Publish/Subscribe systems provide a useful platform for delivering data (events) from publishers to subscribers in an anonymous fashion in distributed networks. In this pa-per, we promote a novel design principle for self-* dynamic and reliable content-based publish/subscribe systems and perform a comparative analysis of its probabilistic and de-terministic implementations. More specifically, we present a generic content-based publish/subscribe system, called DPS (Dynamic Publish/Subscribe). DPS combines classi-cal content-based filtering with self-* (self-organizing, self-configuring, and self-healing) subscription-driven cluster-ing of subscribers. DPS gracefully adapts to failures and changes in the system while achieving scalable events deliv-ery. DPS includes a variety of fault-tolerant deterministic and probabilistic content-based publication/subscription schemes. These schemes are targeted toward scalability, and aim at reducing and distributing the number of mes-sages exchanged. Reliability and scalability of our system are shown through analytical and experimental evaluation.