scholarly journals Minimising Delay and Energy in Online Dynamic Fog Systems

2020 ◽  
Author(s):  
Faten Alenizi ◽  
Omer Rana
Keyword(s):  
Energy Consumption ◽  
Fog Computing ◽  
Cloud Services ◽  
Dynamic Task ◽  
Delay Sensitive ◽  
Reduce Energy Consumption ◽  
Iot Devices ◽  
User Tasks ◽  
Use Of Internet

The increasing use of Internet of Things (IoT) devices generates a greater demand for data transfers and puts increased pressure on networks. Additionally, connectivity to cloud services can be costly and inefficient. Fog computing provides resources in proximity to user devices to overcome these drawbacks. However, optimisation of quality of service (QoS) in IoT applications and the management of fog resources are becoming challenging problems. This paper describes a dynamic online offloading scheme in vehicular traffic applications that require execution of delay-sensitive tasks. This paper proposes a combination of two algorithms: dynamic task scheduling (DTS) and dynamic energy control (DEC) that aim to minimise overall delay, enhance throughput of user tasks and minimise energy consumption at the fog layer while maximising the use of resource-constrained fog nodes. Compared to other schemes, our experimental results show that these algorithms can reduce the delay by up to 80.79% and reduce energy consumption by up to 66.39% in fog nodes. Additionally, this approach enhances task execution throughput by 40.88%.

scholarly journals Dynamically Controlling Offloading Thresholds in Fog Systems

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2512 ◽  
Author(s):  
Faten Alenizi ◽  
Omer Rana
Keyword(s):  
Energy Consumption ◽  
Fog Computing ◽  
Limited Resources ◽  
Location Awareness ◽  
Computing Systems ◽  
Dynamic Task ◽  
Delay Sensitive ◽  
Reduce Energy Consumption ◽  
Iot Devices ◽  
Dynamic Task Scheduling

Fog computing is a potential solution to overcome the shortcomings of cloud-based processing of IoT tasks. These drawbacks can include high latency, location awareness, and security—attributed to the distance between IoT devices and cloud-hosted servers. Although fog computing has evolved as a solution to address these challenges, it is known for having limited resources that need to be effectively utilized, or its advantages could be lost. Computational offloading and resource management are critical to be able to benefit from fog computing systems. We introduce a dynamic, online, offloading scheme that involves the execution of delay-sensitive tasks. This paper proposes an architecture of a fog node able to adjust its offloading threshold dynamically (i.e., the criteria by which a fog node decides whether tasks should be offloaded rather than executed locally) using two algorithms: dynamic task scheduling (DTS) and dynamic energy control (DEC). These algorithms seek to minimize overall delay, maximize throughput, and minimize energy consumption at the fog layer. Compared to other benchmarks, our approach could reduce latency by up to 95%, improve throughput by 71%, and reduce energy consumption by up to 67% in fog nodes.

scholarly journals Fog Computing: Towards Dynamically Controlling the Offloading Threshold and Managing Fog Resources in Online Dynamic Systems

2021 ◽  
Author(s):  
Faten Alenizi ◽  
Omer Rana
Keyword(s):  
Energy Consumption ◽  
Resource Management ◽  
Fog Computing ◽  
Location Awareness ◽  
Computing Systems ◽  
Dynamic Task ◽  
Delay Sensitive ◽  
Maximum Benefit ◽  
Computational Offloading ◽  
Iot Devices

Fog computing is a potential solution to overcome the shortcomings of the cloud computing processing of IoT tasks. These drawbacks can be high latency, location awareness and security, and it is attributed to the distance between IoT devices and servers, network congestion and other variables. Although fog computing has evolved as a solution to these challenges, it is known for having limited resources that need to be consciously utilised, or any of its ad-vantages would be lost. Computational offloading and resource management are critical concerns to be considered to get maximum benefit of the available resource at fog computing systems and benefit from its advantages. Computational offloading and resource management are important issues to be considered to get maximum benefit of the available resource at fog computing systems and benefit from its advantages. In this article, in vehicular traffic applications, we introduce a dynamic online offloading scheme that involves the execution of delay-sensitive ac-tivities. This paper proposes an architecture of a fog node that enables a fog node to adjust its offloading threshold dynamically (i.e., the criteria by which a fog node decides whether tasks should be offloaded rather than executed locally) using two algorithms: dynamic task scheduling (DTS) and dynamic energy control (DEC). These algorithms seek to solve an optimisation problem aimed at minimising overall delay, improving throughput, and minimising energy consumption at the fog layer, while maximising the use of resource-constrained fog nodes. Compared with other benchmarks, our approach can reduce the delay by up to 95.38% and reduce energy consumption by up to 67.71% in fog nodes. Additionally, this approach enhances throughput by 71.08%.

scholarly journals Design and develop Quality of Service Framework using Fog Computing for Smart City Applications

2019 ◽  
Vol 9 (1S) ◽  
pp. 343-348
Keyword(s):  
Quality Of Service ◽  
Energy Consumption ◽  
Power Consumption ◽  
Smart City ◽  
Fog Computing ◽  
Cloud Data ◽  
Efficient Reduction ◽  
Iot Devices ◽  
Service Framework

In today's world, Internet of Things (IoT) is has become the most promising and life-changing technology. In the past few years, IoT has become most productive in the area of healthcare, to improve the quality of care to the patients. This paper aims to reduce the delay, energy consumption of cloud data-centers and minimized the power consumption IoT devices using fog devices. To solve the problem mentioned above, we proposed the Quality of Service framework using fog computing for smart city applications named FATEH, a three-tier architecture for IoT-based application. Various quality of services parameters are optimized as For minimizing the power consumption of IoT devices, the Routing Protocol for Low power and Lossy network (RPL). The other QoS parameter is computing the performance of the proposed framework which has been evaluated through the iFogsim toolkit and the Cooja simulator. Results show the efficient reduction in the delay as well as energy consumption in the proposed scenario and provide better QoS framework

scholarly journals A Containerized Approach for Allocating Distributed Stream Queries to Fog Nodes

2021 ◽  
Author(s):  
Hamed Hasibi ◽  
Saeed Sedighian Kashi
Keyword(s):  
Fog Computing ◽  
Stream Processing ◽  
Stream Data ◽  
Process Data ◽  
Stream Query Processing ◽  
Tremendous Amount ◽  
Stream Processing Engines ◽  
Iot Devices ◽  
Distributed Stream Processing

Fog computing brings cloud capabilities closer to the Internet of Things (IoT) devices. IoT devices generate a tremendous amount of stream data towards the cloud via hierarchical fog nodes. To process data streams, many Stream Processing Engines (SPEs) have been developed. Without the fog layer, the stream query processing executes on the cloud, which forwards much traffic toward the cloud. When a hierarchical fog layer is available, a complex query can be divided into simple queries to run on fog nodes by using distributed stream processing. In this paper, we propose an approach to assign stream queries to fog nodes using container technology. We name this approach Stream Queries Placement in Fog (SQPF). Our goal is to minimize end-to-end delay to achieve a better quality of service. At first, in the emulation step, we make docker container instances from SPEs and evaluate their processing delay and throughput under different resource configurations and queries with varying input rates. Then in the placement step, we assign queries among fog nodes by using a genetic algorithm. The practical approach used in SQPF achieves a near-the-best assignment based on the lowest application deadline in real scenarios, and evaluation results are evidence of this goal.

scholarly journals Industrial Internet of Things and Fog Computing to Reduce Energy Consumption in Drinking Water Facilities

Processes ◽  
2020 ◽  
Vol 8 (3) ◽  
pp. 282 ◽  
Author(s):  
Adrian Korodi ◽  
Ruben Crisan ◽  
Andrei Nicolae ◽  
Ioan Silea
Keyword(s):  
Drinking Water ◽  
Energy Consumption ◽  
Internet Of Things ◽  
Fog Computing ◽  
Industrial Internet Of Things ◽  
Non Invasive ◽  
Data Accumulation ◽  
Industrial Internet ◽  
Reduce Energy Consumption ◽  
And Control

The industry is generally preoccupied with the evolution towards Industry 4.0 principles and the associated advantages as cost reduction, respectively safety, availability, and productivity increase. So far, it is not completely clear how to reach these advantages and what their exact representation or impact is. It is necessary for industrial systems, even legacy ones, to assure interoperability in the context of chronologically dispersed and currently functional solutions, respectively; the Open Platform Communications Unified Architecture (OPC UA) protocol is an essential requirement. Then, following data accumulation, the resulting process-aware strategies have to present learning capabilities, pattern identification, and conclusions to increase efficiency or safety. Finally, model-based analysis and decision and control procedures applied in a non-invasive manner over functioning systems close the optimizing loop. Drinking water facilities, as generally the entire water sector, are confronted with several issues in their functioning, with a high variety of implemented technologies. The solution to these problems is expected to create a more extensive connection between the physical and the digital worlds. Following previous research focused on data accumulation and data dependency analysis, the current paper aims to provide the next step in obtaining a proactive historian application and proposes a non-invasive decision and control solution in the context of the Industrial Internet of Things, meant to reduce energy consumption in a water treatment and distribution process. The solution is conceived for the fog computing concept to be close to local automation, and it is automatically adaptable to changes in the process’s main characteristics caused by various factors. The developments were applied to a water facility model realized for this purpose and on a real system. The results prove the efficiency of the concept.

scholarly journals Moving to the Edge-Cloud-of-Things: Recent Advances and Future Research Directions

Electronics ◽  
2018 ◽  
Vol 7 (11) ◽  
pp. 309 ◽  
Author(s):  
Hind Bangui ◽  
Said Rakrak ◽  
Said Raghay ◽  
Barbora Buhnova
Keyword(s):  
Cloud Computing ◽  
Leading Edge ◽  
Cloud Services ◽  
Future Research ◽  
Research Directions ◽  
Iot Applications ◽  
Future Research Directions ◽  
Iot Devices ◽  
The Internet Of Things

Cloud computing has significantly enhanced the growth of the Internet of Things (IoT) by ensuring and supporting the Quality of Service (QoS) of IoT applications. However, cloud services are still far from IoT devices. Notably, the transmission of IoT data experiences network issues, such as high latency. In this case, the cloud platforms cannot satisfy the IoT applications that require real-time response. Yet, the location of cloud services is one of the challenges encountered in the evolution of the IoT paradigm. Recently, edge cloud computing has been proposed to bring cloud services closer to the IoT end-users, becoming a promising paradigm whose pitfalls and challenges are not yet well understood. This paper aims at presenting the leading-edge computing concerning the movement of services from centralized cloud platforms to decentralized platforms, and examines the issues and challenges introduced by these highly distributed environments, to support engineers and researchers who might benefit from this transition.

Research and Discussion on Energy-Saving of Existing Buildings in Northwest of Liaoning Province

2012 ◽  
Vol 178-181 ◽  
pp. 221-224
Author(s):  
Ya Jun Wu ◽  
Yu Ma
Keyword(s):  
Energy Consumption ◽  
Energy Conservation ◽  
Energy Saving ◽  
Working Environment ◽  
Liaoning Province ◽  
Existing Buildings ◽  
Cold Regions ◽  
The Status ◽  
Reduce Energy Consumption

Abstract. In view of the status of existing buildings in northwest of Liaoning, most of which are lack of energy-saving practices and appear poor comfort, this paper starts from the energy saving concept, aims at figuring out the energy saving measures for cold regions, such as northwest of Liaoning province. The research includes analyzing energy-saving methods, steps and initiatives. Based on these, this paper also proposes specific technical practices to overcome the shortcomings of the existing buildings on energy conservation, and gives advices on how to reduce energy consumption and improve the quality of people’s living and working environment.

scholarly journals Fog Computing-Security Platform for IoT and Cloud in-Healthcare System

2019 ◽  
Vol 9 (2) ◽  
pp. 4419-4424
Keyword(s):  
Cloud Computing ◽  
Quality Of Service ◽  
Service Management ◽  
New Technology ◽  
Fog Computing ◽  
Cloud Services ◽  
Third Party ◽  
Selection System ◽  
Search Tool

The introduction of cloud computing has revolutionized business and technology. Cloud computing has merged technology and business creating an almost indistinguishable framework. Cloud computing has utilized various techniques that have been vital in reshaping the way computers are used in business, IT, and education. Cloud computing has replaced the distributed system of using computing resources to a centralized system where resources are easily shared between user and organizations located in different geographical locations. Traditionally the resources are usually stored and managed by a third-party, but the process is usually transparent to the user. The new technology led to the introduction of various user needs such as to search the cloud and associated databases. The development of a selection system used to search the cloud such as in the case of ELECTRE IS and Skyline; this research will develop a system that will be used to manage and determine the quality of service constraints of these new systems with regards to networked cloud computing. The method applied will mimic the various selection system in JAVA and evaluate the Quality of service for multiple cloud services. The FogTorch search tool will be used for quality service management of three cloud services.

scholarly journals LONGITUDINAL COMPRESSING AND SHEARING PROPERTIES OF SILAGE CORN STALK IN NORTH CHINA PLAIN

2021 ◽  
pp. 47-56
Author(s):  
Meizhou Chen ◽  
Guangfei Xu ◽  
Maojian Wei ◽  
Zhicai Song ◽  
Wenjun Wang ◽  
...  
Keyword(s):  
Energy Consumption ◽  
North China Plain ◽  
Corn Stalk ◽  
Factors Affecting ◽  
Silage Fermentation ◽  
Reduce Energy Consumption ◽  
Shearing Energy ◽  
Cutting Mechanisms ◽  
Working Quality

During silage harvesting, silage corn stalk is compressed by a feeding device and fed into the shearing device to be sheared into qualified segments to make silage fermentation easier. To optimize the working quality of the existing silage harvester and reduce energy consumption, it’s necessary to make a comprehensive analysis of the longitudinal compressing and shearing properties of the silage corn stalks and get a reliable shearing model. According to the different structural properties of the silage corn stalks, the main factors affecting the shearing energy consumption and their levels were obtained by compressing and shearing tests on internodes and nodes in this paper. The results of three-level and three-factor experiments showed that the overall shearing energy consumption for nodes was much higher than that for internodes. Compressing the silage corn stalk to some extent before shearing at the loading direction of 0° and lower shearing speed was beneficial to saving energy during the process of shearing off the silage corn stalk. The reduced energy requirements of the silage corn stalk could be exploited advantageously to present new reference for the feeding and cutting mechanisms of silage harvester. The research results can provide a reference for silage corn harvesting.

scholarly journals Machine Learning for Smart Environments in B5G Networks: Connectivity and QoS

2021 ◽  
Vol 2021 ◽  
pp. 1-23
Author(s):  
Saeed H. Alsamhi ◽  
Faris A. Almalki ◽  
Hatem Al-Dois ◽  
Soufiene Ben Othman ◽  
Jahan Hassan ◽  
...  
Keyword(s):  
Machine Learning ◽  
Smart Cities ◽  
Dynamic Environments ◽  
Iot Applications ◽  
Smart Healthcare ◽  
Intelligent Management ◽  
Reduce Energy Consumption ◽  
Iot Devices ◽  
Shed Light

The number of Internet of Things (IoT) devices to be connected via the Internet is overgrowing. The heterogeneity and complexity of the IoT in terms of dynamism and uncertainty complicate this landscape dramatically and introduce vulnerabilities. Intelligent management of IoT is required to maintain connectivity, improve Quality of Service (QoS), and reduce energy consumption in real time within dynamic environments. Machine Learning (ML) plays a pivotal role in QoS enhancement, connectivity, and provisioning of smart applications. Therefore, this survey focuses on the use of ML for enhancing IoT applications. We also provide an in-depth overview of the variety of IoT applications that can be enhanced using ML, such as smart cities, smart homes, and smart healthcare. For each application, we introduce the advantages of using ML. Finally, we shed light on ML challenges for future IoT research, and we review the current literature based on existing works.

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