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Cloud systems include both locally based servers at user premises and remote servers and multiple Clouds that can be reached over the Internet. This paper describes a smart distributed system that combines local and remote Cloud facilities. It operates with a task allocation system that takes decisions to allocate tasks dynamically to the service that offers the best overall Quality of Service and...
The Cloud supports diverse workloads and simple schemes are needed to allocate jobs with satisfactory QoS and low overhead. This paper presents a further study on the potential of an online work distribution approach in adaptively distributing workloads under variable load conditions for optimizing the two contradictory criteria: reducing the energy consumption per job while maintaining the best possible...
This paper uses big data and machine learning for the real-time management of Internet scale quality-of-service (QoS) route optimisation with an overlay network. Based on the collection of data sampled every 2 min over a large number of source–destinations pairs, we show that intercontinental Internet protocol (IP) paths are far from optimal with respect to QoS metrics such as end-to-end round-trip...
We demonstrate experimentally how an Autonomic Network based on the CPN protocol can provide the Quality of Service (QoS) required by voice communications. The implementation uses Reinforcement Learning to dynamically seek paths that meet the quality requirements of voice communications. Measurements of packet delay, jitter, and loss illustrate the performance obtained from the system.
We present experiments that compare three on-line real time techniques for task allocation to different cloud servers: an adaptive random neural network (RNN) based on reinforcement algorithm, an algorithm based on ``sensible routing'', one which uses a simple analytical model to select the server is estimated to give the best response as a function of workload, and round-robin task allocation. Measurements...
Weighted fair queueing (WFQ) is a practical scheduling discipline for supporting differentiated quality-of-service (QoS) in computer networks and communication systems. Analytical models are important tools for system performance evaluation and resource optimization. However, there is not any comprehensive model reported in the open literature for analytically investigating the performance behaviors...
The provisioning of differentiated QoS is an important objective in the design and implementation of IEEE 802.16 / WiMAX-based broadband wireless networks. To this end, the hybrid scheduling mechanism that combines various fundamental scheduling principles, e.g., priority queueing (PQ), earliest deadline first (EDF), weight fair queue (WFQ), and round robin(RR) within a hierarchical structure for...
Active queue management (AQM) coupled with differentiated scheduling mechanism is an important and promising scheme for congestion control and quality-of-service (QoS) guarantee in communication networks. This paper develops a new analytical performance model for priority-based AQM subject to heterogeneous bursty traffic modelled by Markov-modulated Poisson processes (MMPP) and non-bursty traffic...
Active queue management (AQM) with multiple thresholds is an effective mechanism of buffer allocation for differentiated quality-of-service (QoS) of heterogeneous traffic. This paper develops an original analytical model for a finite buffer queueing system with AQM under two heterogeneous classes of traffic which are modeled, respectively, by the non-bursty Poisson process and bursty Markov-modulated...
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