IIT CSE Project Report on Packet Scheduling Algorithms to Support QOS in Networks

Introduction to Packet Scheduling Algorithms to Support QOS in Networks Project:

The best effort traffic is made possible only with the traditional packet switching networks. Communication services are required by the newer applications and it also allows the end consumers to transmit data with guarantee performance which is given in terms of bandwidth, delay delay variations and rate of loss. The packet algorithm choice should be packed scheduled and that can be used as switching nodes which is a crucial aspect in providing the quality service.

A literature survey covering is conducted by us and it includes various kinds of scheduling disciplines that provides guarantees of performance to the clients. In this paper, we have also compared scheduling disciplines that are selected for experimental studies using the process of simulation. Class based querying, weighed fair queueing and rate controlled static priority queueing are some of the disciplines that are chosen for study. CBR, ABR, UBR and VBR are some of fthe traffics that are chosen for experiments, video traffics, audio source models. RCSP extension designed for using as a model of new traffic. The use of this extension has also been studied for scheduling the flow of real-time. It uses CBQ  in a link sharing paradigm.

In this paper we have a packet scheduling algorithm that is used for routers in a network. For providing high quality service these algorithms are important in terms of delay variation, delay loss rate and bandwidth. Various scheduling disciplines have been surveyed and presented.

A simulation of the test bed platform is used for our study and it is made possible only with some selected scheduling disciplines. A common platform providing option is the main aim of this thesis and it also helps in comparing the performance level of scheduling disciplines. It helps in serving several traffic mixes along with their QOS requirements respectively. The simulation NS 5 is developed at the Lawrence Berkeley network laboratory.

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