With the rapid transformation of computer hardware and algorithms, mobile networking has
evolved from low datacarrying capacity and high latency to better-optimized networks, either …

In order to realize the optimization of resource scheduling in the cloud computing
environment and improve the utilization ratio of network data resource, we need to carry out …

This special issue presents the recent advances in cloud computing and software-defined
network, which\were selected out of the significantly extended versions of accepted papers …

Many datacenters usually process complex jobs such as MapReduce jobs. From a network
perspective, most of these jobs trigger multiple parallel data flows, which comprise a coflow …

The explosive growth of big data imposes a heavy burden on computation, storage, and
communication resources in today's infrastructure. To efficiently exploit the bulk cloud …

In a Big data computing, the processing of data requires a large amount of CPU cycles and
network bandwidth and disk I/O. Dataflow is a programming model for processing Big data …

Data-intensive applications usually need to deal with huge volumes of data within their
deadlines. These applications can be modelled as DAGs and require parallel computation …

With the emergence of Big Data applications and cloud computing in recent years,
nowadays data centers are usually deployed with various kinds of Big Data applications and …

As more and more data-intensive applications have been moved to the cloud, the cloud
network has become the new performance bottleneck for cloud applications. To boost …

In the cloud computing environment, more and more enterprises need to build or rent data
center infrastructure to deploy their own cloud computing applications. However, in the …