Complex Event driven data analysis approach in fog architecture based Smart healthcare

Hiray, Swapnaja; Bhramaramba, R.

doi:10.1109/gcat55367.2022.9971877

Cited by 2 publications

(2 citation statements)

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“…Hiray et al designed a computationally efficient event processing engine (Hiray & Ravi, 2022) for data reduction in smart healthcare based applications. The proposed work reduces unnecessary traffic as well as memory space and data transfer time.…”

Section: Results Analysis and Discussionmentioning

confidence: 99%

“…Rule based algorithms using CEP system and IoT infrastructure was main goal various research studies (Hiray & Ravi, 2022; Roldán‐Gómez et al, 2023; Wang et al, 2009; Wang et al, 2016). Fault‐tolerance along with distributed system was mentioned in various research studies (Cugola & Margara, 2013; Jayasekara et al, 2015; Liu, Guo, et al, 2022; Power & Kotonya, 2019b).…”

Section: Results Analysis and Discussionmentioning

confidence: 99%

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Rule based complex event processing forIoTapplications: Review, classification and challenges

Kumar,

Agarwal

2024

Expert Systems

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In recent decades, data aggregation and correlation have emerged as a significant and challenging area of research for finding useful relationships between different features of streaming data. Similarly, complex event processing (CEP) has emerged as a vital tool for aggregating and finding patterns from streaming data such as video streaming, real‐time stock trades, sensor data and more. In this context, rule‐based classifier algorithms are widely employed to discover valuable patterns from streaming data and cause‐and‐effect relationships between events. However, streaming data is dynamic and complex in nature, and it is not feasible to update the rules manually by domain experts continuously. On the contrary, dynamic data sometimes fails to adopt rules, which leads to sub optimal CEP implementation. Rule‐based CEP systems come up with their own set of challenges, which primarily includes rules adaptability for streaming IoT data. In dynamic environment, shifting patterns in data streams can impact the performance of the CEP system, as well as the correlation between events, and finding useful patterns is very much challenging. In this article, our objective is to provide a comprehensive survey for CEP using rule‐based algorithms applied across various domain and applications. We present a broad literature review using a sequential expansion of methods used for CEP, which primarily include event producers, preprocessing of events, robust rule implementation, and decision support. Additionally, we present a detailed classification of approaches used for different applications. Finally, after applying the rigorous review, it was feasible to present the state‐of‐the‐art research, which focuses on designing robust rules, application specific insights, scalable event‐driven architectures and finding the domain's trends with significant challenges and future scope.

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Section: Results Analysis and Discussionmentioning

confidence: 99%