Title
DCNSim: a unified and cross-layer computer architecture simulation framework for data center network research
Abstract
Within today's large-scale data centers, the inter-node communication is often the major bottleneck. This fact recently blooms the data center network (DCN) research. Since building a real data center is cost prohibitive, most of DCN studies rely on simulations. Unfortunately, state-of-the-art network simulators have limited support for real world applications, which prevents researchers from first-hand investigation. To address this issue, we developed a unified and cross-layer simulation framework, namely the DCNSim. By leveraging the two widely deployed simulators, DCNSim introduces computer architecture solutions into DCN research. With DCNSim, one could run packet-level network simulation driven by commercial applications while varying computer and network parameters, such as CPU frequency, memory access latency, network topology and protocols. With extensive validations, we show that DCNSim could accurately capture performance trends caused by changing computer and network parameters. Finally, we argue that future DCN researches should consider computer architecture factors via several case studies.
Year
DOI
Venue
2013
10.1145/2482767.2482792
Conf. Computing Frontiers
Keywords
Field
DocType
computer architecture solution,network parameter,dcn research,packet-level network simulation,future dcn,computer architecture factor,dcn study,state-of-the-art network simulator,network topology,data center network research,data center network,cross-layer computer architecture simulation
Bottleneck,Latency (engineering),Computer science,Network simulation,Real-time computing,Intelligent computer network,Distributed computing,Computer architecture,Parallel computing,Network topology,Network traffic simulation,Data center,Computer network programming
Conference
Citations 
PageRank 
References 
1
0.36
16
Authors
6
Name
Order
Citations
PageRank
Nongda Hu181.56
Binzhang Fu21069.82
Xiufeng Sui3275.83
Long Li4101.94
Tao Li57216393.45
Lixin Zhang657145.96