摘要
The dynamics of the globalized multimedia sources and request demands, which requires high computations and bandwidths, makes the IT infrastructure a challenge for live streaming applications. Migrating the system to a geo-distributed cloud and leasing servers is an ideal alternative for supporting large-scale live streaming applications with dynamic contents and demands. The new challenge of multimedia live streaming applications in a geo-distributed cloud is how to efficiently arrange and migrate services among different cloud sites to guarantee the distribute users’ experience at modest costs. This paper first investigates cloud leasing policies for live streaming applications and finds that there is no detailed algorithm to help live streaming applications arrange and migrate services among different cloud sites. Then, we present a quality of service（Qo S） guarantee cost-effective cloud leasing policy for live streaming applications. Meanwhile, we design a genetic algorithm（GA） to deal with the leasing policy among cloud sites of diverse lease prices. Experimental results confirm the effectiveness of the proposed model and the efficiency of the involved GA.
The dynamics of the globalized multimedia sources and request demands, which requires high computations and bandwidths, makes the IT infrastructure a challenge for live streaming applications. Migrating the system to a geo-distributed cloud and leasing servers is an ideal alternative for supporting large-scale live streaming applications with dynamic contents and demands. The new challenge of multimedia live streaming applications in a geo-distributed cloud is how to efficiently arrange and migrate services among different cloud sites to guarantee the distribute users’ experience at modest costs. This paper first investigates cloud leasing policies for live streaming applications and finds that there is no detailed algorithm to help live streaming applications arrange and migrate services among different cloud sites. Then, we present a quality of service（Qo S） guarantee cost-effective cloud leasing policy for live streaming applications. Meanwhile, we design a genetic algorithm（GA） to deal with the leasing policy among cloud sites of diverse lease prices. Experimental results confirm the effectiveness of the proposed model and the efficiency of the involved GA.
基金
Supported by the National Key Technology R&D Program during the Twelfth Five-Year Plan Period(2015BAK27B02)
