TY - GEN
T1 - The deployment of shared data objects among handheld and wearable devices
AU - Cheng, Sheng Wei
AU - Chang, Che Wei
AU - Chang, Yuan Hao
AU - Hsiu, Pi Cheng
AU - Tu, Chia Heng
PY - 2015/4/13
Y1 - 2015/4/13
N2 - With the great success on making phones smarter, vendors now plan on replicating the same idea on wearable accessories. Accordingly, applications on these devices are full of new possibilities to interact with users. However, in order to provide consistent user experience, it poses a major challenge on how to efficiently deploy shared application states among the devices. In this paper, we consider to minimize the data transmission latencies between the processes and the shared data objects on a set of mobile devices with distributed shared memory. The problem is proved to be NP-hard. Nevertheless, efficient solutions can still be obtained when special cases are considered. On one hand, we propose a polynomial-time optimal algorithm when the memory of each mobile device is segmented into blocks and each of the shared data objects is of single block. On the other hand, in order to provide a practical way to address the problem, we then propose a (1, ε) asymptotic approximation algorithm, where ε > 0 and can be arbitrarily small, with a 2-augmentation-bound of memory size. In the end, a series of simulations was conducted, and the results were very encouraging.
AB - With the great success on making phones smarter, vendors now plan on replicating the same idea on wearable accessories. Accordingly, applications on these devices are full of new possibilities to interact with users. However, in order to provide consistent user experience, it poses a major challenge on how to efficiently deploy shared application states among the devices. In this paper, we consider to minimize the data transmission latencies between the processes and the shared data objects on a set of mobile devices with distributed shared memory. The problem is proved to be NP-hard. Nevertheless, efficient solutions can still be obtained when special cases are considered. On one hand, we propose a polynomial-time optimal algorithm when the memory of each mobile device is segmented into blocks and each of the shared data objects is of single block. On the other hand, in order to provide a practical way to address the problem, we then propose a (1, ε) asymptotic approximation algorithm, where ε > 0 and can be arbitrarily small, with a 2-augmentation-bound of memory size. In the end, a series of simulations was conducted, and the results were very encouraging.
UR - http://www.scopus.com/inward/record.url?scp=84955486722&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84955486722&partnerID=8YFLogxK
U2 - 10.1145/2695664.2695766
DO - 10.1145/2695664.2695766
M3 - Conference contribution
AN - SCOPUS:84955486722
T3 - Proceedings of the ACM Symposium on Applied Computing
SP - 2245
EP - 2251
BT - 2015 Symposium on Applied Computing, SAC 2015
A2 - Shin, Dongwan
PB - Association for Computing Machinery
T2 - 30th Annual ACM Symposium on Applied Computing, SAC 2015
Y2 - 13 April 2015 through 17 April 2015
ER -