Allocation of applications to Fog resources via semantic clustering techniques: with scenarios from intelligent transportation systems

Xhafa, Fatos; Aly, Alhassan; Juan, Ángel A.

doi:10.1007/s00607-020-00867-w

Cited by 15 publications

(5 citation statements)

References 24 publications

(23 reference statements)

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“…Sports events are a complex group of events, especially the top events such as the Olympic Games, from the beginning of the project to the successful conclusion of the Olympic Games, the long cycle, involving a wide range is unparalleled. erefore, the overall project should be completed in a more sequential and phased manner, with relevant evaluations carried out at each implementation stage and organized at each stage of the evaluation [9].…”

Section: Principle Of Dynamicmentioning

confidence: 99%

Research on Evaluation Method of Sports Events Based on Edge Algorithm

Deng

Gudamu

2021

Security and Communication Networks

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In view of the high computational cost and long computational time of IoT edge algorithm in traditional sports event evaluation, this paper optimizes IoT edge algorithm by introducing deep reinforcement learning technology. Set the IoT edge algorithm cycle through the IoT topology to obtain the data upload speed. In order to improve the evaluation efficiency of sports events, the process of edge algorithm is designed. The contribution rate of evaluation index is calculated, and the consistency, minimum deviation, and minimum difference of the results are taken as the standard to design the evaluation method of sports events. In order to verify the performance of the optimized edge algorithm, the test data set and test platform are set up and the comparative experiment is designed. Compared with the traditional methods, the edge algorithm based on DSLL has lower computational cost, shorter computational time, higher evaluation accuracy, and more practical results.

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Section: Principle Of Dynamicmentioning

confidence: 99%

Research on Evaluation Method of Sports Events Based on Edge Algorithm

Deng

Gudamu

2021

Security and Communication Networks

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“…The IoT, which refers to devices that are connected to the internet and can collect information about the environment, has seen quick growth because of the widespread use of advanced hardware and software, better access to communication networks, and improvements in data analysis tools [54][55][56]. The basic idea behind IoT is to connect various devices that produce or gather data through technologies such as RFID, actuators, sensors, and smartphones, so that these devices can communicate with each other [57].…”

Section: The Iot Conceptmentioning

confidence: 99%

Analyzing Barriers to Internet of Things (IoT) Adoption in Humanitarian Logistics: An ISM–DEMATEL Approach

Rejeb,

Zrelli

2024

Logistics

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Background: Effective humanitarian logistics (HL) is essential in disaster response. The “Internet of Things” (IoT) holds potential to enhance the efficiency and efficacy of HL, yet adoption is slowed by numerous barriers. Methods: This study employs interpretive structural modeling (ISM) and decision-making trial and evaluation laboratory (DEMATEL) to explore and classify barriers to IoT integration in HL. Results: A total of 12 barriers were identified, classified, and ranked according to their driving power and dependence. Key barriers include lack of standardization, organizational resistance, data quality issues, and legal challenges. Conclusions: Overcoming these barriers could significantly improve relief operations, reduce errors, and enhance decision-making processes in HL. This investigation is the first of its kind into IoT barriers in HL, laying the groundwork for further research and providing valuable insights for HL managers.

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“…Hence, techniques for grouping and classifying resources in virtual nodes with large computational capacity are necessary for the co-existence of computational tools with different computations. Due to this issue, based on combining semantic description of resources with semantic clustering techniques, Xhafa et al [52] present some clustering techniques for creating virtual computing nodes from fog/edge nodes and, by using these clusters via heuristics and linear programming, creating an optimal allocation of applications to virtual computing nodes. Additionally, due to the growth of IoT and 5G telecommunication networks, Gohar and Nencioni [53] provide an overview of the benefits of 5G in an economic and technological context, and discuss impacts and concepts of 5G for ITS from various dimensions.…”

Section: Cloud Fog and Edge Computing In Itsmentioning

confidence: 99%

Edge Computing and IoT Analytics for Agile Optimization in Intelligent Transportation Systems

et al. 2021

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With the emergence of fog and edge computing, new possibilities arise regarding the data-driven management of citizens’ mobility in smart cities. Internet of Things (IoT) analytics refers to the use of these technologies, data, and analytical models to describe the current status of the city traffic, to predict its evolution over the coming hours, and to make decisions that increase the efficiency of the transportation system. It involves many challenges such as how to deal and manage real and huge amounts of data, and improving security, privacy, scalability, reliability, and quality of services in the cloud and vehicular network. In this paper, we review the state of the art of IoT in intelligent transportation systems (ITS), identify challenges posed by cloud, fog, and edge computing in ITS, and develop a methodology based on agile optimization algorithms for solving a dynamic ride-sharing problem (DRSP) in the context of edge/fog computing.These algorithms allow us to process, in real time, the data gathered from IoT systems in order to optimize automatic decisions in the city transportation system, including: optimizing the vehicle routing, recommending customized transportation modes to the citizens, generating efficient ride-sharing and car-sharing strategies, create optimal charging station for electric vehicles and different services within urban and interurban areas. A numerical example considering a DRSP is provided, in which the potential of employing edge/fog computing, open data, and agile algorithms is illustrated.

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Allocation of applications to Fog resources via semantic clustering techniques: with scenarios from intelligent transportation systems

Abstract: Portal del coneixement obert de la UPC http://upcommons.upc.edu/e-prints This is a post-peer-review, pre-copy edit version of an article

Cited by 15 publications

References 24 publications

Research on Evaluation Method of Sports Events Based on Edge Algorithm

Research on Evaluation Method of Sports Events Based on Edge Algorithm

Analyzing Barriers to Internet of Things (IoT) Adoption in Humanitarian Logistics: An ISM–DEMATEL Approach

Edge Computing and IoT Analytics for Agile Optimization in Intelligent Transportation Systems

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