The tremendous number of sensors and smart objects being deployed in the Internet of Things pose the potential for IT systems to detect and react to live-situations. For using this hidden potential, Complex Event Processing (CEP) systems offer means to efficiently detect event patterns (complex events) in the sensor streams and therefore help in realizing a "distributed intelligence" in the Internet of Things. With the increasing number of data sources and the increasing volume at which data is produced, parallelization of event detection is crucial to limit the time events need to be buffered before they actually can be processed. In this article, we propose a pattern-sensitive partitioning model for data streams that is capable of achieving a high degree of parallelism in detecting event patterns which formerly could only be consistently detected in a sequential manner or at a low parallelization degree. Moreover, we propose methods to dynamically adapt the parallelization degree to limit the buffering imposed on event detection in the presence of dynamic changes to the workload. Extensive evaluations of the system behavior show that the proposed partitioning model allows for a high degree of parallelism and that the proposed adaptation methods are able to meet a buffering limit for event detection under high and dynamic workloads.

Reliability is of critical importance to many applications involving distributed event processing systems. Especially the use of stateful operators makes it challenging to provide efficient recovery from failures and to ensure consistent event streams. Even during failure-free execution, state-of-the-art methods for achieving reliability incur significant overhead at run-time concerning computational resources, event traffic, and event detection time. This paper proposes a novel method for rollback-recovery that allows for recovery from multiple simultaneous operator failures, but eliminates the need for persistent checkpoints. Thereby, the operator state is preserved in savepoints at points in time when its execution solely depends on the state of incoming event streams which are reproducible by predecessor operators. We propose an expressive event processing model to determine savepoints and algorithms for their coordination in a distributed operator network. Evaluations show that very low overhead at failure-free execution in comparison to other approaches is achieved.

The domains of complex event processing (CEP) and business process management (BPM) have different origins but for many aspects draw on similar concepts. While specific combinations of BPM and CEP have attracted research attention, resulting in solutions to specific problems, we attempt to take a broad view at the opportunities and challenges involved. We first illustrate these by a detailed example from the logistics domain. We then propose a mapping of this area into four quadrants -two quadrants drawing from CEP to create or extend process models and two quadrants starting $ This paper is an outcome of discussions and collaborations that were initiated at the Dagstuhl seminar 16341 on "Integrating Process-Oriented and Event-Based Systems" from a process model to address how it can guide CEP. Existing literature is reviewed and specific challenges and opportunities are indicated for each of these quadrants. Based on this mapping, we identify challenges and opportunities that recur across quadrants and can be considered as the core issues of this combination. We suggest that addressing these issues in a generic manner would form a sound basis for future applications and advance this area significantly.

The educational impact of visualization depends not only on how well students learn when they use it, but also on how widely it is used by instructors. Instructors believe that visualization helps students learn. The integration of visualization techniques in classroom instruction, however, has fallen far short of its potential. This paper considers this disconnect, identifying its cause in a failure to understand the needs of a key member in the hierarchy of stakeholders, namely the instructor. We describe these needs and offer guidelines for both the effective deployment of visualizations and the evaluation of instructor satisfaction. We then consider different forms of evaluation and the impact of student learning styles on learner outcomes.

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SUMMARY Current distributed publish/subscribe systems consider all participants to have similar QoS requirements and contribute equally to the system's resources. However, in many real‐world applications, the message delay tolerance of individual participants may differ widely. Disseminating messages according to individual delay requirements not only allows for the satisfaction of user‐specific needs, but also significantly improves the utilization of the resources that participants contribute to a publish/subscribe system. In this article, we propose a peer‐to‐peer‐based approach to satisfy the individual delay requirements of subscribers in the presence of bandwidth constraints. Our approach allows subscribers to dynamically adjust the granularity of their subscriptions according to their bandwidth constraints and delay requirements. Subscribers maintain the overlay in a decentralized manner, exclusively establishing connections that satisfy their individual delay requirements, and that provide messages exactly meeting their subscription granularity. The evaluations show that for many practical workloads, the proposed publish/subscribe system can scale up to a large number of subscribers and performs robustly in a very dynamic setting. Copyright © 2011 John Wiley & Sons, Ltd.

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