Abstract
The widespread deployment of scientific applications and business services of various types on clouds requires the transfer of big data with different priorities between geographically distributed cloud-based data centers. As a result, Cloud Service Providers (CSP) face a significant challenge to fully utilize the expensive bandwidth resources of the links connecting data centers while guaranteeing Quality of Experience (QoE) for users. Modern data centers are increasingly adopting Software-Defined Networking (SDN) technology, which provides the capability of advance bandwidth reservation. This paper focuses on the collaborative scheduling of multiple prioritized user requests, namely, advance bandwidth reservation with a lower priority and immediate bandwidth reservation with a higher priority, to maximize the total user satisfaction. We formulate this co-scheduling problem with preemption as a generic optimization problem, which is shown to be NP-complete. We design a heuristic algorithm to maximize the number of successfully scheduled requests and minimize the number of preempted advance reservation requests, while minimizing the completion time of each request. Extensive results from simulations with randomly generated networks and emulation-based experiments on an SDN testbed show that our scheduling scheme significantly outperforms greedy approaches in terms of user satisfaction degree, a normalized quantification parameter we define to measure users’ QoE.
Original language | English |
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Pages (from-to) | 3019-3034 |
Number of pages | 16 |
Journal | Cluster Computing |
Volume | 25 |
Issue number | 4 |
DOIs | |
State | Published - Aug 2022 |
Keywords
- Bandwidth reservation
- Big data transfer
- High-performance networks
- Quality of Experience
- Software-defined networks