Microc/OS-II
MANTIS: system support for multimodAl NeTworks of in-situ sensors
WSNA '03 Proceedings of the 2nd ACM international conference on Wireless sensor networks and applications
Evolving real-time systems using hierarchical scheduling and concurrency analysis
RTSS '03 Proceedings of the 24th IEEE International Real-Time Systems Symposium
Enhancing the AvrX Kernel with Efficient Secure Communication Using Software Thread Integration
RTAS '04 Proceedings of the 10th IEEE Real-Time and Embedded Technology and Applications Symposium
Contiki - A Lightweight and Flexible Operating System for Tiny Networked Sensors
LCN '04 Proceedings of the 29th Annual IEEE International Conference on Local Computer Networks
Full TCP/IP for 8-bit architectures
Proceedings of the 1st international conference on Mobile systems, applications and services
Proceedings of the 4th workshop on Embedded networked sensors
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In general, two different types of low-end sensor node platforms are currently considered: event driven and multi-tasking operating systems. It is commonly assumed that event driven operating systems are more suited to WSN (Wireless Sensor Networks) as they use less memory and resources. Hence one of event driven operating systems, TinyOS incorporating a non-preemptive scheduling policy, is quickly deployed for WSN today. While the TinyOS can keep the memory overhead down, it has been shown that scheduling periodic and aperiodic non-preemptive tasks on the TinyOS is NP-hard. In this paper, we present a technique that makes it possible to guarantee the real-time scheduling of periodic tasks and minimize the average response time of aperiodic tasks for low-end sensor node platforms. This paper considers the following two perspectives. First, sensor node platforms available in the literature have not addressed the concept of scheduling for hybrid task sets where both types of periodic and aperiodic tasks exist. Second, each system service in sensor node platforms is decomposed to either a periodic or an aperiodic task in order to provide fully optimal real-time scheduling for given real-time requirements of WSN applications. A case study shows that the proposed technique yields efficient performance in terms of guaranteeing the completion of all the periodic tasks within their deadlines and aiming to provide aperiodic tasks with good average response time.