Performance of Multicast Algorithms over Coded Packet Wireless Networks

Ajibesin, Adeyemi Abel; Ventura, Neco; Chan, H. Anthony; Murgu, A.; Egunsola, O.K.

doi:10.1109/uksim.2012.91

Cited by 9 publications

(7 citation statements)

References 22 publications

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“…With efficiency evaluation, the performance is based on the combination of both inputs and outputs rather than focusing on the outcome results (outputs) only. For example, in [33], the results presented based on average performance show that the performance of the RLNC algorithm in minimizing energy was degraded as the number of sinks increased but improved as the network size increased. This result has been shown to perform better than the existing algorithm when compared.…”

Section: Network Coding Performancementioning

confidence: 99%

Efficient Frontier and Benchmarking Models for Energy Multicast in Wireless Network Coding

Ajibesin¹

2018

Network Coding

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This chapter introduces efficiency frontier and benchmarking concepts to evaluate the efficiency performance of wireless networks for multicast energy. These concepts are efficiency models based on the data envelopment analysis (DEA) technique. The DEA framework allows network administrators to evaluate the technical efficiency and determine how the inefficient wireless networks will attain a targeted efficiency frontier. In order to achieve efficiency frontier and benchmark by a wireless network, this chapter presents several models including the envelopment and the slack. The envelopment model evaluates the technical efficiency scores of each wireless network, while the slack model shows how the inefficient wireless network achieves efficiency frontier. The benchmark model evaluates the efficiency reference set and the lambda values of each network. The efficiency frontier algorithm has shown that many of the wireless networks sampled are inefficient. However, the algorithm has capability to help the inefficient wireless networks to achieve efficiency frontier and benchmark with their peers that are fully efficient.

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Section: Network Coding Performancementioning

confidence: 99%

Efficient Frontier and Benchmarking Models for Energy Multicast in Wireless Network Coding

Ajibesin¹

2018

Network Coding

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“…Also reference [22] studied the performance of multicast algorithms over coded packet wireless network by using Network Coding Algorithm (NCA) and Multicast Incremental Power Algorithm (MIPA). They were particularly interested in showing the performance of network coding on multicast network when the network arcs were weighted.…”

Section: Review Of Some Multicast Algorithmmentioning

confidence: 99%

Multicast Algorithms over Wireless Networks Using Network Coding: A Review

Adedokun

Soja²,

Tekanyi³

2015

COM

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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.

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“…This feature helps in reducing the input resources utilised by the ad hoc wireless multicast networks. In order to achieve input minimisation, the dual of model (5), called the 'envelopment model' is considered [9,13] …”

Section: Input-oriented Vrs Dea Envelopment Modelmentioning

confidence: 99%

Data envelopment analysis with slacks model for energy efficient multicast over coded packet wireless networks

Ajibesin¹,

Ventura²,

Murgu³

et al. 2014

IET Science, Measurement & Technology

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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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Performance of Multicast Algorithms over Coded Packet Wireless Networks

Cited by 9 publications

References 22 publications

Efficient Frontier and Benchmarking Models for Energy Multicast in Wireless Network Coding

Efficient Frontier and Benchmarking Models for Energy Multicast in Wireless Network Coding

Multicast Algorithms over Wireless Networks Using Network Coding: A Review

Data envelopment analysis with slacks model for energy efficient multicast over coded packet wireless networks

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