Abstract

The term "mobile cloud computing" refers  to a new computing paradigm that was developed to increase the capabilities of mobile devices. This kind of computing has been gaining more and more attention in recent years. Existing research focuses mostly on how to make optimal use of the computing power of an individual device by using the processing power of faraway cloud data centers or the capabilities of a local mobile cloud established by devices in the immediate vicinity. In contrast to the studies that have been done before, our research focuses on the question of how to enhance the performance of data sharing in a peer-to-peer mobile cloud, despite the existence of a restricted bandwidth as well as a dynamic and unpredictable wireless channel state. To be more specific, we first formulate the data transmission between devices as a utility maximization problem with the consideration of limited bandwidth, incentive participation, and the QoE (Quality of Experience) heterogeneity, based on incorporating a publish/subscribe component into the base station. This formulation takes into account the fact that there is a limited amount of bandwidth available. After that, a dynamic online method is built that does not need the future context (for example, channel status) of the mobile cloud. This algorithm is used to make the choice of data transmission and the selection of the communication interface concurrently. An exhaustive theoretical study demonstrates that the suggested algorithm is both optimum and successful in achieving its goals. Extensive testing is carried out in order to validate the findings of the study and demonstrate that the suggested algorithm is superior to the techniques that are already in use.

Keywords

• DTNS,
• performance,
• cloud,
• computing,
• algorithm,
• heterogeneity

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