An Empirical Study of Mobile Code Offloading in Unpredictable Environments
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Date
2023
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Abstract
Mobile code offloading is a well-known technique for enhancing the capabilities of mobile platforms by transparently leveraging the resources to the cloud. Although this technique has been studied for years, little empirical evidence exists to demonstrate its alleged benefits in terms of performance in real-life situations. All studies conducted on this topic have so far been relegated to controlled environments in laboratory settings. As such, there is no evidence of how and how well this technique performs in real-life scenarios, where network unreliability is the norm. In this work, we present the first empirical study of an Android mobile application integrated with a code offloading framework being tested in the wild. We distributed an application that contains a set of benchmarks in APK format and deployed it on a wide gamut of Android devices to which we had no physical access. We carefully detail the methodology and infrastructure we used to monitor the benchmarks’ performance of 18 devices. Overall, our results show that the accuracy of the decision-making engine is heavily affected by a couple of factors, mainly the network diagnosis and connection type. Therefore, determining whether or not it is more convenient to execute a given task in the cloud is a difficult task. We summarize five lessons we learned by performing our experiment that we believe should be considered for future experiments in this area.
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Keywords
Android, Empirical studies, Mobile cloud computing, Mobile code offloading