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With the maturity and proliferation of Software-Defined Networking (SDN), there has been an increasing number of network deployments that provide dedicated connections through on-demand and in- advance scheduling in support of data-intensive applications for global scientific collaboration. In such dedicated network environments, bandwidth scheduling serves as a key technique to improve the utilization...
Today's scientific and business applications generate massive data sets that need to be transferred to remote sites for sharing, processing, and long term storage. Because of increasing data volumes and enhancement in current network technology that provide on-demand high-speed data access between collaborating institutions, data handling and scheduling problems have reached a new scale. In this paper,...
Provisioning resources as a service in a scalable on-demand manner is a basic feature in Cloud computing technology. Service provisioning in Clouds is based on Service Level Agreements (SLAs) representing a contract signed between the customer and the service provider stating the terms of the agreement including non-functional requirements of the service specified as Quality of Service (QoS), obligations,...
Data-intensive applications are becoming increasingly common in Grid environments. These applications require enormous volume of data for the computation. Most conventional meta-scheduling approaches are aimed at computation intensive application and they do not take data requirement of the applications into account, thus leading to poor performance. Efficient scheduling of data-intensive applications...
Three applications in wireless networks where model-free stochastic learning is applicable, are discussed. The learning based optimization problems are formulated and simulation results are presented. Some open issues are also discussed.
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