(EMAILWIRE.COM, November 07, 2024 ) According to MarketsandMarkets' latest research, the Edge Computing Market is projected to grow from USD 60.0 billion in 2024 to USD 110.6 billion by 2029, achieving a compound annual growth rate (CAGR) of 13.0%. As the Internet of Things (IoT) continues its rapid...

With the rapid development and application of driverless technology, the number and location of vehicles, the channel and bandwidth of wireless network are time-varying, which leads to the increase of offloading delay and energy consumption of existing algorithms. To solve this problem, the vehicle terminal task offloading decision problem is modelled as a Markov decision process, and a task offloading algorithm based on DDQN is proposed. In order to guide agents to quickly select optimal strategies, this paper proposes an offloading mechanism based on task feature. In order to solve the problem that the processing delay of some edge server tasks exceeds the upper limit of their delay, a task scheduling mechanism based on buffer delay is proposed. Simulation results show that the proposed method has greater performance advantages in reducing delay and energy consumption compared with existing algorithms.

The intelligent financial sharing platform in the online realm is capable of collecting, storing, processing, analysing and sharing financial data through the integration of AI and big data processing technologies. However, as data volume grows exponentially, the cost of financial data storage and processing increases, and the asset accounting and financial profit data sharing analysis structure in financial sharing platforms is inadequate. To address the issue of data security sharing in the intelligent financial digital sharing platform, this paper proposes a data-sharing framework based on blockchain and edge computing. Building upon this framework, a non-separable task distribution algorithm based on data sharing is developed, which employs multiple nodes for cooperative data storage, reducing the pressure on the central server for data storage and solving the problem of non-separable task distribution. Multiple sets of comparative experiments confirm the proposed scheme has good feasibility in improving algorithm performance and reducing energy consumption and latency.

To explore the computer-aided translation technology based on the intelligent algorithm of edge computing. This paper presents the research on computer-aided translation technology based on edge computing intelligent algorithm. In the K-means computer edge algorithm, it analyses the traditional way of average resource allocation and the way of virtual machine allocation. In the process of online solution, we have a more detailed understanding of the data information at the edge, and also avoid the connection relationship between network users and the platform, which has a certain impact on the internal operation efficiency of the system. The network user group is divided into several different types of existence through K-means computer algorithm, and various information resources are counted according to their own characteristics. Computer-aided translation technology can significantly improve the quality of translation, improve the translation efficiency, and reduce the translation cost.

STL Partners announces launch of top 2023 edge computing companies list, including financial milestones and practical edge applications.

ETSI Multi-access Edge Computing opens new working group for MEC deployment

Sophia Antipolis, 14 February 2019

The +85 members of the ETSI Multi-access Edge Computing group (ETSI MEC ISG) are thrilled to announce the creation of the Deployment and Ecosystem Development working group (WG DECODE).

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ETSI Multi-access Edge Computing releases Phase 2 specifications

Sophia Antipolis, 21 March 2019

The ETSI Multi-access Edge Computing group (MEC ISG) announces the release of its first set of Phase 2 specifications, including ETSI GS MEC 002 which includes new requirements for Phase 2, ETSI GS MEC 003 dealing with architecture and framework, and  ETSI GS MEC 009 giving general principles for service APIs.

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ETSI’s 4th NFV Plugtests event broadens its scope with edge computing testing

Sophia Antipolis, 29 July 2019

The 4^th ETSI NFV Plugtests^TM event was one of the sunny June highlights in ETSI, as it took place from 3 to 7 June in Sophia Antipolis.

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Developers at MEC Hackathons endorsed by ETSI challenged to trial edge computing for 5G in UK and China

Sophia Antipolis, 27 September 2019

The successful second edition of the MEC Hackathons endorsed by ETSI recently ended in two different parts of the world simultaneously on 17-18 September in London (UK) and Shenzhen (China).

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ETSI Multi-access Edge Computing builds on NFV and network slicing

Sophia Antipolis, 15 January 2020

The ETSI Multi-access Edge Computing Industry Specification Group is pleased to announce the release of two major reports as part of its Phase 2 work. The report ETSI GR MEC 027 studies the impact of alternative virtualization technologies. The second report, ETSI GR MEC 024, examines network slicing on edge computing systems.

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ETSI Multi-access Edge Computing group reaches 100 members confirming attractiveness of the group

Sophia Antipolis, 31 March 2020

Strategy Analytics believes that 59% of all IoT deployments will be processing data using edge computing of some form by 2025. Furthermore, a survey from ResearchAndMarkets predicts that mobile edge computing as a service market will reach $73M by 2024, driven by enterprise hosted deployments. No wonder that ISG MEC - one of ETSI’s most dynamic Industry Specification Groups - keeps growing and has now welcomed its 100^th member with Mitsubishi Electric R&D Centre Europe.

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ETSI Multi-Access Edge Computing extends services to WiFi to address enterprise needs

Sophia Antipolis, 16 July 2020

The ETSI Industry Specification Group on Multi-Access Edge Computing, ISG MEC, has recently released ETSI MEC GS 028 to extend network information services to the world of WiFi and thus squarely into enterprises space.

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New ETSI white paper: Harmonizing standards for edge computing, a synergized architecture leveraging ETSI ISG MEC and 3GPP specifications

Sophia Antipolis, 27 July 2020

Members and officials of the ETSI Multi-access Edge Computing group and the 3GPP SA WG6 have just published a new white paper which aims to harmonize standards for edge computing. The white paper highlights the role of standards for edge when edge computing is deployed in conjunction with mobile networks. It also reviews the leading efforts in the industry and introduces a synergized architecture which leverages the ETSI ISG MEC and 3GPP specifications. This paper highlights the value proposition of different standards streams and how those standards may be combined when it comes to deployments. Some deployment options are discussed.

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Developers at MEC Hackathon challenged to trial edge computing for 5G at the Droidcon virtual event

Sophia Antipolis, 10 December 2020

The successful last edition of MEC Hackathons endorsed by ETSI took place on 25 to 26 November and was hosted by Droidcon Italy 2020 as a fully virtual event. The competition was open for developers to test their applications with ETSI MEC APIs (Application Programming Interfaces) in a variety of use cases. The organizing committee received a total of 14 submissions, including several topics, from Augmented Reality for Construction Sector, to consumer, media and entertainment application, to automotive services. Admitted teams were offered remote access to MEC servers and software platforms to develop mobile applications for advanced services in MEC-enabled 5G networks, using ETSI MEC technologies. They were also required to onboard their applications in real-life MEC systems and connect with the MEC APIs to receive simulated in-network data.

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MEC is ramping up with Phase 3 work on Multi-access Edge Computing

Sophia Antipolis, 15 March 2022

Since the beginning of 2022 the ETSI MEC Industry Specification Group (ETSI ISG MEC) has moved forward with the on-going Phase 3 work, which is foreseen to help accelerate and enable more effective and fruitful collaboration with other organizations.

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ETSI publishes a new White Paper on Multi-access Edge Computing security

Sophia Antipolis, 28 September 2022

Members from the ETSI Multi-Access Edge Computing group (ISG MEC) have just published a new white paper, “MEC security; Status of standards support and future evolutions".

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Leading to more effective and fruitful cross organization collaboration

Sophia Antipolis, 14 February 2023

In the last three months, ETSI ISG MEC has released its final Phase 2 specification (GS MEC 015, on Traffic Management APIs) and made significant progress on Phase 3 with the release of a number of important specifications, including the MEC Federation Enablement APIs (GS MEC 040): in particular, this specification is critical for supporting the requirements received from GSMA OPG (Operator Platform Group) to enable inter-MEC system communication and allow 5G operators to collaborate among themselves, with service cloud providers and with other stakeholders. 

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Sophia Antipolis, 15 April 2024

ETSI Multi-access Edge Computing completed Phase 3 Work and started Phase 4

Leading to more effective and fruitful cross organization collaboration

In the last three months, ETSI ISG MEC has released its final set of Phase 3 specifications and made significant progress on Phase 4 with the opening of new Work Items. In particular, the last Phase 3 version of MEC 011 (Edge Platform Application Enablement) contains the updates related to the latest alignment with 3GPP on CAPIF, thanks to a fruitful collaboration with SA6, CT3 and SA3 groups. Also, ISG MEC produced an updated version of MEC 040 (Federation Enablement APIs), that carefully considered the relevant work of other industry bodies relating to MEC federation and all relevant work done in ETSI. This work is critical for supporting the requirements from GSMA OPG (Operator Platform Group) to enable inter-MEC system communication and allow 5G operators to collaborate among themselves, with service cloud providers and with other stakeholders. New APIs are introduced for the enablement of MEC federation, helping operators to "federate" edge computing resources by offering their MEC service capabilities for mutual consumption, application developers and end-customers (e.g. vertical markets).

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Edaena Salinas talks with Maria Gorlatova about Edge Computing. Maria Gorlatova is an Associate Research Scholar at Princeton University Department of Electrical Engineering. The discussion covers: IoT, edge computing, the architecture of edge computing, running a machine learning model on the edge, and the benefits of edge computing.

Beyond the buzz, what impact is IoT having in the real world? How is it changing enterprise IT? A panel of experts shares their experience and insight.

Requirements for civilian unmanned aerial vehicles enabled mobile edge computing

Requirements for mobile edge computing enabled content delivery networks

Requirements for edge computing in video surveillance

Frank Indiviglio, NOAA’s deputy director for High Performance Computing & Communications (HPCC), said conversations are happening about how NOAA can containerize its climate models in order to push the models themselves out to the public to understand, build upon and tweak.

The post Edge computing enables NOAA to push workloads closer to public consumers, not just field researchers first appeared on Federal News Network.

CHANDLER, Ariz., Oct. 23, 2024 — The global edge computing market is expected to grow by more than 30 percent in the next five years, serving mission-critical applications in the […]

The post Microchip Expands 64-Bit Portfolio with High-Performance PIC64HX Microprocessors for Edge Computing appeared first on HPCwire.

IEEE Computer Society

Edge computing is the way forward, but are we ready to surrender control to corporations.

Now, any developer could create an app and run it on Amazon, Microsoft or Google’s servers and make millions or billions in the process.

Rescue vessels are the main actors in maritime safety and rescue operations. At the same time, aerial drones bring a significant advantage into this scenario. This paper presents the research directions of the AutoSOS project, where we work in the development of an autonomous multi-robot search and rescue assistance platform capable of sensor fusion and object detection in embedded devices using novel lightweight AI models. The platform is meant to perform reconnaissance missions for initial assessment of the environment using novel adaptive deep learning algorithms that efficiently use the available sensors and computational resources on drones and rescue vessel. When drones find potential objects, they will send their sensor data to the vessel to verity the findings with increased accuracy. The actual rescue and treatment operation are left as the responsibility of the rescue personnel. The drones will autonomously reconfigure their spatial distribution to enable multi-hop communication, when a direct connection between a drone transmitting information and the vessel is unavailable.

In recent years, multi-access edge computing (MEC) is a key enabler for handling the massive expansion of Internet of Things (IoT) applications and services. However, energy consumption of a MEC network depends on volatile tasks that induces risk for energy demand estimations. As an energy supplier, a microgrid can facilitate seamless energy supply. However, the risk associated with energy supply is also increased due to unpredictable energy generation from renewable and non-renewable sources. Especially, the risk of energy shortfall is involved with uncertainties in both energy consumption and generation. In this paper, we study a risk-aware energy scheduling problem for a microgrid-powered MEC network. First, we formulate an optimization problem considering the conditional value-at-risk (CVaR) measurement for both energy consumption and generation, where the objective is to minimize the loss of energy shortfall of the MEC networks and we show this problem is an NP-hard problem. Second, we analyze our formulated problem using a multi-agent stochastic game that ensures the joint policy Nash equilibrium, and show the convergence of the proposed model. Third, we derive the solution by applying a multi-agent deep reinforcement learning (MADRL)-based asynchronous advantage actor-critic (A3C) algorithm with shared neural networks. This method mitigates the curse of dimensionality of the state space and chooses the best policy among the agents for the proposed problem. Finally, the experimental results establish a significant performance gain by considering CVaR for high accuracy energy scheduling of the proposed model than both the single and random agent models.

Yokogawa Electric Corporation (TOKYO: 6841) announces the release of artificial intelligence (AI)-enabled versions of the GX series panel-mount type paperless recorders, GP series portable paperless recorders, and GA10 data logging software, which are components of the highly operable and expandable SMARTDAC+data acquisition and control system. This new AI functionality includes the future pen, a function developed by Yokogawa that enables the drawing of predicted waveforms. Yokogawa is also releasing a new CPU module for the e-RT3 Plus edge computing platform that is environmentally robust and Python compatible. The GX/GP and e-RT3 release is set for April 8, and the GA10 software will be released on May 13. The SMARTDAC+ system is a product in the OpreX Data Acquisition family, and the e-RT3 Plus is part of the OpreX Control Devices family.

Singapore : Springer, c2019.