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The paper deals with the contact center modeling with emphasis on the optimal number of agents. The contact center belongs to the queueing systems and its mathematical model can be described by various important parameters. The Erlang C formula tends to be suitable tool for the modeling of QoS parameters of contact centers. In our paper, we propose two parameters: downtime and administrative task...
We use statistical learning to estimate end-to-end QoS metrics from device statistics, collected from a server cluster and an OpenFlow network. The results from our testbed, which runs a video-on-demand service and a key-value store, demonstrate that the learned models can estimate QoS metrics like frame rate or response time with errors bellow 10% for a given client. Interestingly, we find that service-level...
Memcached is a widely used in-memory caching solution in large-scale searching scenarios. The most pivotal performance metric in Memcached is latency, which is affected by various factors including the workload pattern, the service rate, the unbalanced load distribution and the cache miss ratio. To quantitate the impact of each factor on latency, we establish a theoretical model for the Memcached...
In mixed-criticality systems functionalities of different criticalities, that need to have their correctness validated to different levels of assurance, co-exist upon a shared platform. Multiple specifications at differing levels of assurance may be provided for such systems; the specifications that are trusted at very high levels of assurance tend to be more conservative than those at lower levels...
HTTP Adaptive Streaming (HAS) is a streaming video technique commonly employed over best-effort networks. However, it is characterized by some issues that harm its quality of experience (QoE) in cases of daily use. The main use case of the present investigation involves HAS clients competing for bandwidth inside the same home network. Based on related work, we found that one of the most convenient...
Several approaches to reduce the power consumption of data enters have been described in the literature, most of which aim to improve energy efficiency by trading off performance for reducing power consumption. However, these approaches do not always provide means for administrators and users to specify how they want to explore such trade-offs. This work provides techniques for assigning jobs to distributed...
The literature on Small and Medium Enterprises often discusses the emergent nature of the product development processes, however; it often does not address the lack of planning tools within such organizations. We aim to fill the gap in tool support for the planning process, by developing a discrete event simulation model to compute lead times of product development projects. The developed model explicitly...
MapReduce has become popular and Reduce-side join is one of the most important application of MapReduce. Data skew, in which the data load assigned to each Reduce task fluctuates task by task, increases the MapReduce job completion time. This paper proposes a dynamic profiling and feedback framework that works on a MapReduce cluster. The framework allows programmers to build their own algorithm to...
Power capping on server nodes has become an essential feature in data centers for controlling energy costs and peak power consumption. More than half of the server nodes are virtualized in today's data centers; thus, providing a practical power capping technique for consolidated virtual environments is a significant research problem. This paper proposes a power capping technique, vCap, which makes...
Server load balancing is indispensable in World Wide Web for providing high-quality service. In server load balancing, since the server loads and capacities are not always identical, traffic should be distributed by measuring server performance to improve the service quality. This paper proposes a load balancing technique conducted by passive measurement, which estimates the server performance through...
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