Abstract The increasing popularity of mobile devices calls for effective execution of mobile applications. A lot of research has been conducted on properly splitting and outsourcing computing intensive tasks to exter- nal resources (e.g., public clouds) by considering insufficient computing resources on mobile devices. However, little attention has been paid to the overall users' response time, where the network may dominate. In this talk, we will discuss how we can effectively minimize users' response time for mobile applications. We consider both the impact of the network and the computing itself. We first show that outsourcing to nearby residential computers may be more advantageous than pub- lic clouds for mobile applications due to network impact. Furthermore, to speed up computing, we leverage parallel processing techniques. Ac- cordingly, we propose to build Mobile MapReduce (MMR) to effectively execute outsource computing intensive mobile applications. Based on the original MapReduce framework, a new scheduling model is built in MMR that can always leverage the best computing resources to conduct computation with appropriate parallel processing. To demonstrate the performance of MMR, we run several real-world applications, such as text searching, face detection, and image processing, on the prototype. The results show great potentials of MMR in minimizing the response time of the outsourced mobile applications. Speaker Bio Mohammed A. Hassan is a PhD student at George Mason University. His research interest includes mobile-cloud computing. He completed his BSc in CSE from Bangladesh University of Engineering and Technology in 2006.