Abstract
We focus on utilizing offloading to reduce the energy consumption of the mobile devices or the execution time of event analysis algorithms, and improve the system performance of crowdsensing systems. Event analysis algorithms analyze the sensory data that are collected by mobile users to determine whether events happen or not. The overhead of event analysis algorithms can be offloaded to cloud servers to achieve energy efficiency or better performance. Since offloading benefits depend on many factors, such as network latency and computation capability, we propose an offloading decision algorithm, which considers the context information to decide whether to offload the computation to cloud servers. To show that offloading can be used in existing applications, we develop an APK analysis tool to analyze the third-party applications. Without the source code, the tool determines which part of an application can be offloaded and modify the application to be offload version. To evaluate the impact of crowdsensing system with offloading, we implement a crowdsensing prototype system and integrate offloading technique into the system. The prototype system involves (i) a broker, (ii) offload servers, and (iii) clients. We implement 2 event analysis algorithms in the system. Our experiments show that our offloading decision algorithm improves the system performance through intelligently making offloading decisions, and the accuracy is up to 80\%. The high accuracy significantly reduces the penalty of suboptimal offloading decision. Moreover, by utilizing the APK analysis tool, we analyze and modify third-party applications. The results of offloading the third-party applications show that offloading can be used in existing third-party applications. Last, we conduct experiments with the crowdsensing prototype system with offloading and show that offloading improves the performance of the crowdsensing system.