NFP-6xxx - a 22nm high-performance network flow processor for 200Gb/s Software Defined Networking

2013 ◽  
Author(s):  
Gavin Stark ◽  
Sakir Sezer
Keyword(s):  
Network Flow ◽  
High Performance ◽  
Software Defined Networking

Optimal Reconfiguration of High-Performance VLSI Subarrays with Network Flow

2016 ◽  
Vol 27 (12) ◽  
pp. 3575-3587 ◽  
Author(s):  
Junyan Qian ◽  
Zhide Zhou ◽  
Tianlong Gu ◽  
Lingzhong Zhao ◽  
Liang Chang
Keyword(s):  
Network Flow ◽  
High Performance ◽  
Optimal Reconfiguration

scholarly journals Fog Integrated Secured and Distributed Environment for Healthcare Industry with Software Defined Networking

2021 ◽  
Vol 1 (1) ◽  
pp. 17-30
Author(s):  
Jamal Kh-madhloom
Keyword(s):  
High Performance ◽  
Fog Computing ◽  
Health Care Industry ◽  
Software Defined Networking ◽  
Distributed Environment ◽  
Raw Data ◽  
Vast Number ◽  
Peripheral Equipment ◽  
Data Production ◽  
Data Consumption

Fog computing is a segment of cloud computing where a vast number of peripheral equipment links to the internet. The term "fog" indicates the edges of a cloud in which high performance can be achieved. Many of these devices will generate voluminous raw data as from sensors, and rather than forward all this data to cloud-based servers to be processed, the idea behind fog computing is to do as much processing as possible using computing units co-located with the data-generating devices, so that processed rather than raw data is forwarded, and bandwidth requirements are reduced. A major advantage of processing locally is that data is more often used for the same computation machine which produced the data. Also, the latency between data production and data consumption was reduced. This example is not fully original, since specially programmed hardware has long been used for signal processing. The work presents the integration of software defined networking with the association of fog environment to have the cavernous implementation patterns in the health care industry with higher degree of accuracy.

AFBV: A High-Performance Network Flow Classification Method for Multi-Dimensional Fields and FPGA Implementation

2019 ◽  
Vol 28 (14) ◽  
pp. 1950237
Author(s):  
Ling Zheng ◽  
Zhiliang Qiu ◽  
Weina Wang ◽  
Weitao Pan ◽  
Shiyong Sun ◽  
...  
Keyword(s):  
High Throughput ◽  
Network Flow ◽  
High Speed ◽  
High Performance ◽  
Clock Frequency ◽  
Pipeline Architecture ◽  
Exact Matching ◽  
Flow Classification ◽  
Rule Sets ◽  
Bit Vector

Network flow classification is a key function in high-speed switches and routers. It directly determines the performance of network devices. With the development of the Internet and various kinds of applications, the flow classification needs to support multi-dimensional fields, large rule sets, and sustain a high throughput. Software-based classification cannot meet the performance requirement as high as 100 Gbps. FPGA-based flow classification methods can achieve a very high throughput. However, the range matching is still challenging. For this, this paper proposes a range supported bit vector (RSBV) method. First, the characteristic of range matching is analyzed, then the rules are pre-encoded and stored in memory. Second, the fields of an input packet header are used as addresses to read the memory, and the result of range matching is derived through pipelined Boolean operations. On this basis, bit vector for any types of fields (AFBV) is further proposed, which supports the flow classification for multi-dimensional fields efficiently, including exact matching, longest prefix matching, range matching, and arbitrary wildcard matching. The proposed methods are implemented in FPGA platform. Through a two-dimensional pipeline architecture, the AFBV can operate at a high clock frequency and can achieve a processing speed of more than 100 Gbps. Simulation results show that for a rule set of 512-bit width and 1[Formula: see text]k rules, the AFBV can achieve a throughput of 520 million packets per second (MPPS). The performance is improved by 44% compared with FSBV and 30% compared with Stride BV. The power consumption is reduced by about 43% compared with TCAM solution.

scholarly journals A Framework for Real-Time Intrusion Response in Software Defined Networking Using Precomputed Graphical Security Models

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Taehoon Eom ◽  
Jin B. Hong ◽  
SeongMo An ◽  
Jong Sou Park ◽  
Dong Seong Kim
Keyword(s):  
Real Time ◽  
Network Flow ◽  
Software Defined Networking ◽  
Cyber Attacks ◽  
Security Assessment ◽  
Security Metrics ◽  
Intrusion Response ◽  
Security Models ◽  
Flow Table ◽  
Attack Trees

Software defined networking (SDN) has been adopted in many application domains as it provides functionalities to dynamically control the network flow more robust and more economical compared to the traditional networks. In order to strengthen the security of the SDN against cyber attacks, many security solutions have been proposed. However, those solutions need to be compared in order to optimize the security of the SDN. To assess and evaluate the security of the SDN systematically, one can use graphical security models (e.g., attack graphs and attack trees). However, it is difficult to provide defense against an attack in real time due to their high computational complexity. In this paper, we propose a real-time intrusion response in SDN using precomputation to estimate the likelihood of future attack paths from an ongoing attack. We also take into account various SDN components to conduct a security assessment, which were not available when addressing only the components of an existing network. Our experimental analysis shows that we are able to estimate possible attack paths of an ongoing attack to mitigate it in real time, as well as showing the security metrics that depend on the flow table, including the SDN component. Hence, the proposed approach can be used to provide effective real-time mitigation solutions for securing SDN.

A secure and high-performance multi-controller architecture for software-defined networking

2016 ◽  
Vol 17 (7) ◽  
pp. 634-646 ◽  
Author(s):  
Huan-zhao Wang ◽  
Peng Zhang ◽  
Lei Xiong ◽  
Xin Liu ◽  
Cheng-chen Hu
Keyword(s):  
High Performance ◽  
Software Defined Networking

scholarly journals A Transdisciplinary Approach for Analyzing Stress Flow Patterns in Biostructures

2019 ◽  
Vol 24 (2) ◽  
pp. 47 ◽  
Author(s):  
Reena Patel ◽  
Guillermo Riveros ◽  
David Thompson ◽  
Edward Perkins ◽  
Jan Jeffery Hoover ◽  
...  
Keyword(s):  
Network Flow ◽  
High Performance ◽  
Computational Mechanics ◽  
Integrated Approach ◽  
Flow Patterns ◽  
Complex Model ◽  
Network Approach ◽  
Flow Network ◽  
Mathematical Algorithm ◽  
Stress Flow

This work presents a transdisciplinary, integrated approach that uses computational mechanics experiments with a flow network strategy to gain fundamental insights into the stress flow of high-performance, lightweight, structured composites by investigating the rostrum of paddlefish. Although computational mechanics experiments give an overall distribution of stress in the structural systems, stress flow patterns formed at nascent stages of loading a biostructure are hard to determine. Computational mechanics experiments on a complex model will involve a high degree of freedom thereby making the extraction of finer details computationally expensive. To address this challenge, the evolution of the stress in the rostrum is formulated as a network flow problem generated by extracting the node and connectivity information from the numerical model of the rostrum. The flow network is weighted based on the parameter of interest, which is stress in the current research. The changing kinematics of the system is provided as input to the mathematical algorithm that computes the minimum cut of the flow network. The flow network approach is verified using two simple classical problems. When applied to the model of the rostrum, the flow network approach identifies strain localization in tensile regions, and buckling/crushing in compressive regions.

scholarly journals Load Balancing in Software Defined Networking: A Review

2018 ◽  
Vol 7 (2) ◽  
pp. 1-5
Author(s):  
Prabhjot Kaur ◽  
Jasmeen Kaur Chahal ◽  
Abhinav Bhandari
Keyword(s):  
Load Balancing ◽  
Network Flow ◽  
Software Defined Networking ◽  
Centralized Control ◽  
Control Plane ◽  
Survey Paper ◽  
Data Rates ◽  
Load Balancer ◽  
Service Data ◽  
And Control

Software Defined Networking is an adaptable way of networking, which disconnects data forwarding plane and control-plane of system equipment’s and also solves issues in existing network infrastructure. More specifically, the control-plane of software defined network decides the advancing way of network flow with Centralized Control Manner (CCM). SDN (Software Defined Networking) is a strategy for making, planning and overseeing systems which intend to change this present unfortunate circumstance. It has been used in dissimilar areas, like a campus networks and data center systems. In this survey paper, we’ve reviewed the concept of (SDNs) Software Defined Networks, its architecture and applications. In the survey, it has been found that SDN load balancing has become more smart and efficient and reduces the statistic collection overhead and maintain better QoS (Quality of Service) data rates. In addition, we reviewed the direct routing based algorithms of Load Balancer and compare with Round Robin Strategy. Furthermore, we’ve reviewed and compared the existing work to get better idea about the concept of Load balancing.

Sign in / Sign up

Export Citation Format

Share Document