title: Flow clustering using machine learning techniques

authors: McGregor, Anthony James

subjects: Science & Technology

abstract: Packet header traces are widely used in network analysis. Header traces are the aggregate of traffic from many concurrent applications. We present a methodology, based on machine learning, that can break the trace down into clusters of traffic where each cluster has different traffic characteristics. Typical clusters include bulk transfer, single and multiple transactions and interactive traffic, amongst others. The paper includes a description of the methodology, a visualisation of the attribute statistics that aids in recognising cluster types and a discussion of the stability and effectiveness of the methodology.

text: Flow clustering using machine learning techniques Packet header traces are widely used in network analysis. Header traces are the aggregate of traffic from many concurrent applications. We present a methodology, based on machine learning, that can break the trace down into clusters of traffic where each cluster has different traffic characteristics. Typical clusters include bulk transfer, single and multiple transactions and interactive traffic, amongst others. The paper includes a description of the methodology, a visualisation of the attribute statistics that aids in recognising cluster types and a discussion of the stability and effectiveness of the methodology.

year: 2004

title: On the Benefits of Non-Canonical Filtering in Publish/Subscribe Systems

authors: Bittner, Sven

subjects: computer science

abstract: Current matching approaches in pub/sub systems only allow conjunctive subscriptions. Arbitrary subscriptions have to be transformed into canonical expressions, e.g., DNFs, and need to be treated as several conjunctive subscriptions. This technique is known from database systems and allows us to apply more efficient filtering algorithms. Since pub/sub systems are the contrary to traditional database systems, it is questionable if filtering several canonical subscriptions is the most efficient and scalable way of dealing with arbitrary subscriptions. In this paper we show that our filtering approach supporting arbitrary Boolean subscriptions is more scalable and efficient than current matching algorithms requiring transformations of subscriptions into DNFs.

text: On the Benefits of Non-Canonical Filtering in Publish/Subscribe Systems Current matching approaches in pub/sub systems only allow conjunctive subscriptions. Arbitrary subscriptions have to be transformed into canonical expressions, e.g., DNFs, and need to be treated as several conjunctive subscriptions. This technique is known from database systems and allows us to apply more efficient filtering algorithms. Since pub/sub systems are the contrary to traditional database systems, it is questionable if filtering several canonical subscriptions is the most efficient and scalable way of dealing with arbitrary subscriptions. In this paper we show that our filtering approach supporting arbitrary Boolean subscriptions is more scalable and efficient than current matching algorithms requiring transformations of subscriptions into DNFs.

year: 2005

title: Taking quality work to a new brilliance: Tama Ma on tour [Review]

authors: Crawford, Terri Ripeka

subjects: Tama Ma

abstract: Choreographers: Taiaroa Royal and Taane Mete; Douglas Wright; Michael Parmenter  Okareka Dance Company at Telecom Playhouse Theatre, WEL Energy Trust Academy of Performing Arts, Hamilton
From 17 Jun 2009 to 20 Jun 2009 

Reviewed by Terri Ripeka Crawford, 22 Jun 2009.

text: Taking quality work to a new brilliance: Tama Ma on tour [Review] Choreographers: Taiaroa Royal and Taane Mete; Douglas Wright; Michael Parmenter  Okareka Dance Company at Telecom Playhouse Theatre, WEL Energy Trust Academy of Performing Arts, Hamilton
From 17 Jun 2009 to 20 Jun 2009 

Reviewed by Terri Ripeka Crawford, 22 Jun 2009.

year: 2009