In this paper we study the soft real-time web cluster architecture needed to support e-commerce and related applications. Our testbed is based on an industry standard, which defines a set of web interactions and database transactions with their deadlines, for generating real workload and benchmarking e-commerce applications. In these soft real-time systems, the quality of service (QoS) is usually defined as the fraction of requests that meet the deadlines. When this QoS is measured directly, regardless of whether the request missed the deadline by an epsilon amount of time or by a large difference, the result is always the same. For this reason, only counting the number of missed requests in a period avoids the observation of the real state of the system. Our contributions are theoretical propositions of how to control the QoS, not measuring the QoS directly, but based on the probability distribution of the tardiness in the completion time of the requests. We call this new QoS metric Tardiness Quantile Metric (TQM). The proposed method provides fine-grained control over the QoS so that we can make a closer examination of the relation between QoS and energy efficiency. We validate the theoretical results showing experiments in a multi-tiered e-commerce web cluster implemented using only open-source software solutions.
Multimedia systems such as video-on-demand (VOD) servers are time critical systems. These systems have strict response times, which implies that a delayed response can have serious consequence. For instance, in the case of a VOD server, an immediate consequence of a delayed response time can be user dissatisfaction, what can ultimately lead to the end of a business based on this system. Therefore, analysis and verification of timing properties of multimedia systems is an important problem. To verify if time critical systems satisfy their time bounds, we discuss the use of formal methods tools, in the verification and analysis of multimedia systems. We have used Verus (a formal verification tool) to model and analyze the ALMADEM-VOD server, a component of a true video-on-demand system. The modeling of this server in Verus has provided great insight into its design and its dynamic behavior.Using the quantitative estimates provided by Verus, we have determined performance bounds to the server. These bounds have pointed out that the performance curve of the actual server was almost at the predicted upper bound (worst case) level. These curves have uncovered design inefficiencies. After optimizing the server, its performance has improved over 40%, showing how useful formal verification can be used successfully during the design of multimedia systems.
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