A query-matching mechanism over out-of-order event stream in IOT

Wang, Kun; Yu, Yue

doi:10.1504/ijahuc.2013.055453

Cited by 20 publications

(7 citation statements)

References 18 publications

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“…However, the reduced rate of scheduling will lead to the fact that the strategy might not be the best when the weight of edge changes. How to ensure the efficiency of the strategy when the rate of scheduling is reduced will remain in our future research [41,42].…”

Section: Resultsmentioning

confidence: 99%

A dynamic assignment scheduling algorithm for big data stream processing in mobile Internet services

Yan

Wang²,

et al. 2016

Pers Ubiquit Comput

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As the huge number of mobile devices (e.g., smart phones, tablets and netbooks) increases, more and more people choose to use the Internet services financed by mobile Internet service providers (MISPs). To provide better services, it is quite necessary for MISPs to analyze the information hidden in the big data stream generated by users. Therefore, processing the real-time big data stream efficiently has become increasingly important. However, traditional static data storage technology fails to meet the demands of real-time data processing. To improve processing capacity, many parallel processing structures are proposed, which brings up the problem about how the parallel devices can be scheduled to maximize their efficiency. Accordingly, a dynamic assignment scheduling algorithm for big data stream processing in mobile Internet services is proposed, and a stream query graph is built to calculate the weight of every edge. The edge with the minimum weight is selected to send tuples. Simulation results show that the proper number of the logic devices can dramatically reduce system response time. Furthermore, system context switching is reduced by increasing the number of tuples sent each time.

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Section: Resultsmentioning

confidence: 99%

A dynamic assignment scheduling algorithm for big data stream processing in mobile Internet services

Yan

Wang²,

et al. 2016

Pers Ubiquit Comput

Self Cite

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“…Furthermore, one of the aspects of the fluctuated streams generated by various IoT devices is the out-of-order events problem. Kun et al have proposed a real-time querymatching algorithm to generate queries when the number of event types is large and query length is long by minimizing the overhead and reduce the response time [1]. The distributed Platform for Elastic Stream Processing (PESP) has been introduced to deal with changing rates of streaming data [3].…”

Section: Related Workmentioning

confidence: 99%

“…Industrial IoT dataprocessing poses some unique challenges when endeavouring to make stream processing a reliable solution. Some specific challenges that the IoT industry faces when it comes to data-processing are (1) the retrieval and processing overheads for the huge amount of heterogeneous streaming data generated from a large number of IoT devices, and (2) the missing and delayed events due to unpredictability of data which affects the required rapid response time in the IoT industry [1]. In particular, these IoT devices produce data at a variable rate (e.g., unscheduled events) rather than at a fixed rate, which augments the difficulties for data stream processing platforms to cope with such a sudden increase in streaming rates [2].…”

Section: Introductionmentioning

confidence: 99%

Industry 4.0 towards Forestry 4.0: Fire Detection Use Case

Sahal

Alsamhi

Breslin

et al. 2021

Sensors

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Forestry 4.0 is inspired by the Industry 4.0 concept, which plays a vital role in the next industrial generation revolution. It is ushering in a new era for efficient and sustainable forest management. Environmental sustainability and climate change are related challenges to promote sustainable forest management of natural resources. Internet of Forest Things (IoFT) is an emerging technology that helps manage forest sustainability and protect forest from hazards via distributing smart devices for gathering data stream during monitoring and detecting fire. Stream processing is a well-known research area, and recently, it has gained a further significance due to the emergence of IoFT devices. Distributed stream processing platforms have emerged, e.g., Apache Flink, Storm, and Spark, etc. Querying windowing is the heart of any stream-processing platform which splits infinite data stream into chunks of finite data to execute a query. Dynamic query window-based processing can reduce the reporting time in case of missing and delayed events caused by data drift.In this paper, we present a novel dynamic mechanism to recommend the optimal window size and type based on the dynamic context of IoFT application. In particular, we designed a dynamic window selector for stream queries considering input stream data characteristics, application workload and resource constraints to recommend the optimal stream query window configuration. A research gap on the likelihood of adopting smart IoFT devices in environmental sustainability indicates a lack of empirical studies to pursue forest sustainability, i.e., sustainable forestry applications. So, we focus on forest fire management and detection as a use case of Forestry 4.0, one of the dynamic environmental management challenges, i.e., climate change, to deliver sustainable forestry goals. According to the dynamic window selector’s experimental results, end-to-end latency time for the reported fire alerts has been reduced by dynamical adaptation of window size with IoFT stream rate changes.

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“…In recent years, network function proxies attract much attention in SDNs, because they can provide various network functionalities for service providers in the perspective of traffic scheduling applications, such as social link awareness routing for delay tolerant networks, event stream in Internet of Things, and the fault‐tolerant processing of mobile big data . We review the related development and some innovating research results in the following.…”

Section: Related Workmentioning

confidence: 99%

Traffic scheduling for deep packet inspection in software‐defined networks

Huang

Guo

2016

Concurrency and Computation

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Deep packet inspection (DPI) is important for network security. In this paper, we consider a software-defined network where several DPI proxy nodes are available for serving flows from ingress switches. These DPI proxy nodes can be implemented in either software or hardware.We study an integrated proxy allocation and routing determining problem with the objective of minimizing the total delay of flows from ingress switches to DPI proxies. This problem is formulated as an integer linear programming problem that is NP-hard in general. To solve this problem, we design a 2-phase algorithm that can quickly select proxy and find routing paths for incoming flows. Finally, extensive simulations are conducted to evaluate the performance of our proposed algorithm. Some useful parameter setting insights are obtained.

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A query-matching mechanism over out-of-order event stream in IOT

Cited by 20 publications

References 18 publications

A dynamic assignment scheduling algorithm for big data stream processing in mobile Internet services

A dynamic assignment scheduling algorithm for big data stream processing in mobile Internet services

Industry 4.0 towards Forestry 4.0: Fire Detection Use Case

Traffic scheduling for deep packet inspection in software‐defined networks

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