Name
Abstract | ||
|---|---|---|
The diminishing size and battery requirements of mobile devices restrict the scope of computations possible on such devices and motivate approaches that support the selective offloading of computations to remote resources. With a variety of resources available to potentially host offloaded computations -- such as cloud-provisioned resources, and devices within a user's personal or social network -- a key challenge lies in architecting a framework that enables applications to seamlessly discover available services, effectively and securely communicate with them, and be presented with API interfaces that hide the complexities associated with managing the interactions with a remote device from applications and present the abstraction of a local device. In this paper, we outline a framework that addresses these challenges by layering APIs and an offload infrastructure upon a virtual networking substrate that supports TCP/IP networking and widely-used resource discovery protocols. An intelligent runtime scheduling layer monitors the execution environment and provides opportunistic remote offloads based on the performance requirements, offload benefits and expendable power. We demonstrate the feasibility of the approach through experiments that evaluate end-to-end application execution times and energy consumption in offloaded mobile devices, as well as the ability to support universal plug-and-play (UPnP) resource discovery in both local- and wide-area environments. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1145/2342509.2342516 | MCC@SIGCOMM |
Keywords | Field | DocType |
cloud-provisioned resource,opportunistic remote offloads,mobile device,end-to-end application execution time,remote resource,social networking-inspired accelerator,local device,offload benefit,remote device,available service,execution environment,social network,secure communication | Social network,Scheduling (computing),Computer science,Computer network,Real-time computing,Distributed computing,Virtual network,Large segment offload,.NET Remoting,Universal Plug and Play,Parallel computing,Mobile device,Energy consumption | Conference |
Citations | PageRank | References |
5 | 0.44 | 6 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Heungsik Eom | 1 | 31 | 2.99 |
| Pierre St. Juste | 2 | 63 | 6.68 |
| Renato Figueiredo | 3 | 87 | 6.67 |
| Omesh Tickoo | 4 | 389 | 31.58 |
| Ramesh Illikkal | 5 | 481 | 33.98 |
| Ravishankar Iyer | 6 | 720 | 35.52 |