An event service supporting autonomic management of ubiquitous systems for e-health

An event system suitable for very simple devices corresponding to a body area network for monitoring patients is presented. Event systems can be used both for self-management of the components as well as indicating alarms relating to patient health state. Traditional event systems emphasise scalability and complex event dissemination for internet based systems, whereas we are considering ubiquitous systems with wireless communication and mobile nodes which may join or leave the system over time intervals of minutes. Issues such as persistent delivery are also important. We describe the design, prototype implementation, and performance characteristics of an event system architecture targeted at this application domain

On the Benefits of Non-Canonical Filtering in Publish/Subscribe Systems

Current matching approaches in pub/sub systems only allow conjunctive subscriptions. Arbitrary subscriptions have to be transformed into canonical expressions, e.g., DNFs, and need to be treated as several conjunctive subscriptions. This technique is known from database systems and allows us to apply more efficient filtering algorithms. Since pub/sub systems are the contrary to traditional database systems, it is questionable if filtering several canonical subscriptions is the most efficient and scalable way of dealing with arbitrary subscriptions. In this paper we show that our filtering approach supporting arbitrary Boolean subscriptions is more scalable and efficient than current matching algorithms requiring transformations of subscriptions into DNFs

Enabling Confidentiality in Content-Based Publish/Subscribe Infrastructures

Content-Based Publish/Subscribe (CBPS) is an interaction model where the interests of subscribers are stored in a content-based forwarding infrastructure to guide routing of notifications to interested parties. In this paper, we focus on answering the following question: Can we implement content-based publish/subscribe while keeping subscriptions and notifications confidential from the forwarding brokers? Our contributions include a systematic analysis of the problem, providing a formal security model and showing that the maximum level of attainable security in this setting is restricted. We focus on enabling provable confidentiality for commonly used applications and subscription languages in CBPS and present a series of practical provably secure protocols, some of which are novel and others adapted from existing work. We have implemented these protocols in SIENA, a popular CBPS system. Evaluation results show that confidential content-based publish/subscribe is practical: A single broker serving 1000 subscribers is able to route more than 100 notifications per second with our solutions

Investigating the memory requirements for publish/subscribe filtering algorithms

Various filtering algorithms for publish/subscribe systems have been proposed. One distinguishing characteristic is their internal representation of Boolean subscriptions: They either require conversions to disjunctive normal forms (canonical approaches) or are directly exploited in event filtering (non-canonical approaches). In this paper, we present a detailed analysis and comparison of the memory requirements of canonical and non-canonical filtering algorithms. This includes a theoretical analysis of space usages as well as a verification of our theoretical results by an evaluation of a practical implementation. This practical analysis also considers time (filter) efficiency, which is the other important quality measure of filtering algorithms. By correlating the results of space and time efficiency, we conclude when to use non-canonical and canonical approaches

Explicit context matching in content-based publish/subscribe systems

Although context could be exploited to improve performance, elasticity and adaptation in most distributed systems that adopt the publish/subscribe (P/S) communication model, only a few researchers have focused on the area of context-aware matching in P/S systems and have explored its implications in domains with highly dynamic context like wireless sensor networks (WSNs) and IoT-enabled applications. Most adopted P/S models are context agnostic or do not differentiate context from the other application data. In this article, we present a novel context-aware P/S model. SilboPS manages context explicitly, focusing on the minimization of network overhead in domains with recurrent context changes related, for example, to mobile ad hoc networks (MANETs). Our approach represents a solution that helps to efficiently share and use sensor data coming from ubiquitous WSNs across a plethora of applications intent on using these data to build context awareness. Specifically, we empirically demonstrate that decoupling a subscription from the changing context in which it is produced and leveraging contextual scoping in the filtering process notably reduces (un)subscription cost per node, while improving the global performance/throughput of the network of brokers without fltering the cost of SIENA-like topology changes

Practical high-throughput content-based routing using unicast state and probabilistic encodings

We address the problem that existing publish/subscribe messaging systems, including such commonly used ones as Apache’s ActiveMQ and IBM’s WebSphere MQ, exhibit degraded end-to-end throughput performance in a wide-area network setting. We contend that the cause of this problem is the lack of an appropriate routing protocol. Building on the idea of a content-based network, we introduce a protocol called B-DRP that can demonstrably improve the situation. A content-based network is a content-based publish/subscribe system architected as a datagram network: a message is forwarded hop-by-hop and delivered to any and all hosts that have expressed interest in the message content. This fits well with the character of a wide-area messaging system. B-DRP is based on two main techniques: a message delivery mechanism that utilizes and exploits unicast forwarding state, which can be easily maintained using standard protocols, and a probabilistic data structure to effciently represent and evaluate receiver interests. We present the design of B-DRP and the results of an experimental evaluation that demonstrates its support for improved throughput in a wide-area setting

Efficient Probabilistic Subsumption Checking for Content-Based Publish/Subscribe Systems

Abstract. Efficient subsumption checking, deciding whether a subscription or publication is covered by a set of previously defined subscriptions, is of paramount importance for publish/subscribe systems. It provides the core system functionality—matching of publications to subscriber needs expressed as subscriptions—and additionally, reduces the overall system load and generated traffic since the covered subscriptions are not propagated in distributed environments. As the subsumption problem was shown previously to be co-NP complete and existing solutions typically apply pairwise comparisons to detect the subsumption relationship, we propose a ‘Monte Carlo type ’ probabilistic algorithm for the general subsumption problem. It determines whether a publication/subscription is covered by a disjunction of subscriptions in O(k md), wherek is the number of subscriptions, m is the number of distinct attributes in subscriptions, and d is the number of tests performed to answer a subsumption question. The probability of error is problem-specific and typically very small, and sets an upper bound on d. Our experimental results show significant gains in term of subscription set reduction which has favorable impact on the overall system performance as it reduces the total computational costs and networking traffic. Furthermore, the expected theoretical bounds underestimate algorithm performance because it performs much better in practice due to introduced optimizations, and is adequate for fast forwarding of subscriptions in case of high subscription rate.