Abstract
In the P2PPS (P2P (peer-to-peer) type of a topic-based PS (publish/subscribe)) model, each peer can be a subscriber and publisher. Peers publishes messages to communicate with other peers. Here, messages are characterized by topics. Messages which have a common topic are considered to be related. In our previous studies, a hierarchical group model of peers is proposed, which is composed of a gateway subgroup and member subgroups of peers where related messages are causally delivered by using the linear time vector. Every member subgroup is constructed so that the member subgroup is a collection of member peers in same network in an NBG (network-based grouping) method. In this paper, we propose an HTBG (hot-topic-based grouping) method where each subgroup is dynamically constructed based on the hot topics which are more frequently used at that time. Here, each subgroup is constructed so that the subgroup is composed of peers which subscribe common hot topics. In the evaluation, we show the number of messages exchanged among subgroups can be reduced in the HTBG method compared with the NBG method. However, the larger number of messages are broadcast in a member subgroup in the HTBG method than the NBG method.
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Saito, T., Nakamura, S., Enokido, T., Takizawa, M. (2020). Topic-Based Subgroups for Reducing Messages Exchanged Among Subgroups. In: Barolli, L., Okada, Y., Amato, F. (eds) Advances in Internet, Data and Web Technologies. EIDWT 2020. Lecture Notes on Data Engineering and Communications Technologies, vol 47. Springer, Cham. https://doi.org/10.1007/978-3-030-39746-3_5
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DOI: https://doi.org/10.1007/978-3-030-39746-3_5
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