Name
Abstract | ||
|---|---|---|
Wearable computing becomes an emerging computing paradigm for various recently developed wearable devices, such as Google Glass and the Samsung Galaxy Smartwatch, which have significantly changed our daily life with new functions. To magnify the applications on wearable devices with limited computational capability, storage, and battery capacity, in this paper, we propose a novel three-layer architecture consisting of wearable devices, mobile devices, and a remote cloud for code offloading. In particular, we offload a portion of computation tasks from wearable devices to local mobile devices or remote cloud such that even applications with a heavy computation load can still be upheld on wearable devices. Furthermore, considering the special characteristics and the requirements of wearable devices, we investigate a code offloading strategy with a novel just-in-time objective, i.e., maximizing the number of tasks that should be executed on wearable devices with guaranteed delay requirements. Because of the NP-hardness of this problem as we prove, we propose a fast heuristic algorithm based on the genetic algorithm to solve it. Finally, extensive simulations are conducted to show that our proposed algorithm significantly outperforms the other three offloading strategies. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/TETC.2014.2387688 | IEEE Trans. Emerging Topics Comput. |
Keywords | Field | DocType |
mobile devices,wearable computers,wearable computing,samsung galaxy smartwatch,delay requirements,np-hard problem,google glass,remote cloud,wearable devices,code offloading,fast heuristic algorithm,computational complexity,cloud,genetic algorithm,genetic algorithms,just-in-time,cloud computing,mobile computing,just-in-time code offloading,np hard problem,computer architecture,approximation algorithms | Mobile computing,Heuristic (computer science),Wearable computer,Computer science,Real-time computing,Mobile device,Body area network,Wearable technology,Smartwatch,Embedded system,Cloud computing | Journal |
Volume | Issue | ISSN |
3 | 1 | 2168-6750 |
Citations | PageRank | References |
22 | 0.84 | 17 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zixue Cheng | 1 | 411 | 52.10 |
| Peng Li | 2 | 207 | 18.60 |
| Junbo Wang | 3 | 35 | 3.07 |
| Song Guo | 4 | 3431 | 278.71 |