High performance and security in cloud computing 1 INTRODUCTION"Cloud" is a common metaphor for an Internet accessible infrastructure (e.g., data storage and computing hardware) that is hidden from users. Cloud computing makes data truly mobile and a user can simply access a chosen cloud with any internet accessible device. In cloud computing, IT-related capabilities are provided as services, accessible without requiring detailed knowledge of the underlying technology. Thus, many mature technologies are used as components in cloud computing, but still there are many unresolved and open problems.
THEMES OF THIS SPECIAL ISSUEThis special issue includes articles addressing the state-of-the-art in strengthening performance and security and cloud computing. Eight representative research articles were carefully selected based on the original presentations at the 2016 International Conference on Cloud Computing and Big Data (CloudCom-Asia'16). The objective of this conference is to bring together researchers who work on cloud computing and related technologies. According to whether its research theme relates more to performance or security, the accepted papers are briefly described in the remaining part of this section.
PerformanceTask scheduling is critical for guaranteeing cloud performance. In the past years, more and more business-to-consumer and enterprise applications start running in the heterogeneous cloud. Such cloud bag-of-tasks (BoT) applications are usually budget-constrained and their scheduling is an essential problem for cloud provider. The problem is even more complex and challenging when the accurate knowledge about task execution time is unknown in advance. Focusing on these challenges, Tang et al 1 build a cloud resource management architecture and stochastic task model, which divides cloud task into two execution parts. Then they deduce BoT applications schedule length and total cost according to heterogenous clouds online feedback information. They further formulate this stochastic scheduling problem as a linear programming problem and propose a time and cost multi-objective stochastic task scheduling genetic algorithm, which can find Pareto-optimal schedules for stochastic cloud task that meet its budget constraint.With the rapid development of Internet and cloud computing, the high performance requirements for data center networks (DCNs) are increasing for meeting the need of users. A large number of data need to be processed and shared among servers in a data center. Recently, multicast traffic in DCNs has attracted much attention from academia due to the fact that multicast traffics have the dominating advantages for group communications in DCNs. Therefore, the appropriate multicast traffic scheduling in data center networks cannot only improve network efficiency but also save network resources. Li et al 2 propose a multicast scheduling algorithm to appropriately schedule flows to achieve traffic load balance so that network blocking can be avoided. In order to reduce the network blocking, they...