Large-scale donation-based distributed infrastructures need to cope with the inherent unreliability of participant nodes. A widely-used work scheduling technique in such environments is to redundantly schedule the out sourced computations to a number of nodes. We present the design and implementation of RIDGE, a reliability aware system which uses a node's prior performance and behavior to make more effective scheduling decisions. We have implemented RIDGE on top of the BOINC distributed computing infrastructure and have evaluated its performance on a live test bed consisting of 120 PlanetLab nodes. Our experimental results show that RIDGE is able to match or surpass the throughput of the best vanilla BOINC configuration under different reliability environments, by automatically adapting to the characteristics of the underlying environment. In addition, RIDGE is able to provide much lower work unit makes pans compared to BOINC, which indicates its desirability in service-oriented environments with time constraints.

Large-scale donation-based distributed infrastructures need to cope with the inherent unreliability of participant nodes. A widely-used work scheduling technique in such environments is to redundantly schedule the outsourced computations to a number of nodes. We present the design and implementation of RIDGE, a reliability-aware system which uses a node's prior performance and behavior to make more effective scheduling decisions. We have implemented RIDGE on top of the BOINC distributed computing infrastructure and have evaluated its performance on a live PlanetLab testbed. Our experimental results show that RIDGE is able to match or surpass the throughput of the best BOINC configuration by automatically adapting to the characteristics of the underlying environment. In addition, RIDGE is able to provide much lower workunit makespans compared to BOINC. RIDGE is also able to produce significantly lower communication makespans for downloading clients. Collectively, the results suggest that RIDGE has great promise for service-oriented environments with time constraints.