In cloud storage applications where the data is shared by multiple mobile users, it is essential to provide the consistency among mobile users by means of appropriate synchronization algorithms. In particular, if the data is frequently updated and the number of mobile users sharing the data is large, the synchronization traffic can be significant. Moreover, the excessive synchronization traffic in mobile networks is more important in terms of radio resource utilization and energy consumption. In this paper, we propose an efficient delta synchronization (EDS) algorithm that aggregates the updated data to reduce the synchronization traffic and synchronizes the aggregated one periodically to satisfy the consistency. To find out the optimal policy for the aggregation and the periodical synchronization, an optimization problem is formulated as a Markov decision process (MDP) and a value iteration algorithm is presented for computing the stationary deterministic policy. Numerical results demonstrate that EDS can choose the optimal action that strikes a balance between the reduction of the synchronization traffic and the satisfaction of the consistency.
Bibliographical noteFunding Information:
This work was supported in part by NRF of Korea Grant funded by the Korean Government (No. NRF-2014R1A2A1A12066986) and in part by the R&D program of MOTIE/KEIT (No. 10051306). A preliminary version of this paper was presented at the IEEE International Conference on Cloud Networking (CloudNet) 2014, Luxembourg, October 2014 .
- Cloud storage applications
- Markov decision process (MDP)
- efficient delta synchronization
ASJC Scopus subject areas
- Hardware and Architecture
- Computer Science Applications
- Computer Networks and Communications
- Information Systems and Management