QoS evaluation of bandwidth schedulersin IPTV networks offered SRD fluidvideo traffic: a simulation study

IPTV is now offered by several operators in Europe, US and Asia using broadcast video over private IP networks that are isolated from Internet. IPTV services rely ontransmission of live (real-time) video and/or stored video. Video on Demand (VoD)and Time-shifted TV are implemented by IP unicast and Broadcast TV (BTV) and Near video on demand are implemented by IP multicast. IPTV services require QoS guarantees and can tolerate no more than 10-6 packet loss probability, 200 ms delay, and 50 ms jitter. Low delay is essential for satisfactory trick mode performance(pause, resume,fast forward) for VoD, and fast channel change time for BTV. Internet Traffic Engineering (TE) is defined in RFC 3272 and involves both capacity management and traffic management. Capacity management includes capacityplanning, routing control, and resource management. Traffic management includes (1)nodal traffic control functions such as traffic conditioning, queue management, scheduling, and (2) other functions that regulate traffic flow through the network orthat arbitrate access to network resources. An IPTV network architecture includes multiple networks (core network, metronetwork, access network and home network) that connects devices (super head-end, video hub office, video serving office, home gateway, set-top box). Each IP router in the core and metro networks implements some queueing and packet scheduling mechanism at the output link controller. Popular schedulers in IP networks include Priority Queueing (PQ), Class-Based Weighted Fair Queueing (CBWFQ), and Low Latency Queueing (LLQ) which combines PQ and CBWFQ.The thesis analyzes several Packet Scheduling algorithms that can optimize the tradeoff between system capacity and end user performance for the traffic classes. Before in the simulator FIFO,PQ,GPS queueing methods were implemented inside. This thesis aims to implement the LLQ scheduler inside the simulator and to evaluate the performance of these packet schedulers. The simulator is provided by ErnstNordström and Simulator was built in Visual C++ 2008 environmentand tested and analyzed in MatLab 7.0 under windows VISTA.

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.

Role of dietary fats in modulating cardiometabolic risk during moderate weight gain : a randomized double-blind overfeeding trial (LIPOGAIN study)

BACKGROUND: Whether the type of dietary fat could alter cardiometabolic responses to a hypercaloric diet is unknown. In addition, subclinical cardiometabolic consequences of moderate weight gain require further study. METHODS AND RESULTS: In a 7-week, double-blind, parallel-group, randomized controlled trial, 39 healthy, lean individuals (mean age of 27±4) consumed muffins (51% of energy [%E] from fat and 44%E refined carbohydrates) providing 750 kcal/day added to their habitual diets. All muffins had identical contents, except for type of fat; sunflower oil rich in polyunsaturated fatty acids (PUFA diet) or palm oil rich in saturated fatty acids (SFA diet). Despite comparable weight gain in the 2 groups, total: high-density lipoprotein (HDL) cholesterol, low-density lipoprotein:HDL cholesterol, and apolipoprotein B:AI ratios decreased during the PUFA versus the SFA diet (-0.37±0.59 versus +0.07±0.29, -0.31±0.49 versus +0.05±0.28, and -0.07±0.11 versus +0.01±0.07, P=0.003, P=0.007, and P=0.01 for between-group differences), whereas no significant differences were observed for other cardiometabolic risk markers. In the whole group (ie, independently of fat type), body weight increased (+2.2%, P<0.001) together with increased plasma proinsulin (+21%, P=0.007), insulin (+17%, P=0.003), proprotein convertase subtilisin/kexin type 9, (+9%, P=0.008) fibroblast growth factor-21 (+31%, P=0.04), endothelial markers vascular cell adhesion molecule-1, intercellular adhesion molecule-1, and E-selectin (+9, +5, and +10%, respectively, P<0.01 for all), whereas nonesterified fatty acids decreased (-28%, P=0.001). CONCLUSIONS: Excess energy from PUFA versus SFA reduces atherogenic lipoproteins. Modest weight gain in young individuals induces hyperproinsulinemia and increases biomarkers of endothelial dysfunction, effects that may be partly outweighed by the lipid-lowering effects of PUFA. CLINICAL TRIAL REGISTRATION URL: http://ClinicalTrials.gov. Unique identifier: NCT01427140.