Pham Ngoc Nam

ECODANE: A customizable hybrid testbed for green data center networks

In this paper we propose a new testbed architecture that combines hardware network devices with virtual emulation test environment to improve scalability, flexibility and accuracy. The testbed enables to design and experiment new concepts for energy-efficient data center. It is based on OpenFlow, a Software Defined Networking (SDN) technology that facilitates the deployment of energy-aware protocols and mechanisms.

Enabling experiments for energy-efficient data center networks on OpenFlow-based platform

Energy efficiency is becoming increasingly important in todays networking infrastructure, especially in data center networks. Recent surveys have shown that the energy utilized by computing and networking components in a data center considerably contributes to its operation costs. Therefore performance and energy issues are important for the design of large multi-tier data centers that can support multiple services. However, the design, analysis, and experiments of such a large and complex system often suffer from the lack of appropriate experimental environments. With this motivation, we present a platform for in-depth analysis of energy-aware data center networks. The platform is a combination of hardware testbed and emulation. Based on real traffic patterns measured in a data center and with the energy model obtained from realistic measurements on NetFPGA-based OpenFlow switches, the experimental platform is designed to capture details of energy consumed by all network components such as links, ports, and switches under different scenarios.

Power aware OpenFlow switch extension for energy saving in data centers

Data centers play an important role in our daily activities. The increasing demand for data centers in both scale and size has led to huge energy consumption. The cost and environmental impact of data centers increases due to large amounts of carbon emissions. One solution to this problem is to intelligently control the power consumption of switches used in data centers. This paper proposes an extension to OpenFlow switches to support different power saving modes. The extension includes defining new messages in Openflow standard and designing an OpenFlow Switch Controller (OSC) that is able to turn on/off switches and disable/enable ports. To prove the soundness of the proposed extension, the OSC has been used to control the NetFPGA based OpenFlow switches in the ECODANE framework. The results presented in this paper can aslo be used by the OpenFlow compliant switches manufacturer or by power aware research community.

Request adaptation for adaptive streaming over HTTP/2

In this paper, we propose a client-based adaptation method for Adaptive Streaming over HTTP/2 leveraging the server push feature. A cost function that takes into account both the number of pushed segments and the playout buffer level is defined. Experiment results show that the proposed method can improve the tradeoff between the number of requests and buffer stability compared to existing solutions.

A reliable analyzer for energy-saving approaches in Large Data Center Networks

Nowadays a big effort has been paid to make energy-efficient Data Center Networks (DCNs). There are several proposed solutions to reduce the energy consumption in DCN. However, for researchers, it is difficult to evaluate the energy saving performance of those approaches in a large-size network due to the testbed/emulation environment limitation. In this paper we construct a Performance Evaluation Simulator (called GreenDC Analyzer) that can model a large DCN of thousands of servers. The tool is shown to have a reliability and flexibility in processing and providing accurate and stable performance evaluations with various switch types, and different energy-saving schemes under the same traffic conditions. The tool also allows us to have a deeper investigation of the energy saving performance for the two well-known energy-saving schemes: Power Scaling and Idle Logic. In the bottom line, the Analyzer could be a useful tool for researchers to study pros and cons of different energy-saving approaches in a data center.

Energy saving for OpenFlow switch on the NetFPGA platform based on queue engineering.

Data centers play an important role in our daily activities. The increasing demand on data centers in both scale and size has led to huge energy consumption that rises the cost of data centers. Besides, environmental impacts also increase considerably due to a large amount of carbon emissions. In this paper, we present a design aimed at green networking by reducing the power consumption for routers and switches. Firstly, we design the Balance Switch on the NetFPGA platform to save consumed energy based on Queue Engineering. Secondly, we design the test-bed system to precisely measure the consumed energy of our switches. Experimental results show that energy saving of our switches is about 30% - 35% of power consumption according to variation of input traffic compared with normal Openflow Switch. Finally, we describe performance evaluations.

An Evaluation of Screen Content Casting over Mobile and Wireless Networks

Thanks to the availability of many smart devices, displays, and broadband connections, screen casting/sharing has become an important functionality for user devices. Meanwhile, a new video standard called screen content coding (SCC) is going to be issued to support this trend. This paper presents a standard-compliant implementation and evaluation of SCC streaming to mobile devices. The study is targeted at a feasible design and settings for customer devices, supporting both content-generating side and content-consuming side. The evaluation results help to answer how a sending device should generate screen content videos, and how a receiving device could be implemented and adjusted in time-varying environments of mobile networks and wireless home networks. To the best of our knowledge, this is the first evaluation study for SCC casting.

A QoS-adaptive framework for screen sharing over Internet

In this paper, we present a QoS-adaptive framework for screen sharing over heterogeneous networks. Basic requirements and important issues of a screen sharing system are described. For determining optimal video coding parameters, adaptation trajectory is used as the hints in making decisions. Further, experiments are carried out to investigate the trade-off between video bitrate and the buffering delay in time-varying networks.

A probability-based adaption method for server-pushed streaming over HTTP 2.0

Nowadays, HTTP protocol contributes significantly in media streaming. Recently, the deployment of HTTP 2.0 has introduced several novel instruments for developers to control and optimize the streaming process. In this paper, we propose a streaming solution for live streaming services with small buffer sizes, focusing on pushed function of HTTP 2.0. By adjusting the number of pushed-segments in each request from client, our method provides an option to achieve a balance between the number of requests and the stability of the service. The experimental results show that our proposed method surpasses conventional streaming strategy in terms of buffer level and overall network overhead.

Dynamic mapping of quality adjustable applications on NoC-based reconfigurable platforms

NoC based SoC FPGAs are a promising technology for high performance embedded systems because they provide a good balance between performance, rapid time to market, cost and flexibility. The reconfigurability aspect of FPGAs allows FPGA platforms to adapt themselves to the various processing requirement of applications. On the other hand, many applications are designed in such a way that their quality level can be adjusted to match the processing capability of hardware platforms. In this paper, we consider the problem of mapping quality adjustable applications onto heterogeneous NoC-based dynamically reconfigurable platforms under resource constraints while ensuring the maximum overall quality of service (QoS) of the applications. The parameters such as resource usage efficiency, processing time, communication overhead and quality of service will be considered in the mapping. Simulation results show that the proposed solution is very flexible and can accommodate more applications than existing solutions on the same platform.