In distributed machine learning (DML) based on the parameter server (PS) architecture, unbalanced communication load distribution of PSs will lead to a significant slowdown of model synchronization in heterogeneous networks due to low utilization of bandwidth. To address this problem, a network-aware adaptive PS load distribution scheme is proposed, which accelerates model synchronization by proactively adjusting the communication load on PSs according to network states. We evaluate the proposed scheme on MXNet, known as a real-world distributed training platform, and results show that our scheme achieves up to 2.68 times speed-up of model training in the dynamic and heterogeneous network environment.

Distributed Denial of Service (DDoS) attacks have been one of the most destructive threats to Internet security. By decoupling the network control and data plane, software defined networking (SDN) offers a flexible network management paradigm to solve DDoS attack in traditional networks. However, the centralized nature of SDN is also a potential vulnerability for DDoS attack. In this paper, we first provide some SDN-supported mechanisms against DDoS attack in traditional networks. A systematic review of various SDN-self DDoS threats are then presented as well as the existing literatures on quickly DDoS detection and defense in SDN. Finally, some promising research directions in this field are introduced.

The Internet plays increasingly important roles in everyone s life; however, the existence of a mismatch between the basic architectural idea beneath the Internet and the emerging requirements for it is becoming more and more obvious. Although the Internet community came up with a cons ensus that the future network should be trustworthy, the concept of trustworthy networks and the ways leading us to a trustworthy network are not yet clear. This res earch insists that the security, controllability, manageability, and survivability should be basic properties of a trustworthy network. The key ideas and techniques involved in these properties are studied, and recent developments and progresses are surveyed. At the same time, the technical trends and challenges are briefly discussed. The network trustworthiness could and should be eventually achieved.