Online Mode Switch Algorithms for Maintaining Data Freshness in Dynamic Cyber-Physical Systems

Maintaining the freshness of real-time data is one of the crucial design issues in cyber-physical systems (CPS). Past studies have focused on designing update algorithms to minimize the workload imposed by a fixed set of update tasks while ensuring the temporal validity of data. In this paper, we revisit this problem in dynamic cyber-physical systems (DCPS) which may exhibit multi-modal behavior. Any solution to this problem must recognize that: (1) different update algorithms may be needed in different modes according to the workload in each mode, and (2) temporal validity of data must be maintained not only in each mode but also during the mode switch. To strike a balance between data freshness and system schedulability, we propose a utilization-based scheduling selection (UBSS) strategy. We first introduce two synchronous mode switch algorithms, named search-based switch (SBS) and adjustment-based switch (ABS) to search for the proper switch point online and execute all update tasks in the new mode synchronously. SBS checks for temporal validity at the beginning time slot of each idle period in the schedule, while ABS relaxes this restriction through schedule adjustment. To support immediate mode switch, we propose an asynchronous switch algorithm named instant switch (IS) to reduce the switch delay. IS schedules outstanding jobs from the old mode together with the jobs in the new mode using the least-available-laxity-first scheduling policy. Our experimental results demonstrate the effectiveness of these three algorithms. They also show that UBSS strategy can significantly outperform a single fixed update algorithm in terms of maintaining better data freshness while incurring only limited online switch overhead.

[1]  Insup Lee,et al.  Cyber-physical systems: The next computing revolution , 2010, Design Automation Conference.

[2]  Alan Burns,et al.  Mode changes in priority preemptively scheduled systems , 1992, [1992] Proceedings Real-Time Systems Symposium.

[3]  L. DiPippo,et al.  Real-Time Databases , 1995 .

[4]  Qiong Wang,et al.  On earliest deadline first scheduling for temporal consistency maintenance , 2008, Real-Time Systems.

[5]  Jörgen Hansson,et al.  Dynamic on-demand updating of data in real-time database systems , 2004, SAC '04.

[6]  Song Han,et al.  A deferrable scheduling algorithm for real-time transactions maintaining data freshness , 2005, 26th IEEE International Real-Time Systems Symposium (RTSS'05).

[7]  Jian-Jia Chen,et al.  Workload-Aware Partitioning for Maintaining Temporal Consistency upon Multiprocessor Platforms , 2011, 2011 IEEE 32nd Real-Time Systems Symposium.

[8]  Victor C. S. Lee,et al.  Workload-Efficient Deadline and Period Assignment for Maintaining Temporal Consistency under EDF , 2013, IEEE Transactions on Computers.

[9]  Rolf Ernst,et al.  Scenario Aware Analysis for Complex Event Models and Distributed Systems , 2007, 28th IEEE International Real-Time Systems Symposium (RTSS 2007).

[10]  Gultekin Özsoyoglu,et al.  Temporal and Real-Time Databases: A Survey , 1995, IEEE Trans. Knowl. Data Eng..

[11]  A. Morse,et al.  Basic problems in stability and design of switched systems , 1999 .

[12]  Alfons Crespo,et al.  Mode Change Protocols for Real-Time Systems: A Survey and a New Proposal , 2004, Real-Time Systems.

[13]  Song Han,et al.  Online Scheduling Switch for Maintaining Data Freshness in Flexible Real-Time Systems , 2009, 2009 30th IEEE Real-Time Systems Symposium.

[14]  Alan Burns,et al.  Schedulability analysis for mode changes in flexible real-time systems , 1998, Proceeding. 10th EUROMICRO Workshop on Real-Time Systems (Cat. No.98EX168).

[15]  James W. Layland,et al.  Scheduling Algorithms for Multiprogramming in a Hard-Real-Time Environment , 1989, JACM.

[16]  Aloysius K. Mok,et al.  WirelessHART™: Real-Time Mesh Network for Industrial Automation , 2010 .

[17]  Lui Sha,et al.  Mode change protocols for priority-driven preemptive scheduling , 1989, Real-Time Systems.

[18]  Lothar Thiele,et al.  Reliable mode changes in real-time systems with fixed priority or EDF scheduling , 2009, 2009 Design, Automation & Test in Europe Conference & Exhibition.

[19]  Johannes Schumacher,et al.  An Introduction to Hybrid Dynamical Systems, Springer Lecture Notes in Control and Information Sciences 251 , 1999 .

[20]  Vana Kalogeraki,et al.  Facilitating Congestion Avoidance in Sensor Networks with a Mobile Sink , 2007, RTSS 2007.

[21]  Alan Burns,et al.  Choosing Task Periods to Minimise System Utilisation in Time Triggered Systems , 1996, Inf. Process. Lett..

[22]  Song Han,et al.  Deferrable Scheduling for Maintaining Real-Time Data Freshness: Algorithms, Analysis, and Results , 2008, IEEE Transactions on Computers.

[23]  Song Han,et al.  On Co-Scheduling of Update and Control Transactions in Real-Time Sensing and Control Systems: Algorithms, Analysis, and Performance , 2013, IEEE Transactions on Knowledge and Data Engineering.

[24]  Krithi Ramamritham,et al.  Deriving deadlines and periods for real-time update transactions , 1999, IEEE Transactions on Computers.

[25]  Song Han,et al.  Schedulability Analysis of DeferrableScheduling Algorithms for MaintainingReal-Time Data Freshness , 2014, IEEE Transactions on Computers.

[26]  Edward A. Lee,et al.  Introduction to Embedded Systems - A Cyber-Physical Systems Approach , 2013 .

[27]  Tei-Wei Kuo,et al.  Similarity-based load adjustment for real-time data-intensive applications , 1997, Proceedings Real-Time Systems Symposium.