Proactive resource allocation for asynchronous real-time distributed systems in the presence of processor failures

We present two proactive resource allocation algorithms, RBA^*-FT and OBA-FT, for fault-tolerant asynchronous real-time distributed systems. The algorithms consider an application model where task timeliness is specified by Jensen's benefit functions and the anticipated application workload during future time intervals is described by adaptation functions. In addition, we assume that reliability functions of processors are available a priori. Given these models, our objective is to maximize aggregate task benefit and minimize aggregate missed deadline ratio in the presence of processor failures. Since determining the optimal solution is computationally intractable, the algorithms heuristically compute sub-optimal resource allocations, but in polynomial time. Experimental results reveal that RBA^*-FT and OBA-FT outperform their non-fault-tolerant counterparts in the presence of processor failures. Furthermore, RBA^*-FT performs better than OBA-FT, although OBA-FT incurs better worst-case and amortized computational costs. Finally, we observe that both algorithms robustly withstand errors in the estimation of anticipated failures.