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The future market demand for the wireless broadband services, internet of things, machine to machine communications, and wireless data offload requires the deployment of the next generation wireless networks, which will need a rapid and a more flexible access to the radio frequency spectrum.
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Under the common scenario of data offloading process, APOs have the higher precedence than MNO; after APO i 's data offloading decisions, MNO can plan to effectively allocate its resource to obtain the most profitable usage.
Mobile data offloading is a promising strategy to alleviate the burden on the cellular network by leveraging unused bandwidth across different wireless technologies.
Mobile data offloading has been proposed as a solution for the network congestion problem that is continuously aggravating due to the increase in mobile data demand.
Additionally, some flows can be adaptively offloaded to the cognitive radio network using data offloading techniques.
Fig. 8 Offloaded data volume by Wi-Fi data offloading in terms of different arriving traffic volumes.
It is seen that the proposed data offloading schemes achieve much higher MUE sum rate than the scheme without data offloading.
In the next subsection, we present an SDN-based data offloading algorithm.
In this section, we evaluate the performance of the proposed partial data offloading scheme.
In [11], authors have proposed an energy-aware data offloading scheme for cloud RAN.
The main steps of the proposed data offloading scheme are given next (Fig. 2) (Algorithm 1).
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