Fog computing is an architecture that distributes computing, storage, control and networking functions closer to users along the cloud-to-thing continuum compared to traditional cloud computing architectures. It aims to provide a seamless continuum of services from the cloud to end devices. Key differences between fog and edge computing are that fog is more inclusive, seeks to realize a seamless continuum rather than isolated platforms, and envisions a horizontal platform to support multiple industries. Fog computing is expected to enable new commercial opportunities and business models by providing integrated end-to-end services and applications through the convergence of cloud and fog platforms.
Security and Privacy Issues of Fog Computing: A SurveyHarshitParkar6677
Abstract. Fog computing is a promising computing paradigm that ex-
tends cloud computing to the edge of networks. Similar to cloud comput-
ing but with distinct characteristics, fog computing faces new security
and privacy challenges besides those inherited from cloud computing. In
this paper, we have surveyed these challenges and corresponding solu-
tions in a brief manner.
ABSTRACT
Cloud computing promises to significantly change the way we use computers and access and store our personal and business information. With these new computing and communications paradigms arise new data security challenges. Existing data protection mechanisms such as encryption have failed in preventing data theft attacks, especially those perpetrated by an insider to the cloud provider.
For securing user data from such attacks a new paradigm called fog computing can be used. Fog Computing is a paradigm that extends Cloud computing and services to the edge of the network. Similar to Cloud, Fog provides data, compute, storage, and application services to end-users. The motivation of Fog computing lies in a series of real scenarios, such as Smart Grid, smart traffic lights in vehicular networks and software defined network This technique can monitor the user activity to identify the legitimacy and prevent from any unauthorized user access. Here we have discussed this paradigm for preventing misuse of user data and securing information.
CONCLUSION
This proposal of monitoring data access patterns by profiling user behavior to determine if and when a malicious insider illegitimately accesses someone’s documents in a Cloud service. Decoy documents stored in the Cloud alongside the user’s real data also serve as sensors to detect illegitimate access. Once unauthorized data access or exposure is suspected, and later verified, with challenge questions for instance, this inundate the malicious insider with bogus information in order to dilute the user’s real data. Such preventive attacks that rely on disinformation technology could provide unprecedented levels of security in the Cloud and in social networks.
Security and Privacy Issues of Fog Computing: A SurveyHarshitParkar6677
Abstract. Fog computing is a promising computing paradigm that ex-
tends cloud computing to the edge of networks. Similar to cloud comput-
ing but with distinct characteristics, fog computing faces new security
and privacy challenges besides those inherited from cloud computing. In
this paper, we have surveyed these challenges and corresponding solu-
tions in a brief manner.
ABSTRACT
Cloud computing promises to significantly change the way we use computers and access and store our personal and business information. With these new computing and communications paradigms arise new data security challenges. Existing data protection mechanisms such as encryption have failed in preventing data theft attacks, especially those perpetrated by an insider to the cloud provider.
For securing user data from such attacks a new paradigm called fog computing can be used. Fog Computing is a paradigm that extends Cloud computing and services to the edge of the network. Similar to Cloud, Fog provides data, compute, storage, and application services to end-users. The motivation of Fog computing lies in a series of real scenarios, such as Smart Grid, smart traffic lights in vehicular networks and software defined network This technique can monitor the user activity to identify the legitimacy and prevent from any unauthorized user access. Here we have discussed this paradigm for preventing misuse of user data and securing information.
CONCLUSION
This proposal of monitoring data access patterns by profiling user behavior to determine if and when a malicious insider illegitimately accesses someone’s documents in a Cloud service. Decoy documents stored in the Cloud alongside the user’s real data also serve as sensors to detect illegitimate access. Once unauthorized data access or exposure is suspected, and later verified, with challenge questions for instance, this inundate the malicious insider with bogus information in order to dilute the user’s real data. Such preventive attacks that rely on disinformation technology could provide unprecedented levels of security in the Cloud and in social networks.
The term “fog computing” or “edge computing” means that rather than hosting and working from a centralized cloud, fog systems operate on network ends. It is a term for placing some processes and resources at the edge of the cloud, instead of establishing channels for cloud storage and utilization.
Abstract Fog Computing is a paradigm that extends Cloud computing and services to the edge of the network. Similar to Cloud, Fog provides data, compute, storage, and application services to end-users. It is a model in which data, processing and applications are concentrated in devices at the network edge rather than existing almost entirely in the cloud. This document describes the various features of Fog Computing and a case study along with the actual implementation of fog computing in traffic analysis to understand how fog computing is applied to the edge environment. This document also contains the difference between the fog computing and cloud computing. Keywords— Fog Computing, Characteristics of Fog computing, Application of Fog computing, Difference between Cloud computing and Fog Computing.
A Study on Cloud and Fog Computing Security Issues and SolutionsAM Publications
Cloud computing is the significant part of the data world. The security level in cloud is undefined. Fog computing is the new buzz word added to the technical world. And the term Fog was coined by CISCO. The need for Fog computing is security and gets the data more closely to the end-user. Fog Computing is not going to replace the Cloud computing, it will be acting as the intermediate layer for securing the data which is stored inside the cloud. The principal idea of this paper is to provide data safety measures to the Cloud storage through Fog Computing. Fog Computing will be playing the vital role for the future technology. The Internet of Things (IoT) will be using the Fog computing to implement the smart World concept. So, in the future we have to handle huge amount of data and we need to provide the security for the Data. This study gives the security solutions available for the different issues.
Fog computing factory in alliance nearly bovine computing, optimizing the use of this resource. Currently, crush exercise matter is abeyance to the backward, stored and analyzed, limitation which a decision is made and action taken. But this practices isn’t efficient. Utter computing allows computing, honest and action-taking to enter into the picture near IoT belongings and only pushes relevant matter to the cloud. “Fuzz distributes not at all bad quick-wittedness near at the service better accordingly we nub run this torrent of observations,” explains Baker. “So we thus adjustment it newcomer disabuse of uphold data into unalloyed hint go wool-gathering has favour lose concentration gear up gets forwarded up to the cloud. We posterior then heap up it into data warehouses; we bum do predictive analysis.” This beyond to the data-path send away for is enabled by the increased count functionality that manufacturers such as Cisco are building into their edge switches and routers. Fog Computing plays a role. Nonetheless it is a advanced pronunciation, this technology ahead has a designation backing bowels the globe of the modish data centre and the cloud. Bringing details adjust to the user. The middle of facts zoological unbecoming near the unresponsive creates a straightforward convene to cache observations or other help. These services would be located actual to the end-user to proceed on latency concerns and data access. Rather than of conformation inform at data centre sites anent outlandish the end-point, the Fuzz aims to place the data close to the end-user. Creating purblind geographical distribution. Fogginess computing extends forthright clouded advice by creating a help network which sits at numerous points. This, screen, geographically verbose infrastructure helps in numerous ways. Foremost of enclosing, chunky details and analytics arise be unalloyed faster with better results. Gifted-bodied, administrators are able to on ice location-based
Fog Computing Reality Check: Real World Applications and ArchitecturesBiren Gandhi
Is Fog Computing just a buzz or a real business?
The IoT is flooded with a variety of platforms and solutions. Fog Computing has been notably appearing as an evolving term in the context of IoT software. There is skepticism that Fog Computing is just another buzzword destined to disappear in the dust of time. Get insight from concrete business cases in a variety of IoT verticals – Agriculture, Industrial Manufacturing, Transportation, Smart & Connected Communities etc. and learn how Fog Computing can play a substantial role in each one of these verticals. Develop a judicious point of view with respect to the future of Fog Computing through market research, technology disruption vectors and ROI use cases presented in this session.
ABSTRACT
Cloud computing promises to significantly change the way we use computers and access and store our personal and business information. With these new computing and communications paradigms arise new data security challenges. Existing data protection mechanisms such as encryption have failed in preventing data theft attacks, especially those perpetrated by an insider to the cloud provider. For securing user data from such attacks a new paradigm called fog computing can be used. Fog Computing is a paradigm that extends Cloud computing and services to the edge of the network. Similar to Cloud, Fog provides data, compute, storage, and application services to end-users. The motivation of Fog computing lies in a series of real scenarios, such as Smart Grid, smart traffic lights in vehicular networks and software defined network .This technique can monitor the user activity to identify the legitimacy and prevent from any unauthorized user access. Here we have discussed this paradigm for preventing misuse of user data and securing information.
Fog computing has emerged as a new paradigm for architecting IoT applications that require greater scalability, performance and security. This talk will motivate the need to Fog Computing and explain what it is and how it differs from other initiatives in Telco such as Mobile/Multiple-Access Edge Computing.
An increasing number of Consumer and Internet Internet of Things applications require some form of edge computing characterised by low latency, peer-to-peer communication, and mobility. Fog computing has recently emerged as the paradigm to address the needs of edge computing in IoT applications. Fog computing complements Cloud computing to allow the design and implementation of IoT systems that scale better, are more reactive and in which local communication and decision is enabled whenever possible.
This presentation introduces the key concepts behind Fog Computing, compare and contrast it with Cloud Computing and explain how the VORTEX platform enables Fog computing architectures.
Fog Computing is a paradigm that complements and extends cloud computing by providing an end-to-end virtualisation of computing, storage and communication resources. As such, fog computing allow applications to be transparently provisioned and managed end-to-end. This presentation first motivates the need for fog computing, then introduced fog05 the first and only Open Source fog computing platform!
Fog Computing – between IoT Devices and The Cloud presentation covers following topics:
- Edge, Fog, Mist & Cloud Computing
- Fog domains and fog federation, wireless sensor networks, - multi-layer IoT architecture
- Fog computing standards and specifications
- Practical use-case scenarios & advantages of fog
- Fog analytics and intelligence on the edge
- Technologies for distributed asynchronous event processing - and analytics in real time
- Lambda architecture – Spark, Storm, Kafka, Apex, Beam, Spring - Reactor & WebFlux
- Eclipse IoT platform
All the details of Fog Computing is discussed in this PPT, its better to get knowledge about this ppt,All the details of applications and examples are covered..
The term “fog computing” or “edge computing” means that rather than hosting and working from a centralized cloud, fog systems operate on network ends. It is a term for placing some processes and resources at the edge of the cloud, instead of establishing channels for cloud storage and utilization.
Abstract Fog Computing is a paradigm that extends Cloud computing and services to the edge of the network. Similar to Cloud, Fog provides data, compute, storage, and application services to end-users. It is a model in which data, processing and applications are concentrated in devices at the network edge rather than existing almost entirely in the cloud. This document describes the various features of Fog Computing and a case study along with the actual implementation of fog computing in traffic analysis to understand how fog computing is applied to the edge environment. This document also contains the difference between the fog computing and cloud computing. Keywords— Fog Computing, Characteristics of Fog computing, Application of Fog computing, Difference between Cloud computing and Fog Computing.
A Study on Cloud and Fog Computing Security Issues and SolutionsAM Publications
Cloud computing is the significant part of the data world. The security level in cloud is undefined. Fog computing is the new buzz word added to the technical world. And the term Fog was coined by CISCO. The need for Fog computing is security and gets the data more closely to the end-user. Fog Computing is not going to replace the Cloud computing, it will be acting as the intermediate layer for securing the data which is stored inside the cloud. The principal idea of this paper is to provide data safety measures to the Cloud storage through Fog Computing. Fog Computing will be playing the vital role for the future technology. The Internet of Things (IoT) will be using the Fog computing to implement the smart World concept. So, in the future we have to handle huge amount of data and we need to provide the security for the Data. This study gives the security solutions available for the different issues.
Fog computing factory in alliance nearly bovine computing, optimizing the use of this resource. Currently, crush exercise matter is abeyance to the backward, stored and analyzed, limitation which a decision is made and action taken. But this practices isn’t efficient. Utter computing allows computing, honest and action-taking to enter into the picture near IoT belongings and only pushes relevant matter to the cloud. “Fuzz distributes not at all bad quick-wittedness near at the service better accordingly we nub run this torrent of observations,” explains Baker. “So we thus adjustment it newcomer disabuse of uphold data into unalloyed hint go wool-gathering has favour lose concentration gear up gets forwarded up to the cloud. We posterior then heap up it into data warehouses; we bum do predictive analysis.” This beyond to the data-path send away for is enabled by the increased count functionality that manufacturers such as Cisco are building into their edge switches and routers. Fog Computing plays a role. Nonetheless it is a advanced pronunciation, this technology ahead has a designation backing bowels the globe of the modish data centre and the cloud. Bringing details adjust to the user. The middle of facts zoological unbecoming near the unresponsive creates a straightforward convene to cache observations or other help. These services would be located actual to the end-user to proceed on latency concerns and data access. Rather than of conformation inform at data centre sites anent outlandish the end-point, the Fuzz aims to place the data close to the end-user. Creating purblind geographical distribution. Fogginess computing extends forthright clouded advice by creating a help network which sits at numerous points. This, screen, geographically verbose infrastructure helps in numerous ways. Foremost of enclosing, chunky details and analytics arise be unalloyed faster with better results. Gifted-bodied, administrators are able to on ice location-based
Fog Computing Reality Check: Real World Applications and ArchitecturesBiren Gandhi
Is Fog Computing just a buzz or a real business?
The IoT is flooded with a variety of platforms and solutions. Fog Computing has been notably appearing as an evolving term in the context of IoT software. There is skepticism that Fog Computing is just another buzzword destined to disappear in the dust of time. Get insight from concrete business cases in a variety of IoT verticals – Agriculture, Industrial Manufacturing, Transportation, Smart & Connected Communities etc. and learn how Fog Computing can play a substantial role in each one of these verticals. Develop a judicious point of view with respect to the future of Fog Computing through market research, technology disruption vectors and ROI use cases presented in this session.
ABSTRACT
Cloud computing promises to significantly change the way we use computers and access and store our personal and business information. With these new computing and communications paradigms arise new data security challenges. Existing data protection mechanisms such as encryption have failed in preventing data theft attacks, especially those perpetrated by an insider to the cloud provider. For securing user data from such attacks a new paradigm called fog computing can be used. Fog Computing is a paradigm that extends Cloud computing and services to the edge of the network. Similar to Cloud, Fog provides data, compute, storage, and application services to end-users. The motivation of Fog computing lies in a series of real scenarios, such as Smart Grid, smart traffic lights in vehicular networks and software defined network .This technique can monitor the user activity to identify the legitimacy and prevent from any unauthorized user access. Here we have discussed this paradigm for preventing misuse of user data and securing information.
Fog computing has emerged as a new paradigm for architecting IoT applications that require greater scalability, performance and security. This talk will motivate the need to Fog Computing and explain what it is and how it differs from other initiatives in Telco such as Mobile/Multiple-Access Edge Computing.
An increasing number of Consumer and Internet Internet of Things applications require some form of edge computing characterised by low latency, peer-to-peer communication, and mobility. Fog computing has recently emerged as the paradigm to address the needs of edge computing in IoT applications. Fog computing complements Cloud computing to allow the design and implementation of IoT systems that scale better, are more reactive and in which local communication and decision is enabled whenever possible.
This presentation introduces the key concepts behind Fog Computing, compare and contrast it with Cloud Computing and explain how the VORTEX platform enables Fog computing architectures.
Fog Computing is a paradigm that complements and extends cloud computing by providing an end-to-end virtualisation of computing, storage and communication resources. As such, fog computing allow applications to be transparently provisioned and managed end-to-end. This presentation first motivates the need for fog computing, then introduced fog05 the first and only Open Source fog computing platform!
Fog Computing – between IoT Devices and The Cloud presentation covers following topics:
- Edge, Fog, Mist & Cloud Computing
- Fog domains and fog federation, wireless sensor networks, - multi-layer IoT architecture
- Fog computing standards and specifications
- Practical use-case scenarios & advantages of fog
- Fog analytics and intelligence on the edge
- Technologies for distributed asynchronous event processing - and analytics in real time
- Lambda architecture – Spark, Storm, Kafka, Apex, Beam, Spring - Reactor & WebFlux
- Eclipse IoT platform
All the details of Fog Computing is discussed in this PPT, its better to get knowledge about this ppt,All the details of applications and examples are covered..
Fog computing is defined as a decentralized infrastructure that places storage and processing components at the edge of the cloud, where data sources such as application users and sensors exist.It is an architecture that uses edge devices to carry out a substantial amount of computation (edge computing), storage, and communication locally and routed over the Internet backbone.To achieve real-time automation, data capture and analysis has to be done in real-time without having to deal with the high latency and low bandwidth issues that occur during the processing of network data In 2012, Cisco introduced the term fog computing for dispersed cloud infrastructures.. In 2015, Cisco partnered with Microsoft, Dell, Intel, Arm and Princeton University to form the OpenFog Consortium.The consortium's primary goals were to both promote and standardize fog computing. These concepts brought computing resources closer to data sources.Fog computing also differentiates between relevant and irrelevant data. While relevant data is sent to the cloud for storage, irrelevant data is either deleted or transmitted to the appropriate local platform. As such, edge computing and fog computing work in unison to minimize latency and maximize the efficiency associated with cloud-enabled enterprise systemsFog computing consists of various componets such as fog nodes.Fog nodes are independent devices that pick up the generated information. Fog nodes fall under three categories: fog devices, fog servers, and gateways. These devices store necessary data while fog servers also compute this data to decide the course of action. Fog devices are usually linked to fog servers. Fog gateways redirect the information between the various fog devices and servers. With Fog computing, local data storage and scrutiny of time-sensitive data become easier. With this the amount and the distance of passing data to the cloud is reduced, therefore reducing the security challenges.Fog computing enables data processing based on application demands, available networking and computing resources. This reduces the amount of data required to be transferred to the cloud, ultimately saving network bandwidth.Fog computing can run independently and ensure uninterrupted services even with fluctuating network connectivity to the cloud. It performs all time-sensitive actions close to end users which meets latency constraints of IoT applications.
IoT applications where data is generated in terabytes or more, where a quick and large amount of data processing is required and sending data to the cloud back and forth is not feasible, are good candidates for fog computing. Fog computing provides real-time processing and event responses which are critical in healthcare. Besides, it also addresses issues regarding network connectivity and traffic required for remote storage, processing and medical record retrieval from the cloud.
A Comparison of Cloud Execution Mechanisms Fog, Edge, and Clone Cloud Computing IJECEIAES
Cloud computing is a technology that was developed a decade ago to provide uninterrupted, scalable services to users and organizations. Cloud computing has also become an attractive feature for mobile users due to the limited features of mobile devices. The combination of cloud technologies with mobile technologies resulted in a new area of computing called mobile cloud computing. This combined technology is used to augment the resources existing in Smart devices. In recent times, Fog computing, Edge computing, and Clone Cloud computing techniques have become the latest trends after mobile cloud computing, which have all been developed to address the limitations in cloud computing. This paper reviews these recent technologies in detail and provides a comparative study of them. It also addresses the differences in these technologies and how each of them is effective for organizations and developers.
Fog Computing and Its Role in the Internet of ThingsHarshitParkar6677
Fog Computing extends the Cloud Computing paradigm to
the edge of the network, thus enabling a new breed of applications
and services. Dening characteristics of the Fog
are: a) Low latency and location awareness; b) Wide-spread
geographical distribution; c) Mobility; d) Very large number
of nodes, e) Predominant role of wireless access, f) Strong
presence of streaming and real time applications, g) Heterogeneity.
In this paper we argue that the above characteristics
make the Fog the appropriate platform for a number
of critical Internet of Things (IoT) services and applications,
namely, Connected Vehicle, Smart Grid , Smart
Cities, and, in general, Wireless Sensors and Actuators Networks
(WSANs).
The practice of using a network of remote servers hosted on the Internet to store, manage, and process data, rather than a local server or a personal computer.
A review on orchestration distributed systems for IoT smart services in fog c...IJECEIAES
This paper provides a review of orchestration distributed systems for IoT smart services in fog computing. The cloud infrastructure alone cannot handle the flow of information with the abundance of data, devices and interactions. Thus, fog computing becomes a new paradigm to overcome the problem. One of the first challenges was to build the orchestration systems to activate the clouds and to execute tasks throughout the whole system that has to be considered to the situation in the large scale of geographical distance, heterogeneity and low latency to support the limitation of cloud computing. Some problems exist for orchestration distributed in fog computing are to fulfil with high reliability and low-delay requirements in the IoT applications system and to form a larger computer network like a fog network, at different geographic sites. This paper reviewed approximately 68 articles on orchestration distributed system for fog computing. The result shows the orchestration distribute system and some of the evaluation criteria for fog computing that have been compared in terms of Borg, Kubernetes, Swarm, Mesos, Aurora, heterogeneity, QoS management, scalability, mobility, federation, and interoperability. The significance of this study is to support the researcher in developing orchestration distributed systems for IoT smart services in fog computing focus on IR4.0 national agenda.
Fog computing is a model in which data, processing and applications are concentrated in devices at the network edge rather than existing almost entirely in the cloud.
Fog Computing is a paradigm that extends Cloud Computing and services to the edge of the network, similar to Cloud, Fog provides data, compute, storage, and application services to end-users.
Mobile Fog: A Programming Model for Large–Scale Applications on the Internet ...HarshitParkar6677
creating a new environment, namely the Internet of Things
(IoT), that enables a wide range of future Internet applications.
In this work, we present Mobile Fog, a high level
programming model for future Internet applications that are
geospatially distributed, large–scale, and latency–sensitive.
We analyze use cases for the programming model with camera
network and connected vehicle applications to show the
efficacy of Mobile Fog. We also evaluate application performance
through simulation.
Fog computing or fog networking, also known as fogging, is an architecture that uses edge devices to carry out a substantial amount of computation, storage, and communication locally and routed over the internet backbone.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
"Impact of front-end architecture on development cost", Viktor TurskyiFwdays
I have heard many times that architecture is not important for the front-end. Also, many times I have seen how developers implement features on the front-end just following the standard rules for a framework and think that this is enough to successfully launch the project, and then the project fails. How to prevent this and what approach to choose? I have launched dozens of complex projects and during the talk we will analyze which approaches have worked for me and which have not.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Search and Society: Reimagining Information Access for Radical FuturesBhaskar Mitra
The field of Information retrieval (IR) is currently undergoing a transformative shift, at least partly due to the emerging applications of generative AI to information access. In this talk, we will deliberate on the sociotechnical implications of generative AI for information access. We will argue that there is both a critical necessity and an exciting opportunity for the IR community to re-center our research agendas on societal needs while dismantling the artificial separation between the work on fairness, accountability, transparency, and ethics in IR and the rest of IR research. Instead of adopting a reactionary strategy of trying to mitigate potential social harms from emerging technologies, the community should aim to proactively set the research agenda for the kinds of systems we should build inspired by diverse explicitly stated sociotechnical imaginaries. The sociotechnical imaginaries that underpin the design and development of information access technologies needs to be explicitly articulated, and we need to develop theories of change in context of these diverse perspectives. Our guiding future imaginaries must be informed by other academic fields, such as democratic theory and critical theory, and should be co-developed with social science scholars, legal scholars, civil rights and social justice activists, and artists, among others.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
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GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Clarifying fog computing and networking 10 questions and answers
1. IEEE Communications Magazine • April 201718
Tutorial
1. What Is Fog Computing and How Is It Different
from Edge Computing?
Fog computing is an end-to-end horizontal architecture that dis-
tributes computing, storage, control, and networking functions
closer to users along the cloud-to-thing continuum.
The word “edge” may carry different meanings. A common
usage of the term refers to the edge network as opposed to
the core network, with equipment such as edge routers, base
stations, and home gateways. In that sense, there are several
differences between fog and edge.
First, fog is inclusive of cloud, core, metro, edge, clients, and
things. The fog architecture will further enable pooling, orches-
trating, managing, and securing the resources and functions
distributed in the cloud, anywhere along the cloud-to-thing
continuum, and on the things to support end-to-end services
and applications. Second, fog seeks to realize a seamless con-
tinuum of computing services from the cloud to the things
rather than treating the network edges as isolated computing
platforms. Third, fog envisions a horizontal platform that will
support the common fog computing functions for multiple
industries and application domains, including but not limited
to traditional telco services. Fourth, a dominant part of edge
is mobile edge, whereas the fog computing architecture will
be flexible enough to work over wireline as well as wireless
networks.
2. Is Fog Just a Smaller Cloud?
First, the size of the fog is flexible — it can range from a sin-
gle small fog node to large fog systems comparable to existing
clouds, depending on the application needs.
While fog will bring many cloud-like services closer to end
users and can have smaller footprints than the cloud, it has
a different vision from that of smaller or mini-clouds. Mini-
clouds tend to be designed as isolated computing platforms.
Fog envisions a seamlessly integrated cloud-fog-thing architec-
ture to enable computing anywhere along the cloud-to-things
continuum. Fog-to-cloud and fog-to-fog interactions will there-
fore be a focus of an end-to-end fog computing architecture
to distribute computing functions, and then manage, pool,
orchestrate, and secure the distributed resources and func-
tions. Fog may form a hierarchical architecture between the
cloud and the things, with fog nodes at different architectural
levels collaborating with each other to support end-to-end
applications.
Fog also concerns the control of cyber-physical systems and
D2D communication, in addition to computation and storage in
clouds, big or small.
3. Is Fog Equivalent to IoT?
Fog is an architecture. The Internet of Things (IoT) often refers
to a set of services and applications.
An architecture decides the allocation of functionalities. It
formulates and answers questions such as “who does what, and
at what timescale and location?” An architecture supports many
applications, some in existence today and others more futuristic.
For example, TCP/IP represents an Internet architecture. It
includes several key principles, such as addressing, and alloca-
tion of functionalities, such as congestion-independent, hop-
by-hop routing, and congestion-dependent, end-to-end session
control. Applications that leverage TCP/IP have come from a
wide and increasing range: from the web to emails and from
P2P to video streaming.
The relationship between fog and IoT is similar to that
between the Internet architecture and the web applications. Fog
also supports other areas of applications, such as those in fifth
generation (5G) cellular or embedded artificial intelligence.
4. Is Fog for Computation, or Communication, or
Control?
Fog is an umbrella term that includes an architecture for com-
putation, an architecture for communication, an architecture for
storage, and an architecture for control (both control of the
network itself and networked control in cyber-physical systems).
For example, fog computing explores new ways to decom-
pose a computational task so as to match an underlying compu-
tation substrate that is heterogeneous (in hardware and software
capabilities), volatile (in availability, mobility, and security), and
constrained (by bandwidth or battery). Fog communication
explores how devices may talk to each other despite intermit-
tent global connectivity. Fog control explores how clients might
crowd-sense network conditions and self-configure, and how to
leverage small and almost deterministic latency to enable feed-
back control loops.
5. What Are the Unique Advantages Offered by Fog?
Unique advantages that are potentially offered by fog can be
summarized with an acronym: “SCALE.” These advantages in
turn enable new services and business models, and may help
broaden revenues, reduce cost, or accelerate product rollouts.
Security: While fog faces unique security challenges, it also
offers certain advantages. In particular, by reducing the distance
that information needs to traverse, there is less chance of eaves-
dropping. By leveraging proximity-based authentication challeng-
es, identity verification can be strengthened.
Cognition: Awareness of client-centric objectives. A fog
architecture, aware of customer requirements, can best deter-
mine where to carry out the computing, storage, and control
functions along the cloud-to-thing continuum. Fog applications,
being close to the end users, can be built to be better aware of
and closely reflect customer requirements.
Agility: Rapid innovation and affordable scaling. It is usually
much faster and cheaper to experiment with client and edge
devices rather than waiting for vendors of large network and
cloud boxes to initiate or adopt an innovation. Fog will make it
easier to create an open marketplace for individuals and small
teams to use open application programming interfaces (APIs),
open software development kits (SDKs), and the proliferation of
mobile devices to innovate, develop, deploy, and operate new
services.
Latency: Real-time processing and cyber-physical system con-
trol. Fog enables data analytics at the network edge and can
support time-sensitive control functions for local cyber-physical
systems. This is essential for not only commercial applications but
also for the Tactile Internet vision to enable embedded AI applica-
tions with millisecond reaction times.
Efficiency: Pooling resources along the cloud-to-thing con-
tinuum. Fog can distribute computing, storage, and control
functions anywhere between the cloud and the endpoint to
take full advantage of the resources available along this con-
tinuum. It can also allow applications to leverage otherwise
idle computing, storage, and networking resources abundantly
available on network edge and end-user devices such as tab-
lets, laptops, smart home appliances, connected vehicles and
trains, and network edge routers. Fog’s closer proximity to
the endpoints will enable it to be more closely integrated with
end-user systems to enhance overall system efficiency and per-
Clarifying Fog Computing and Networking: 10 Questions and Answers
By Mung Chiang, Sangtae Ha, Chih-Lin I, Fulvio Risso, and Tao Zhang
2. IEEE Communications Magazine • April 2017 19
Tutorial
formance. This is especially important for performance-critical
cyber-physical systems.
6. Is Fog Good or Bad for Security and Privacy?
Fog systems and applications will often be distributed and oper-
ated remotely. Some fog systems can also be resource-con-
strained. Compared to centralized clouds, such distributed,
remote, and resource-constrained fog systems pose additional
security challenges often encountered in distributed systems.
On the other hand, fog can bring more processing resources
closer to the endpoints to help better protect the vast popu-
lation of diverse endpoints that often do not have sufficient
resources to adequately protect themselves. In other words,
fog systems can provide a wide range of local security services
to make the IoT as a whole more secure. For example, fog
systems can perform local security monitoring, local threat
detection, and local threat protection functions on behalf of
the endpoints. Fog nodes can also serve as proxies of the end-
points to help manage and update the security credentials and
software on the endpoints, eliminating the often impractical
needs for all the endpoints to directly communicate with the
remote cloud for such functions.
7. Will the Need for Fog Diminish as Network
Capacity and Delay Improve over Time?
While it is true that a primary benefit of fog computing is its abil-
ity to reduce latency and delay, the drivers for fog go far beyond
pure latency issues to include a variety of operational, regulato-
ry, business, and reliability issues.
For example, instead of the traditional way of adding new
applications by adding dedicated new local servers and network-
ing gear, fog can provide a common end-to-end platform for all
services provided to each customer. This can provide a unified
platform to support life cycle management, networking, and
security for all applications, which will reduce system complexity
and costs and also allow applications from different providers to
better interact with each other rather than stay siloed on their
dedicated hardware and software platforms. Fog can enable crit-
ical services to be operated autonomously or managed from the
cloud, the perimeter, or a variety of points in the network. Fog is
equally advantageous for areas where network connectivity can
be unreliable due to weather or other conditions. It can also sig-
nificantly reduce network bandwidth loads through its proximity
to where the data is generated. With fog, local operational and
business policies can be applied to enable more efficient local
data processing and analytics on premises.
As another example in cellular networks, cloud RAN, with
centralized or distributed network architecture, has the advan-
tage of being physically close to the end users and the capabili-
ty of utilizing the network resources at the edge. Consequently,
the cloud radio access network (C-RAN) will be an integral part
of the solution to meet stringent network delay requirements
that the traditional RAN network may fail to meet. Consequent-
ly, the Third Generation Partnership Project (3GPP) is now dis-
cussing a RAN architecture that contains both the central units
and the distributed units. Extending prior notions in C-RAN, fog
network is unique in the sense that the end user computing
and storage resource is considered as an integral part of the
whole network, by forming ad hoc subnets among end nodes.
Careful exploitation of such features will bring unique values
for fog networks.
8. What New Technologies and Standards, If Any,
Do We Need to Develop for Fog?
Fog systems will need to interact with each other, with the
clouds, and with a diverse range of user end devices. Therefore,
the success and wide adoption of fog computing will rely on
standards. While fog computing can benefit from many existing
standards, new standards may also be required, for example, in
the following areas:
Building unified fog-cloud platforms: Interfaces and pro-
tocols for the fog and the cloud to interact with each other
to enable unified cloud-fog service platform and applications,
move computing functions and applications between the
cloud and the fog, pool resources distributed in the cloud
and the fog, and manage the life cycle of the fog systems and
applications.
Support distributed and hierarchical fog systems over possi-
bly heterogeneous, volatile, and constrained physical resourc-
es: interfaces and protocols for different hierarchical levels in
a fog system to interact with each other, and for different fog
systems at the same hierarchical level to collaborate with each
other to serve as each other’s backup.
Access to fog services: A fog system, bringing resources
closer to end users, can enable a wide range of new fog-based
services. Standards will be required for users and their devices to
interact with the fog system to discover, request, and receive fog
services. So will automatic and lightweight bidding mechanisms
for access to fog resources and services to reinforce the eco-
nomic sustainability of the fog computing model, and enabling
economic transactions.
Data management: Local processing and management of
data is one of the important drivers for fog computing. Data,
however, comes from an increasingly wide range of sources.
Data management also imposes widely diverse requirements
from industry to industry. New standards may be required to
manage the diverse data, such as storing, accessing, and secur-
ing the data distributed in the fog and cloud.
Security and privacy: A distributed and remotely oper-
ated fog system can pose new security challenges not
present in centralized systems. Addressing these new
challenges may require new standards. For example, fog
computing will need to run a diverse set of local hardware
platforms. Therefore, new interfaces may be required for
fog software to interact with the various hardware plat-
forms, which may be provided by different vendors, to
ensure a trusted computing environment. New interfaces
and protocols may be required for automatic detection
of security compromises in a distributed and remote fog
system, and also for remote and automatic responses to
security compromises.
Furthermore, although standards may exist for some fog com-
puting needs, additional requirements in fog computing environ-
ments (e.g., low-latency, large number of resource-constrained
devices) may necessitate new standards that are more suitable
for fog computing environments.
9. What New Research Challenges Do We Have to
Address to Enable Fog?
Research challenges in fog span a wide range: from compu-
tation decomposition over heterogeneous and constrained
nodes to cloud-fog interface definition, from state consisten-
cy in dispersive computing to elastic storage over volatile
substrate, from pricing for economic incentives to scalable
security measures. Fundamental to these topics is the intrinsic
trade-off between “local” and “global” and between “brick”
and “click” as we slide between cloud and things in decid-
ing where to allocate a function and how to glue them back
together.
For example, fog computing enables a complex service
to possibly be delivered through a set of elementary soft-
ware elements that operate on heterogeneous nodes, such
as end user terminals and local servers, but also network ele-
ments and data centers. The problem of the orchestration of
3. 20 IEEE Communications Magazine • April 2017
Tutorial
the above complex services is definitely an important chal-
lenge, complicated by the highly dynamic environment, the
many fog-enabled applications installed on end user devices
and things, and the necessity to support different adminis-
trative domains, to adapt the service to the extreme hetero-
geneity of the infrastructure, and to adapt the service (and
the orchestration algorithms) to the external environment.
For instance, fog applications cannot always count on the
availability of powerful computing devices that can execute
complex orchestration algorithms; in critical conditions (e.g.,
broken infrastructure as in the case of an earthquake), the fog
infrastructure has to be able to orchestrate services even in
the presence of limited computing capabilities, with an intrin-
sic degree of resiliency. Along this line, another important
challenge is the capability to create self-adapting applications,
which are able to automatically adapt their behavior based
on the surrounding environment, for example, in case some
required services (e.g., high-capacity storage or a high-pre-
cision sensor) cannot be reached, while still being able to
deliver the service the user is expecting, albeit with some
degradation.
10. What Commercial Opportunities Will Fog Bring?
Fog computing will bring many new commercial opportunities and
will disrupt the existing industry landscapes and business models,
disrupting the balance of power along the industry food chain.
For example, networking functions (e.g., routing and switch-
ing), application servers, and storage functions are already con-
verging into integrated “fog nodes”: edge devices that integrate
edge router and local application server and storage functions
are already commercially available. The emerging fog systems
will empower the cloud to do what it cannot effectively do
today by, for example, acting as proxies to connect and then
provide cloud services to the many devices that cannot be prac-
tically connected to the cloud directly. A growing range of inno-
vative fog-based services, including fog systems and services as
a service, will emerge. The cloud and the fog will converge into
unified end-to-end platforms and provide integrated services and
applications, creating opportunities for fundamental disruptions
to the existing cloud computing business models. Players of all
sizes will be able to deploy fog systems and operate fog ser-
vices. And the list goes on.