• Title/Summary/Keyword: causal message delivery ordering

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Epidemic-Style Group Communication Algorithm ensuring Causal Order Delivery (인과적 순서 전달을 보장하는 전염형 그룹 통신 알고리즘)

  • Kim Chayoung;Ahn Jinho
    • The KIPS Transactions:PartA
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    • v.12A no.2 s.92
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    • pp.137-144
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    • 2005
  • Many reliable group communication algorithms were presented to satisfy predetermined message ordering properties in small or medium-scale distributed systems. However, the previous algorithms with their strong reliability properties may be unappropriate for large-scale systems. To address this issue, some epidemic-style group communication algorithms were proposed for considerably improving scalability while guaranteeing the reasonably weaker reliability property than the existing ones. The algorithms are all designed for ensuring the atomic order message delivery property. But, some distributed applications such as multimedia systems and collaborative work, may require only the weaker message ordering property, i.e., causal order delivery. This paper proposes an efficient epidemic-style group communication algorithm ensuring causal order delivery to provide the indigenous scalability of the epidemic-style approach.

Causal Information Transmission Protocol Between Publishers and Subscribers for Overlapping Groups (중복 그룹을 위한 공급자와 소비자 간 인과관계 정보 전송 프로토콜)

  • Kim, Cha-Young;Ahn, Jin-Ho
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.11 no.6
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    • pp.215-221
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    • 2011
  • Communication infrastructure of wireless sensor networks significantly tends to depend on application requirements. Gossip communication is becoming one of the promising solutions for addressing its scalability problems in providing information propagation functionality based on the P (publish)/S (subscribe) paradigm. In particular, despite the importance of both guaranteeing message delivery order required and supporting overlapping groups in sensor networks, there exist little research works on development of gossip-style dissemination protocols to satisfy all these requirements. In this paper, we present the latest causal information transmission protocol between publishers and subscribers for overlapping groups. In this protocol, sensor leaders as publishers might guarantee consistently causally ordered message delivery among themselves by aggregating causality information. On the other hand, only the latest causal information piggybacked on each multicast message is transmitted from publishers to subscribers through gossip-style dissemination. Its scalability feature might be highly suitable for the area of the applications requiring only the minimum meaningful information.