Causally Ordered Delivery of Event Messages with Keyword Vectors in P2P Publish/Subscribe Systems

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 〈V<;sub>1<;/sub>, ..., V<;sub>m<;/sub>〉 of keywords k , ..., k<;sub>m<;/sub> to causally order event messages. Each event message e carries the keyword vector e.V. An event message e<;sub>1<;/sub> causally precedes an event message e<;sub>2<;/sub> with respect to a subscription S<;sub>i<;/sub> iff e<;sub>1<;/sub>·V<;sub>h<;/sub> <; e<;sub>2<;/sub>·V<;sub>h<;/sub> for every keyword k<;sub>h<;/sub> which is in the publications of the event messages e<;sub>1<;/sub> and e<;sub>2<;/sub> and the subscription S<;sub>i<;/sub>. Only a pair of related messages are causally delivered to common subscriber peers.