• Journal of KIISE:Information Networking
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• v.30 no.2
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• pp.143-154
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• 2003

There is a growing trend in developing system for distributed mobile system that supports services - job flow management, video conference, replicated data management and resource allocation. Supporting these services, applications have to use causally ordered message delivery. Previous proposals that provide causally ordered message delivery have problems such as communication overhead, message delaying, scalability, computing overload of mobile host. In this paper, we proposed efficient protocol for causally ordered message delivery using the methods that MSS maintains dependency information matrix between MSS and MH, Piggybacking dependency information about each immediate predecessor message. Proposed algorithm, when compared with previous proposals, provides a low message overhead, and low probability of unnecessary inhibition in delivering messages. Also, it consider resource restriction of MH and low bandwidth of wireless communication by computing most of algorithm at MSS, and reduce processing delay by executing causally ordered message delivery a unit of MH.

• 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.