scholarly journals A Real-time and Energy-aware Framework for Data Stream Processing in the Internet of Things

2021 ◽  
Author(s):  
Egberto R. de Oliveira ◽  
Flavia Delicato ◽  
Atslands R. da Rocha ◽  
Marta Mattoso
Keyword(s):  
Internet Of Things ◽  
Real Time ◽  
Data Stream ◽  
Stream Processing ◽  
The Internet ◽  
Energy Aware ◽  
Data Stream Processing ◽  
Time And Energy ◽  
The Internet Of Things

scholarly journals An energy-aware data cleaning workflow for real-time stream processing in the internet of things

2020 ◽  
Author(s):  
Egberto Armando Rabello De Oliveira ◽  
Flávia Coimbra Delicato ◽  
Marta Lima de Queirós Mattoso
Keyword(s):  
Internet Of Things ◽  
Power Consumption ◽  
Real Time ◽  
Data Streams ◽  
Data Cleaning ◽  
Stream Processing ◽  
The Internet ◽  
Energy Aware ◽  
The Internet Of Things

The Internet of things (IoT) has recently transformed the internet, enabling the communication between every kind of objects (things). The growing number of sensors and smart devices enhanced data creation and collection capabilities and led to an explosion of generated data in the form of Data Streams. Processing these data streams is complex and presents challenges and opportunities in the stream processing field. Due to the inherent lacking of accuracy and completeness of sensor generated data, the quality of raw data is often poor. Data cleaning tasks are required to help increasing the quality of the data being processed in an IoT application. This work proposes a data stream processing workflow for IoT to be deployed at the edge of the network. It performs a fast data cleaning with low power consumption from edge and sensor nodes. The edge computing paradigm is used to bring the data cleaning task closer to the data sources and allow actions to be triggered immediately. In addition, an energy-aware data collection component is designed to reduce the network traffic and, as a consequence, decrease the power consumption of the network devices. The proposed workflow enables the deployment of long running real-time processing systems on remote outdoor environments.

scholarly journals Analysis of Data Stream Processing At Edge Layer for Internet of Things

2020 ◽  
Vol 2 (1) ◽  
pp. 26-37
Author(s):  
Dr. Pasumponpandian
Keyword(s):  
Internet Of Things ◽  
Data Streams ◽  
Data Stream ◽  
Smart Cities ◽  
Stream Processing ◽  
Middle Layer ◽  
Cloud Services ◽  
Decentralized Systems ◽  
Data Stream Processing ◽  
Edge Layer

The progress of internet of things at a rapid pace and simultaneous development of the technologies and the processing capabilities has paved way for the development of decentralized systems that are relying on cloud services. Though the decentralized systems are founded on cloud complexities still prevail in transferring all the information’s that are been sensed through the IOT devices to the cloud. This because of the huge streams of information’s gathered by certain applications and the expectation to have a timely response, incurring minimized delay, computing energy and enhanced reliability. So this kind of decentralization has led to the development of middle layer between the cloud and the IOT, and was termed as the Edge layer, meaning bringing down the service of the cloud to the user edge. The paper puts forth the analysis of the data stream processing in the edge layer taking in the complexities involved in the computing the data streams of IOT in an edge layer and puts forth the real time analytics in the edge layer to examine the data streams of the internet of things offering a data- driven insight for parking system in the smart cities.

Applying Security to a Big Stream Cloud Architecture for the Internet of Things

2020 ◽  
pp. 1260-1284
Author(s):  
Laura Belli ◽  
Simone Cirani ◽  
Luca Davoli ◽  
Gianluigi Ferrari ◽  
Lorenzo Melegari ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Real Time ◽  
Large Data ◽  
The Internet ◽  
Low Latency ◽  
Stream Data ◽  
Memory Processing ◽  
Cloud Architecture ◽  
Iot Devices ◽  
The Internet Of Things

The Internet of Things (IoT) is expected to interconnect billions (around 50 by 2020) of heterogeneous sensor/actuator-equipped devices denoted as “Smart Objects” (SOs), characterized by constrained resources in terms of memory, processing, and communication reliability. Several IoT applications have real-time and low-latency requirements and must rely on architectures specifically designed to manage gigantic streams of information (in terms of number of data sources and transmission data rate). We refer to “Big Stream” as the paradigm which best fits the selected IoT scenario, in contrast to the traditional “Big Data” concept, which does not consider real-time constraints. Moreover, there are many security concerns related to IoT devices and to the Cloud. In this paper, we analyze security aspects in a novel Cloud architecture for Big Stream applications, which efficiently handles Big Stream data through a Graph-based platform and delivers processed data to consumers, with low latency. The authors detail each module defined in the system architecture, describing all refinements required to make the platform able to secure large data streams. An experimentation is also conducted in order to evaluate the performance of the proposed architecture when integrating security mechanisms.

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