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<p>In a distributed real-time system, nonuniform task arrivals may temporarily overload some nodes while leaving some other nodes idle. As a result, some of the tasks on anoverloaded node may miss their deadlines even if the overall system has the capacity tomeet the deadlines of all tasks. A decentralized, dynamic load sharing (LS) scheme hasbeen proposed as a solution to this problem. Analytic queuing models to comparativelyevaluate this LS scheme as well as three other schemes-no LS, LS with random selectionof a receiver node, and LS with perfect information- are developed. The evolution of anode's load state is modeled as a continuous-time semi-Markov process, wherecumulative execution time (CET), rather than the commonly-used queue length (QL), isemployed to describe the workload of a node. The proposed scheme is compared againstother LS schemes. The validity of analytic models is checked with simulations. Bothanalytic and simulation results indicate that by using judicious exchange/use of stateinformation and Bayesian decision mechanism, the proposed scheme makes a significantimprovement over other existing LS schemes in minimizing the probability of dynamicfailure.</p>
Index Termsanalytic models; decentralised load sharing; continuous time semiMarkov process;adaptive load sharing schemes; distributed real-time systems; nonuniform task arrivals;dynamic load sharing; queuing models; random selection; cumulative execution time;commonly-used queue length; simulation; Bayesian decision mechanism; probability ofdynamic failure; Bayes methods; decision theory; distributed processing; performanceevaluation; queueing theory; real-time systems

K. Shin and C. Hou, "Analytic Models of Adaptive Load Sharing Schemes in Distributed Real-Time Systems," in IEEE Transactions on Parallel & Distributed Systems, vol. 4, no. , pp. 740-761, 1993.
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