The rapid evolution of computer networks, increase in the number of internet users, and popularity of multimedia applications have exacerbated the congestion control problem. In view of the fastgrowing internet traffic, this paper propose a distributed traffic management framework, in which routers are deployed with intelligent data rate controllers to tackle the traffic mass. Then, through a number of examples, we illustrate the power of the methodology by the successful application of fuzzy based congestion control in the two diverse networking technologies of atm and tcpip. This is one of the most economic fuzzy rule based model by which it is easy to detect congestion before congestion collapse so that effective steps is taken to prevent the risk of congestion collapse.
Intelligent network traffic control in high speed networks. In this paper, we propose a fuzzy adhoc ratebased congestion control farcc to enhance the efficiency of network in. A fuzzy logic based controller to provide endtoend. Control protocol tcp congestion control mechanisms are explained. Intelligent traffic lights control system using fuzzy logic. A congestion window control mechanism based on fuzzy logic to improve tcp performance in manets. Congestion control techniques in computer networks. Congestion can be controlled at core and bottleneck router differently. Fuzzy logic in congestion control of computer network.
Congestion control in wireless communication network using. Intelligent traffic lights control system using fuzzy logic 2014360359 this paper describes the development of an intelligent traffic lights control system using fuzzy logic concepts. Ltd we are ready to provide guidance to successfully complete your projects and also download the abstract, base paper from our web. Wireless overlay networks a hierarchical structure of roomsizeand wide area data networks, solve the difficulty of providing network connectivity to a huge number of mobile users in anproficient and scalable way 1. Congestion control and prediction schemes using fuzzy logic system with. Congestion problems and solutions are constantly shifting in response to technological and operational events. Fuzzy logic based high speed network congestion control.
Pdf a fuzzy based tcp congestion control for wired networks. This challenge is crucial in wireless sensor networks wsns with restrictions and. While traditional logic contains only two truth values true and false or 1 and 0, fuzzy logic may contain an infinite number of truth values on the continuous range 0. The fuzzy logic based controller can measure the router queue size directly by using congestion control algorithm.
This paper, proposes a generic active queue management aqm control methodology in tcpip networks, based on fuzzy logic control principles. Interval type2 fuzzy logic congestion control for video. In this work, we designed and developed an intelligent traffic lights control system, using fuzzy logic technology. Ijca proceedings on international conference on recent trends in information technology and computer science 2012 icrtitcs12. A rate based congestion control mechanism using fuzzy. To get better quality of service over the best effort network, multiple queue management algorithms can be used. Pdf congestion control in computer networks using fuzzy logic. It stands for dynamic congestion control for mobile networks. For this purpose, a new active queue management scheme, implemented within the diffserv framework, has recently been proposed to provide congestion control in tcpip networks using a fuzzy logic. A rate based congestion control mechanism using fuzzy controller in manets the traditional congestion control mechanism tcp, performs very poorly in manets because there are a number of new challenges such as wireless link error, medium contention and frequent route failures in this kind of networks. Congestion control in ip networks using fuzzy logic control. The complexity and immensity of the task was recognized.
The chapter outlines the design of a congestion controller that relies on network packet delay and delay trend as inputs. In the proposed method, congestion announcement and control are carried out by using three main parameters, i. The 5g cellular networks need to cope with such skyrocketing traffic requests from these devices to avoid network congestion. Engineering congestion control of internet video streaming. Citeseerx differentiated services fuzzy assured forward.
Background in fuzzy control systems and fuzzy inference can be found in 19. Congestion control and prediction schemes using fuzzy logic system with adaptive membership function in wireless sensor networks phet aimtongkham, 1 tri gia nguyen, 2 and chakchai so in 1 1 applied network technology ant laboratory, department of computer science, faculty of science, khon kaen university, khon kaen, thailand. The main difference between flow control and congestion control is that the flow control is a mechanism that controls the traffic between sender and receiver. Fuzzy based congestion detection in computer network. Congestion control techniques can be broadly classified into two categories. Fuzzybased congestion control for wireless multimedia sensor. A fuzzy based tcp congestion control for wired networks.
A traffic control and offense reporting system using fuzzy logic. The results of simulations confirm that a cross layer design using fuzzy logic at different levels can achieve low and stable endtoend delay, and. This chapter introduces the control problem faced in designing a fuzzy logic congestion controller in terms of the restrictions of a compressed video bitstream and the uncertainties that affect congestion control. Congestion control and prediction schemes using fuzzy.
A traffic control and offense reporting system using fuzzy. Network congestion in data networking and queueing theory is the reduced quality of service that occurs when a network node or link is carrying more data than it can handle. Concepts of fuzzy sets, fuzzy logic, and fuzzy logic control have been introduced and developed by zadeh in a series of articles spanning a few yearsfor an introduction, the reader is referred to 1621. The system was developed using fuzzy logic technology which is capable of accommodating inherent uncertainty and vagueness in traffic control and implementation was. Almost all the consumer products have fuzzy control. Accordingly, in this paper, using fuzzy logic, a new congestion control method was proposed for these networks. The performance is measured in terms of the packet loss percentages, link utilization and queue size. Internet congestion control using fuzzy integral controller. School of computer science and software engineering, swinburne university of. A fuzzy logic controller flc can be conceived as a nonlinear controller of. Using fuzzy logic control to provide intelligent traffic. Fuzzy logic, congestion control, active queue management, atm, tcpip, quality of service. Congestion avoidance is a qos 1 method that prevents considerable packet loss in networks and assures successful packet forwarding to destination. A multiagent based autonomous traffic lights control system.
Using fuzzy inference to improve tcp congestion control. A comparison was made between the fuzzy logic controller and the conventional. Temperature control system using fuzzy logic technique. Backpressure is a nodetonode congestion control that starts with a node and propagates, in the opposite direction of data flow. Congestion is an important issue that can arise in packet switched network. We present a new fuzzy logic based aqm control methodology to provide effective congestion control in tcpip networks. Fuzzy logic was developed owing to this imprecise nature of solving control problems by computer. Keywords congestion control, fuzzy logic, atm networks, neural. Pdf network congestion control is a complex problem that requires robust, possibly intelligent. Sep 21, 2017 fifth generation 5g cellular networks will be comprised of millions of connected devices like wearable devices, androids, iphones, tablets, and the internet of things iot with a plethora of applications generating requests to the network. A multiagent based autonomous traffic lights control. Using fuzzy logic, fuzzyqos3 uses fuzzy thresholds to adapt to the dynamic conditions.
Fuzzy logic based congestion control cntd the proposed fuzzy logic approach allows the use of linguistic knowledge to capture the dynamics of nonlinear probability marking functions uses multiple inputs to capture the dynamic state of the network more accurately. His research interests are in parallel and distributed computing, wireless sensor networks and fuzzy logic control. The congestion control is handled either by the source or the destination. International journal of computer applications 0975 8887 volume 89 no. The system was developed using fuzzy logic technology which is capable of accommodating inherent uncertainty and vagueness in traffic control and implementation was done with java programming language. The evaluation of fuzzyqos performances was studied under different mobility, channel, and traffic conditions.
No matter at what rate water enters the bucket, the outflow is at. Fuzzy logic based congestion controller is a model free controller that utilizes qualitative reasoning to implement nonlinear control functions efficiently. Congestion control in computer networks using fuzzy logic. Congestion control and prediction schemes using fuzzy logic system with adaptive membership function in wireless sensor networks phet aimtongkham, 1 tri gia nguyen, 2 and chakchai soin 1 1 applied network technology ant laboratory, department of computer science, faculty of science, khon kaen university, khon kaen, thailand. Matlab software used to calculate the degree of congestion over various network parameters. A new aqm scheme, fuzzy explicit marking fem has recently been proposed to provide congestion control in tcpip besteffort networks using a fuzzy logic control approach. An energyaware distributed clustering protocol in wireless. Application of fuzzy control techniques to problem of congestion control in networks is. Congestion control mechanisms in wireless sensor networks. As such, there is need to find ways of controlling this problem.
Effective control of traffic flow in atm networks using fuzzy. Proposing a method for controlling congestion in wireless. Fuzzy logic congestion control in tcpip besteffort networks. If delay increases, retransmission occurs, making situation worse. Some of the examples include controlling your room temperature with the help of airconditioner, antibraking system used in vehicles, control on traffic lights, washing machines, large economic systems, etc. Fifth generation 5g cellular networks will be comprised of millions of connected devices like wearable devices, androids, iphones, tablets, and the internet of things iot with a plethora of applications generating requests to the network. Fuzzy logic based congestion control fuzzy logic control has been applied successfully for controlling systems in which analytical models are not easily obtainable or the model itself, if available, is too complex and possibly highly nonlinear. Congestion is a challenging problem for sensor networks because it causes the waste of communication and reduces energy efficiency. Using fuzzy logic control to provide intelligent traffic management service for highspeed networks abstract. Fuzzy logic is applied with great success in various control application. Intelligent qos management for multimedia services support in. Suit provides fuzzy logicbased congestion estimation and an efficient. The traditional congestion control mechanism tcp, performs very poorly in manets because there are a number of new challenges such as wireless link error, medium contention and frequent route failures in this kind of networks.
While many aqm mechanisms have recently been proposed, these require careful configuration of nonintuitive control parameters, and show weaknesses to detect and control congestion under dynamic traffic changes, and a slow response to regulate queues. Ossama mohamed younis m05 received the bs and ms degrees in computer science from alexandria university, alexandria, egypt, in 1995 and 1999, respectively, and the phd degree in computer science from purdue university, west. We adopt fuzzy logic due to its reported strength in controlling nonlinear systems using linguistic information. Accordingly, in this paper, using fuzzy logic, a new congestion control method was proposed. Part of theamerican studies commons this thesis is brought to you for free and open access by the graduate school at scholar commons. In view of the fastgrowing internet traffic, this paper propose a distributed traffic management framework, in which routers are deployed with. An application of fuzzy logic model in solving road traffic. Difference between flow control and congestion control with. Using fuzzy inference to improve tcp congestion control over. A fuzzy logic controller flc can be conceived as a nonlinear controller of which the inputoutput relationship can.
Softwaredefined congestion control algorithm for ip networks. In such virtual circuit each node knows the upstream node from which a data flow is coming. Congestion control is a key factor in ensuring network stability and robustness. There is a continuum of congestion control measures. Congestion control refers to the techniques used to control or prevent congestion. Network congestion control drives the network up to but not into congestion. Their simulation result shows that fuzzy explicit rate marking. This methodology is developed to offer a simple and generic process, and thus it is. Create and evaluate a complete hardware and software stack, as well as novel. Fuzzy logic offers the possibility to compute with words, by using a mechanism for representing linguistic constructs common on real world problems.
New metrics have been newly invented and introduced like normalized advancing index nai and complete transmission time ctt. A fuzzy logic based controller to provide endtoend congestion control for streaming media applications bay pavlick university of south florida follow this and additional works at. Unlike other explicit traffic control protocols that have to estimate network parameters e. Fuzzy logic helps to increase throughput, reduction in packet drop and delays. Jammeh, ea and fleury, m and wagner, c and hagras, h and ghanbari, m 2009 interval type2 fuzzy logic congestion control for video streaming across ip networks. The quality of service is assured by the good performance of the fuzzy based controller using target buffer.
Congestion is a situation in communication networks in which too many packets are present in a part of the subnet, performance degrades. A rate based congestion control mechanism using fuzzy controller in manets the traditional congestion control mechanism tcp, performs very poorly in manets because there are a number of new challenges such as wireless link error, medium contention. Institute of technology, ulhasnagar, india madhu nashipudi asst. Typical effects include queueing delay, packet loss or the blocking of new connections. Professor piit, new panvel navi mumbai maharashtra, india abstract congestion being a nonlinear and dynamic problem in the. A state occurring in network layer when the message traffic is so heavy that it slows down network response time. Jan, 2014 unlike other explicit traffic control protocols that have to estimate network parameters e. Network congestion control is a complex problem that requires robust, possibly intelligent, control methodologies to obtain satisfactory performance. Saleem khan, khalil ahmed, abdul salam mubashar abstract this research work presents an application of fuzzy logic for multiagent based autonomous traffic lights control system using wireless sensors to overcome problems like congestion, accidents, speed and traffic irregularity.
On evaluating these parameters using fuzzy logic, a desired output for congestion control can be determined and its efficiency is evaluated using machine learning tools. The backpressure technique can be applied only to virtual circuit networks. Open loop congestion control policies are applied to prevent congestion before it happens. Department of computer networks systems, amman, jordan. Fuzzy logic in congestion control of computer network shilpa n. Congestion control, fuzzy logic control, quality of service, maxmin fairness, robustness, traffic management. Fuzzy logic control for active queue management in tcpip. On the other hand, the congestion control mechanism controls the traffic into the network. Fuzzy logicbased call admission control in 5g cloud radio. A simple, effective and efficient nonlinear control law is built, using a linguistic model of the system, rather than a traditional mathematical model, which is easily adapted in different network environments e.
When the underlying network and flow information are unknown, the transmission control protocol tcp must increase or reduce the size of. Lights control system using fuzzy control yousaf saeed, m. Fuzzy logic approach for congestion control thesai org. In 2010 ieee 35th conference on local computer networks lcn pp. Congestion control and prediction schemes using fuzzy logic. Congestion control in computer networks geeksforgeeks. In this article we have implemented a new queuing mechanism that uses fuzzy logic with assured forwarding in the intermediate routers, in order to control and avoid congestion by using an aqm 2 method. Compared to traditional wireless sensor networks, the probability of congestion occurrence in wireless multimedia sensor networks is higher due to the high volume of data arising from multimedia streaming. Rather our intention is to motivate the fuzzy logic based approach. Congestion control in asynchronous transfer mode atm. Adaptive control of congestion in tough wireless environments.
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