Distributed Scheduling of Tasks with Deadlines and Resource Requirements
IEEE Transactions on Computers
Scheduling Processes with Release Times, Deadlines, Precedence and Exclusion Relations
IEEE Transactions on Software Engineering
HARTS: A Distributed Real-Time Architecture
Computer - Special issue on real-time systems
Advances in real-time systems
Improved algorithms for synchronizing computer network clocks
IEEE/ACM Transactions on Networking (TON)
Scheduling in distributed soft real-time systems with autonomous components
Scheduling in distributed soft real-time systems with autonomous components
Mechanisms for detecting and handling timing errors
Communications of the ACM
Scheduling Algorithms for Multiprogramming in a Hard-Real-Time Environment
Journal of the ACM (JACM)
Resource Management Middleware for Dynamic, DependableReal-Time Systems
Real-Time Systems - Special issue on challenges in design and implementation of middlewares for real time systems
Real-Time Systems: Design Principles for Distributed Embedded Applications
Real-Time Systems: Design Principles for Distributed Embedded Applications
Deadline Scheduling for Real-Time Systems: Edf and Related Algorithms
Deadline Scheduling for Real-Time Systems: Edf and Related Algorithms
Advances in Real-Time Systems
Foundations of Real-Time Computing: Scheduling and Resource Management
Foundations of Real-Time Computing: Scheduling and Resource Management
Hard Real-Time Systems
The Spring Kernel: A New Paradigm for Real-Time Systems
IEEE Software
A Dynamic Real-time Benchmark for Assessment of QoS and Resource Management Technology
RTAS '99 Proceedings of the Fifth IEEE Real-Time Technology and Applications Symposium
Specification and Modeling of Dynamic, Distributed Real-Time Systems
RTSS '98 Proceedings of the IEEE Real-Time Systems Symposium
Journal of Parallel and Distributed Computing
Resource Management in Real Time Distributed System with Security Constraints: A Review
International Journal of Distributed Systems and Technologies
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We present adaptive resource management middleware techniques for periodic tasks in dynamic real-time distributed systems. The techniques continuously monitor the application at run-time for adherence to the desired real-time requirements, detect timing failures or trends for impending failures (due to workload fluctuations), and dynamically allocate resources by replicating subtasks of application tasks for load sharing. The objective of the techniques is to minimize (end-to-end) missed deadline ratios of the tasks. We present "predictive" resource allocation algorithms that determine the number of subtask replicas that are required for adapting the application to a given workload situation using statistical regression theory. The algorithms use regression equations that forecast subtask timeliness as a function of external load parameters such as number of sensor reports and internal resource load parameters such as CPU utilization. To evaluate the performance of the predictive algorithms, we consider algorithms that determine the number of subtask replicas using empirically determined heuristic functions. We implemented the resource management algorithms as part of a middleware infrastructure and measured the performance of the algorithms using a real-time benchmark. The experimental results indicate that the predictive algorithms outperform the heuristic strategies under the workload conditions that were studied.