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

Abstract

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 k1, ..., km to causally order event messages. Each event message e carries the keyword vector e.V. An event message e1 causally precedes an event message e2 with respect to a subscription Si iff e1.Vh < e2.Vh for every keyword kh which is in the publications of the event messages e1 and e2 and the subscription Si. Only a pair of related messages are causally delivered to common subscriber peers.