Traffic and Congestion Control in ATM Networks Using Neuro-Fuzzy Approach
نویسندگان
چکیده
In this paper, a neuro-fuzzy based Call Admission Control (CAC) algorithm for ATM networks has been simulated. The algorithm presented employs neuro-fuzzy approach to calculate the bandwidth require to support multimedia traffic with QoS requirements. The neuro-fuzzy based CAC calculates bandwidth required per call using measurements of the traffic via its count-process, instead of relying on simple parameters such as the peak, average bit rate and burst length. Furthermore, to enhance the statistical multiplexing gain, the controller calculates the gain obtained from multiplexing multiple streams of traffic supported on separate virtual (i.e, class multiplexing). Refer
منابع مشابه
A neuro-fuzzy approach to vehicular traffic flow prediction for a metropolis in a developing country
Short-term prediction of traffic flow is central to alleviating congestion and controlling the negative impacts of environmental pollution resulting from vehicle emissions on both inter- and intra-urban highways. The strong need to monitor and control congestion time and costs for metropolis in developing countries has therefore motivated the current study. This paper establishes the applicatio...
متن کاملFuzzy Congestion Control Scheme in ATM Networks
Fuzzy approach to control congestion in ATM networks is inevitable in research areas. . A control scheme that dynamically regulates traffic flow according to changing network conditions however requires the understanding of network dynamics. To minimize congestion, for a gradual change we proposed fuzzy approach. In our scheme, burst length as well as buffer occupancy are represented by triangu...
متن کاملFuzzy Logic Control in Atm Network
Due to the unpredictable behavior of the traffic and various traffic characteristics, it has become a great challenge for ATM networks to effectively control traffic and congestion while at the same time provide the desired quality of service. In this paper, a fuzzy logic traffic controller is proposed to perform traffic and congestion control functions. Simulation results showed the feasibilit...
متن کاملBio-inspired Neuro-Fuzzy Based Dynamic Route Selection to Avoid Traffic Congestion
this paper presents the bio-inspired neurofuzzy based route selection system to avoid traffic congestion. The proposed neuro-fuzzy system selects the best multi-parameters direction between two desired nodes: source and the endpoint. This research practices a mixture of neuro-fuzzy logic and ant colony system (ACS) algorithm for the principal routing to fulfill all the preferred requirements of...
متن کاملAdaptive Online Traffic Flow Prediction Using Aggregated Neuro Fuzzy Approach
Short term prediction of traffic flow is one of the most essential elements of all proactive traffic control systems. Although various methodologies have been applied to forecast traffic parameters, several researchers have showed that compared with the individual methods, hybrid methods provide more accurate results . These results made the hybrid tools and approaches a more common method for ...
متن کامل