FIT: A Flexible, LIght-Weight, and Real-Time Scheduling System for Wireless Sensor Platforms

We propose FIT, a flexible, light-weight and real-time scheduling system for wireless sensor platforms. There are three salient features of FIT. First, its two-tier hierarchical framework supports customizable application-specific scheduling policies, hence FIT is very flexible . Second, FIT is light-weight in terms of minimizing thread number to reduce preemptions and memory consumption while at the same time ensuring system schedulability. We propose a novel Minimum Thread Scheduling Policy (MTSP) exploration algorithm within FIT to achieve this goal. Finally, FIT provides a detailed real-time schedulability analysis method to help check if application's temporal requirements can be met. We implemented FIT on MICAz motes, and carried out extensive evaluations. Results demonstrate that FIT is indeed flexible and light-weight for implementing real-time applications, at the same time, the schedulability analysis provided can predict the real-time behavior. FIT is a promising scheduling system for implementing complex real-time applications in sensor networks.

[1]  Jens Palsberg,et al.  Avrora: scalable sensor network simulation with precise timing , 2005, IPSN 2005. Fourth International Symposium on Information Processing in Sensor Networks, 2005..

[2]  Yunhao Liu,et al.  Sea Depth Measurement with Restricted Floating Sensors , 2007, RTSS 2007.

[3]  Manas Saksena,et al.  Scheduling fixed-priority tasks with preemption threshold , 1999, Proceedings Sixth International Conference on Real-Time Computing Systems and Applications. RTCSA'99 (Cat. No.PR00306).

[4]  Shirish S. Sathaye,et al.  Fixed Priority Scheduling with Limited Priority Levels , 1995, IEEE Trans. Computers.

[5]  Bhavani M. Thuraisingham,et al.  Scheduling and Priority Mapping for Static Real-Time Middleware , 2001, Real-Time Systems.

[6]  Cormac J. Sreenan,et al.  Adding preemption to TinyOS , 2007, EmNets '07.

[7]  John Regehr,et al.  HLS: a framework for composing soft real-time schedulers , 2001, Proceedings 22nd IEEE Real-Time Systems Symposium (RTSS 2001) (Cat. No.01PR1420).

[8]  Anthony Rowe,et al.  Nano-RK: an energy-aware resource-centric RTOS for sensor networks , 2005, 26th IEEE International Real-Time Systems Symposium (RTSS'05).

[9]  Nigamanth Sridhar,et al.  Abstractions for safe concurrent programming in networked embedded systems , 2006, SenSys '06.

[10]  Yunhao Liu,et al.  Iso-Map: Energy-Efficient Contour Mapping in Wireless Sensor Networks , 2007, 27th International Conference on Distributed Computing Systems (ICDCS '07).

[11]  Adam Dunkels,et al.  Contiki - a lightweight and flexible operating system for tiny networked sensors , 2004, 29th Annual IEEE International Conference on Local Computer Networks.

[12]  Mani B. Srivastava,et al.  A dynamic operating system for sensor nodes , 2005, MobiSys '05.

[13]  John Regehr,et al.  Evolving real-time systems using hierarchical scheduling and concurrency analysis , 2003, RTSS 2003. 24th IEEE Real-Time Systems Symposium, 2003.

[14]  Jeff Rose,et al.  MANTIS OS: An Embedded Multithreaded Operating System for Wireless Micro Sensor Platforms , 2005, Mob. Networks Appl..

[15]  Sanjoy K. Baruah,et al.  A framework for achieving inter-application isolation in multiprogrammed, hard real-time environments , 2000, Proceedings 21st IEEE Real-Time Systems Symposium.