Causally Ordered Delivery of Event Messages with Keyword Vectors in P2P Publish/Subscribe Systems
Hiroki Nakayama, Dilawaer Duolikun, Tomoya Enokido, Makoto Takizawa · 2015
In distributed systems, a group of multiple processes are cooperating with one another by exchanging messages in networks. A process is modeled to be a finite state machine. In this paper, we discuss a peer-to-peer (P2P) model of a publish/subscribe (P2PPS) system composed of peer processes (peers). Each peer can both subscribe a subscription and publish event messages with a publication. In this paper, subscriptions and publications are specified in terms of keywords. If a subscription of a subscriber peer and a publication of an event message include some common keywords, the subscriber peer is a target peer of the event message. The event message is notified to the target subscriber peer. A pair of event messages are related, which have a common target subscriber peer. Only a pair of related event messages are required to be delivered to common target subscriber peers in the causal order. We newly propose vectors of 〈V1, ..., Vm〉 of keywords k , ..., kmto causally order event messages. Each event message e carries the keyword vector e.V. An event message e1causally precedes an event message e2with respect to a subscription Siiff e1·Vh2·Vhfor every keyword khwhich is in the publications of the event messages e1and e2and the subscription Si. Only a pair of related messages are causally delivered to common subscriber peers.