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MODIST is the first model checker designed for transparently checking unmodified distributed systems running on unmodified operating systems. It achieves this transparency via a novel architecture: a thin interposition layer exposes all actions in a distributed system and a centralized, OS-independent model checking engine explores these actions(More)
Peer-to-peer networks often use incentive policies to encourage cooperation between nodes. Such systems are generally susceptible to collusion by groups of users in order to gain unfair advantages over others. While techniques have been proposed to combat collusion, our lack of understanding of user collusion in existing systems makes evaluating such(More)
Cloud services inevitably fail: machines lose power, networks become disconnected, pesky software bugs cause sporadic crashes, and so on. Unfortunately, failure recovery itself is often faulty; e.g. recovery can accidentally re-cursively replicate small failures to other machines until the entire cloud service fails in a catastrophic outage, amplifying a(More)
Much work has been done to address the need for incentive models in real deployed peer-to-peer networks. In this paper, we discuss problems found with the incentive model in a large, deployed peer-to-peer network, Maze. We evaluate several alternatives, and propose an incentive system that generates preferences for well-behaved nodes while correctly(More)
BACKGROUND Asthma is a complex disease characterized by striking ethnic disparities not explained entirely by environmental, social, cultural, or economic factors. Of the limited genetic studies performed on populations of African descent, notable differences in susceptibility allele frequencies have been observed. OBJECTIVES We sought to test the(More)
Defects in clearance of dying cells have been proposed to underlie the pathogenesis of systemic lupus erythematosus (SLE). Mice lacking molecules associated with dying cell clearance develop SLE-like disease, and phagocytes from patients with SLE often display defective clearance and increased inflammatory cytokine production when exposed to dying cells in(More)
<i>Batched stream processing</i> is a new distributed data processing paradigm that models recurring batch computations on incrementally bulk-appended data streams. The model is inspired by our empirical study on a trace from a large-scale production data-processing cluster; it allows a set of effective query optimizations that are not possible in a(More)