programmable network
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2021 ◽  
Author(s):  
Felipe A. Lopes

The programmable network architectures that emerged in the last decade have allowed new ways to enable Autonomic Networks. However, there are several open issues to address before making such a possibility into a feasible reality. For instance, defining network goals, translating them into network rules, and granting the correct functioning of the network control loop in a self-adaptive manner are examples of complex tasks required to enable an autonomic networking environment. Fortunately, architectures based on the concept of Models at Runtime (MART) provide ways to overcome such complexity. This paper proposes a MART-based framework – using the RFC 7575 as reference (i.e., definitions and design goals for autonomic networking) – to implement autonomic management into a programmable network. The evaluation shows the proposed framework is suitable for satisfying the functional and performance requirements of a simulated network.


2020 ◽  
Vol 58 (4) ◽  
pp. 38-44 ◽  
Author(s):  
Gyeongsik Yang ◽  
Bong-yeol Yu ◽  
Heesang Jin ◽  
Chuck Yoo

2020 ◽  
Vol 245 ◽  
pp. 04012
Author(s):  
Shawn McKee ◽  
Benjeman Meekhof ◽  
Ezra Kissel ◽  
Andrew Keen ◽  
Kenneth M. Merz ◽  
...  

We report on the status of the OSiRIS project (NSF Award #1541335, UM, IU, MSU and WSU) after its fourth year. OSiRIS is delivering a distributed Ceph storage infrastructure coupled together with software-defined networking to support multiple science domains across Michigan’s three largest research universities as well as the Van Andel Institute. The project’s goal is to provide a single scalable, distributed storage infrastructure that allows researchers at each campus to work collaboratively with other researchers across campus or across institutions. The NSF CC*DNI DIBBs program which funded OSiRIS is seeking solutions to the challenges of multi-institutional collaborations involving large amounts of data and we are exploring the creative use of Ceph and networking to address those challenges. We will present details on the current status of the project and its various science domain users and use-cases. In the presentation we will cover the various design choices, configuration and the tuning and operational challenges we have encountered in providing a multiinstitutional Ceph deployment interconnected by a monitored, programmable network fabric. We will conclude with our plans for the final year of the project and its longer term outlook.


2019 ◽  
Vol 9 (22) ◽  
pp. 4786
Author(s):  
Farhadi Beldachi ◽  
Tzanakaki ◽  
Nejabati ◽  
Simeonidou

The time shared optical network (TSON) has been proposed as a dynamic optical transport network solution to provide high bandwidth and low latency connectivity in support of 5G technology and beyond. This work reviews the TSON evolution stages developed in the framework of the U.K. national project Towards Ultimate Convergence of All Networks (TOUCAN). The details of the TSON architecture and its various development phases are discussed, and the performance of its latest implementation is evaluated through relevant demonstration activities across the Smart Internet Lab’s 5G (5GUK) test network.


2019 ◽  
Vol 9 (21) ◽  
pp. 4541
Author(s):  
Syed Asif Raza Shah ◽  
Seo-Young Noh

Large scientific experimental facilities currently are generating a tremendous amount of data. In recent years, the significant growth of scientific data analysis has been observed across scientific research centers. Scientific experimental facilities are producing an unprecedented amount of data and facing new challenges to transfer the large data sets across multi continents. In particular, these days the data transfer is playing an important role in new scientific discoveries. The performance of distributed scientific environment is highly dependent on high-performance, adaptive, and robust network service infrastructures. To support large scale data transfer for extreme-scale distributed science, there is the need of high performance, scalable, end-to-end, and programmable networks that enable scientific applications to use the networks efficiently. We worked on the AmoebaNet solution to address the problems of a dynamic programmable network for bulk data transfer in extreme-scale distributed science environments. A major goal of the AmoebaNet project is to apply software-defined networking (SDN) technology to provide “Application-aware” network to facilitate bulk data transfer. We have prototyped AmoebaNet’s SDN-enabled network service that allows application to dynamically program the networks at run-time for bulk data transfers. In this paper, we evaluated AmoebaNet solution with real world test cases and shown that how it efficiently and dynamically can use the networks for bulk data transfer in large-scale scientific environments.


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