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Graph search for cloud network management
KTH, School of Electrical Engineering (EES), Communication Networks. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
KTH, School of Electrical Engineering (EES), Communication Networks. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
2014 (English)In: IEEE/IFIP NOMS 2014 - IEEE/IFIP Network Operations and Management Symposium: Management in a Software Defined World, IEEE conference proceedings, 2014Conference paper, Published paper (Refereed)
Abstract [en]

A large part of operational and configuration information in networks and clouds has graph structure, e.g., virtual network topologies, IP flows, communication links of distributed cloud applications. The final objective of this work is to develop a scalable management system that allows real-time management applications, such as network analytics and anomaly detection applications, to search for graph-structured operational information. The paper contains a step towards this objective. The key challenge is to devise an efficient and scalable search process on data that is volatile and distributed across the network infrastructure. Approaches that are currently pursued for distributed graph databases are not applicable in this context. This paper presents design options and possible solutions for engineering a scalable graph search system that supports management applications. It includes a simple information model based on property graphs and a search query language based on keyword search. The architecture of the system centers around a distributed search plane that performs query processing using a network of search nodes. Finally, the paper outlines the design of a search node, which contains a local database that maintains graph partitions.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2014.
Keyword [en]
distributed management, distributed query processing, graph search, in-network management, network search, Electric network topology, Network management, Query languages, Query processing, Search engines, Information management
National Category
Communication Systems
Identifiers
URN: urn:nbn:se:kth:diva-167623DOI: 10.1109/NOMS.2014.6838335ISI: 000356862300105Scopus ID: 2-s2.0-84904150733ISBN: 9781479909131 (print)OAI: oai:DiVA.org:kth-167623DiVA: diva2:813900
Conference
IEEE/IFIP Network Operations and Management Symposium: Management in a Software Defined World, NOMS 2014, 5 May 2014 - 9 May 2014, Krakow
Note

QC 20150525

Available from: 2015-05-25 Created: 2015-05-22 Last updated: 2016-04-11Bibliographically approved
In thesis
1. A Bottom-Up Approach to Real-Time Search in Large Networks and Clouds
Open this publication in new window or tab >>A Bottom-Up Approach to Real-Time Search in Large Networks and Clouds
2016 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Networked systems, such as telecom networks and cloud infrastructures, generate and hold vast amounts of conguration and operational data. The goal of this work is to make all this data available through a real-time search process named network search , which will enable new real-time management solutions. The thesis contains several contributions towards engineering a network search system. Key elements of our design are a weakly structured information model that includes spatial properties, a query language that supports location- and schema-oblivious search queries, a peer-to-peer architecture, a set of echo protocols for scalable query processing, and an indexing protocol for ecient routing for spatial queries. The data against which network search is performed is maintained in local real-time databases close to the data sources. The design follows a bottom-up approach in the sense that the topology for query routing is constructed from the underlying network topology. We have built a prototype of the system on a cloud testbed and developed applications that use network search functionality. Testbed measurements suggest that it is feasible to engineer a network search system that processes queries at low latency and low overhead and that can scale to 100'000 nodes. Simulation results for spatial queries show that query processing achieves response times and incurs overhead close to an optimal protocol, and that query result remains accurate under signicant churn.

Place, publisher, year, edition, pages
Stockholm: Kungliga Tekniska högskolan, 2016. 122 p.
Series
TRITA-EE, ISSN 1653-5146 ; 2016:012
National Category
Communication Systems Telecommunications
Research subject
Electrical Engineering
Identifiers
urn:nbn:se:kth:diva-184236 (URN)978-91-7595-858-3 (ISBN)
Public defence
2016-05-03, F3, Lindstedtsvägen 26, våningsplan 2, Sing-Sing, KTH Campus, Stockholm, 09:30 (English)
Opponent
Supervisors
Note

QC 20160411

Available from: 2016-04-11 Created: 2016-03-31 Last updated: 2017-08-16Bibliographically approved

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