Software-defined networking-based resource management: data offloading with load balancing in 5G HetNet

The explosive growth of mobile data traffic and the shortage of the available spectral resources have created new challenges for future cellular networks. In particular, resource management in heterogeneous network environment has become a critical issue. In this paper, we propose software-defined n...

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Vydané v:EURASIP journal on wireless communications and networking Ročník 2015; číslo 1; s. 1 - 13
Hlavní autori: Duan, Xiaoyu, Akhtar, Auon Muhammad, Wang, Xianbin
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Cham Springer International Publishing 23.06.2015
Springer Nature B.V
Predmet:
5G Wireless Mobile Technologies
Algorithms
Cellular communication
Communications Engineering
Engineering
Information Systems Applications (incl.Internet)
Load balancing (computing)
Networks
Resources management
Shortages
Signal,Image and Speech Processing
Traffic engineering
Traffic flow
Software-defined networking
HetNet
Load balancing
Resource management
Wi-Fi data offloading
Quality of service
ISSN:1687-1499, 1687-1472, 1687-1499
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Shrnutí:The explosive growth of mobile data traffic and the shortage of the available spectral resources have created new challenges for future cellular networks. In particular, resource management in heterogeneous network environment has become a critical issue. In this paper, we propose software-defined networking (SDN)-based resource management algorithms for future cellular network. Specifically, in this work, we have a threefold objective: i) alleviate spectrum shortage concerns by efficiently offloading traffic over the Wi-Fi network, ii) address network congestion by optimally balancing loads across multiple cells and iii) achieve the aforementioned objectives while taking network conditions and the end user quality-of-service (QoS) requirements into consideration. To this end, we present SDN-based partial data offloading and load balancing algorithms. The proposed algorithms exploit an SDN controller’s global view of the network and take optimized resource allocation decisions. We analyze the performance of the proposed algorithms under realistic network model. Moreover, we also present an analytical framework to quantify the delay incurred due to the SDN-based data processing and forwarding. Our analysis and system-level simulations show that the proposed load balancing algorithm significantly improves the equilibrium extent and network stability as compared to the baseline algorithms. On the other hand, the proposed partial data offloading algorithm is shown to satisfy end user’s quality-of-service while saving a significant amount of cellular resources.
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ISSN:1687-1499
1687-1472
1687-1499
DOI:10.1186/s13638-015-0405-3