Current mobile applications treat the end-user device as a "thin client," with all of the heavy computations being offloaded to an infrastructure cloud. However, the computational capabilities of mobile devices are constantly improving, and it is worthwhile considering whether an edge-cloud that consists purely of mobile devices (operating effectively as "thick clients") can perform as well as, or even better than, an infrastructure cloud. In this paper, we study the trade-offs between offloading computation to an infrastructure cloud versus retaining the computation within a mobile edge-cloud. To this end, we develop and run two classes of applications on both types of clouds, and we analyze the performance of the two clouds in terms of the time taken to run the application, along with the total amount of battery power consumed in both cases. Our results indicate that there are indeed classes of applications where an edge-cloud can outperform an infrastructure cloud in terms of both latency and battery power.
In 2010, over 20.3 million vehicles were recalled. Software issues related to automotive controls such as cruise control, anti-lock braking system, traction control and stability control, account for an increasingly large percentage of the overall vehicles recalled. There is a need for new and scalable methods to evaluate automotive controls in a realistic and open setting. We have developed AutoPlug, an automotive Electronic Controller Unit (ECU) test-bed to diagnose, test, update and verify controls software. AutoPlug consists of multiple ECUs interconnected by a CAN bus, a race car driving simulator which behaves as the plant model and a vehicle controls monitor in Matlab. As the ECUs drive the simulated vehicle, the physicsbased simulation provides feedback to the controllers in terms of acceleration, yaw, friction and vehicle stability. This closedloop platform is then used to evaluate multiple vehicle control software modules such as traction, stability and cruise control. With this test-bed we highlight approaches for runtime ECU software diagnosis and testing of the stability and performance of the vehicle. Code updates can be executed via a smart phone so drivers may remotely "patch" their vehicle. This closedloop automotive control test-bed allows the automotive research community to explore the capabilities and challenges of safe and secure remote code updates for vehicle recalls management. As the ECUs drive the simulated vehicle, the physicsbased simulation provides feedback to the controllers in terms of acceleration, yaw, friction and vehicle stability. This closedloop platform is then used to evaluate multiple vehicle control software modules such as traction, stability and cruise control. With this test-bed we highlight approaches for runtime ECU software diagnosis and testing of the stability and performance of the vehicle. Code updates can be executed via a smart phone so drivers may remotely "patch" their vehicle. This closedloop automotive control test-bed allows the automotive research community to explore the capabilities and challenges of safe and secure remote code updates for vehicle recalls management.
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