No abstract

One important class of applications for the Internet of Things is related to the need to gain timely and continuous situational awareness, like smart cities, automated traffic control, or emergency and rescue operations. Events happening in the real-world need to be detected in real-time based on sensor data and other data sources. Complex Event Processing (CEP) is a technology to detect complex (or composite) events in data streams and has been successfully applied in high volume and high velocity applications like stock market analysis. However, these application domains faced only the challenge of high performance, while the Internet of Things and Mobile Big Data introduce a new set of challenges caused by mobility. This chapter aims to explain these challenges and to give an overview on how they are solved respectively how far state-of-the-art research has advanced to be useful to solve Mobile Big Data problems. At the infrastructure level the main challenge is to trade performance against resource consumption and energy efficiency and operator placement is the most dominant mechanism to address these problems. At the application and consumer level, mobile queries pose a new set of challenges for CEP related to continuously changing positions of consumers and data sources, and the need to adapt the query processing to these changes. Finally, proper methods and tools for systematical testing and reproducible performance evaluation for mobile distributed CEP are needed but not yet available.

Distributed Complex Event Processing (CEP) is gaining increasing interest for two reasons: (1) to scale system performance to handle higher workloads in real-time, and (2) to perform in-network processing, e.g., in mobile networks to reduce the amount of data that has to be transferred through the network. System scalability and the complexity of mobile systems are some of the major challenges when evaluating the performance of new Distributed CEP solutions. We propose an open framework for distributed CEP (DCEP-Sim) built on a well-established network simulator, i.e, ns-3. e design of DCEP-Sim is based on the engineering principles of separation of concerns and the separation of mechanisms and policies. By leveraging the ns-3 feature of object aggregation it is very easy to add new policies, e.g., placement or selection policies, and evaluate them without changing anything else in the DCEP-Sim. e fact that ns-3 includes many accurate network models implies that Distributed CEP simulation with DCEP-Sim will also be much more accurate than ad-hoc handcra ed simulations. We demonstrate in a use case how easy it is to con gure performance evaluation experiments and we perform experiments to con rm that the integration of the Distributed CEP in ns-3 is good foundation for large-scale experiments. e evaluation results demonstrate that DCEP-Sim substantially reduces the e ort and costs of Distributed CEP evaluation.

Evaluation of Distributed Complex Event Processing (CEP) systems is a rather challenging task. To simplify this task, we developed the open simulation framework for Distributed CEP, called DCEP-Sim. The goal of this tutorial is to facilitate the process of using DCEP-Sim. Since DCEP-Sim is designed and implemented in the popular network simulator ns-3 we introduce the most important concepts of ns-3. Simulations in ns-3 are congured and executed though a main program called an ns-3 script. We use a simple example script to explain how simulations with DCEP-Sim are set up and executed. To give an idea how DCEP-Sim can be adjusted to particular needs, we explain how DCEP-Sim can be adapted (e.g., through changing the workload and the network topology) and how new Distributed CEP solutions can be added by explaining how to add a new operator to DCEP-Sim. CCS CONCEPTS • Computing methodologies → Simulation tools;