Energy Efficiency in Software Defined Networking: A Survey

被引：0
作者：
Rout S. [1 ]
Sahoo K.S. [2 ]
Patra S.S. [3 ]
Sahoo B. [4 ]
Puthal D. [5 ]
机构：
[1] Department of CSE, Silicon Institute of Technology, Odisha, Bhubaneswar
[2] Department of Computer Science and Engineering, SRM University, AP, Amaravati
[3] School of Computer Applications, KIIT University, Odisha, Bhubaneswar
[4] Department of CSE, NIT Rourkela, Odisha, Rourkela
[5] School of Computing, Newcastle University, Newcastle upon Tyne
来源：
SN Computer Science | 2021年 / 2卷 / 4期
关键词：
End-host aware; Energy efficiency; Rule placement; SDN; Software defined networking; Traffic aware;
D O I：
10.1007/s42979-021-00659-9
中图分类号：
学科分类号：
摘要：
Software defined networking has solved many challenging issues in the field of networking industry. It separates the control plane from the data forwarding plane. This makes SDN to be more powerful than traditional networking. However, energy cost enhances the overall network cost. Therefore, this issue needs to be addressed to improve design requirements and boost the networking performance. In this article, several energy efficiency techniques have been discussed. To represent it in more detail, a thematic taxonomy of energy efficiency techniques in SDN is given by considering several technical studies of the past research. These studies have been categorized into three sub categories of traffic aware model, end-host aware model and finally rule placement. These models are provided with detailed objective functions, parameters, constraints and detailed information. Furthermore, useful visions of each approach, its advantages and disadvantages and compressive analysis of energy efficiency techniques are also discussed. Finally, the paper is highlighted with the future directions for energy efficiency in SDN. © 2021, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.
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共 106 条
[1]  
Bannour F., Souihi S., Mellouk A., Distributed SDN control: Survey, taxonomy, and challenges, IEEE Commun Surv Tutor, 20, 1, pp. 333-354, (2018)
[2]  
Rafique W., Et al., Complementing IoT services through software defined networking and edge computing: a comprehensive survey, IEEE Commun Surv Tutor, 22, 3, pp. 1761-1804, (2020)
[3]  
Habibi P., Et al., Fog Computing: A Comprehensive Architectural Survey, IEEE Access, 8, pp. 69105-69133, (2020)
[4]  
Javadzadeh G., Amir M.R., Fog computing applications in smart cities: a systematic survey, Wirel Netw., 26, 2, pp. 1433-1457, (2020)
[5]  
Markus A., Attila K., A survey and taxonomy of simulation environments modelling fog computing, Simul Model Pract Theory, 1, pp. 101-102, (2020)
[6]  
Welsh T., Elhadj B., On resilience in cloud computing: a survey of techniques across the cloud domain, ACM Comput Surv (CSUR), 53, 3, pp. 1-36, (2020)
[7]  
Zhu J., Et al., TRUS: towards the real-time route update scheduling in SDN for data centers, IEEE Access, 8, pp. 68682-68694, (2020)
[8]  
Emani C.K., Nadine C., Christophe N., Understandable big data: a survey, Comput Sci Rev, 17, pp. 70-81, (2015)
[9]  
Chahal M., Et al., A survey on software-defined networking in vehicular ad hoc networks: challenges, applications and use cases, Sustain Cities Soc, 35, pp. 830-840, (2017)
[10]  
Shoumy Nusrat J., Et al., Multimodal big data affective analytics: a comprehensive survey using text, audio, visual and physiological signals, J Netw Comput Appl, 149, (2020)
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