Data Envelopment Analysis (DEA) is an operational research tool that is used for measuring the performance efficiency of an algorithm or organization. In this paper, DEA is applied on the simulation results of an Improved Network Coding Algorithm (INCA) with two and three performance in order to establish the performance efficiency of the two algorithms in terms of bandwidth utilization during video conferencing over a wireless network. Most researches which focus largely on determining the effectiveness of the INCA in terms of bandwidth consumption during video conferencing. However, this approach which uses DEA, the simulation results showed that the INCA with two parameters is the most cost-Efficient algorithm in terms of performance than the INCA with three parameters.
Multicasting over wireless network has been an area of intensive research and many researchers have employed the use of algorithms for addressing multicast problems. With the fast development in technology and the use of multimedia applications, efficient multicasting over the internet is taking the center stage. For this back drop, the review of some multicast algorithms over wireless network becomes compulsory with the aim of addressing some of the challenges encountered and seeing the possibilities of implementing these algorithms in real time situations. In this paper, we have reviewed some multicast algorithms developed based on network coding based multicast with the view of recognizing some of their strengths and weakness in order to open wide areas for future research and applications.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.