24 September 2013, Shenzhen--ZTE today announced the release of the BigMatrix 9900 series of data center switches, the world＇ s largest-capacity data center switches. The BigMatrix 9900 product family comprises data...24 September 2013, Shenzhen--ZTE today announced the release of the BigMatrix 9900 series of data center switches, the world＇ s largest-capacity data center switches. The BigMatrix 9900 product family comprises data switches with the largest capacity in the world. The switches are designed large cloud computing and big data scenarios and allow for higher-density deployment in data centers. Each single slot can support up to 144 10G ports, 36 40G ports, or 12 IOOG ports. The Big Matrix 9900 series comprises four switch models-9916, 9912, 9908, and 9904-each of which supports a maximum switching capacity of 84.48 Tbps.展开更多
Virtualization is a common technology for resource sharing in data center. To make efficient use of data center resources, the key challenge is to map customer demands （modeled as virtual data center, VDC） to the ph...Virtualization is a common technology for resource sharing in data center. To make efficient use of data center resources, the key challenge is to map customer demands （modeled as virtual data center, VDC） to the physical data center effectively. In this paper, we focus on this problem. Distinct with previous works, our study of VDC embedding problem is under the assumption that switch resource is the bottleneck of data center networks （DCNs）. To this end, we not only propose relative cost to evaluate embedding strategy, decouple embedding problem into VM placement with marginal resource assignment and virtual link mapping with decided source-destination based on the property of fat-tree, but also design the traffic aware embedding algorithm （TAE） and first fit virtual link mapping （FFLM） to map virtual data center requests to a physical data center. Simulation results show that TAE＋FFLM could increase acceptance rate and reduce network cost （about 49% in the case） at the same time. The traffie aware embedding algorithm reduces the load of core-link traffic and brings the optimization opportunity for data center network energy conservation.展开更多
文摘24 September 2013, Shenzhen--ZTE today announced the release of the BigMatrix 9900 series of data center switches, the world＇ s largest-capacity data center switches. The BigMatrix 9900 product family comprises data switches with the largest capacity in the world. The switches are designed large cloud computing and big data scenarios and allow for higher-density deployment in data centers. Each single slot can support up to 144 10G ports, 36 40G ports, or 12 IOOG ports. The Big Matrix 9900 series comprises four switch models-9916, 9912, 9908, and 9904-each of which supports a maximum switching capacity of 84.48 Tbps.
基金This research was partially supported by the National Grand Fundamental Research 973 Program of China under Grant （No. 2013CB329103）, Natural Science Foundation of China grant （No. 61271171）, the Fundamental Research Funds for the Central Universities （ZYGX2013J002, ZYGX2012J004, ZYGX2010J002, ZYGX2010J009）, Guangdong Science and Technology Project （2012B090500003, 2012B091000163, 2012556031）.
文摘Virtualization is a common technology for resource sharing in data center. To make efficient use of data center resources, the key challenge is to map customer demands （modeled as virtual data center, VDC） to the physical data center effectively. In this paper, we focus on this problem. Distinct with previous works, our study of VDC embedding problem is under the assumption that switch resource is the bottleneck of data center networks （DCNs）. To this end, we not only propose relative cost to evaluate embedding strategy, decouple embedding problem into VM placement with marginal resource assignment and virtual link mapping with decided source-destination based on the property of fat-tree, but also design the traffic aware embedding algorithm （TAE） and first fit virtual link mapping （FFLM） to map virtual data center requests to a physical data center. Simulation results show that TAE＋FFLM could increase acceptance rate and reduce network cost （about 49% in the case） at the same time. The traffie aware embedding algorithm reduces the load of core-link traffic and brings the optimization opportunity for data center network energy conservation.
