A dynamic operating system for sensor nodes

Sensor network nodes exhibit characteristics of both embedded systems and general-purpose systems. They must use little energy and be robust to environmental conditions, while also providing common services that make it easy to write applications. In TinyOS, the current state of the art in sensor node operating systems, reusable components implement common services, but each node runs a single statically-linked system image, making it hard to run multiple applications or incrementally update applications. We present SOS, a new operating system for mote-class sensor nodes that takes a more dynamic point on the design spectrum. SOS consists of dynamically-loaded modules and a common kernel, which implements messaging, dynamic memory, and module loading and unloading, among other services. Modules are not processes: they are scheduled cooperatively and there is no memory protection. Nevertheless, the system protects against common module bugs using techniques such as typed entry points, watchdog timers, and primitive resource garbage collection. Individual modules can be added and removed with minimal system interruption. We describe SOS's design and implementation, discuss tradeoffs, and compare it with TinyOS and with the Maté virtual machine. Our evaluation shows that despite the dynamic nature of SOS and its higher-level kernel interface, its long term total usage nearly identical to that of systems such as Matè and TinyOS.

[1]  Chenyang Lu,et al.  Rapid Development and Flexible Deployment of Adaptive Wireless Sensor Network Applications , 2005, 25th IEEE International Conference on Distributed Computing Systems (ICDCS'05).

[2]  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..

[3]  Brian N. Bershad,et al.  Extensibility safety and performance in the SPIN operating system , 1995, SOSP.

[4]  Margaret Martonosi,et al.  Impala: a middleware system for managing autonomic, parallel sensor systems , 2003, PPoPP '03.

[5]  David E. Culler,et al.  Versatile low power media access for wireless sensor networks , 2004, SenSys '04.

[6]  Mani B. Srivastava,et al.  Design and implementation of a framework for efficient and programmable sensor networks , 2003, MobiSys '03.

[7]  David E. Culler,et al.  The nesC language: A holistic approach to networked embedded systems , 2003, PLDI '03.

[8]  Koen Langendoen,et al.  Efficient code distribution in wireless sensor networks , 2003, WSNA '03.

[9]  Gaurav S. Sukhatme,et al.  Networked Infomechanical Systems (NIMS) for Ambient Intelligence , 2005, Ambient Intelligence.

[10]  Michael B. Jones,et al.  Mach: a system software kernel , 1989, Digest of Papers. COMPCON Spring 89. Thirty-Fourth IEEE Computer Society International Conference: Intellectual Leverage.

[11]  Jeff Rose,et al.  MANTIS: system support for multimodAl NeTworks of in-situ sensors , 2003, WSNA '03.

[12]  Deborah Estrin,et al.  A Remote Code Update Mechanism for Wireless Sensor Networks , 2003 .

[13]  David E. Culler,et al.  The Emergence of Networking Abstractions and Techniques in TinyOS , 2004, NSDI.

[14]  David E. Culler,et al.  Incremental network programming for wireless sensors , 2004, 2004 First Annual IEEE Communications Society Conference on Sensor and Ad Hoc Communications and Networks, 2004. IEEE SECON 2004..

[15]  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.

[16]  John Anderson,et al.  Wireless sensor networks for habitat monitoring , 2002, WSNA '02.

[17]  Robert Szewczyk,et al.  System architecture directions for networked sensors , 2000, ASPLOS IX.

[18]  David E. Culler,et al.  The dynamic behavior of a data dissemination protocol for network programming at scale , 2004, SenSys '04.

[19]  Dawson R. Engler,et al.  Exokernel: an operating system architecture for application-level resource management , 1995, SOSP.

[20]  Philip Levis,et al.  Maté: a tiny virtual machine for sensor networks , 2002, ASPLOS X.

[21]  Yong Wang,et al.  Energy-efficient computing for wildlife tracking: design tradeoffs and early experiences with ZebraNet , 2002, ASPLOS X.