Publish/subscribe systems are successfully used to decouple distributed applications. However, their e#ciency is closely tied to the topology of the underlying network, the design of which has been neglected. Peer-to-peer network topologies can o#er inherently bounded delivery depth, load sharing, and self-organisation. In this paper, we present a contentbased publish/subscribe system routed over a peer-to-peer topology graph. The implications of combining these approaches are explored and a particular implementation using elements from Rebeca and Chord is proven correct.

This paper presents the design and evaluation of a support service for mobile, wireless clients of a distributed publish/subscribe system. A distributed publish/subscribe system is a networked communication infrastructure where messages are published by senders and then delivered to the receivers whose subscriptions match the messages. Communication therefore does not involve the use of explicit addresses, but rather emerges from the dynamic arrangement of publishers and subscribers. Such a communication mechanism is an ideal platform for a variety of Internet applications, including multi-party messaging, personal information management, information sharing, on-line news distribution, service discovery, and electronic auctions. Our goal is to support such applications on mobile, wireless host devices in such a way that the applications can, if they chose, be oblivious to the mobility and intermittent connectivity of their hosts as they move from one publish/subscribe access point to another. In this

Gossip-based broadcast algorithms have been considered as a viable alternative to traditional deterministic reliable broadcast algorithms in large scale environments. However, these algorithms focus on broadcasting events inside a large group of processes, while the multicasting of events to a subset of processes in a group only, potentially varying for every event, has not been considered. We propose a scalable gossip-based multicast algorithm which ensures, with a high probability, that (1) a process interested in a multicast event delivers that event (just like in typical gossip-based broadcast algorithms), and that (2) a process not interested in that event does not receive it (unlike in broadcast algorithms).

Overlay broker networks are an important part of an event-based middleware. In this paper, we investigate the requirements of overlay broker networks and argue that using peer-to-peer techniques for their creation and the content-based routing of events has many advantages. We support our claims with an experimental evaluation of Hermes, an event-based middleware architecture that uses a peer-topeer routing substrate, in comparison with a standard publish /subscribe system that has a simple, predefined overlay topology. The results reveal that Hermes has better routing e#ciency and keeps less routing state at the event brokers.

We consider distributed applications that continuously stream data across the network, where data needs to be aggregated and processed to produce a 'useful ' stream of updates. Centralized approaches to performing data aggregation suffer from high communication overheads, lack of scalability, and unpredictably high processing workloads at central servers. This paper describes a scalable and efficient solution to distributed stream management based on (1) resource-awareness, which is middleware-level knowledge of underlying network and processing resources, (2) overlay-based in-network data aggregation, and (3) high-level programming constructs to describe data-flow graphs for composing useful streams. Technical contributions include a novel algorithm based on resource-aware network partitioning to support dynamic deployment of dataflow graph components across the network, where efficiency of the deployed overlay is maintained by making use of partition-level resource-awareness. Contributions also include efficient middleware-based support for component deployment, utilizing runtime code generation rather than interpretation techniques, thereby addressing both high performance and resource-constrained applications. Finally, simulation experiments and benchmarks attained with actual operational data corroborate this paper's claims. 1.

Distributed content-based publish-subscribe middleware provides the necessary decoupling, flexibility, expressiveness, and scalability required by modern distributed applications. Unfortunately, this kind of middleware usually does not provide reliability guarantees, as this problem has been thus far largely disregarded by the research community and solutions developed in other contexts are not immediately applicable.

We contribute a new paradigm for publish/subscribe systems. It is centered on the novel notion of subscription summarization. We first present the summarization structures for a broker’s subscriptions and accompanying algorithms, which operate on the summary structures to match incoming events to the brokers with relevant subscriptions and for the maintenance of subscriptions in the face of updates. Second, we present novel algorithms for efficiently propagating subscription summaries to brokers. Finally, we present a novel algorithm for the efficient distributed processing of incoming events, utilizing the propagated subscription summaries to route the events to brokers with matched subscriptions. We study the performance of our contributions, comparing them against a baseline approach and against corresponding techniques employed in a well-known event-based distributed system. Our results show the significant performance gains introduced for both the subscription propagation and distributed event processing tasks. 1.

Research into publish/subscribe messaging has so far done little to propose architectures for the support of access control, yet this will be an increasingly critical requirement as systems move to Internet-scale. This paper discusses the general requirements of publish/subscribe systems with access control. We then present our specific integration of OASIS role-based access control into the Hermes publish /subscribe middleware platform. Our system supports many advanced features, such as the ability to work within a network where nodes are attributed different levels of trust, and employs a variety of access restriction methods which balance expressiveness with the content-based routing optimisations available. We illustrate our achievements by discussing an application scenario in which our system will be of particular use.

Mainstream approaches to content-based distributed publish-subscribe typically route events deterministically based on information collected from subscribers, and do so by relying on a tree-shaped overlay network. While this solution achieves scalability in fixed, large-scale settings, it is less appealing in scenarios characterized by high dynamicity, e.g., mobile ad hoc networks or peer-to-peer systems. At the other extreme, researchers in the related fields of multicast and group communication have successfully exploited probabilistic techniques that provide increased fault tolerance, resilience to changes, and yet are scalable. In this paper, we propose a novel approach where event routing relies on deterministic decisions driven by a limited view on the subscription information and, when this is not sufficient, resorts to probabilistic decisions performed by selecting links at random. Simulations show that the particular mix of deterministic and probabilistic decisions we put forth in this work is very effective at providing high event delivery and low overhead in highly dynamic scenarios, without sacrificing scalability. 1.

We consider pervasive computing applications that process and aggregate data-streams emanating from highly distributed data sources to produce a stream of updates that have an implicit business-value. Middleware that enables such aggregation of datastreams must support scalable and efficient selfmanagement to deal with changes in the operating conditions and should have an embedded businesssense. In this paper, we present a novel self-adaptation algorithm that has been designed to scale efficiently for thousands of streams and aims to maximize the overall business utility attained from running middleware-based applications. The outcome is that the middleware not only deals with changing network conditions or resource requirements, but also responds appropriately to changes in business policies. An important feature of the algorithm is a hierarchical node-partitioning scheme that decentralizes reconfiguration and suitably localizes its impact. Extensive simulation experiments and benchmarks attained with actual enterprise operational data corroborate this paper's claims. 1.