Scalable CEP for Smart Cities
Forfatter
Fernando
Last Updated
6 years ago
License
Creative Commons CC BY 4.0
Resumé
Evaluating Scalability for Complex Event Processing in the Context of Smart Cities
Evaluating Scalability for Complex Event Processing in the Context of Smart Cities
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\author[ffs@ime.usp.br]{Fernando Freire Scattone}
\title{Scalable CEP for Smart Cities}
\institute{Instituto de Matemática e Estatística - Universidade de São Paulo}
\subtitle{Evaluating Scalability for \\Complex Event Processing \\in the Context of Smart Cities}
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\begin{block}{Complex Event Processing}
\begin{itemize}
\item Complex Event Processing (CEP) is a defined set of tools and techniques for analyzing and controlling the complex series of interrelated events . \cite{Luckham:2001:PEI:515781}
\item Simple events can be anything, from a temperature measure to a specific log on a given system and come as data streams to the CEP engines.
\item Complex events are defined by rules which are based on CEP operators.Complex Events can be defined based on the occurrence of single on other complex events.
%\item This technology helps professionals understand what is happening within the system, quickly identify and solve problems, and more effectively utilize events for enhanced operation, performance, and security.
\end{itemize}
\end{block}
\begin{block}{Scalability}
\begin{itemize}
\item In a distributed systems 3 resources can become bottlenecks:
\begin{itemize}
\item CPU usage
\item memory usage
\item Bandwidth
\end{itemize}
\item A system is scalable when those 3 resources are balanced while the system is increasing in size.
\end{itemize}
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\begin{block}{Smart Cities}
\begin{itemize}
\item A Smart City is a city in which its social, business, and
technological aspects are supported by Information and Communication Technologies to improve the experience of
the citizen within the city. \cite{7810114}
\item Every time a lot of different measured are being taken everywhere on cities.From mobile phones to humidity sensors spread across the neighborhoods.
\item This data, by itself , has little meaning.When combined, correlations not previously thought could be recognized and studied.
\end{itemize}
\end{block}
\begin{block}{Achieving Scalability with CEP}
\begin{itemize}
\item CEP operators have a great variety of correlation operations that involve joining information from different data streams or data streams and a database with specific conditions that must be met in order to detect complex events.
\item Most of the challenges are related to distributing the processing without compromising too much the CEP operators.
\end{itemize}
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\begin{block}{Proposal}
\begin{itemize}
\item Search all scalability technics for Complex Event Processing and find which ones can be combined to lower resource usage.
\item Monitor the CPU, memory and bandwidth usage to more easily adapt to the addition or subtraction of available machines for processing
\item Discover Smart Cities requirements that may affect the Scalability of the CEP system and try to overcome them.
\item Maybe use the city natural disposition and features to improve the processing, based on the correlation between geographical localization and information relevance to people on that place.
\end{itemize}
\end{block}
\begin{block}{References}
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