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With the tremendous growth of cloud computing, it is increasingly critical to provide quantifiable performance to tenants and to improve resource utilization for the cloud provider. Though many recent proposals focus on guaranteeing job performance (with a particular note on network bandwidth) in the cloud, they usually lack efficient utilization  of cloud resource, or vice versa. In this paper we present DCloud, which leverages the (soft) deadlines of cloud computing jobs to enable flexible and efficient resource utilization in data centers. With the deadline requirement of a job guaranteed, DCloud employs both time sliding (postponing the launching time of a job) and bandwidth scaling (adjusting the bandwidth associated with VMs) in resource allocation, so as to better match the resource allocated to the job with the cloud's residual resource. Extensive simulations and testbed experiments show that DCloud can accept much more jobs than existing solutions, and significantly increase the cloud provider's revenue with less cost for individual tenants. [ABSTRACT FROM AUTHOR]

The explosive expansion of data center sizes aggravates the power consumption and carbon footprint, which has restricted the sustainable growth of cloud services and seriously troubled data center operators. In recent years, plenty of advanced data center network architectures have been proposed. They usually employ richly-connected topologies and multi-path routing to provide high network capacity. Unfortunately, they also undergo inefficient network energy usage during the traffic valley time. To address the problem, many energy-aware flow scheduling algorithms are proposed recently, primarily considering how to aggregate traffic by flexibly choosing the routing paths, with flows fairly sharing the link bandwidths. In this paper, we leverage software defined network (SDN) technique and explore a new solution to energy-aware flow scheduling, i.e., scheduling flows in the time dimension and using exclusive routing (EXR) for each flow, i.e., a flow always exclusively utilizes the links of its routing path. The key insight is that exclusive occupation of link resources usually results in higher link utilization in high-radix data center networks, since each flow does not need to compete for the link bandwidths with others. When scheduling the flows, EXR leaves flexibility to operators to define the priorities of flows, e.g., based on flow size, flow deadline, etc. Extensive simulations and testbed experiments both show that EXR can effectively save network energy compared with the regular fair-sharing routing (FSR), and significantly reduce the average flow completion time if assigning higher scheduling priorities to smaller flows. [ABSTRACT FROM PUBLISHER]