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Data envelopment analysis with slacks model for energy efficient multicast over coded packet wireless networks
Author(s) -
Ajibesin Adeyemi Abel,
Ventura Neco,
Murgu Alexandru,
Chan H. Anthony
Publication year - 2014
Publication title -
iet science, measurement and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.418
H-Index - 49
eISSN - 1751-8830
pISSN - 1751-8822
DOI - 10.1049/iet-smt.2013.0195
Subject(s) - multicast , computer science , data envelopment analysis , computer network , network packet , wireless , telecommunications , mathematical optimization , mathematics
Green communication has recorded much attention in industry, academia and government. It has been recorded that information communication and technology nodes consume roughly 3% of the world‐wide energy supply and are responsible for 2% of the global carbon dioxide (CO 2 ) emission. As a result, researchers have devoted huge attention to prevent its growth. In order to address this problem we studied coded packet approach, which is the current method of minimising energy in wireless multicast networks. Then, we propose novel approaches that are based on data envelopment analysis (DEA) to further optimise energy consumption in wireless multicast networks. We found that existing approaches to energy efficient multicast are unsuitable for evaluating efficiency adequately. This paper takes the position that true efficiency evaluation is obtained when both inputs and outputs with multiple variables are considered in measuring performance using ratios of weighted outputs to weighted inputs. As a result, we developed the input‐oriented variable return to scale (VRS) envelopment with slacks models for energy efficiency in ad hoc wireless multicast networks. We explored the random linear network coding (RLNC) based on simulation approach and compared the results with the input‐oriented VRS DEA envelopment with slacks approach. The results show the DEA approach substantially saves energy compared to the RLNC. Furthermore, we show that DEA method has the capability to identify which ad hoc network is inefficient and projected them onto the efficient frontier.

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