Abstract
In this paper, we focus our studies on a distributed keyword continuous query processing system that is built on distributed hash tables. Treating bandwidth as a first-class resource, we propose novel query indexing algorithms including MHI and SAP-MHI, multicast-based document announcement, and adaptive query resolution to reduce bandwidth cost. Our detailed simulations show that our proposed techniques, combined together, effectively and greatly cut down bandwidth consumption.
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Notes
Document alert is outside of the scope of the paper since it can be decoupled from the system and implemented in various ways, e.g., via multicast, emails or RSS.
Note that term IDs uniquely identify terms. Each query inverted list may additionally store the term ID so that the term ID uniquely identifies the inverted list.
Given k term IDs contained in an announcement message, if we piggyback r successor term IDs for each of these k term IDs, the total number of term IDs in the message is at most k+r rather than k⋅r. So, the piggyback overhead is at most r term IDs.
The number of documents in which a term appears.
In this paper, we set y to be larger than \(\log {N}\) where N is the number of nodes in the underlying DHT.
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Extended version of the work [1] presented in Proceedings of ICPP’08.
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Zhu, Y. Towards bandwidth-efficient keyword continuous query processing over DHTs. Peer-to-Peer Netw. Appl. 9, 142–158 (2016). https://doi.org/10.1007/s12083-014-0319-6
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DOI: https://doi.org/10.1007/s12083-014-0319-6