Performance and Evaluation of Integrated Video Transmission and Quality of Service for internet and Satellite Communication Traffic of ATM Networks P. Rajan Dr. K.L.Shanmuganathan Research Scholar Prof. and Head Bharathiyar University Dept. of CSE Coimbatore-641046 RMK Engg. College, Chennai-601206. Abstract-- Virtual path provisioning has gained wide acceptance as an effective resource management technique for improving transmission efficiency in ATM network. A suggested control method provides fairness among the traffic and confirms the effectiveness for integrating of multimedia traffic [4] over ATM network. ATM is currently considered the primary WAN technology with internet protocols providing the routing and transport requirements. To fully understand the end to end quality of service as each layer [5], quality of service parameters [6] and the current research are surveyed. Further research on quality of service architecture performance methods for TCP enhancements internetworking functions, interoperability and standardization effort is included. The performance effort of TCP enhancements for UBR over ATM for large bandwidth delay environments with end system policies and drop policies and drop policies for several buffer sizes are presented. In this paper we summarize basic issues underlying this subject and describe a particular approach to achieving a multilayer broadband congestion, flow control and error control architecture based on a core congestion and control strategy that we term bandwidth management. 1. INTRODUCTION Design of a traffic delay analysis model [3] for the admission control of real time multicast connection in ATM networks. Design of a distributed and delay [1] bounded multicast routing algorithm which generate sub optimal routing trees under real time constraints. Development of an integrated connection setup which integrates multicast routing with admission control. It significantly reduces time messages required for a connection setup. To achieve well defined performance objectives by protecting both the user and the network against congestion. These performance objectives can be expressed in terms of cell loss probabilities cell transfer delay and cell delay variation. To achieve efficiency and optimization of the usage of network resources needed to ensure the above mentioned performance requirements. Temporarily overload conditions due to the statistical functions of variable bit rate traffic. Malicious user who deliberately offer more traffic to the network to obtain operational or economical advantage with respect to the user. Malfunctioning of terminal equipment leading to unexpected traffic volumes entering the network. 2. PROBLEM STATEMENT The multilevel traffic and congestion control provide a framework that allows effective management of congestion occurring in different time scales. Many research effort have been directed towards the development of various traffic admission control algorithm [2] applied at network access node to manage traffic loading. However the issue of network resource management and maintenance which is equally essential for the multilevel traffic control to be successful has not yet been well addressed. The capability of a network element to engineer critical resource adequately in both normal and overload conditions is necessary and crucial for ATM networks. Many research problems are a. Many data resources are very bursty and highly un predictable and they are difficult to be accurately characterized in advance of transmissions. b. Interaction between different traffic stream within a packet networks packet flow can cluster together and create local congestion even when the arrival traffic streams are well regulated at their access nodes. c. Operational network user may sometimes misbehaves a user may transmit data at a high rate without listening to the network control information. This research is intended to investigate effective integrated control mechanism [7] as well as proper architecture for switching nodes within an ATM environment. The integrated controls when incorporated within a well suited access control scheme can be applied to ATM switch to enhance overall network performance and to deal with different service demands. 2014-15, IJIRIS- All Rights Reserved Page -17
International Journal of Innovative Research in Information Security (IJIRIS) ISSN: 2349-7017(O) 3. RELATED ALGORITHMS a. Generate cell rate algorithm. Two individuals are mated in order to exchange generic information. High selectivity i.e. the capability to detect any non complaint traffic situations and transparency for connections that respect the parameter values negotiated. Rapid response to parameter violations simplicity of implementations and cost effectiveness because there will be an UPC mechanism [8] for each user. Ability to addictive learning and generalization. Higher computation rate due to the massive parallelism of the hardware implementation. Robustness and fault tolerance due to the nature of distributed processing. FOR EX.TABLE 1. Group A B C D E F Bandwidth 0.038 0.075 0.221 0.038 0.075 0.334 Bottle Neck Link S1-S2 S4 S5 S3 S4 S1 S2 S4 S5 S2 S3 TABLE 2 Bit rate 155.51 200.76 246.00 291.25 336.51 381.76 427.00 472.25 517.50 562.75 First cell 2.725 2.113 1.724 1.457 1.258 1.112 0.994 0.899 0.818 0.754 Text 10.48 8.129 6.634 5.604 4.848 4.275 3.822 3.454 3.154 3.097 Image 21.92 16.98 13.84 11.71 10.12 8.92 7.97 7.21 6.58 6.05 Video 1,7202 1.394 1.088 0.91 0.795 0.701 0.627 0.566 0.517 0.475 Audio 0.470 0.364 0.297 0.250 0.217 0.196 0.173 0.156 0.142 0.94 TABLE 2: GRAPH 20000 Bit rate 15000 First cell 10000 Text Image 5000 Video 0 Image 1 2 3 4 5 6 7 Audio Bit rate 8 9 10 2014-15, IJIRIS- All Rights Reserved Page -18
TABLE 3 : RTT COMPARISON Size No Prediction Prediction % of Decrease 4 1111 1020 8 20 1128 1038 8 80 1323 1288 3 200 15621 1521 3 500 2185 2141 2 1400 2963 2975 0 4000 5951 5890 1 8000 11475 10635 7 35000 30000 25000 20000 15000 10000 5000 0 TABLE 3: GRAPH 1 2 3 4 5 6 7 8 % of Decrease Prediction No Prediction Size TABLE : 4 ATM VS ETHERNET COMPARISION Size Ethernet ATM % of Decrease 4 1941 1020 46 20 2335 1040 54 80 2591 1290 51 200 2805 1521 44 500 4120 2141 46 1400 6555 2975 55 4000 13167 5980 54 8000 22142 10635 53 TABLE 4: GRAPH 100% 80% 60% 40% 20% % of Decrease ATM Ethernet Size 0% 1 2 3 4 5 6 7 8 2014-15, IJIRIS- All Rights Reserved Page -19
1. ADAPTIVE RATE CONTROL ALGORITHM Procedure calculate window-size Find out current allocation rate Find out current window size Do while cell is transmitting { If cell drop is found then { Calculate new allocation rate Current allocation rate = new allocation rate Calculate new window size Current window size = new window size } Else no cell drop is found then { Current allocation rate = current allocation rate Current window size = current window size } } Enddo where : find current allocation rate Source rate = window size * cell size / (cell drop * cell delay time) Cell delay time = cell travelling time between source to destination Find current window size Window size = bandwidth * cell delay time 4. ATM CELL FUNCTIONALITY Generate flow control a 4 bit field providing flow control at the user network interface for traffic organizing at user equipment and diverse into the network. It is used as part of the virtual path field at the network to network interface. Virtual channel is a concept used to describe unidirectional transport of ATM cells associated by a common unique identifier value called virtual channel identified is a 16bit field. Virtual path is a concept used to describe unidirectional transport of ATM cells belongs to VC that are associated by a common id value responded to as the VP identifier. VPI is an 8-12 bit field. Pay load type is a 3 bit field indicating the type of information in the information field. Cell loss priority is a one bit field i.e. used to provide guidance to the network in the event of congestion. A value 0 indicates a cell of relatively higher priority which should not be discarded unless no other alternative is available. A value 1 indicates that a cell can be discarded within the network in case of congestion. Header error control an 8 bit field used mainly for 2 purposes. To defect 2 bit and correct 1 bit error in the ATM cell delineation. 5. SIMULATION ENVIRONMENT The network model is a typical cell in a wireless network with are BS and N active mobiles. MS are buffered possible unit that produce data packets according to source bursty random process. All data packets are queued in the mobiles buffer until the BS allocates them a time slot for transmission. The uplink and down link channels are simulated as separate channel. Both uplink and down link channels are time slotted. The network is assumed to have fixed number of active mobiles throughput each experiment. The network traffic stays same for the duration of the experiment. The slotted ALOHA with BEB algorithm is used as the random access scheme in the RA channel. The length of the time slot is assumed the same for two protocols. Network delay is due to access delay and service delay. Propagation delay between mobile and BS are assumed negotiable. Title : On/Off Source Model Silence State α Active state A β 2014-15, IJIRIS- All Rights Reserved Page -20
Flow Model International Journal of Innovative Research in Information Security (IJIRIS) ISSN: 2349-7017(O) Define Problem Gather Data Build Models Run Simulation Analyzed Result Make Decision Generate Cell Rate Algorithm Arrival of a cell K at time t a (k) TAT < TAT = T a (K) TAT = T a (K) TAT <T a (K)+L TAT = TAT+1 6. QOS CHALLENGES AND REQUIREMENTS Cell loss ratio of the number of cells of the number of cells lost in the network to the number of cells lost. Cell transfer delay experienced by a cell between network entry and exit points. It includes propagation delay and queuing delay and service time at queuing points. Cell delay variation[9] is a measure of cell transfer delay. Packet cell rate the maximum number of instantaneous rate at which the user will transmit. Sustainable cell rate is the average rate as measured over a long internal. Cell loss ratio the number of cells that are lost in the network due to error or congestion are not delivered to the destination. Cell loss ratio = Number of lost cells / Number of transmitted cells Network flexibility is becoming central to enterprise strategy. Traffic is fractal and bursty. Interactive applications such as voice and video have stringent bandwidth and latency demands. Multiple applications requirement are being combined into consolidated corporate utility networks. Web browsing, email, file transfer or other low priority or bulk traffic leave little space for critical transaction traffic leading to bandwidth connection and latency problems. Decision have to be made as to who control and how they control and competing demand for network service and backbone connectivity. Fair share = Target rate / Number of active connections 2014-15, IJIRIS- All Rights Reserved Page -21
7. PERFORMANCE EVALUATION The long term network utilization is equal to utility. The long term network stability is guaranteed. The long term QOS for unconcentrate source[10] is guaranteed. The long term losses for the controllable group of traffic are also bounded at the same value as for the uncontrollable sources. Robustness against traffic are traffic uncertainties and connections and disconnections without sacrificing network throughput. Tolerance of fairly long propagation delays. Fairness among different flows was used to evaluate the proposed scheme especially it was investigated if the proposed scheme is TCP friendly i.e. how fairly the multicast flow controlled by the proposed scheme share the bandwidth with a competing TCP flow. Responsiveness in order to effective feedback based congestion control scheme must react in a timely fashion to changes in the network congestion status. Scalability is another important performance measure of a multicast congestion scheme. The degree of throughput degradation as the group size increase was used to evaluate the scalability of the proposed scheme. CONCLUSION We have presented the performance of VP based ring architecture based on ATM network and ADM for carrying multimedia video, voice and data traffic. I have presented a method called a control mechanism which beans an acceptable character for the integration of voice and video data traffic on the proposed ATM network. The simulation result clearly shows that it is an efficient and simple method which adopt the ratios of the voice and video traffic on the network. The simulation result also confirms its efficient to adapt the ratios of all traffic and provides fairness among traffic which depends on the applied offered load of each traffic it is promising enough. The application of sliding modes and linear quadratic optimization techniques in the design of flow control allows for eliminating data losses and achieving the maximum throughput in the communication system. The favorable properties of the designed controllers are maintained even if the feedback information necessary for rate adjustment is accessible at irregular time instant the propagation delays are determined with limited accuracy and sources do not always follow the controller command due to internal or external transfer limitations. Acronyms VC Virtual Circuit VP Virtual Path QOS Quality of Service TCP Transmission Control Protocol VBR Variable Bit Rate IP Internet Protocol ABR Available Bit Rate TAT Total Arrival Time REFERENCES [1]. Integrated Traffic Control Mechanism for ATM Networks by Shang-Yi-Lu, December 1994. [2]. Intelligent Techniques for VBR Traffic Control in ATM Networks by Arif-Al-Hammadi, March 2000. [3]. Some Aspects of Traffic Control and Performance Evaluation of ATM Networks by Fan. Zhong, September 1997 [4]. Video Transmission on ATM Networks by Yun-Chang-Chen, November 1993. [5]. Quality of Service in ATM Networks by Domenico Ferrari, December 1990. [6]. Quality of Service for Broadband Satellite Internet ATM and IP Services in Networks by by Sastri L Kota, December 2002. [7]. Modelling and Analysis of Self Similar Traffic in ATM Networks by Rajab Faraj, Jun 2000. [8]. Modelling and Simulation of Traffic Control Mechanism in ATM Networks by Sakshi Kaushal, August 2008. [9]. Traffic Management of the ABR Service Category in ATM Networks by Abhijit S Pandya, November 1998. [10]. ATM Technology for Broadband Telecommunication Networks by R. Bolla, December 1997. 2014-15, IJIRIS- All Rights Reserved Page -22