Review on pre-fetching for Mobile Cloud Computing

Performance analysis of time and cost efficient data pre-fetching in mobile cloud computing

“…By historical access, it applies a proper mining information to identify the metadata by AMP. Table 2.2, provides a summary of pros and cons in the previously studied approaches in this report, and it is similar to the work the author did in [5]. [19] Proposed a framework to enhance the quality of video services for mobile users, which includes two parts: cloud assisted adaptive video energy and cost regarding the usage patterns of mobile users Pre-fetching is considered as the best way to handle latency problems, however over using this method over time may cause overhead storage, and may lead to network congestion.…”

“…Considering the above conditions, we will categorize the previous work done in this area into tables and have a comparison between them [5].…”

“…Considering the major limitations MCC faces such a battery, storage and bandwidth, the pre-fetching approaches were proposed. MCC architecture can be summarized in three layers: presentation phase, application phase and database phase [5]. In the model presented in Fig.…”

“…Compared with other ML approaches it does not need a large amount of input from analysts [5], [19]. CART is a strong decision tree for data mining, pre-processing and predictive modelling Singh et al [30].…”

“…Table 2.3 shows a comparison of the ML approaches on prefetching methods, their pros and cons [5]. Consequently, in this review, ML schemes will be used to optimize the outcome that is utilized for the pre-fetching.…”