Monitoring Partially Synchronous Distributed Systems Using SMT Solvers

Abstract

In this paper, we discuss the feasibility of monitoring partially synchronous distributed systems to detect latent bugs, i.e., errors caused by concurrency and race conditions among concurrent processes. We present a monitoring framework where we model both system constraints and latent bugs as Satisfiability Modulo Theories (SMT) formulas, and we detect the presence of latent bugs using an SMT solver. We demonstrate the feasibility of our framework using both synthetic applications where latent bugs occur at any time with random probability and an application involving exclusive access to a shared resource with a subtle timing bug. We illustrate how the time required for verification is affected by parameters such as communication frequency, latency, and clock skew. Our results show that our framework can be used for real-life applications, and because our framework uses SMT solvers, the range of appropriate applications will increase as these solvers become more efficient over time.

Genetic Improvement of TCP Congestion Avoidance

“…After this work, several papers have tried to use an EA to evolve a variety of network protocols: MAC access protocols [14,15], e.g. through Finite State Machines (FSMs) [16][17][18]; wireless protocols [19]; aggregation protocols [20][21][22]; and protocol adaptors [23].…”