Search results for "reunalaskenta"

showing 4 items of 4 documents

Incentive Mechanism for Edge Computing-Based Blockchain: A Sequential Game Approach

2022

The development of the blockchain framework is able to provide feasible solutions for a wide range of Industrial Internet of Things (IIoT) applications. While the IIoT devices are usually resource-limited, how to make sure the acquisition of computational resources and participation of the devices will be the driving force to realize blockchain. In this work, an edge computing-based blockchain framework is considered, where multiple edge service providers (ESPs) can provide computational resources to the IIoT devices. We focus on investigating the trading between the devices and ESPs, where ESPs are the sellers and devices are the buyers. A sequential game is formulated and by exploring the…

computational modelingblockchainsInternet of ThingsmininglohkoketjutComputer Science Applicationsedge computingreunalaskentaControl and Systems Engineeringtask analysispricinginformaticsincentive mechanismpeliteoriaesineiden internettiedonlouhintaElectrical and Electronic EngineeringgamesInformation SystemsIEEE Transactions on Industrial Informatics
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Resource Allocation and Computation Offloading for Multi-Access Edge Computing With Fronthaul and Backhaul Constraints

2021

Edge computing is able to provide proximity solutions for the future wireless network to accommodate different types of devices with various computing service demands. Meanwhile, in order to provide ubiquitous connectivities to massive devices over a relatively large area, densely deploying remote radio head (RRH) is considered as a cost-efficient solution. In this work, we consider a vertical and heterogeneous multi-access edge computing system. In the system, the RRHs are deployed for providing wireless access for the users and the edge node with computing capability can process the computation requests from the users. With the objective to minimize the total energy consumption for proces…

energiankulutus (energiateknologia)Computer Networks and CommunicationsComputer scienceDistributed computingresource allocationAerospace Engineeringlangaton tekniikkaresursointifronthaul/backhaul linkmulti-access edge computingoptimointioffloadingWirelessComputation offloadingResource managementElectrical and Electronic EngineeringEdge computingWireless networkbusiness.industryRemote radio headBackhaul (telecommunications)reunalaskentaAutomotive EngineeringResource allocationbusinesslangattomat verkotIEEE Transactions on Vehicular Technology
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Towards Seamless IoT Device-Edge-Cloud Continuum:

2021

In this paper we revisit a taxonomy of client-side IoT software architectures that we presented a few years ago. We note that the emergence of inexpensive AI/ML hardware and new communication technologies are broadening the architectural options for IoT devices even further. These options can have a significant impact on the overall end-to-end architecture and topology of IoT systems, e.g., in determining how much computation can be performed on the edge of the network. We study the implications of the IoT device architecture choices in light of the new observations, as well as make some new predictions about future directions. Additionally, we make a case for isomorphic IoT systems in whic…

software architectureIoTsulautettu tietotekniikkaprogrammable worldembedded devicesohjelmistotuotantointernet of thingsliquid softwarepilvipalvelutedge computingisomorphismreunalaskentaohjelmistoarkkitehtuuriisomorphic softwareesineiden internetsoftware engineering
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Tiny Machine Learning for Resource-Constrained Microcontrollers

2022

We use 250 billion microcontrollers daily in electronic devices that are capable of running machine learning models inside them. Unfortunately, most of these microcontrollers are highly constrained in terms of computational resources, such as memory usage or clock speed. These are exactly the same resources that play a key role in teaching and running a machine learning model with a basic computer. However, in a microcontroller environment, constrained resources make a critical difference. Therefore, a new paradigm known as tiny machine learning had to be created to meet the constrained requirements of the embedded devices. In this review, we discuss the resource optimization challenges of …

sulautettu tietotekniikkakoneoppiminenreunalaskentaesineiden internetresurssit
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