Titlebook: Rendezvous in Distributed Systems; Theory, Algorithms a Zhaoquan Gu,Yuexuan Wang,Francis C.M. Lau Book 2017 Springer Nature Singapore Pte L

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Digest

Distributed Computingproblems that can be solved efficiently in distributed systems, such as data gathering in wireless sensor networks, computing graph properties, and leader election in a distributed system. In this chapter, we introduce the elementary concepts about distributed computing and some of the important com

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Blind Rendezvous Problemetworks and cognitive radio networks, rendezvous is the prerequisite for communication, via which the users try to choose the same channel for data transmission. Here, we introduce the ., where . means the entities or the users in the system do not know the others’ information and they have to make

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Asymmetric Blind Rendezvous Algorithmsre eight different rendezvous settings when . is fixed as asymmetric and . fixed as non-oblivious, in designing asymmetric algorithms, users’ ID do not matter much. This is because the users’ IDs are typically used to break symmetry in distributed computing, but we already assume the users can be di

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Asynchronous Blind Rendezvous Algorithms for Anonymous Users, which implies that we will design efficient algorithms that have good performance for both symmetric and asymmetric port situations. In this chapter, we will introduce a commonly used technique in designing rendezvous algorithms for cognitive radio networks, which is called Channel Hopping (CH) [.

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Blind Rendezvous for Multi-users Multihop Systemms have a large number of entities, and two users wanting to communicate may not be able to that directly. Therefore, we extend the blind rendezvous algorithms between two users to multiple users in a multi-hop system in this chapter. Actually, the idea for the extension is not hard to follow. We ta