QoS Evaluation of BandwidthSchedulers in IPTV Networks OfferedSRD Fluid Video Traffic

Internet protocol TV (IPTV) is predicted to be the key technology winner in the future. Efforts to accelerate the deployment of IPTV centralized model which is combined of VHO, encoders, controller, access network and Home network. Regardless of whether the network is delivering live TV, VOD, or Time-shift TV, all content and network traffic resulting from subscriber requests must traverse the entire network from the super-headend all the way to each subscriber's Set-Top Box (STB).IPTV services require very stringent QoS guarantees When IPTV traffic shares the network resources with other traffic like data and voice, how to ensure their QoS and efficiently utilize the network resources is a key and challenging issue. For QoS measured in the network-centric terms of delay jitter, packet losses and bounds on delay. The main focus of this thesis is on the optimized bandwidth allocation and smooth datatransmission. The proposed traffic model for smooth delivering video service IPTV network with its QoS performance evaluation. According to Maglaris et al [5] First, analyze the coding bit rate of a single video source. Various statistical quantities are derived from bit rate data collected with a conditional replenishment inter frame coding scheme. Two correlated Markov process models (one in discrete time and one incontinuous time) are shown to fit the experimental data and are used to model the input rates of several independent sources into a statistical multiplexer. Preventive control mechanism which is to be include CAC, traffic policing used for traffic control.QoS has been evaluated of common bandwidth scheduler( FIFO) by use fluid models with Markovian queuing method and analysis the result by using simulator andanalytically, Which is measured the performance of the packet loss, overflow and mean waiting time among the network users.

QoS evaluation of Bandwidth Schedulers in IPTV Networks Offered SRD Fluid Video Traffic

Internet protocol TV (IPTV) is predicted to be the key technology winner in the future. Efforts to accelerate the deployment of IPTV centralized model which is combined of VHO, encoders, controller, access network and Home network. Regardless of whether the network is delivering live TV, VOD, or Time-shift TV, all content and network traffic resulting from subscriber requests must traverse the entire network from the super-headend all the way to each subscriber's Set-Top Box (STB). IPTV services require very stringent QoS guarantees When IPTV traffic shares the network resources with other traffic like data and voice, how to ensure their QoS and efficiently utilize the network resources is a key and challenging issue. For QoS measured in the network-centric terms of delay jitter, packet losses and bounds on delay. The main focus of this thesis is on the optimized bandwidth allocation and smooth data transmission. The proposed traffic model for smooth delivering video service IPTV network with its QoS performance evaluation. According to Maglaris et al [5] first, analyze the coding bit rate of a single video source. Various statistical quantities are derived from bit rate data collected with a conditional replenishment inter frame coding scheme. Two correlated Markov process models (one in discrete time and one in continuous time) are shown to fit the experimental data and are used to model the input rates of several independent sources into a statistical multiplexer. Preventive control mechanism which is to be including CAC, traffic policing used for traffic control. QoS has been evaluated of common bandwidth scheduler( FIFO) by use fluid models with Markovian queuing method and analysis the result by using simulator and analytically, Which is measured the performance of the packet loss, overflow and mean waiting time among the network users.

PERFORMANCE EVOLUTION OF PEER TO PEER NETWORKS

This thesis work concerns about the Performance evolution of peer to peer networks, where we used different distribution technique’s of peer distribution like Weibull, Lognormal and Pareto distribution process. Then we used a network simulator to evaluate the performance of these three distribution techniques.During the last decade the Internet has expanded into a world-wide network connecting millions of hosts and users and providing services for everyone. Many emerging applications are bandwidth-intensive in their nature; the size of downloaded files including music and videos can be huge, from ten megabits to many gigabits. The efficient use of network resources is thus crucial for the survivability of the Internet. Traffic engineering (TE) covers a range of mechanisms for optimizing operational networks from the traffic perspective. The time scale in traffic engineering varies from the short-term network control to network planning over a longer time period.Here in this thesis work we considered the peer distribution technique in-order to minimise the peer arrival and service process with three different techniques, where we calculated the congestion parameters like blocking time for each peer before entering into the service process, waiting time for a peers while the other peer has been served in the service block and the delay time for each peer. Then calculated the average of each process and graphs have been plotted using Matlab to analyse the results

Identifiering av parametrar till ackumulatortanken Solus1050 från consolar - en metodbeskrivning

This report describes the work done creating a computer model of a kombi tank from Consolar. The model was created with Presim/Trnsys and Fittrn and DF were used to identify the parameters. Measurements were carried out and were used to identify the values of the parameters in the model. The identifications were first done for every circuit separately. After that, all parameters are normally identified together using all the measurements. Finally the model should be compared with other measurements, preferable realistic ones. The two last steps have not yet been carried out, because of problems finding a good model for the domestic hot water circuit.The model of the domestic hot water circuit give relatively good results for low flows at 5 l/min, but is not good for higher flows. In the report suggestions for improving the model are given. However, there was not enough time to test this within the project as much time was spent trying to solve problems with the model crashing. Suggestions for improving the model for the domestic circuit are given in chapter 4.4. The improved equations that are to be used in the improved model are given by equation 4.18, 4.19 and 4.22.Also for the boiler circuit and the solar circuit there are improvements that can be done. The model presented here has a few shortcomings, but with some extra work, an improved model can be created. In the attachment (Bilaga 1) is a description of the used model and all the identified parameters.A qualitative assessment of the store was also performed based on the measurements and the modelling carried out. The following summary of this can be given: Hot Water PreparationThe principle for controlling the flow on the primary side seems to work well in order to achieve good stratification. Temperatures in the bottom of the store after a short use of hot water, at a coldwater temperature of 12°C, was around 28-30°C. This was almost independent of the temperature in the store and the DHW-flow.The measured UA-values of the heat exchangers are not very reliable, but indicates that the heat transfer rates are much better than for the Conus 500, and in the same range as for other stores tested at SERC.The function of the mixing valve is not perfect (see diagram 4.3, where Tout1 is the outlet hot water temperature, and Tdhwo and Tdhw1 is the inlet temperature to the hot and cold side of the valve respectively). The outlet temperature varies a lot with different temperatures in the storage and is going down from 61°C to 47°C before the cold port is fully closed. This gives a problem to find a suitable temperature setting and gives also a risk that the auxiliary heating is increased instead of the set temperature of the valve, when the hot water temperature is to low.Collector circuitThe UA-value of the collector heat exchanger is much higher than the value for Conus 500, and in the same range as the heat exchangers in other stores tested at SERC.Boiler circuitThe valve in the boiler circuit is used to supply water from the boiler at two different heights, depending on the temperature of the water. At temperatures from the boiler above 58.2°C, all the water is injected to the upper inlet. At temperatures below 53.9°C all the water is injected to the lower inlet. At 56°C the water flow is equally divided between the two inlets. Detailed studies of the behaviour at the upper inlet shows that better accuracy of the model would have been achieved using three double ports in the model instead of two. The shape of the upper inlet makes turbulence, that could be modelled using two different inlets. Heat lossesThe heat losses per m3 are much smaller for the Solus 1050, than for the Conus 500 Storage. However, they are higher than those for some good stores tested at SERC. The pipes that are penetrating the insulation give air leakage and cold bridges, which could be a major part of the losses from the storage. The identified losses from the bottom of the storage are exceptionally high, but have less importance for the heat losses, due to the lower temperatures in the bottom. High losses from the bottom can be caused by air leakage through the insulation at the pipe connections of the storage.