CoMoT is a platform-as-a-service that provides tools for programming, deploying, controlling, monitoring, and testing elasticity in cloud systems. It introduces concepts of elastic objects and fundamental building blocks for engineering multi-dimensional elasticity. CoMoT's tools include programming elastic services using enriched OCCI and TOSCA, deploying and controlling elasticity based on requirements, monitoring elasticity using metrics, and testing elastic properties. The platform aims to provide native support for elasticity across all phases of cloud service engineering.
The presentation from a MSc seminar course at the University of Cyprus, on cloud computing, elasticity and the research interests of the CELAR project (http://www.celarcloud.eu).
CELAR Components Featured
=======================
- Cloud Application Management Framework (CAMF)
- JCatascopia Cloud Monitoring Framework
- ADVISE Cloud Elasticity Evalaution Framework
SYBL: An extensible language for elasticity specifications in cloud applicati...Georgiana Copil
Presentation given at CCGRID, May 2013
Abstract: Elasticity in cloud computing is a complex problem, regarding not only resource elasticity but also quality and cost elasticity, and most importantly, the relations among the three. Therefore, existing support for controlling elasticity in complex applications, focusing solely on resource scaling, is not adequate. In this paper we present SYBL - a novel language for controlling elasticity in cloud applications - and its runtime system. SYBL allows specifying in detail elasticity monitoring, constraints, and strategies at different levels of cloud applications, including the whole application, application component, and within application component code. Based on simple SYBL elasticity directives, our runtime system will perform complex elasticity controls for the client, by leveraging underlying cloud monitoring and resource management APIs. We also present a prototype implementation and experiments illustrating how SYBL can be used in real-world scenarios.
Pets vs. Cattle: The Elastic Cloud StoryRandy Bias
My recent presentation to the Chicago DevOps Meetup that explains how we're moving from a servers as Pets world to a servers as Cattle world. Understanding this change is critical to success in cloud, DevOps, and delivering new value to the enterprise.
Modeling and Provisioning IoT Cloud Systems for Testing UncertaintiesHong-Linh Truong
Modern Cyber-Physical Systems (CPS) and Internet of Things (IoT)
systems consist of both loosely and tightly interactions among
various resources in IoT networks, edge servers and cloud data
centers. These elements are being built atop virtualization layers
and deployed in both edge and cloud infrastructures. They also deal
with a lot of data through the interconnection of different types of
networks and services. Therefore, several new types of uncertainties
are emerging, such as data, actuation, and elasticity uncertainties.
This triggers several challenges for testing uncertainty in such
systems. However, there is a lack of novel ways to model and
prepare the right infrastructural elements covering requirements
for testing emerging uncertainties. In this paper, first we present
techniques for modeling CPS/IoT Systems and their uncertainties
to be tested. Second, we introduce techniques for determining and
generating deployment configuration for testing in different IoT
and cloud infrastructures. We illustrate our work with a real-world
use case for monitoring and analysis of Base Transceiver Stations.
.NET Application Modernization with PAS and Azure DevOpsVMware Tanzu
SpringOne Platform 2019
.NET Application Modernization with PAS and Azure DevOps
Speakers: Shawn Neal, Principal Solutions Architect, Pivotal and Jason Stevens, Senior Software Engineer, Microsoft
YouTube: https://youtu.be/ehGojYVLzlI
The presentation from a MSc seminar course at the University of Cyprus, on cloud computing, elasticity and the research interests of the CELAR project (http://www.celarcloud.eu).
CELAR Components Featured
=======================
- Cloud Application Management Framework (CAMF)
- JCatascopia Cloud Monitoring Framework
- ADVISE Cloud Elasticity Evalaution Framework
SYBL: An extensible language for elasticity specifications in cloud applicati...Georgiana Copil
Presentation given at CCGRID, May 2013
Abstract: Elasticity in cloud computing is a complex problem, regarding not only resource elasticity but also quality and cost elasticity, and most importantly, the relations among the three. Therefore, existing support for controlling elasticity in complex applications, focusing solely on resource scaling, is not adequate. In this paper we present SYBL - a novel language for controlling elasticity in cloud applications - and its runtime system. SYBL allows specifying in detail elasticity monitoring, constraints, and strategies at different levels of cloud applications, including the whole application, application component, and within application component code. Based on simple SYBL elasticity directives, our runtime system will perform complex elasticity controls for the client, by leveraging underlying cloud monitoring and resource management APIs. We also present a prototype implementation and experiments illustrating how SYBL can be used in real-world scenarios.
Pets vs. Cattle: The Elastic Cloud StoryRandy Bias
My recent presentation to the Chicago DevOps Meetup that explains how we're moving from a servers as Pets world to a servers as Cattle world. Understanding this change is critical to success in cloud, DevOps, and delivering new value to the enterprise.
Modeling and Provisioning IoT Cloud Systems for Testing UncertaintiesHong-Linh Truong
Modern Cyber-Physical Systems (CPS) and Internet of Things (IoT)
systems consist of both loosely and tightly interactions among
various resources in IoT networks, edge servers and cloud data
centers. These elements are being built atop virtualization layers
and deployed in both edge and cloud infrastructures. They also deal
with a lot of data through the interconnection of different types of
networks and services. Therefore, several new types of uncertainties
are emerging, such as data, actuation, and elasticity uncertainties.
This triggers several challenges for testing uncertainty in such
systems. However, there is a lack of novel ways to model and
prepare the right infrastructural elements covering requirements
for testing emerging uncertainties. In this paper, first we present
techniques for modeling CPS/IoT Systems and their uncertainties
to be tested. Second, we introduce techniques for determining and
generating deployment configuration for testing in different IoT
and cloud infrastructures. We illustrate our work with a real-world
use case for monitoring and analysis of Base Transceiver Stations.
.NET Application Modernization with PAS and Azure DevOpsVMware Tanzu
SpringOne Platform 2019
.NET Application Modernization with PAS and Azure DevOps
Speakers: Shawn Neal, Principal Solutions Architect, Pivotal and Jason Stevens, Senior Software Engineer, Microsoft
YouTube: https://youtu.be/ehGojYVLzlI
JDD2015: Sustainability Supporting Data Variability: Keeping Core Components ...PROIDEA
SUSTAINABILITY SUPPORTING DATA VARIABILITY: KEEPING CORE COMPONENTS CLEAN WHILE DEALING WITH DATA VARIABILITY
A big challenge in building complex, data-intensive systems is how to sustainably support data variation, schema, and feature evolution. This talk examines strategies, practices, and patterns drawn from real experiences that support new and evolving data-processing requirements while keeping the core architecture clean. As complex systems evolve to meet varying data formats, they can devolve into poorly architected Big Balls of Mud filled with special-case logic and one-off processing. Alternatively, you can isolate core components of your system and protect them from entanglements and unnecessary complexity by designing them to operate on common data formats while providing extension mechanisms that enable processing variations.
JDD2015: Sustainability Supporting Data Variability: Keeping Core Components ...PROIDEA
SUSTAINABILITY SUPPORTING DATA VARIABILITY: KEEPING CORE COMPONENTS CLEAN WHILE DEALING WITH DATA VARIABILITY
A big challenge in building complex, data-intensive systems is how to sustainably support data variation, schema, and feature evolution. This talk examines strategies, practices, and patterns drawn from real experiences that support new and evolving data-processing requirements while keeping the core architecture clean. As complex systems evolve to meet varying data formats, they can devolve into poorly architected Big Balls of Mud filled with special-case logic and one-off processing. Alternatively, you can isolate core components of your system and protect them from entanglements and unnecessary complexity by designing them to operate on common data formats while providing extension mechanisms that enable processing variations.
Enabling Production Grade Containerized Applications through Policy Based Inf...Docker, Inc.
This session covers the solution addressing the needs of enabling product-grade containerized applications. You will learn how operations teams running containerized applications in a shared infrastructure can define and enforce policies to provide security, monitoring, and performance for network, storage, and computing. You will learn about Contiv and Mantl, open source projects that create a framework for cloud native application development and infrastructure with application intent and operational policies. Contiv integrates Cisco infrastructure (UCS, Nexus, and ACI) with Docker Datacenter to help enterprises adopt containers at a larger scale.
On Engineering Analytics of Elastic IoT Cloud SystemsHong-Linh Truong
Developing IoT cloud platforms is very challenging, as IoT
cloud platforms consist of a mix of cloud services and IoT elements, e.g.,
for sensor management, near-realtime events handling, and data analyt-
ics. Developers need several tools for deployment, control, governance
and analytics actions to test and evaluate designs of software compo-
nents and optimize the operation of di erent design con gurations. In
this paper, we describe requirements and our techniques on support-
ing the development and testing of IoT cloud platforms. We present our
choices of tools and engineering actions that help the developer to design,
test and evaluate IoT cloud platforms in multi-cloud environments.
Dependability assessments of reliable services in a private cloud environmentKPOST
Private cloud is a type of cloud computing that delivers similar advantages to public cloud, including scalability and self-service, but through a proprietary architecture. It promises significant cost savings by making it possible to consolidate workloads and share infrastructure resources among multiple applications resulting in higher cost and energy-efficiency. However, these benefits come at the cost of increased system complexity and dynamicity posing new challenges in providing service dependability and resilience for applications running in a private Cloud environment. This paper discusses about implementing a private cloud using open source software and operating system. This private cloud is capable of providing the infrastructure and platform as a service. Infrastructure includes the storage, servers, virtualization, compute and network services and platform as a service includes the operating system, middleware and runtime environment.
The DevOps movement has made significant traction but many organizations still have immature processes and technologies. The presentation reviews the areas of concerns.
Enabling and controlling elasticity of cloud comput-
ing applications is a challenging issue. Elasticity programming directives have been introduced to
delegate elasticity control to infrastructures and to
separate elasticity control from application logic. Since
coordination models provide a general approach to manage interaction and elasticity control entails interactions among cloud infrastructure components, we present a coordination-based approach to elasticity control, supporting delegation and separation of concerns at design and run-time, paving the way towards coordination-aware elasticity.
Continuous Integration and Continuous Delivery on AzureCitiusTech
Healthcare organizations are increasingly turning to cloud computing to address business and patient needs of their rapidly evolving environment and modernize legacy applications. With Azure DevOps, healthcare IT teams can drive innovation, build new products and modernize their application environment.
Comparison of open source paas architectural componentscsandit
Cloud computing is a widely used technology with three basic service models such as Software
as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS). This
paper focuses on the PaaS model. Open source PaaS model provides choice of cloud, developer
framework and application service. In this paper detailed study of four open PaaS packages
such as AppScale, Cloud Foundry, Cloudify, and OpenShift are explained with the considerable
architectural component aspects. We also explained some other PaaS packages like Stratos,
Stakato and mOSAIC briefly. In this paper we present the comparative study of major open
PaaS packages.
COMPARISON OF OPEN-SOURCE PAAS ARCHITECTURAL COMPONENTScscpconf
Cloud computing is a widely used technology with three basic service models such as Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS). This paper focuses on the PaaS model. Open source PaaS model provides choice of cloud, developer framework and application service. In this paper detailed study of four open PaaS packages such as AppScale, Cloud Foundry, Cloudify, and OpenShift are explained with the considerable architectural component aspects. We also explained some other PaaS packages like Stratos, Stakato and mOSAIC briefly. In this paper we present the comparative study of major open PaaS packages.
Comparative Study of Various Platform as a Service Frameworks neirew J
Cloud computing is an emerging paradigm with three basic service models such as Software as a Service
(SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS). This paper focuses on
different kinds of PaaS frameworks. PaaS model provides choice of cloud, developer framework and
application service. In this paper, detailed study of four open PaaS frameworks like AppScale, Cloud
Foundry, Cloudify, and OpenShift are explained with the architectural components. We also explained
more PaaS packages like Stratos, mOSAIC, BlueMix, Heroku, Amazon Elastic Beanstalk, Microsoft Azure,
Google App Engine and Stakato briefly. In this paper we present the comparative study of PaaS
frameworks.
COMPARATIVE STUDY OF VARIOUS PLATFORM AS A SERVICE FRAMEWORKSijccsa
Cloud computing is an emerging paradigm with three basic service models such as Software as a Service
(SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS). This paper focuses on
different kinds of PaaS frameworks. PaaS model provides choice of cloud, developer framework and
application service. In this paper, detailed study of four open PaaS frameworks like AppScale, Cloud
Foundry, Cloudify, and OpenShift are explained with the architectural components. We also explained
more PaaS packages like Stratos, mOSAIC, BlueMix, Heroku, Amazon Elastic Beanstalk, Microsoft Azure,
Google App Engine and Stakato briefly. In this paper we present the comparative study of PaaS
frameworks.
Webinar presentation October 22, 2015.
The model behind Platform-as-a-Service (PaaS) is to provide a platform for customers to develop, run, and manage web applications without needing to build or maintain the infrastructure, which can reduce costs while increasing flexibility and speed-to-market.
In the CSCC deliverable, Practical Guide to Platform-as-a-Service, learn how to use PaaS to solve business challenges, specifically:
- Definition of PaaS, the benefits of using PaaS, and examples of PaaS offerings
- Applications best suited for PaaS and the considerations for architecture, development, and operations
- Recommendations for the best use of PaaS services
Download the deliverable: http://www.cloud-council.org/resource-hub
JDD2015: Sustainability Supporting Data Variability: Keeping Core Components ...PROIDEA
SUSTAINABILITY SUPPORTING DATA VARIABILITY: KEEPING CORE COMPONENTS CLEAN WHILE DEALING WITH DATA VARIABILITY
A big challenge in building complex, data-intensive systems is how to sustainably support data variation, schema, and feature evolution. This talk examines strategies, practices, and patterns drawn from real experiences that support new and evolving data-processing requirements while keeping the core architecture clean. As complex systems evolve to meet varying data formats, they can devolve into poorly architected Big Balls of Mud filled with special-case logic and one-off processing. Alternatively, you can isolate core components of your system and protect them from entanglements and unnecessary complexity by designing them to operate on common data formats while providing extension mechanisms that enable processing variations.
JDD2015: Sustainability Supporting Data Variability: Keeping Core Components ...PROIDEA
SUSTAINABILITY SUPPORTING DATA VARIABILITY: KEEPING CORE COMPONENTS CLEAN WHILE DEALING WITH DATA VARIABILITY
A big challenge in building complex, data-intensive systems is how to sustainably support data variation, schema, and feature evolution. This talk examines strategies, practices, and patterns drawn from real experiences that support new and evolving data-processing requirements while keeping the core architecture clean. As complex systems evolve to meet varying data formats, they can devolve into poorly architected Big Balls of Mud filled with special-case logic and one-off processing. Alternatively, you can isolate core components of your system and protect them from entanglements and unnecessary complexity by designing them to operate on common data formats while providing extension mechanisms that enable processing variations.
Enabling Production Grade Containerized Applications through Policy Based Inf...Docker, Inc.
This session covers the solution addressing the needs of enabling product-grade containerized applications. You will learn how operations teams running containerized applications in a shared infrastructure can define and enforce policies to provide security, monitoring, and performance for network, storage, and computing. You will learn about Contiv and Mantl, open source projects that create a framework for cloud native application development and infrastructure with application intent and operational policies. Contiv integrates Cisco infrastructure (UCS, Nexus, and ACI) with Docker Datacenter to help enterprises adopt containers at a larger scale.
On Engineering Analytics of Elastic IoT Cloud SystemsHong-Linh Truong
Developing IoT cloud platforms is very challenging, as IoT
cloud platforms consist of a mix of cloud services and IoT elements, e.g.,
for sensor management, near-realtime events handling, and data analyt-
ics. Developers need several tools for deployment, control, governance
and analytics actions to test and evaluate designs of software compo-
nents and optimize the operation of di erent design con gurations. In
this paper, we describe requirements and our techniques on support-
ing the development and testing of IoT cloud platforms. We present our
choices of tools and engineering actions that help the developer to design,
test and evaluate IoT cloud platforms in multi-cloud environments.
Dependability assessments of reliable services in a private cloud environmentKPOST
Private cloud is a type of cloud computing that delivers similar advantages to public cloud, including scalability and self-service, but through a proprietary architecture. It promises significant cost savings by making it possible to consolidate workloads and share infrastructure resources among multiple applications resulting in higher cost and energy-efficiency. However, these benefits come at the cost of increased system complexity and dynamicity posing new challenges in providing service dependability and resilience for applications running in a private Cloud environment. This paper discusses about implementing a private cloud using open source software and operating system. This private cloud is capable of providing the infrastructure and platform as a service. Infrastructure includes the storage, servers, virtualization, compute and network services and platform as a service includes the operating system, middleware and runtime environment.
The DevOps movement has made significant traction but many organizations still have immature processes and technologies. The presentation reviews the areas of concerns.
Enabling and controlling elasticity of cloud comput-
ing applications is a challenging issue. Elasticity programming directives have been introduced to
delegate elasticity control to infrastructures and to
separate elasticity control from application logic. Since
coordination models provide a general approach to manage interaction and elasticity control entails interactions among cloud infrastructure components, we present a coordination-based approach to elasticity control, supporting delegation and separation of concerns at design and run-time, paving the way towards coordination-aware elasticity.
Continuous Integration and Continuous Delivery on AzureCitiusTech
Healthcare organizations are increasingly turning to cloud computing to address business and patient needs of their rapidly evolving environment and modernize legacy applications. With Azure DevOps, healthcare IT teams can drive innovation, build new products and modernize their application environment.
Comparison of open source paas architectural componentscsandit
Cloud computing is a widely used technology with three basic service models such as Software
as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS). This
paper focuses on the PaaS model. Open source PaaS model provides choice of cloud, developer
framework and application service. In this paper detailed study of four open PaaS packages
such as AppScale, Cloud Foundry, Cloudify, and OpenShift are explained with the considerable
architectural component aspects. We also explained some other PaaS packages like Stratos,
Stakato and mOSAIC briefly. In this paper we present the comparative study of major open
PaaS packages.
COMPARISON OF OPEN-SOURCE PAAS ARCHITECTURAL COMPONENTScscpconf
Cloud computing is a widely used technology with three basic service models such as Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS). This paper focuses on the PaaS model. Open source PaaS model provides choice of cloud, developer framework and application service. In this paper detailed study of four open PaaS packages such as AppScale, Cloud Foundry, Cloudify, and OpenShift are explained with the considerable architectural component aspects. We also explained some other PaaS packages like Stratos, Stakato and mOSAIC briefly. In this paper we present the comparative study of major open PaaS packages.
Comparative Study of Various Platform as a Service Frameworks neirew J
Cloud computing is an emerging paradigm with three basic service models such as Software as a Service
(SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS). This paper focuses on
different kinds of PaaS frameworks. PaaS model provides choice of cloud, developer framework and
application service. In this paper, detailed study of four open PaaS frameworks like AppScale, Cloud
Foundry, Cloudify, and OpenShift are explained with the architectural components. We also explained
more PaaS packages like Stratos, mOSAIC, BlueMix, Heroku, Amazon Elastic Beanstalk, Microsoft Azure,
Google App Engine and Stakato briefly. In this paper we present the comparative study of PaaS
frameworks.
COMPARATIVE STUDY OF VARIOUS PLATFORM AS A SERVICE FRAMEWORKSijccsa
Cloud computing is an emerging paradigm with three basic service models such as Software as a Service
(SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS). This paper focuses on
different kinds of PaaS frameworks. PaaS model provides choice of cloud, developer framework and
application service. In this paper, detailed study of four open PaaS frameworks like AppScale, Cloud
Foundry, Cloudify, and OpenShift are explained with the architectural components. We also explained
more PaaS packages like Stratos, mOSAIC, BlueMix, Heroku, Amazon Elastic Beanstalk, Microsoft Azure,
Google App Engine and Stakato briefly. In this paper we present the comparative study of PaaS
frameworks.
Webinar presentation October 22, 2015.
The model behind Platform-as-a-Service (PaaS) is to provide a platform for customers to develop, run, and manage web applications without needing to build or maintain the infrastructure, which can reduce costs while increasing flexibility and speed-to-market.
In the CSCC deliverable, Practical Guide to Platform-as-a-Service, learn how to use PaaS to solve business challenges, specifically:
- Definition of PaaS, the benefits of using PaaS, and examples of PaaS offerings
- Applications best suited for PaaS and the considerations for architecture, development, and operations
- Recommendations for the best use of PaaS services
Download the deliverable: http://www.cloud-council.org/resource-hub
Similar to CoMoT – A Platform-as-a-Service for Elasticity in the Cloud (20)
Integrated Analytics for IIoT Predictive Maintenance using IoT Big Data Cloud...Hong-Linh Truong
For predictive maintenance of equipment with In-
dustrial Internet of Things (IIoT) technologies, existing IoT Cloud
systems provide strong monitoring and data analysis capabilities
for detecting and predicting status of equipment. However, we
need to support complex interactions among different software
components and human activities to provide an integrated analyt-
ics, as software algorithms alone cannot deal with the complexity
and scale of data collection and analysis and the diversity of
equipment, due to the difficulties of capturing and modeling
uncertainties and domain knowledge in predictive maintenance.
In this paper, we describe how we design and augment complex
IoT big data cloud systems for integrated analytics of IIoT
predictive maintenance. Our approach is to identify various
complex interactions for solving system incidents together with
relevant critical analytics results about equipment. We incorpo-
rate humans into various parts of complex IoT Cloud systems
to enable situational data collection, services management, and
data analytics. We leverage serverless functions, cloud services,
and domain knowledge to support dynamic interactions between
human and software for maintaining equipment. We use a real-
world maintenance of Base Transceiver Stations to illustrate our
engineering approach which we have prototyped with state-of-
the art cloud and IoT technologies, such as Apache Nifi, Hadoop,
Spark and Google Cloud Functions.
Testing Uncertainty of Cyber-Physical Systems in IoT Cloud Infrastructures: C...Hong-Linh Truong
Today’s cyber-physical systems (CPS) span IoT and cloud-based
datacenter infrastructures, which are highly heterogeneous with
various types of uncertainty. Thus, testing uncertainties in these
CPS is a challenging and multidisciplinary activity. We need several
tools for modeling, deployment, control, and analytics to test and
evaluate uncertainties for different configurations of the same CPS.
In this paper, we explain why using state-of-the art model-driven
engineering (MDE) and model-based testing (MBT) tools is not
adequate for testing uncertainties of CPS in IoT Cloud infrastruc-
tures. We discus how to combine them with techniques for elastic
execution to dynamically provision both CPS under test and testing
utilities to perform tests in various IoT Cloud infrastructures.
Towards a Resource Slice Interoperability Hub for IoTHong-Linh Truong
Interoperability for IoT is a challenging problem
because it requires us to tackle (i) cross-system interoperability
issues at the IoT platform sides as well as relevant network
functions and clouds in the edge systems and data centers
and (ii) cross-layer interoperability, e.g., w.r.t. data formats,
communication protocols, data delivery mechanisms, and perfor-
mance. However, existing solutions are quite static w.r.t software
deployment and provisioning for interoperability. Many middle-
ware, services and platforms have been built and deployed as
interoperability bridges but they are not dynamically provisioned
and reconfigured for interoperability at runtime. Furthermore,
they are often not considered together with other services as a
whole in application-specific contexts. In this paper, we focus
on dynamic aspects by introducing the concept of Resource
Slice Interoperability Hub (rsiHub). Our approach leverages
existing software artifacts and services for interoperability to
create and provision dynamic resource slices, including IoT,
network functions and clouds, for addressing application-specific
interoperability requirements. We will present our key concepts,
architectures and examples toward the realization of rsiHub.
On Supporting Contract-aware IoT Dataspace ServicesHong-Linh Truong
Advances in the Internet of Things (IoT) enable a
huge number of connected devices that produce large amounts
of data. Such data is increasingly shared among various
stakeholders to support advanced (predictive) analytics and
precision decision making in different application domains like
smart cities and industrial internet. Currently there are several
platforms that facilitate sharing, buying and selling IoT data.
However, these platforms do not support the establishment and
monitoring of usage contracts for IoT data. In this paper we
address this research issue by introducing a new extensible
platform for enabling contract-aware IoT dataspace services,
which supports data contract specification and IoT data flow
monitoring based on established data contracts. We present
a general architecture of contract monitoring services for
IoT dataspaces and evaluate our platform through illustrative
examples with real-world datasets and through performance
analysis.
Towards the Realization of Multi-dimensional Elasticity for Distributed Cloud...Hong-Linh Truong
As multiple types of distributed, heterogeneous cloud computing environments have proliferated, cloud software can leverage
diverse types of infrastructural, platform and data resources with di
erent cost and quality models. This introduces a multi-
dimensional elasticity perspective for cloud software that would greatly meet changing demands from the user. However, we argue
that current techniques are not enough for dealing with multi-dimensional elasticity in distributed cloud environments. We present
our approach to the realization of multi-dimensional elasticity by introducing novel concepts and a roadmap to achieve them.
HINC – Harmonizing Diverse Resource Information Across IoT, Network Functions...Hong-Linh Truong
Effective resource management in IoT systems must
represent IoT resources, edge-to-cloud network capabilities, and
cloud resources at a high-level, while being able to link to diverse
low-level types of IoT devices, network functions, and cloud
computing infrastructures. Hence resource management in such
a context demands a highly distributed and extensible approach,
which allows us to integrate and provision IoT, network functions,
and cloud resources from various providers. In this paper, we
address this crucial research issue. We first present a high-
level information model for virtualized IoT, network functions
and cloud resource modeling, which also incorporates software-
defined gateways, network slicing and data centers. This model
is used to glue various low-level resource models from different
types of infrastructures in a distributed manner to capture
sets of resources spanning across different sub-networks. We
then develop a set of utilities and a middleware to support
the integration of information about distributed resources from
various sources. We present a proof of concept prototype with
various experiments to illustrate how various tasks in IoT cloud
systems can be simplified as well as to evaluate the performance
of our framework.
SINC – An Information-Centric Approach for End-to-End IoT Cloud Resource Prov...Hong-Linh Truong
We present SINC –
Slicing IoT, Network Functions, and Clouds – which enables designers to dynamically create/update end-to-end slices of the overall IoT network in order to simultaneously meet multiple user needs.
Governing Elastic IoT Cloud Systems under UncertaintiesHong-Linh Truong
we introduce U-GovOps – a novel framework for
dynamic, on-demand governance of elastic IoT cloud systems under
uncertainty. We introduce a declarative policy language to simplify
the development of uncertainty- and elasticity-aware governance
strategies. Based on that we develop runtime mechanisms, which
enable mitigating the uncertainties by monitoring and governing
the IoT cloud systems through specified strategies.
SmartSociety – A Platform for Collaborative People-Machine ComputationHong-Linh Truong
We present the SmartSociety Platform for Collaborative People-Machine computation carried out in the FET SmartSociety project: http://www.smart-society-project.eu/
On Developing and Operating of Data Elasticity Management ProcessHong-Linh Truong
The Data-as-a-Service (DaaS) model enables data analytics
providers to provision and offer data assets to their consumers. To achieve quality of results for the data assets, we need to enable DaaS elasticity by trading off quality and cost of resource usage. However, most of the current work on DaaS is focused on infrastructure elasticity, such as scaling
in/out data nodes and virtual machines based on performance and usage, without considering the data assets' quality of results. In this talk, we introduce an elastic data asset model for provisioning data enriched with quality of results. Based on this model, we present techniques to generate and operate data elasticity management process that is used to
monitor, evaluate and enforce expected quality of results. We develop a runtime system to guarantee the quality of resulting data assets provisioned on-demand. We present several experiments to demonstrate the usefulness of our proposed techniques.
Palestine last event orientationfvgnh .pptxRaedMohamed3
An EFL lesson about the current events in Palestine. It is intended to be for intermediate students who wish to increase their listening skills through a short lesson in power point.
Biological screening of herbal drugs: Introduction and Need for
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A Strategic Approach: GenAI in EducationPeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
Introduction to AI for Nonprofits with Tapp NetworkTechSoup
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2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
The Roman Empire A Historical Colossus.pdfkaushalkr1407
The Roman Empire, a vast and enduring power, stands as one of history's most remarkable civilizations, leaving an indelible imprint on the world. It emerged from the Roman Republic, transitioning into an imperial powerhouse under the leadership of Augustus Caesar in 27 BCE. This transformation marked the beginning of an era defined by unprecedented territorial expansion, architectural marvels, and profound cultural influence.
The empire's roots lie in the city of Rome, founded, according to legend, by Romulus in 753 BCE. Over centuries, Rome evolved from a small settlement to a formidable republic, characterized by a complex political system with elected officials and checks on power. However, internal strife, class conflicts, and military ambitions paved the way for the end of the Republic. Julius Caesar’s dictatorship and subsequent assassination in 44 BCE created a power vacuum, leading to a civil war. Octavian, later Augustus, emerged victorious, heralding the Roman Empire’s birth.
Under Augustus, the empire experienced the Pax Romana, a 200-year period of relative peace and stability. Augustus reformed the military, established efficient administrative systems, and initiated grand construction projects. The empire's borders expanded, encompassing territories from Britain to Egypt and from Spain to the Euphrates. Roman legions, renowned for their discipline and engineering prowess, secured and maintained these vast territories, building roads, fortifications, and cities that facilitated control and integration.
The Roman Empire’s society was hierarchical, with a rigid class system. At the top were the patricians, wealthy elites who held significant political power. Below them were the plebeians, free citizens with limited political influence, and the vast numbers of slaves who formed the backbone of the economy. The family unit was central, governed by the paterfamilias, the male head who held absolute authority.
Culturally, the Romans were eclectic, absorbing and adapting elements from the civilizations they encountered, particularly the Greeks. Roman art, literature, and philosophy reflected this synthesis, creating a rich cultural tapestry. Latin, the Roman language, became the lingua franca of the Western world, influencing numerous modern languages.
Roman architecture and engineering achievements were monumental. They perfected the arch, vault, and dome, constructing enduring structures like the Colosseum, Pantheon, and aqueducts. These engineering marvels not only showcased Roman ingenuity but also served practical purposes, from public entertainment to water supply.
Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
CoMoT – A Platform-as-a-Service for Elasticity in the Cloud
1. CoMoT – a Platform-as-a-Service for
Elasticity in the Cloud
Future of PaaS@IC2E 2014
Hong-Linh Truong, Schahram Dustdar, Georgiana Copil,
Alessio Gambi, Waldemar Hummer, Duc-Hung Le, Daniel
Moldovan
Distributed Systems Group
Vienna University of Technology
truong@dsg.tuwien.ac.at
Future of PaaS@IC2E 2014, 11 Mar
2014, Boston, USA
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2. Outline
Motivation
Programming, deploying, controlling,
monitoring and testing elasticity
CoMoT architecture
Illustrating example
Conclusions and future work
Future of PaaS@IC2E 2014,
11 Mar 2014, Boston, USA
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3. Motivation (1)
Multi-dimensional elasticity is the fundamental
requirement for native cloud services
resource elasticity, cost elasticity and quality
elasticity
But fragmented support on engineering
elasticity requirements, execution, monitoring
and testing, e.g.,
Only at resource elasticity at the IaaS level
Lack of elasticity monitoring for applications
Testing is not integrated with other phases
Future of PaaS@IC2E 2014,
11 Mar 2014, Boston, USA
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4. Service
Developer
Infrastructure
Provider
Service
Owner
Service
Developer
Designing and
programming software-
defined elastic services
Designing and
programming software-
defined elastic services
Automatic service
deployment
Automatic service
deployment
Elasticity monitoring and
analysis
Elasticity monitoring and
analysis
Elasticity ControlElasticity Control
Service
Owner
Infrastructure
Provider
Service
Owner
Easy to
program
elasticity
requirements
Reduced time to
market
+
Easy to understand
service’s elasticity
boundaries
+
Maintains service’s
performance while
reducing cost
Reduces
resources
overprovisioning
+
Motivation (2)
Future of PaaS@IC2E 2014,
11 Mar 2014, Boston, USA
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Native cloud service engineering
6. Fundamental building blocks for
the elasticity
Conceptualizing and modeling elastic objects and
execution environments
So we can manage diverse types of artifacts and their runtime
in a similar manner
Defining elasticity primitive operations associated with
elastic objects and environments
Programming elastic objects
a software-defined elastic service (SES) is built from elastic
objects
Runtime deploying, control, monitoring and testing
techniques for elastic objects
Future of PaaS@IC2E 2014,
11 Mar 2014, Boston, USA
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7. Elastic objects and execution
environments
Future of PaaS@IC2E 2014,
11 Mar 2014, Boston, USA
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Modeling type of units (e.g.,
computation, data,
monitoring,) and their
dependencies
Consumption,
ownership, provisioning,
price, etc.
Elastic
Service
Unit
Service
model
Unit
Dependency
Elastic
Capability
Function
The functional
capability of the unit
and interface to
access the function Capabilities to be elastic
under different
requirements
10. Deploying, Control, Monitoring and
Testing
Runtime deployment
Complex services at multiple software stacks (IaaS,
PaaS and application)
Using and enriching TOSCA for describing
deployment topology
Different interactions between deploying and control
and monitoring components
Control elasticity
Using a high-level specification for specifying
elasticity requirements, constraints and strategies
Based on SYBL/rSYBL ([CCGrid 2013])
Future of PaaS@IC2E 2014,
11 Mar 2014, Boston, USA
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11. Deploying, Control, Monitoring and
Testing
Elasticity monitoring and analysis
Utilize low-level metrics to build „Elasticity Space“
and analyze the elasticity based on such spaces
(based on MELA – [CloudCom 2013])
Monitoring/analysis at multiple levels level (single
unit, topology/group, and the whole service
Testing elasticity
Using clouds to test cloud applications as well as to
test elasticity properties of cloud applications
[ASE2013, IC2014]
Future of PaaS@IC2E 2014,
11 Mar 2014, Boston, USA
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12. Software-defined
Elastic System
Programming
Software-defined
Elastic System
Programming
Tooling – Elasticity
Programming in
Cloud Systems
Elastic Service
Ecosystem and
Recommendation
Elastic Service
Ecosystem and
Recommendation
DeploymentDeployment
Deployment
Service
Deployment
Service
Test Generating
and Execution
Test Generating
and Execution
Elastic Test
Service
Elastic Test
Service
deploy SDS/
service units
deploy elasticity
controller and monitor
Elasticity
Analysis
Elasticity
Analysis
deploy
test cases
ElasticizingElasticizing
Elasticity
Monitoring
and Analysis
Elasticity
Monitoring
and Analysis
Elasticity
Control
Elasticity
Control
test
control
monitor
CoMoT PaaS
Core Services
Multi-Cloud
Environments
Service
Ecosystems
Service Artifact
Repository
Service units
CoMoT (1)
CoMoT is built atop: rSYBL, MELA, SALSA, AutoCles
GIT: https://github.com/tuwiendsg and https://github.com/whummer/AUToCLES
Note: CoMoT code is not there yet but other packages
CoMoT is built atop: rSYBL, MELA, SALSA, AutoCles
GIT: https://github.com/tuwiendsg and https://github.com/whummer/AUToCLES
Note: CoMoT code is not there yet but other packages
Future of PaaS@IC2E 2014,
11 Mar 2014, Boston, USA
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17. Conclusions and future work
Native cloud applications need novel PaaSs
Design, deployment, control, monitoring and testing
of elasticity in interwoven engineering phases
CoMoT introduces concepts of elastic objects and
fundamental building blocks for engineering an end-
to-end elasticity for cloud services
Future works
Programming languages for elastic objects
Further work on hot deployment and configuration
under elasticity control
Testing elasticity dependencies
Future of PaaS@IC2E 2014,
11 Mar 2014, Boston, USA
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18. Thanks for your attention!
Hong-Linh Truong
Distributed Systems Group
TU Wien
truong@dsg.tuwien.ac.at
dsg.tuwien.ac.at/research/viecom
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11 Mar 2014, Boston, USA
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