Background Traffic Load Aware Video Class-lecture Client Admission in a Bandwidth Constrained Campus Network

Abstract

Video class-lecture streaming is regarded as a popular means in improving quality of teaching and learning in schools and universities. Several research findings reveal that, recorded lecture videos (streamed over the Internet) are a useful supplement to non-classroom learning. Despite knowing this importance, some schools or universities are reluctant to use video lecture streaming service in their campus network, thinking video streaming service would impose additional traffic load in their network. In fact, in a bandwidth constrained campus network, other regular traffic flows may experience lower throughput, packet drop and delay due to presence of class lecture video streaming traffic, resulting in deteriorating Quality of Experience (QoE) of campus users. In this paper, we propose video streaming service model for the bandwidth constrained campus networks. We refer to our solution as Class Lecture on Demand (CLD) service that can be easily adopted in a campus. CLD de nes the policies for admitting number of clients that request for video stream- ing service taking into account peak hour and o -peak hour background tra c load. This paper provides a detailed procedures, showing how a network administrator in a bandwidth constrained campus network can measure the maximum number class lecture streaming requests that a video streaming server should accommodated at di erent part of a day without affecting other traffic flows. Additionally, we provide an insightful discussion (policies) in order to make video lecture streaming in a bandwidth constrained campus network easily adopted

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