An intelligent, uncertainty driven management scheme for software updates in pervasive IoT applications

Kolomvatsos, Kostas

doi:10.1016/j.future.2018.01.036

Cited by 18 publications

(9 citation statements)

References 52 publications

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“…A rerouting network function was developed and operated without troubling the transmission of data dynamically. Kolomvatsos et al [151] recommended an intelligent supplied paradigm to improve the impartial nature of IoT nodes for revising management in IoT applications. The study suggested that each node processes the update procedure independently by examining certain network implementation elements.…”

Section: Infrastructural Applicationsmentioning

confidence: 99%

Internet of Things and Its Applications: A Comprehensive Survey

et al. 2020

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With the evolution of the fifth-generation (5G) wireless network, the Internet of Things (IoT) has become a revolutionary technique that enables a diverse number of features and applications. It can able a diverse amount of devices to be connected in order to create a single communication architecture. As it has significantly expanded in recent years, it is fundamental to study this trending technology in detail and take a close look at its applications in the different domains. It represents an enabler of new communication possibilities between people and things. The main asset of this concept is its significant influence through the creation of a new world dimension. The key features required for employing a large-scale IoT are low-cost sensors, high-speed and error-tolerant data communications, smart computations, and numerous applications. This research work is presented in four main sections, including a general overview of IoT technology, a summary of previous correlated surveys, a review regarding the main IoT applications, and a section on the challenges of IoT. The purpose of this study is to fully cover the applications of IoT, including healthcare, environmental, commercial, industrial, smart cities, and infrastructural applications. This work explains the concept of IoT and defines and summarizes its main technologies and uses, offering a next-generation protocol as a solution to the challenges. IoT challenges were investigated to enhance research and development in the fields. The contribution and weaknesses of each research work cited are covered, highlighting eventual possible research questions and open matters for IoT applications to ensure a full analysis coverage of the discussed papers.

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Section: Infrastructural Applicationsmentioning

confidence: 99%

Internet of Things and Its Applications: A Comprehensive Survey

et al. 2020

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“…Several intelligent technologies have emerged to ensure the proper functioning of IoT devices and their incorporation into the above discussed ecosystem. For instance, the efficient management of software updates of IoT devices aiming at the minimization of the conclusion time and the maximization of their and network's performance is the subject of some recent studies [62], [63], [68]. Cloud provides many benefits to the IoT infrastructure, e.g., highperformance computing, storage resources, processing and analysis of huge volumes of data.…”

Section: Intelligence At the Edge Of The Networkmentioning

confidence: 99%

“…However, the EC/EM hardware infrastructure should be efficiently connected with the Cloud 'premises' to facilitate the easy communication between the two frameworks when executing the proposed algorithms/models. 63 . This way, IoT devices will be facilitated to transfer data in an upwards mode and cooperate in processing activities.…”

Section: Hardware Requirementsmentioning

confidence: 99%

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On the Use of Intelligent Models towards Meeting the Challenges of the Edge Mesh

et al. 2021

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Nowadays, we are witnessing the advent of the Internet of Things (IoT) with numerous devices performing interactions between them or with their environment. The huge number of devices leads to huge volumes of data that demand the appropriate processing. The “legacy” approach is to rely on Cloud where increased computational resources can realize any desired processing. However, the need for supporting real-time applications requires a reduced latency in the provision of outcomes. Edge Computing (EC) comes as the “solver” of the latency problem. Various processing activities can be performed at EC nodes having direct connection with IoT devices. A number of challenges should be met before we conclude a fully automated ecosystem where nodes can cooperate or understand their status to efficiently serve applications. In this article, we perform a survey of the relevant research activities towards the vision of Edge Mesh (EM), i.e., a “cover” of intelligence upon the EC. We present the necessary hardware and discuss research outcomes in every aspect of EC/EM nodes functioning. We present technologies and theories adopted for data, tasks, and resource management while discussing how machine learning and optimization can be adopted in the domain.

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“…Such strategy does not use any approximated values to calculate future estimations being then immune to accumulation of errors. We use an ensemble of forecasters and randomly select one for each of the t steps as studied in [29]. Based on the T forecasts, i.e.,ṽ t+1 ,.…”

Section: B Network Performance Probability Forecastermentioning

confidence: 99%

Proactive & Time-Optimized Data Synopsis Management at the Edge

Kolomvatsos

Anagnostopoulos

Koziri

et al. 2020

IEEE Trans. Knowl. Data Eng.

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Internet of Things offers the infrastructure for smooth functioning of autonomous context-aware devices being connected towards the Cloud. Edge Computing (EC) relies between the IoT and Cloud providing significant advantages. One advantage is to perform local data processing (limited latency, bandwidth preservation) with real time communication among IoT devices, while multiple nodes become hosts of the collected data (reported by IoT devices). In this work, we provide a mechanism for the exchange of data synopses (summaries of extracted knowledge) among EC nodes that are necessary to give the knowledge on the data present in EC environments. The overarching aim is to intelligently decide on when nodes should exchange data synopses in light of efficient execution of tasks. We enhance such a decision with a stochastic optimization model based on the Theory of Optimal Stopping. We provide the fundamentals of our model and the relevant formulations on the optimal time to disseminate data synopses to network edge nodes. We report a comprehensive experimental evaluation and comparative assessment related to the optimality achieved by our model and the positive effects on EC.

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An intelligent, uncertainty driven management scheme for software updates in pervasive IoT applications

Cited by 18 publications

References 52 publications

Internet of Things and Its Applications: A Comprehensive Survey

Internet of Things and Its Applications: A Comprehensive Survey

On the Use of Intelligent Models towards Meeting the Challenges of the Edge Mesh

Proactive & Time-Optimized Data Synopsis Management at the Edge

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