Scalable Interactive Volume Rendering Using Off-the-shelf Components

This paper describes an application of a second generation implementation of the Sepia architecture (Sepia-2) to interactive volu-metric visualization of large rectilinear scalar fields. By employingpipelined associative blending operators in a sort-last configuration a demonstration system with 8 rendering computers sustains 24 to 28 frames per second while interactively rendering large data volumes (1024x256x256 voxels, and 512x512x512 voxels). We believe interactive performance at these frame rates and data sizes is unprecedented. We also believe these results can be extended to other types of structured and unstructured grids and a variety of GL rendering techniques including surface rendering and shadow map-ping. We show how to extend our single-stage crossbar demonstration system to multi-stage networks in order to support much larger data sizes and higher image resolutions. This requires solving a dynamic mapping problem for a class of blending operators that includes Porter-Duff compositing operators

A Survey on Enterprise Network Security: Asset Behavioral Monitoring and Distributed Attack Detection

Enterprise networks that host valuable assets and services are popular and frequent targets of distributed network attacks. In order to cope with the ever-increasing threats, industrial and research communities develop systems and methods to monitor the behaviors of their assets and protect them from critical attacks. In this paper, we systematically survey related research articles and industrial systems to highlight the current status of this arms race in enterprise network security. First, we discuss the taxonomy of distributed network attacks on enterprise assets, including distributed denial-of-service (DDoS) and reconnaissance attacks. Second, we review existing methods in monitoring and classifying network behavior of enterprise hosts to verify their benign activities and isolate potential anomalies. Third, state-of-the-art detection methods for distributed network attacks sourced from external attackers are elaborated, highlighting their merits and bottlenecks. Fourth, as programmable networks and machine learning (ML) techniques are increasingly becoming adopted by the community, their current applications in network security are discussed. Finally, we highlight several research gaps on enterprise network security to inspire future research.Comment: Journal paper submitted to Elseive

Load Balancing Algorithms In Software Defined Network

Compared with the traditional networks, the SDN networks have shown great advantages in many aspects, but also exist the problem of the load imbalance. If the load distribution uneven in the SDN networks, it will greatly affect the performance of network. Many SDN-based load balancing strategies have been proposed to improve the performance of the SDN networks. Therefore, in this paper a finding form comprehensive review help to improve further understanding of lead b balancing algorithms in SDN

Techniques for Processing TCP/IP Flow Content in Network Switches at Gigabit Line Rates

The growth of the Internet has enabled it to become a critical component used by businesses, governments and individuals. While most of the traffic on the Internet is legitimate, a proportion of the traffic includes worms, computer viruses, network intrusions, computer espionage, security breaches and illegal behavior. This rogue traffic causes computer and network outages, reduces network throughput, and costs governments and companies billions of dollars each year. This dissertation investigates the problems associated with TCP stream processing in high-speed networks. It describes an architecture that simplifies the processing of TCP data streams in these environments and presents a hardware circuit capable of TCP stream processing on multi-gigabit networks for millions of simultaneous network connections. Live Internet traffic is analyzed using this new TCP processing circuit

Inter-domain networking innovation on steroids: Empowering IXPs with SDN capabilities

While innovation in inter-domain routing has remained stagnant for over a decade, Internet Exchange Points (IXPs) are consolidating their role as economically advantageous interconnection points for reducing path latencies and exchanging ever increasing amounts of traffic. As such, IXPs appear as a natural place to foster network innovation and assess the benefits of Software-Defined Networking (SDN), a recent technological trend that has already boosted innovation within data-center networks. In this paper, we give a comprehensive overview of use cases for SDN at IXPs, which leverage the superior vantage point of an IXP to introduce advanced features like load-balancing and DDoS mitigation. We discuss the benefits of SDN solutions by analyzing real-world data from one of the largest IXPs. We also leverage insights into IXP operations to not only shape benefits for members but also for operators.This research is (in part) supported by European Union’s Horizon 2020 research and innovation programme under the ENDEAVOUR project (grant agreement 644960).This is the author accepted manuscript. The final version is available from IEEE via https://doi.org/ 10.1109/MCOM.2016.758827

A Decentralized Lightweight Blockchain Nodes Architecture Based on a Secure OpenFlow Protocol Controller Channel

The Blockchain technology raises many concerns because all transactions must be verified by every node in the Blockchain network. Because of this the spread of Blockchain technology in all sectors has been very slow. This paper introduces Blockchain nodes and the difference between nodes and then our approach light node control node based on SDN that has a more secure routing mechanism than only light nodes or networks without full nodes and light nodes. In peer to peer networks nodes connect and disconnect all the time and some of these nodes are malicious and will cost the network security and scalability. We applied a technique that uses route packet information by making a table of the IP address with OpenFlow. We calculate our approach flow measurement performance using large scale simulations. The result showed that by using an IP table we can control the nodes connections and make more scalable, secure ones without the need of full nodes working all the time. The proposed model is a distributed architecture based on Blockchain and OpenFlow protocol technology that provides a low-cost, secure, intelligent, and simple approach in all types of computer network infrastructure

Mitigating interconnect and end host congestion in modern networks

One of the most critical building blocks of the Internet is the mechanism to mitigate network congestion. While existing congestion control approaches have served their purpose well in the last decades, the last few years saw a significant increase in new applications and user demand, stressing the network infrastructure to the extent that new ways of handling congestion are required. This dissertation identifies the congestion problems caused by the increased scale of the network usage, both in inter-AS connects and on end hosts in data centers, and presents abstractions and frameworks that allow for improved solutions to mitigate congestion. To mitigate inter-AS congestion, we develop Unison, a framework that allows an ISP to jointly optimize its intra-domain routes and inter-domain routes, in collaboration with content providers. The basic idea is to provide the ISP operator and the neighbors of the ISP with an abstraction of the ISP network in the form of a virtual switch (vSwitch). Unison allows the ISP to provide hints to its neighbors, suggesting alternative routes that can improve their performance. We investigate how the vSwitch abstraction can be used to maximize the throughput of the ISP. To mitigate end-host congestion in data center networks, we develop a backpressure mechanism for queuing architecture in congested end hosts to cope with tens of thousands of flows. We show that current end-host mechanisms can lead to high CPU utilization, high tail latency, and low throughput in cases of congestion of egress traffic. We introduce the design, implementation, and evaluation of zero-drop networking (zD) stack, a new architecture for handling congestion of scheduled buffers. Besides queue overflow, another cause of congestion is CPU resource exhaustion. The CPU cost of processing packets in networking stacks, however, has not been fully investigated in the literature. Much of the focus of the community has been on scaling servers in terms of aggregate traffic intensity, but bottlenecks caused by the increasing number of concurrent flows have received little attention. We conduct a comprehensive analysis on the CPU cost of processing packets and identify the root cause that leads to high CPU overhead and degraded performance in terms of throughput and RTT. Our work highlights considerations beyond packets per second for the design of future stacks that scale to millions of flows.Ph.D

ENDEAVOUR: A Scalable SDN Architecture For Real-World IXPs.

Innovation in interdomain routing has remained stagnant for over a decade. Recently, IXPs have emerged as economically-advantageous interconnection points for reducing path latencies and exchanging ever increasing traffic volumes among, possibly, hundreds of networks. Given their far-reaching implications on interdomain routing, IXPs are the ideal place to foster network innovation and extend the benefits of SDN to the interdomain level. In this paper, we present, evaluate, and demonstrate EN- DEAVOUR, an SDN platform for IXPs. ENDEAVOUR can be deployed on a multi-hop IXP fabric, supports a large number of use cases, and is highly-scalable while avoiding broadcast storms. Our evaluation with real data from one of the largest IXPs, demonstrates the benefits and scalability of our solution: ENDEAVOUR requires around 70% fewer rules than alternative SDN solutions thanks to our rule partitioning mechanism. In addition, by providing an open source solution, we invite ev- eryone from the community to experiment (and improve) our implementation as well as adapt it to new use cases.European Union’s Horizon 2020 research and innovation programme under the ENDEAVOUR project (grant agreement 644960)

Declaratively programmable ultra-low latency audio effects processing on FPGA

WaveCore is a coarse-grained reconfigurable processor architecture, based on data-flow principles. The processor architecture consists of a scalable and interconnected cluster of Processing Units (PU), where each PU embodies a small floating-point RISC processor. The processor has been designed in technology-independent VHDL and mapped on a commercially available FPGA development platform. The programming methodology is declarative, and optimized to the application domain of audio and acoustical modeling. A benchmark demonstrator algorithm (guitar-model, comprehensive effects-gear box, and distortion/cabinet model) has been developed and applied to the WaveCore development platform. The demonstrator algorithm proved that WaveCore is very well suited for efficient modeling of complex audio/acoustical algorithms with negligible latency and virtually zero jitter. An experimental Faust-to-WaveCore compiler has shown the feasibility of automated compilation of Faust code to the WaveCore processor target