On Efficient Content Matching in Distributed Pub/Sub Systems

Abstract

Abstract-The efficiency of matching structures is the key issue for content publish/subscribe systems. In this paper, we propose an efficient matching tree structure, named COBASTREE, for a distributed environment. Particularly, we model a predicate in each subscription filter as an interval and published content value as a data point. The COBASTREE is designed to index all subscription intervals and a matching algorithm is proposed to match the data points to these indexed intervals. Through a set of techniques including selective multicast by bounding intervals, cost model-based interval division, and COBASTREE merging, COBASTREE can match the published contents against subscription filters with a high efficiency. We call the whole framework including COBASTREE and the associated techniques as COBAS. The performance evaluation in simulation environment and PlanetLab environment shows COBAS significantly outperforms two counterparts with low cost and fast forwarding.

DTA: Dynamic topology algorithms in content-based Publish/Subscribe

“…In this part, we would like to compare the system with our algorithms with the system with another algorithm. Among all the current researches on topology in Pub/Sub system, some are about Pub/Sub routing [17][18][19][20] and some are about content-based matching [21][22][23]. We choose one algorithm in [17] called dynamic publication routing (we call it DPR for short) which is also suitable for cyclic or acyclic topology.…”

Distributed top-k full-text content dissemination

“…However, Pub/Sub differs from this work as follows. First, the content-based pub/sub builds an indexing structure of either a full-dimensional index to cover all attributes or an index per attribute [31]. Given our problem with millions of query terms and document terms, the techniques used by the content-based pub/sub to build the traditional index (either a full-dimensional index to cover all attributes or an index per attribute) is inefficient due to the well known curse of dimensionality issue.…”

“…In terms of distributed content-based pub/sub (they adopt the similar filtering model as [11]), Cobas [31], Meghdoot [16] and Siena [9] are typical examples of distributed content-based pub/sub systems. Meghdoot [16] utilizes the favorable properties (e.g., scalability, fault tolerance, etc.)…”

“…of CAN [33] by mapping filter conditions to the CAN multiple-dimensional space. Cobas [31] builds distributed interval and segment trees to index subscription filters. Instead, Siena [9] focuses on a general distributed environment without specially organizing nodes into a structured P2P network like CAN.…”

A distributed full-text top-k document dissemination system in distributed hash tables

“…A number of subscription semantics and matching schemes have been considered for the publish/subscribe paradigm in the literature. Of those, content-based pub/sub [3,6,7,15], is deemed to provide the most flexible filtering model. It is also possible to implement contentbased pub/sub on top of a DHT [2,9].…”