scholarly journals A Lightweight Secure and Energy-Efficient Fog-Based Routing Protocol for Constraint Sensors Network

Energies ◽  
2020 ◽  
Vol 14 (1) ◽  
pp. 89
Author(s):  
Khalid Haseeb ◽  
Naveed Islam ◽  
Yasir Javed ◽  
Usman Tariq
Keyword(s):  
Real Time ◽  
Energy Efficient ◽  
High Performance ◽  
Cost Effective ◽  
Sensor Nodes ◽  
Time Data ◽  
Energy Efficient Routing ◽  
Routing Security ◽  
Simulation Based

The Wireless Sensor Network (WSN) has seen rapid growth in the development of real-time applications due to its ease of management and cost-effective attributes. However, the balance between optimization of network lifetime and load distribution between sensor nodes is a critical matter for the development of energy-efficient routing solutions. Recently, many solutions have been proposed for constraint-based networks using the cloud paradigm. However, they achieve network scalability with the additional cost of routing overheads and network latency. Moreover, the sensors’ data is transmitted towards application users over the uncertain medium, which leads to compromised data security and its integrity. Therefore, this work proposes a light-weight secure and energy-efficient fog-based routing (SEFR) protocol to minimize data latency and increase energy management. It exploits the Quality of Service (QoS) factors and facilitates time-sensitive applications with network edges. Moreover, the proposed protocol protects real-time data based on two levels of cryptographic security primitives. In the first level, a lightweight data confidentiality scheme is proposed between the cluster heads and fog nodes, and in the second level, a high-performance asymmetric encryption scheme is proposed among fog and cloud layers. The analysis of simulation-based experiments has proven the significant outcomes of the proposed protocol compared to existing solutions in terms of routing, security, and network management.

scholarly journals Iso-Quality of Service: Fairly Ranking Servers for Real-Time Data Analytics

2015 ◽  
Vol 25 (03) ◽  
pp. 1541004 ◽  
Author(s):  
Giorgis Georgakoudis ◽  
Charles Gillan ◽  
Ahmed Sayed ◽  
Ivor Spence ◽  
Richard Faloon ◽  
...  
Keyword(s):  
Quality Of Service ◽  
Real Time ◽  
Energy Efficient ◽  
High Performance ◽  
Real Life ◽  
Evaluation Methodology ◽  
Time Data ◽  
Output Quality ◽  
Qos Evaluation

We present a mathematically rigorous iso-Quality-of-Service (QoS) metric which relates the achievable quality of service (QoS) for a real-time analytics service with workload specific and use case specific performance and output quality requirements to the energy cost of offering the service by different server architectures. Using a new iso-QoS evaluation methodology, we scale server resources to meet QoS targets and directly rank the servers in terms of their energy-efficiency and by extension cost of ownership. Our metric and method are platform-independent and enable fair comparison of datacenter compute servers with significant architectural diversity, including micro-servers. We deploy our metric and methodology to compare three servers running financial option pricing workloads on real-life market data. We find that server ranking is sensitive to data inputs and desired QoS level and that although scale-out micro-servers can be up to two times more energy-efficient than conventional heavyweight servers for the same target QoS, they are still six times less energy efficient than high-performance computational accelerators.

Secured Energy-Efficient Routing in Wireless Sensor Networks Using Machine Learning Algorithm

2020 ◽  
pp. 23-41
Author(s):  
Ahona Ghosh ◽  
Chiung Ching Ho ◽  
Robert Bestak
Keyword(s):  
Machine Learning ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Energy Efficient ◽  
Learning Algorithm ◽  
Low Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Efficient Routing

Wireless sensor networks consist of unattended small sensor nodes having low energy and low range of communication. It has been observed that if there is any system to periodically start and stop the sensors sensing activities, then it saves some energy, and thus, the network lifetime gets extended. According to the current literature, security and energy efficiency are the two main concerns to improve the quality of service during transmission of data in wireless sensor networks. Machine learning has proved its efficiency in developing efficient processes to handle complex problems in various network aspects. Routing in wireless sensor network is the process of finding the route for transmitting data among different sensor nodes according to the requirement. Machine learning has been used in a broad way for designing energy efficient routing protocols, and this chapter reviews the existing works in the said domain, which can be the guide to someone who wants to explore the area further.

scholarly journals Development of an Automatic Image Cropping and Feature Extraction System for Real-Time Warping Monitoring in 3D Printing

2021 ◽  
Author(s):  
Jiarui Xie
Keyword(s):  
Real Time ◽  
Detection System ◽  
Region Of Interest ◽  
Cost Effective ◽  
Time Warping ◽  
Time Data ◽  
Fused Filament Fabrication ◽  
System A ◽  
Effective Manner

Fused Filament Fabrication (FFF) is an additive manufacturing technology that can produce complicated structures in a simple-to-use and cost-effective manner. Although promising, the technology is prone to defects, e.g. warping, compromising the quality of the manufactured component. To avoid the adverse effects caused by warping, this thesis utilizes deep-learning algorithms to develop a warping detection system using Convolutional Neural Networks (CNN). To create such a system, a real-time data acquisition and analysis pipeline is laid out. The system is responsible for capturing a snapshot of the print layer-bylayer and simultaneously extracting the corners of the component. The extracted region-of-interest is then passed through a CNN outputting the probability of a corner being warped. If a warp is detected, a signal is sent to pause the print, thereby creating a closed-loop monitoring system. The underlying model is tested on a real-time manufacturing environment yielding a mean accuracy of 99.21%.

scholarly journals Efficient Energy Routing Protocol based on Energy & Buffer Residual Status (EBRS) for Wireless Sensor Networks

2019 ◽  
Vol 9 (1S5) ◽  
pp. 33-37 ◽  
Keyword(s):  
Routing Protocol ◽  
Energy Efficient ◽  
Heavy Traffic ◽  
Data Gathering ◽  
Cost Effective ◽  
Residual Energy ◽  
Sensor Nodes ◽  
Energy Efficient Routing ◽  
Communication Range ◽  
Bottleneck Node

Wireless networks consist of nodes, having the ability that, they can sense and collect the information from the nearby surroundings. It has the responsibility of designed protocol to send this collected information by data gathering and forward it to the outside network via a sink node. Furthermore, WSNs doesn’t need any predetermined network structure; all the nodes used in WSN can operate as a router as well as the host. It uses multiple hops to send information to the node outside the communication range through different neighbor nodes. All the sensor nodes in WSN have their range of communication and can send and collect messages straight to each other until they were in the communication range. Moreover, the Self-organizing property of nodes in the network made WSN outstanding amongst the major applications. Nevertheless, the wireless nodes there in the network have a battery with restricted energy and can’t be recharge or change once deployed. Hence, the node energy must be utilized efficiently for various functions as sensing the information, processing the sensed information, and transmitting the processed information to another node. With the enhancements of the innovation and cost-effective hardware, our visualization presents a tremendous life enhancement of WSN into several new applications. To modify following such background, the energy-efficient routing protocol is extremely desirable and can be achieved by clustering in WSN. In the literature survey, various energy-efficient routing techniques based on cluster have been given to attain the energy-efficiency and enhance the lifetime of the network. However, these protocols were suffering from the bottleneck node issue. It is the situation in the network where the router node subjected to heavy traffic due to its presence in energy-efficient routing path or high remaining energy. This paper aims to moderate the possibility of the node to become a bottleneck node throughout the application. Thus, we attain the objective by design and develop the cluster-based efficient-routing protocol by selecting the head nodes of the cluster based on their residual energy and buffer status. Performance outcome shows that the projected work out-performs in contrast with present cluster-based routing protocols.

scholarly journals Design and implementation of a cloud-based event-driven architecture for real-time data processing in wireless sensor networks

2021 ◽  
Author(s):  
Sabrine Khriji ◽  
Yahia Benbelgacem ◽  
Rym Chéour ◽  
Dhouha El Houssaini ◽  
Olfa Kanoun
Keyword(s):  
Real Time ◽  
Design Patterns ◽  
Business Models ◽  
Cost Effective ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Low Latency ◽  
Time Data ◽  
Event Driven ◽  
Real Time Data Processing

AbstractThe growth of the Internet of Things (IoTs) and the number of connected devices is driven by emerging applications and business models. One common aim is to provide systems able to synchronize these devices, handle the big amount of daily generated data and meet business demands. This paper proposes a cost-effective cloud-based architecture using an event-driven backbone to process many applications’ data in real-time, called REDA. It supports the Amazon Web Service (AWS) IoT core, and it opens the door as a free software-based implementation. Measured data from several wireless sensor nodes are transmitted to the cloud running application through the lightweight publisher/subscriber messaging transport protocol, MQTT. The real-time stream processing platform, Apache Kafka, is used as a message broker to receive data from the producer and forward it to the correspondent consumer. Micro-services design patterns, as an event consumer, are implemented with Java spring and managed with Apache Maven to avoid the monolithic applications’ problem. The Apache Kafka cluster co-located with Zookeeper is deployed over three availability zones and optimized for high throughput and low latency. To guarantee no message loss and to simulate the system performances, different load tests are carried out. The proposed architecture is reliable in stress cases and can handle records goes to 8000 messages in a second with low latency in a cheap hosted and configured architecture.

scholarly journals Comparative study of cluster based routing protocols in WSN

2017 ◽  
Vol 7 (1.2) ◽  
pp. 171
Author(s):  
Varsha Bhatia ◽  
Sunita Kumawat ◽  
Vivek Jaglan
Keyword(s):  
Routing Protocols ◽  
Data Transmission ◽  
Energy Efficient ◽  
Hierarchical Cluster ◽  
Sensor Nodes ◽  
Maintenance Cost ◽  
Energy Efficient Routing ◽  
Wireless Sensor Nodes ◽  
Dynamic Topology ◽  
Cluster Based Routing

Wireless Sensors network is a type of wireless network, used in diverse applications and has its own set of challenges. Apart from organizing and managing WSN, the main challenges include limited resources, dynamic topology and low scalability. Wireless Sensor nodes are battery operated, so energy scarceness is a major concern. The energy consumption is maximal at the time of data transmission between network devices or nodes. Various energy conservation schemes are applied in WSN; Energy Efficient Routing is one of the possible solutions. Energy Efficient Routing is used to minimize the maintenance cost of the network and maximize the performance of the node. In this paper different hierarchical cluster based routing protocols are discussed.

scholarly journals QoS Management for Embedded Databases in Multicore-Based Embedded Systems

2015 ◽  
Vol 2015 ◽  
pp. 1-14 ◽  
Author(s):  
Woochul Kang ◽  
Jaeyong Chung
Keyword(s):  
Embedded Systems ◽  
Real Time ◽  
Control Method ◽  
Network Connectivity ◽  
Time Data ◽  
Quality Of Data ◽  
Multiple Control ◽  
Data Intensive ◽  
Real Time Data

With ubiquitous deployment of sensors and network connectivity, amounts of real-time data for embedded systems are increasing rapidly and database capability is required for many embedded systems for systematic management of real-time data. In such embedded systems, supporting the timeliness of tasks accessing databases is an important problem. However, recent multicore-based embedded architectures pose a significant challenge for such data-intensive real-time tasks since the response time of accessing data can be significantly affected by potential intercore interferences. In this paper, we propose a novel feedback control scheme that supports the timeliness of data-intensive tasks against unpredictable intercore interferences. In particular, we use multiple inputs/multiple outputs (MIMO) control method that exploits multiple control knobs, for example, CPU frequency and the Quality-of-Data (QoD) to handle highly unpredictable workloads in multicore systems. Experimental results, using actual implementation, show that the proposed approach achieves the target Quality-of-Service (QoS) goals, such as task timeliness and Quality-of-Data (QoD) while consuming less energy compared to baseline approaches.

scholarly journals EERP-DPM: Energy Efficient Routing Protocol Using Dual Prediction Model for Healthcare Using IoT

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Faris A. Almalki ◽  
Soufiene Ben Othman ◽  
Fahad A. Almalki ◽  
Hedi Sakli
Keyword(s):  
Energy Consumption ◽  
Prediction Model ◽  
Routing Protocol ◽  
Health Care Professionals ◽  
Energy Efficient ◽  
Temporal Correlation ◽  
Sensor Nodes ◽  
Energy Efficient Routing ◽  
Battery Lifetime ◽  
Redundant Data

Healthcare is one of the most promising domains for the application of Internet of Things- (IoT-) based technologies, where patients can use wearable or implanted medical sensors to measure medical parameters anywhere and anytime. The information collected by IoT devices can then be sent to the health care professionals, and physicians allow having a real-time access to patients’ data. However, besides limited batteries lifetime and computational power, there is spatio-temporal correlation, where unnecessary transmission of these redundant data has a significant impact on reducing energy consumption and reducing battery lifetime. Thus, this paper aims to propose a routing protocol to enhance energy-efficiency, which in turn prolongs the sensor lifetime. The proposed work is based on Energy Efficient Routing Protocol using Dual Prediction Model (EERP-DPM) for Healthcare using IoT, where Dual-Prediction Mechanism is used to reduce data transmission between sensor nodes and medical server if predictions match the readings or if the data are considered critical if it goes beyond the upper/lower limits of defined thresholds. The proposed system was developed and tested using MATLAB software and a hardware platform called “MySignals HW V2.” Both simulation and experimental results confirm that the proposed EERP-DPM protocol has been observed to be extremely successful compared to other existing routing protocols not only in terms of energy consumption and network lifetime but also in terms of guaranteeing reliability, throughput, and end-to-end delay.

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