Keep Fresh: Real-Time Data Retrieval with Speed Adaptation in Mobile Cyber-Physical Systems
- Resource Type
- Conference
- Authors
- Fu, Chenchen; Qiu, Xiaoxing; Yun, Zelin; Han, Song; Wu, Weiwei; Xue, Chun Jason
- Source
- 2021 IEEE Real-Time Systems Symposium (RTSS) RTSS Real-Time Systems Symposium (RTSS), 2021 IEEE. :304-315 Dec, 2021
- Subject
- Aerospace
Communication, Networking and Broadcast Technologies
Computing and Processing
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Performance evaluation
Schedules
Heuristic algorithms
Data integrity
Cyber-physical systems
Real-time systems
Mobile handsets
Real time data retrieval
cyber-physical systems
dynamic programming
temporal validity
availability
- Language
- ISSN
- 2576-3172
Mobile devices have been increasingly deployed in large-scale cyber-physical systems (CPS) to traverse the field and retrieve data measurements from designated physical entities with stringent performance requirements. This work studies the availability-constrained real-time data retrieval problem in CPS with a speed adjustable mobile device (AFDR-SA). The goal is to maintain the temporal validity of the real-time data to be retrieved in the system while meeting the data availability constraints imposed by the communication range between the mobile device and the physical entities. A dynamic programming (DP)-based optimal algorithm is proposed for a special but commonly presented scenario where the retrieval times of individual data items are of the same length. Based on this optimal algorithm, an effective heuristic method is further developed for the general case where data items can have arbitrary retrieval times. The effectiveness of the proposed methods are validated through extensive experiments. Our results demonstrate the optimality of the DP-based algorithm, and show that the heuristic method outperforms the state-of-the-art schemes and performs close to the optimal solution obtained by the exhaustive search with much less computational overhead.