ICPP '97 Proceedings of the international Conference on Parallel Processing
RTAS '03 Proceedings of the The 9th IEEE Real-Time and Embedded Technology and Applications Symposium
Online robust optimization framework for QoS guarantees in distributed soft real-time systems
EMSOFT '10 Proceedings of the tenth ACM international conference on Embedded software
Journal of Systems and Software
Proceedings of the 15th ACM international conference on Modeling, analysis and simulation of wireless and mobile systems
Adaptive energy-efficient scheduling for hierarchical wireless sensor networks
ACM Transactions on Sensor Networks (TOSN)
| Hi-index | 0.00 |
In a real-time system, tasks are constrained by global end-to-end deadlines. In order to cater for high task schedulability, these deadlines must be distributed over component subtasks in an intelligent way. Existing methods for automatic distribution of end-to-end deadlines are all based on the assumption that task assignments are entirely known beforehand. This assumption is not necessarily valid for large real-time systems. Furthermore, most task assignment strategies require information on deadlines in order to make good assignments, thus forming a circular dependency between deadline distribution and task assignment. We present a heuristic approach that performs deadline distribution prior to task assignment. The deadline distribution problem is presented in the context of large distributed hard real-time systems with relaxed locality constraints, where schedulability analysis must be performed off-line, and only a subset of the tasks are constrained by predetermined assignments to specific processors. Using experimental results we identify drawbacks of previously-proposed techniques, and then show that our solution provides significantly better performance for a large variety of system configurations.