Multicaloric and coupled-caloric effects

The multicaloric effect refers to the thermal response of a solid material driven by simultaneous or sequential application of more than one type of external field.For practical applications,the multicaloric effect is a potentially interesting strategy to improve the efficiency of refrigeration devices.Here,the state of the art in multi-field driven multicaloric effect is reviewed.The phenomenology and fundamental thermodynamics of the multicaloric effect are well established.A number of theoretical and experimental research approaches are covered.At present,the theoretical understanding of the multicaloric effect is thorough.However,due to the limitation of the current experimental technology,the experimental approach is still in progress.All these researches indicated that the thermal response and effective reversibility of multiferroic materials can be improved through multicaloric cycles to overcome the inherent limitations of the physical mechanisms behind single-field-induced caloric effects.Finally,the viewpoint of further developments is presented.

Minimizing Resource Cost for Camera Stream Scheduling in Video Data Center

Video surveillance service, which receives live streams from IP cameras and forwards the streams to end users, has become one of the most popular services of video data center. The video data center focuses on minimizing the resource cost during resource provisioning for the service. However, little of the previous work comprehensively considers the bandwidth cost optimization of both upload and forwarding streams, and the capacity of the media server. In this paper, we propose an efficient resource scheduling approach for online multi-camera video forwarding, which tries to optimize the resource sharing of media servers and the networks together. Firstly, we not only provide a fine-grained resource usage model for media servers, but also evaluate the bandwidth cost of both upload and forwarding streams. Without loss of generality, we utilize two resource pricing models with different resource cost functions to evaluate the resource cost： the linear cost function and the non-linear cost functions. Then, we formulate the cost minimization problem as a constrained integer programming problem. For the linear resource cost function, the drift-plus-penalty optimization method is exploited in our approach. For non-linear resource cost functions, the approach employs a heuristic method to reduce both media server cost and bandwidth cost. The experimental results demonstrate that our approach obviously reduces the total resource costs on both media servers and networks simultaneously.