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Fine-Grained, Multi-Domain Network Resource Abstraction as a Fundamental Primitive to Enable High-Performance, Collaborative Data Sciences

Published: 07 August 2018 Publication History

Abstract

Recently, a number of multi-domain network resource information and reservation systems have been developed and deployed, driven by the demand and substantial benefits of providing predictable network resources. A major lacking of such systems, however, is that they are based on coarse-grained or localized information, resulting in substantial inefficiencies. In this paper, we present Explorer, a simple, novel, highly efficient multi-domain network resource discovery system to provide fine-grained, global network resource information, to support high-performance, collaborative data sciences. The core component of Explorer is the use of linear inequalities, referred to as resource state abstraction (ReSA), as a compact, unifying representation of multi-domain network available bandwidth, which simplifies applications without exposing network details. We develop a ReSA obfuscating protocol and a proactive full-mesh ReSA discovery mechanism to ensure the privacy-preserving and scalability of Explorer. We fully implement Explorer and demonstrate its efficiency and efficacy through extensive experiments using real network topologies and traces.

References

[1]
The large hadron collider. https://home.cern/topics/large-hadron-collider.
[2]
Oscars: On-demand secure circuits and advance reservation system. https://www.es.net/engineering-services/oscars/.
[3]
CMS Task Monitoring. http://dashb-cms-job.cern.ch/.

Cited By

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  • (2020)ANI: Abstracted Network Inventory for Streamlined Service Placement in Distributed Clouds2020 6th IEEE Conference on Network Softwarization (NetSoft)10.1109/NetSoft48620.2020.9165443(319-325)Online publication date: Jun-2020

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  1. Fine-Grained, Multi-Domain Network Resource Abstraction as a Fundamental Primitive to Enable High-Performance, Collaborative Data Sciences

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          cover image ACM Conferences
          SIGCOMM '18: Proceedings of the ACM SIGCOMM 2018 Conference on Posters and Demos
          August 2018
          165 pages
          ISBN:9781450359153
          DOI:10.1145/3234200
          Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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          New York, NY, United States

          Publication History

          Published: 07 August 2018

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          Author Tags

          1. Collaborative Data Sciences
          2. Interdomain
          3. Resource Discovery
          4. Resource State Abstraction

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          • Short-paper
          • Research
          • Refereed limited

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          SIGCOMM '18
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          SIGCOMM '18: ACM SIGCOMM 2018 Conference
          August 20 - 25, 2018
          Budapest, Hungary

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          Overall Acceptance Rate 92 of 158 submissions, 58%

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          • (2020)ANI: Abstracted Network Inventory for Streamlined Service Placement in Distributed Clouds2020 6th IEEE Conference on Network Softwarization (NetSoft)10.1109/NetSoft48620.2020.9165443(319-325)Online publication date: Jun-2020

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