Technical reports
ECCO: Data centric asynchronous communication
December 2006, 210 pages
This technical report is based on a dissertation submitted September 2006 by the author for the degree of Doctor of Philosophy to the University of Cambridge, Lucy Cavendish College.
DOI: 10.48456/tr-677
Abstract
This dissertation deals with data centric networking in distributed systems, which relies on content addressing instead of host addressing for participating nodes, thus providing network independence for applications. Publish/subscribe asynchronous group communication realises the vision of data centric networking that is particularly important for networks supporting mobile clients over heterogeneous wireless networks. In such networks, client applications prefer to receive specific data and require selective data dissemination. Underlying mechanisms such as asynchronous message passing, distributed message filtering and query/subscription management are essential. Furthermore, recent progress in wireless sensor networks brought a new dimension of data processing in ubiquitous computing, where the sensors are used to gather high volumes of different data types and to feed them as contexts to a wide range of applications.
Particular emphasis has been placed on fundamental design of event representation. Besides existing event attributes, event order, and continuous context information such as time or geographic location can be incorporated within an event description. Data representation of event and query will be even more important in future ubiquitous computing, where events flow over heterogeneous networks. This dissertation presents a multidimensional event representation (i.e., Hypercube structure in RTree) for efficient indexing, filtering, matching, and scalability in publish/subscribe systems. The hypercube event with a typed content-based publish/subscribe system for wide-area networks is demonstrated for improving the event filtering process.
As a primary focus, this dissertation investigates a structureless, asynchronous group communication over wireless ad hoc networks named ‘ECCO Pervasive Publish/Subscribe’ (ECCO-PPS). ECCO-PPS uses context-adaptive controlled flooding, which takes a cross-layer approach between middleware and network layers and provides a content-based publish/subscribe paradigm. Traditionally events have been payload data within network layer components; the network layer never touches the data contents. However, application data have more influence on data dissemination in ubiquitous computing scenarios.
The state information of the local node may be the event forwarding trigger. Thus, the model of publish/subscribe must become more symmetric, with events being disseminated based on rules and conditions defined by the events themselves. The event can thus choose the destinations instead of relying on the potential receivers’ decision. The publish/subscribe system offers a data centric approach, where the destination address is not described with any explicit network address. The symmetric publish/subscribe paradigm brings another level to the data-centric paradigm, leading to a fundamental change in functionality at the network level of asynchronous group communication and membership maintenance.
To add an additional dimension of event processing in global computing, It is important to understand event aggregation, filtering and correlation. Temporal ordering of events is essential for event correlation over distributed systems. This dissertation introduces generic composite event semantics with interval-based semantics for event detection. This precisely defines complex timing constraints among correlated event instances.
In conclusion, this dissertation provides advanced data-centric asynchronous communication, which provides efficiency, reliability, and robustness, while adapting to the underlying network environments.
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BibTeX record
@TechReport{UCAM-CL-TR-677,
author = {Yoneki, Eiko},
title = {{ECCO: Data centric asynchronous communication}},
year = 2006,
month = dec,
url = {https://www.cl.cam.ac.uk/techreports/UCAM-CL-TR-677.pdf},
institution = {University of Cambridge, Computer Laboratory},
doi = {10.48456/tr-677},
number = {UCAM-CL-TR-677}
}