Moreover, a fuzzy controller and a neural-fuzzy controller stream the MPEG video data to conform to the current condition of dynamic wireless channel to maintain image quality during the transmission. In the intelligent system, rather than choosing the parameters associated with a given membership function arbitrarily, these parameters are chosen as such to tailor the membership functions to the desired input/output data. The intelligent system computes and trains the system in such a way that its output will be equal to the desired value. Computer simulation results demonstrate that the proposed intelligent technique increases transmission rate and reduces data loss, excessive delay and image quality degradation as compared with a conventional video transmission over 2.4 GHz frequency band.

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

Cited by 26 publications

References 16 publications

Applying Ant Colony System algorithm in multi-objective resource allocation for virtual services

Applying Ant Colony System algorithm in multi-objective resource allocation for virtual services

Performance Evaluation and Comparison of Fuzzy-Based Intelligent CAC Systems for Wireless Cellular Networks

An intelligent MPEG rate control in 2.4 GHz frequency

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