Characterizing Phases in Service-Oriented Applications

The behavior of service-oriented programs depends strongly on the input. A compiler, for example, behaves differently when compiling different functions. Similar input dependences can be seen in interpreters, compression and encoding utilities, databases, and dynamic content servers. Because their behavior is hard to predict, these programs pose a special challenge for dynamic adaptation mechanisms, which attempt to enhance performance by modifying hardware or software to fit application needs. We present a new technique to detect phases—periods of distinctive behavior—in service-oriented programs. We begin by using special inputs to induce a repeating pattern of behavior. We then employ frequency-based filtering on basic block traces to detect both top-level and second-level repetitions, which we mark via binary rewriting. When the instrumented program runs, on arbitrary input, the inserted markers divide execution into phases of varying length. Experiments with service-oriented programs from the Spec95 and Spec2K benchmark suites indicate that program behavior within phases is surprisingly predictable in many (though not all) cases. This in turn suggests that dynamic adaptation, either in hardware or in software, may be applicable to a wider class of programs than previously believed