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Erschienen in:
Performance Optimization in IoT-Based Next-Generation Wireless Sensor Networks Kapitel lesen Erstes Kapitel lesen

2019 | OriginalPaper | Buchkapitel

A Flexible Synchronization Protocol to Learn Hidden Topics in P2PPS Systems

verfasst von : Shigenari Nakamura, Tomoya Enokido, Makoto Takizawa

Erschienen in: Transactions on Computational Collective Intelligence XXXIII

Verlag: Springer Berlin Heidelberg

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Abstract

We consider the P2PPS (peer-to-peer type of topic-based publish/subscribe) model where each peer process (peer) can publish and subscribe event messages with no centralized coordinator. Here, hidden topics are topics which a source peer is allowed to subscribe but a target peer is not allowed to subscribe. After receipt of an event message \(e_1\) with hidden topics, if a peer publishes another event message \(e_2\), the event message \(e_2\) may be related with the hidden topics of the event message \(e_1\). Hence, if an event message with hidden topics is received by another target peer which does not subscribe the hidden topics, the target peer can get information on the hidden topics. This means, illegal information flow to the target peer occurs. However, some hidden topics may be related with a subscription topic of a target peer and the target peer just may not know about the hidden topics. In this paper, we newly introduce a learning mechanism where each peer newly obtains hidden topics if the hidden topics are related with subscription topics. In this paper, we newly propose an FS-H (flexible synchronization for hidden topics) protocol. In the evaluation, we show the fewest number of event messages are prohibited from being received in the FS-H protocol compared with the other protocols.

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Vorheriges Kapitel Enabling Custom Security Controls as Plugins in Service Oriented Environments
Nächstes Kapitel QoS Preservation in Web Service Selection
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Metadaten
Titel
A Flexible Synchronization Protocol to Learn Hidden Topics in P2PPS Systems
verfasst von
Shigenari Nakamura
Tomoya Enokido
Makoto Takizawa
Copyright-Jahr
2019
Verlag
Springer Berlin Heidelberg
Buch
Transactions on Computational Collective Intelligence XXXIII

Print ISBN: 978-3-662-59539-8

Electronic ISBN: 978-3-662-59540-4

Copyright-Jahr: 2019

DOI
https://doi.org/10.1007/978-3-662-59540-4_3

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