The process group approach to reliable distributed computing
Communications of the ACM
Improved algorithms for synchronizing computer network clocks
IEEE/ACM Transactions on Networking (TON)
IEEE Transactions on Software Engineering
Guest Editors' Introduction to Special Section on Asynchronous Real-Time Distributed Systems
IEEE Transactions on Computers
IEEE Transactions on Computers
Deadline Assignment in a Distributed Soft Real-Time System
IEEE Transactions on Parallel and Distributed Systems
An Adaptive, Distributed Airborne Tracking System ("process the Right Tracks at the Right Time")
Proceedings of the 11 IPPS/SPDP'99 Workshops Held in Conjunction with the 13th International Parallel Processing Symposium and 10th Symposium on Parallel and Distributed Processing
End-Host Architecture for QoS-Adaptive Communication
RTAS '98 Proceedings of the Fourth IEEE Real-Time Technology and Applications Symposium
On adaptive resource allocation for complex real-time applications
RTSS '97 Proceedings of the 18th IEEE Real-Time Systems Symposium
A Dynamic Quality of Service Middleware Agent for Mediating Application Resource Usage
RTSS '98 Proceedings of the IEEE Real-Time Systems Symposium
Specification and Modeling of Dynamic, Distributed Real-Time Systems
RTSS '98 Proceedings of the IEEE Real-Time Systems Symposium
Scheduling dependent real-time activities
Scheduling dependent real-time activities
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We present a proactive resource allocation algorithm, called BEA, for fault-tolerant asynchronous real-time distributed systems. BEA considers an application model where trans-node application timeliness requirements are expressed using benefit functions, and anticipated workload during future time intervals are expressed using adaptation functions. Furthermore, BEA considers an adaptation model where subtasks of application tasks are replicated at run-time for tolerating failures as well as for sharing workload increases. Given such models, the objective of the algorithm is to maximize the aggregate real-time benefit and the ability to tolerate host failures during the time window of adaptation functions. Since determining the optimal solution is computationally intractable, BEA heuristically computes suboptimal resource allocations in polynomial-time. We show that BEA can achieve almost the same fault-tolerance ability as full replication, and accrue most of real-time benefit that full replication can accrue. In the meanwhile, BEA requires much fewer replicas than full replication, and hence is cost effective.