Sven Bittner

The area graph-based mobility model and its impact on data dissemination

When analyzing dissemination protocols in mobile ad-hoc networks the underlying mobility model is an important factor because it strongly influences the performance of these protocols. So far most of the research only deals with homogeneous mobility models like the very common random waypoint mobility model and the random walk mobility model. In this paper we introduce a new model, the area graph-based mobility model, which considers the major characteristics of realistic scenarios such as their heterogeneity. By analyzing the results of experiments using different broadcast protocols we examine the characteristics of the area graph-based mobility model. Furthermore, we show that in heterogeneous scenarios it is necessary to use adaptive broadcast protocols, otherwise an efficient dissemination in areas with differing topologies and densities is not possible.

Efficient distribution-based event filtering

Event notification services are used in various applications, for example, stock tickers, environmental monitoring, and facility management. Several filtering algorithms for such services have been proposed. The best performance results are achieved by tree-based algorithms. However to our knowledge existing algorithms do not consider the influence of event and profile distribution on the filter performance. In this paper we propose a distribution-dependent improvement of the tree-algorithm. We present the test results of our prototypical implementation that show the influence of various distribution-based measures on the performance.

Classification and Analysis of Distributed Event Filtering Algorithms

Publish/subscribe middleware provides efficient support for loosely coupled communication in distributed systems. A number of different distributed message-filtering algorithms have been proposed. So far, a systematic comparison and analysis of these filter algorithms is still missing.

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.

The arbitrary Boolean publish/subscribe model: making the case

In this paper, we present BoP, a content-based publish/subscribe system for arbitrary Boolean subscriptions and advertisements. BoP targets at the time and space-efficient matching of event messages using the wide-spread attribute-value pair event model. In contrast to other content-based publish/subscribe systems focussing on an efficient matching process, BoP internally supports subscriptions and advertisements as arbitrary Boolean expressions. As we will show in this paper, directly handling these representations leads to efficiency benefits for applications using this class of expressions. The support of arbitrary Boolean subscriptions and advertisements requires the introduction of efficient matching and overlapping calculation algorithms, as well as applicable routing optimizations. In this paper, we will outline these solutions that have been integrated into BoP. The evaluation part of this work presents the results of a comparative study of our approaches and recent conjunctive solutions.

A detailed investigation of 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 into DNFs (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.

Supporting arbitrary Boolean subscriptions in distributed publish/subscribe systems

Publish/subscribe systems are currently gaining increasing attention in both academia and industry. One of the reasons for this interest is the wide applicability, in theory, of these systems, ranging from low-level monitoring of distributed systems to high-level applications for e-commerce. Whereas several current research activities deal with extensions of the main publish/subscribe functionalities, this work concentrates on the basic principles and foundations of these systems. This different focus originates from the insufficiency, in our opinion, of current solutions.This paper describes the research problems identified by the author and tackled within the associated PhD thesis. In particular, the corresponding PhD thesis will investigate the suitability of publish/subscribe systems internally supporting conjunctive subscription languages for scenarios requiring more expressive, i.e., arbitrary Boolean, subscriptions. This paper is structured as follows: After giving the context of the work more precisely and introducing the required concepts and foundations, we motivate our research problems and state two condensed research questions. Afterwards, we present our results so far and conclude by describing further steps we want to take to answer the identified questions.

Dimension-Based Subscription Pruning for Publish/Subscribe Systems

Subscription pruning has been proven as valuable routing optimization for Boolean subscriptions in publish/ subscribe systems. It aims at optimizing subscriptions independently of each other and is thus applicable for all kinds of subscriptions regardless of their individual and collective structures. The original subscription pruning approach tries to optimize the event routing process based on the expected increase in network load. However, a closer look at pruning-based routing reveals its further applicability to optimizations in respect to other dimensions. In this paper, we introduce and investigate subscription pruning based on three dimensions of optimization: network load, memory usage, and system throughput. We present the algorithms to perform prunings based on these dimensions and discuss the results of a series of practical experiments. Our analysis reveals the advantages and disadvantages of the different dimensions of optimization and allows conclusions about the suitability of dimension-based pruning for different application requirements.

Optimizing pub/sub systems by advertisement pruning

Supporting advertisements in large publish/subscribe services has an improving influence on the system scalability The additional application of event routing optimizations based on subscriptions further increases the event throughput and decreases the memory usage of publish/subscribe systems However, also advertisement-based optimizations can improve these system properties but have been widely neglected so far In particular, no current optimizations are applicable to advertisements defined as arbitrary Boolean filter expressions. In this paper, we outline the final milestone on the way to practically support the arbitrary Boolean publish/subscribe model: We firstly develop a novel optimization approach, advertisement pruning, that is tailored to arbitrary Boolean advertisements Secondly, we present a detailed evaluation of the optimization potential of this advertisement-based solution We finally analyze the effects of additionally optimizing subscriptions on the advertisement pruning optimization.