COMPARATIVE ANALYSIS OF NEURO- FUZZY AND SIMPLEX OPTIMIZATION MODEL FOR CONGESTION CONTROL IN ATM NETWORK.

Congestion always occurred when the transmission rate increased the data handling capacity of the network. Congestion normally arises when the network resources are not managed efficiently. Therefore if the source delivers at a speed higher then service rate queue, the queue size will be higher. Also if the queue size is finite, then the packet will observed delay. MATLAB Software was used to carry out simulations to develop Congestion control optimization Scheme for ATM Network with the aims to reducing the congestion of Enugu ATM Network. The results of the research reveal the minimization of congestion application model for Enugu ATM using optimization and Neuro-fuzzy. The result shows that congestion control model with Optimization and Neuro-fuzzy were 0.00003153 and 0.00002098 respectively. The ATM Congestion was reduced by 0.0000105, which is 18.2% decrease after Neuro-fuzzy controller was used. The results show the application of Neuro-fuzzy model which can use to control and minimized the ATM Congestion of Enugu ATM Network. The result shows that when Neuro-fuzzy is applied the congestion and the packet queue length in the buffer will be minimized. Key words: Congestion, MATLAB, Optimization, Neuro-fuzzy, ATM DOI: 10.7176/CTI/10-05 Publication date:July 31st 2020

A genetic algorithm for the design of a fuzzy controller for active queue management

Active queue management (AQM) policies are those policies of router queue management that allow for the detection of network congestion, the notification of such occurrences to the hosts on the network borders, and the adoption of a suitable control policy. This paper proposes the adoption of a fuzzy proportional integral (FPI) controller as an active queue manager for Internet routers. The analytical design of the proposed FPI controller is carried out in analogy with a proportional integral (PI) controller, which recently has been proposed for AQM. A genetic algorithm is proposed for tuning of the FPI controller parameters with respect to optimal disturbance rejection. In the paper the FPI controller design metodology is described and the results of the comparison with random early detection (RED), tail drop, and PI controller are presented

B&W Call Admission Control for Multimedia Communication Networks

In the multimedia communication networks providing quality of service (QoS), an interface between the signal processing systems and the communication systems is the call admission control (CAC) mechanism. Owing to the heterogeneous traffic produced by diverse signal processing systems in a multimedia communication network, the traditional CAC mechanism that used only one CAC algorithm can no longer satisfy the aim of QoS CAC: Utilize the network resource to the most best and still satisfy the QoS requirements of all connections. For satisfying the aim of QoS CAC in the multimedia communication networks, this study proposed an innovative CAC mechanism called black and white CAC (B&W CAC), which uses two CAC algorithms. One of them is called black CAC controller and is used for the traffic with specifications more uncertain, which is called black traffic here. The other is call white CAC controller and is for the traffic with clearer specifications, which is call white traffic. Because white traffic is simple, an equivalent bandwidth CAC is taken as the white CAC. On the other hand, a neural network CAC (NNCAC) is employed to be the black CAC to overcome the uncertainty of black traffic. Furthermore, owing to more parameters needed in a QoS CAC mechanism, a hierarchical NNCAC is proposed instead of the common used NNCAC. Besides to accommodate more parameters, a hierarchical NNCAC can keep the complexity low. The simulation results show the B&W CAC can obtain higher utilization and still meet the QoS requirements of traffic sources

Application of learning algorithms to traffic management in integrated services networks.

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Statistical multiplexing and connection admission control in ATM networks

Asynchronous Transfer Mode (ATM) technology is widely employed for the transport of network traffic, and has the potential to be the base technology for the next generation of global communications. Connection Admission Control (CAC) is the effective traffic control mechanism which is necessary in ATM networks in order to avoid possible congestion at each network node and to achieve the Quality-of-Service (QoS) requested by each connection. CAC determines whether or not the network should accept a new connection. A new connection will only be accepted if the network has sufficient resources to meet its QoS requirements without affecting the QoS commitments already made by the network for existing connections. The design of a high-performance CAC is based on an in-depth understanding of the statistical characteristics of the traffic sources

Performance Evaluation of Fuzzy based Congestion Control for TCP/IP Networks

It by and large acknowledged that the trouble of system congestion control stays a basic issue and a high need, particularly given the developing size, request, and speed (transfer speed) of the inexorably coordinated administrations systems. In spite of the examination endeavors spreading over several decades and accordingly the sizable measure of different plans proposed, there are no generally worthy control arrangements. Current arrangements in existing systems are progressively getting insufficient, and it's commonly acknowledged that these arrangements can only with significant effort extent even with different proposed "fixes". In this paper, a Fuzzy based congestion control is talked about to manage the congestion control issue. The exhibition of the controlled framework is assessed by means of reenactment

Application of an automatically designed fuzzy logic decision support system to connection admission control in ATM networks

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Motorized cart

Motorized cart is known as an effective tool and timeless that help people carry heavy loads. For farmers, it has an especially vital tool for moving goods. Oil palm farmers typically uses the wheelbarrow to move the oil palm fruit (Figure 10.1). However, there is a lack of equipment that should be further enhanced in capabilities. Motorized carts that seek to add automation to wheelbarrow as it is to help people save manpower while using it. At present, oil palm plantation industry is among the largest in Malaysia. However, in an effort to increase the prestige of the industry to a higher level there are challenges to be faced. Shortage of workers willing to work the farm for harvesting oil palm has given pain to manage oil palm plantations. Many have complained about the difficulty of hiring foreign workers and a high cost. Although there are tools that can be used to collect or transfer the proceeds of oil palm fruits such as carts available. However, these tools still have the disadvantage that requires high manpower to operate. Moreover, it is not suitable for all land surfaces and limited cargo space. Workload and manpower dependence has an impact on farmers' income