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Strong replica consistency models ensure that the data delivered by a replica always includes the latest updates, although this may result in poor response times. On the other hand, weak replica consistency models provide quicker access to information, but do not usually provide guarantees about the degree of staleness in the data they deliver. In order to support emerging distributed applications that are characterized by high concurrency demands, an increasing shift towards dynamic content, and timely delivery, we need quality of service models that allow us to explore the intermediate space between these two extreme approaches to replica consistency. Further, for better support of time-sensitive applications that can tolerate relaxed consistency in exchange for better responsiveness, we need to understand how the desired level of consistency affects the timeliness of a response. The QoS model we have developed to realize these objectives considers both timeliness and consistency, and treats consistency along two dimensions: order and staleness. We evaluate experimentally the framework we have developed to study the timeliness/consistency tradeoffs for replicated services and present experimental results that compare these tradeoffs in the context of sequential and FIFO ordering.