Two Michigan Papers Share the Best Paper Award at MobiSys 2015
In an unusual turn of events, we've tied with ourselves for this one.
Two papers with authors from Michigan shared the best paper award at the 13th International Conference on Mobile Systems, Applications, and Services (MobiSys 2015), which took place May 18-22 in Florence, Italy.
The first, entitled “Accelerating Mobile Applications through Flip-Flop Replication,” was authored by Mark S. Gordon, David Ke Hong, Prof. Peter M. Chen, Prof. Jason Flinn, Prof. Scott Mahlke, and Prof. Z. Morley Mao. All of the authors are from Michigan.
The paper introduces Tango, a new method for using a remote server to accelerate the performance of mobile applications. Tango replicates the application and executes it on both the client and the server. Since either the client or the server execution may be faster during different phases of the application, Tango allows either replica to lead the execution. Tango attempts to reduce user-perceived application latency by predicting which replica will be faster and allowing it to lead execution and display output, leveraging the better network and computation resources of the server when the application can benefit from it. It uses techniques inspired by deterministic replay to keep the two replicas in sync, and it uses flip-flop replication to allow leadership to float between replicas. Tango currently works for several unmodified Android applications. In the researchers’ results, two computation-heavy applications obtain up to 2–3x speedup, and five network applications obtain from 0–2.6x speedup.
The second, entitled “Outatime: Using Speculation to Enable Low-Latency Continuous Interaction for Mobile Cloud Gaming,” was a collaboration from amongst Michigan, Microsoft Research, and other authors. Michigan authors included Kyungmin Lee and Prof. Jason Flinn.
The paper presents Outatime, a speculative execution system for mobile cloud gaming that is able to mask up to 120ms of network latency. Outatime renders speculative frames of future possible outcomes, delivering them to the client one entire RTT (round trip time) ahead of time, and recovers quickly from mis-speculations when they occur. Clients perceive little latency. To achieve this, Outatime combines: 1) future state prediction; 2) state approximation with image-based rendering and event time-shifting; 3) fast state checkpoint and rollback; and 4) state compression for bandwidth savings. The researchers evaluated the Outatime speculation system using two high quality, commercially-released games: a twitch-based first person shooter, Doom 3, and an action role playing game, Fable 3. Through user studies and performance benchmarks, they found that players strongly prefer Outatime to traditional thin-client gaming where the network RTT is fully visible, and that Outatime successfully mimics playing across a low-latency network.