Furthermore, the experimental results presented in [Wel98] were performed on a benchmark system, whereas this paper presents results from applying the technology within an experimental Navy distribu... (The motivation for our work is provided in part by the characteristics of combat systems.) There are several implications of these charact ..." Abstract.
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However, potential benefits of a posteriori approaches are significant, including the ability to function correctly in dynamic environments through adaptability to unforeseen conditions and higher actual utilization of computing resources.
In this paper we present an approach that is appropriate for systems which experience large variations in workload (as described in [Har94]).
The approach dynamically manages a distributed collection of computing resources by continuously computing and assessing an a posteriori time series of execution latencies and resource utilizations. Citation Context ..to a large distributed computing system.
In this paper we define a new Qo S reference architecture, and we elaborate the details of the language, system model, metrics, and middleware presented in =-=[Wel98]-=-. This paper deals with large, distributed real-time systems that have execution times and resource utilizations which cannot be characterized a priori.
Specifically, the paper presents an adaptive distributed system reference architecture that is suitable for such an approach.
This reference architecture provides the capabilities and infrastructure needed to construct multi-component, replicated, distributed object real-time systems that negotiate for a given level of Qo S from the underlying distributed computing resources. Real-time computing models that are based on benefit (also called utility and value) offer a generic paradigm that captures the spectrum from hard- to firm- to soft-realtime requirements.
Furthermore, it allows robust, flexible real-time systems to be developed.
Certain real-time applications must operate in highly dynamic environments (e.g., battle environments), thereby precluding accurate characterization of the applications' workloads by static models.
In such contexts, temporal and execution characteristics can only be known at run time.
Thus, gua ..." Certain real-time applications must operate in highly dynamic environments (e.g., battle environments), thereby precluding accurate characterization of the applications' workloads by static models.
Thus, guarantees of real-time performance based on a priori characterizations will not be possible.