process and abstract the features of data to useful information and knowledge are the breakthroughs on integrating the DKaaS with wireless networks.

Moreover, the SP who directly serves the end-user might be the one who has the most convinces to access the data. However, it is quite common that the SP may not have the data processing capability nor the data is meaningful to them. For example, the data obtained from wireless sensor networks or wearable devices may contain extra information that help the NSP to provide personalized and flexible services to the end-users. Thus, how to provide these data, compress these data or extract useful information and knowledge from them, can attract interests from different third parties from technique, business or social perspective are the most challenging parts. Beside, the data/knowledge acquisition and abstraction are also absorbing from network operation point-of-view, as the local data processing or introducing professionals of data mining may ease the data transmission over wirless/wired link and abstracted knowledge can help the network operator to run the network in a easier and cost-efficient way. Therefore, addressing these challenges can significantly help to realize the DKaaS concept and also open the arms of wireless networks to 