SERENE 2014 School on Engineering Resilient Cyber Physical Systems
Talk: Measurement-Driven Resilience Design of Cloud-Based Cyber-Physical Systems, by Imre Kocsis
This document presents research on assessing risk to determine the optimal level of redundancy needed when moving critical applications to the cloud. It develops fault tree models based on the physical structure of clouds to calculate failure frequency. It factors in varying resource quality and the costs of downtime and VMs. The results show that deploying between 4-6 redundant VMs provides significant availability gains and reduces total costs by lowering risk compared to basic redundancy approaches. The aim was met of leveraging cloud features in modeling to support high-value, mission critical applications on public clouds.
Engineering Cross-Layer Fault Tolerance in Many-Core SystemsSERENEWorkshop
1) The document discusses engineering cross-layer fault tolerance in many-core systems. It proposes a cross-layer approach where fault tolerance is distributed across system layers rather than handled solely within a single layer.
2) A motivating example of cross-layer fault tolerance is discussed using TCP/IP, where errors can be detected and recovered across multiple layers for improved efficiency.
3) The challenges of ensuring cross-layer fault tolerance for many-core systems containing tens to thousands of cores are discussed to improve reliability, performance and energy efficiency.
4) The plan is to implement a case study of a car number plate recognition application to gain experience with cross-layer fault tolerance, and apply order graphs to model performance
Iaetsd survey on big data analytics for sdn (software defined networks)Iaetsd Iaetsd
This document discusses using software-defined networking and OpenFlow to improve network architectures for scientific data sharing. It proposes exploring a virtual switch network abstraction combined with SDN concepts to provide a simple, adaptable framework for science users. The challenges of current campus networks not being optimized for large data flows are outlined. Leveraging SDN could help build end-to-end network services with traffic isolation to meet the needs of data-intensive science applications and collaborations.
Presentation at the International Industry-Academia Workshop on Cloud Reliability and Resilience. 7-8 November 2016, Berlin, Germany.
Organized by EIT Digital and Huawei GRC, Germany.
Twitter: @CloudRR2016
This document discusses machine learning techniques for reconstructing radio maps in wireless networks. It addresses challenges like high mobility, noisy channels, and stringent 5G requirements. It proposes using adaptive learning to reconstruct pathloss, traffic, and load maps online from user measurements. Key ingredients discussed are sparse multi-kernel approaches for pathloss, Gaussian processes for traffic, and hybrid-driven methods for load estimation. The techniques can provide probabilistic bounds and optimize network configuration for energy efficiency.
This document presents research on assessing risk to determine the optimal level of redundancy needed when moving critical applications to the cloud. It develops fault tree models based on the physical structure of clouds to calculate failure frequency. It factors in varying resource quality and the costs of downtime and VMs. The results show that deploying between 4-6 redundant VMs provides significant availability gains and reduces total costs by lowering risk compared to basic redundancy approaches. The aim was met of leveraging cloud features in modeling to support high-value, mission critical applications on public clouds.
Engineering Cross-Layer Fault Tolerance in Many-Core SystemsSERENEWorkshop
1) The document discusses engineering cross-layer fault tolerance in many-core systems. It proposes a cross-layer approach where fault tolerance is distributed across system layers rather than handled solely within a single layer.
2) A motivating example of cross-layer fault tolerance is discussed using TCP/IP, where errors can be detected and recovered across multiple layers for improved efficiency.
3) The challenges of ensuring cross-layer fault tolerance for many-core systems containing tens to thousands of cores are discussed to improve reliability, performance and energy efficiency.
4) The plan is to implement a case study of a car number plate recognition application to gain experience with cross-layer fault tolerance, and apply order graphs to model performance
Iaetsd survey on big data analytics for sdn (software defined networks)Iaetsd Iaetsd
This document discusses using software-defined networking and OpenFlow to improve network architectures for scientific data sharing. It proposes exploring a virtual switch network abstraction combined with SDN concepts to provide a simple, adaptable framework for science users. The challenges of current campus networks not being optimized for large data flows are outlined. Leveraging SDN could help build end-to-end network services with traffic isolation to meet the needs of data-intensive science applications and collaborations.
Presentation at the International Industry-Academia Workshop on Cloud Reliability and Resilience. 7-8 November 2016, Berlin, Germany.
Organized by EIT Digital and Huawei GRC, Germany.
Twitter: @CloudRR2016
This document discusses machine learning techniques for reconstructing radio maps in wireless networks. It addresses challenges like high mobility, noisy channels, and stringent 5G requirements. It proposes using adaptive learning to reconstruct pathloss, traffic, and load maps online from user measurements. Key ingredients discussed are sparse multi-kernel approaches for pathloss, Gaussian processes for traffic, and hybrid-driven methods for load estimation. The techniques can provide probabilistic bounds and optimize network configuration for energy efficiency.
In this deck from the Stanford HPC Conference, Peter Dueben from the European Centre for Medium-Range Weather Forecasts (ECMWF) presents: Machine Learning for Weather Forecasts.
"I will present recent studies that use deep learning to learn the equations of motion of the atmosphere, to emulate model components of weather forecast models and to enhance usability of weather forecasts. I will than talk about the main challenges for the application of deep learning in cutting-edge weather forecasts and suggest approaches to improve usability in the future."
Peter is contributing to the development and optimization of weather and climate models for modern supercomputers. He is focusing on a better understanding of model error and model uncertainty, on the use of reduced numerical precision that is optimised for a given level of model error, on global cloud- resolving simulations with ECMWF's forecast model, and the use of machine learning, and in particular deep learning, to improve the workflow and predictions. Peter has graduated in Physics and wrote his PhD thesis at the Max Planck Institute for Meteorology in Germany. He worked as Postdoc with Tim Palmer at the University of Oxford and has taken up a position as University Research Fellow of the Royal Society at the European Centre for Medium-Range Weather Forecasts (ECMWF) in 2017.
Watch the video: https://youtu.be/ks3fkRj8Iqc
Learn more: https://www.ecmwf.int/
and
http://www.hpcadvisorycouncil.com/events/2020/stanford-workshop/
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
The document lists generic technology project titles from 2011 across several domains including mobile computing, networks, software engineering, wireless networks, cloud computing, network security, data mining, and grid computing. It includes titles such as "A Privacy-Preserving Location Monitoring System for Wireless Sensor Networks", "Supporting Efficient and Scalable Multicasting over Mobile Ad Hoc Networks", "A Unified Approach to Optimizing Performance in Networks serving Heterogeneous Flows", and "Secure and Practical Outsourcing of Linear Programming in Cloud Computing". It also lists some non-IEEE project titles from 2011 related to domains like voice, image processing and other applications.
ENERGY EFFICIENT MULTIHOP QUALITY PATH BASED DATA COLLECTION IN WIRELESS SENS...Editor IJMTER
In recent years there has been an increased focus on the use of sensor networks to sense and measure
the environment. This leads to a wide variety of theoretical and practical issues on appropriate protocols for data
sensing and transfer. Recent work shows sink mobility can improve the energy efficiency in wireless sensor
networks (WSNs). However, data delivery latency often increases due to the speed limit of mobile sink. Most of
them exploit mobility to address the problem of data collection in WSNs. The WSNs with MS (mobile Sink) and
provide a comprehensive taxonomy of their architectures, based on the role of the MS. An overview of the data
collection process in such a scenario, and identify the corresponding issues and challenges. A protocol named
weighted rendezvous planning (WRP) which is a heuristic method that finds a near-optimal traveling tour that
minimizes the energy consumption of sensor nodes. Focus on the path selection problem in delay-guaranteed
sensor networks with a path-constrained mobile sink. Concentrate an efficient data collection scheme, which
simultaneously improves the total amount of data and reduces the energy consumption. The optimal path is chosen
to meet the requirement on delay as well as minimize the energy consumption of entire network. Predictable sink
mobility is exploited to improve energy efficiency of sensor networks.
Presentation by Steffen Zeuch, Researcher at German Research Center for Artificial Intelligence (DFKI) and Post-Doc at TU Berlin (Germany), at the FogGuru Boot Camp training in September 2018.
Modeling Uncertainty For Middleware-based Streaming Power Grid ApplicationsJenny Liu
The document describes modeling uncertainty in middleware-based streaming applications for power grids. It presents a discrete-event model built in Ptolemy II to capture uncertainty from sources like middleware latency, network delays, and number of sensor streams. Monte Carlo simulations are run over this model by varying parameters like middleware concurrency and sensor streams. Regression analysis is then used to understand the relationship between these influential parameters and the end-to-end application run time.
This document provides an introduction and overview of wireless visual sensor networks (WVSNs) and the coverage problem in WVSNs. It begins with defining WVSNs as sensor networks equipped with camera sensors that can send visual data to enable applications in wildlife observation and security surveillance. It then covers the hardware components of WVSNs, applications of WVSNs, how WVSNs differ from traditional wireless sensor networks, sensing models in WVSNs, major design issues in WVSNs including coverage, and principles for enhancing coverage in WVSNs. It concludes by stating that coverage is a central design issue for visual monitoring applications using WVSNs.
4 TeraGrid Sites Have Focal Points:
SDSC – The Data Place
Large-scale and high-performance data analysis/handling
Every Cluster Node is Directly Attached to SAN
NCSA – The Compute Place
Large-scale, Large Flops computation
Argonne – The Viz place
Scalable Viz walls
Caltech – The Applications place
Data and flops for applications – Especially some of the GriPhyN Apps
Specific machine configurations reflect this
Reinventing the Share Button for Physical SpacesDarren Carlson
This document presents the Ambient Dynamix framework, which allows browser-based apps to access sensor and device context from the physical environment. The framework includes a web extension that gives apps access to plug-ins for various sensors and devices through a central repository. This allows apps to gain awareness of their physical context and enable ad-hoc interactions. The presentation demonstrates the framework enabling a web app to control lights and projectors in the environment based on user context. It provides examples of plug-ins for various sensors and devices that could be accessed through the framework.
Positioning University of California Information Technology for the Future: S...Larry Smarr
05.02.15
Invited Talk
The Vice Chancellor of Research and Chief Information Officer Summit
“Information Technology Enabling Research at the University of California”
Title: Positioning University of California Information Technology for the Future: State, National, and International IT Infrastructure Trends and Directions
Oakland, CA
OOFELIE::Multiphysics is a 3D multiphysics simulation software that allows for the design and analysis of microsystems, such as MEMS and MOEMS devices. It uses strongly coupled finite element analysis to obtain accurate results for increasingly smaller components in a timely manner. The software automates design space exploration through parametric studies and optimization to identify the best design. It also links with CAD and EDA tools to facilitate the design flow from concept to fabrication. OOFELIE::Multiphysics was used by ONERA to simulate a vibrating inertial accelerometer and optimize its performance.
A Survey on Secure Alternate Path Selection for Enhanced Network Lifetime in ...IRJET Journal
This document summarizes a research paper that proposes techniques to enhance the lifetime of wireless sensor networks. It discusses how sensor nodes closer to the sink node consume more energy transmitting data, creating hotspots and shortening the network's lifetime. To address this, the paper proposes using alternate shortest paths to route data and relocating the sink node when the energy of alternate paths gets low. It also uses elliptic curve cryptography and a hybrid encryption method using AES and ECC to securely transmit data and further increase the network lifetime. Evaluation results show the proposed energy-aware sink relocation technique effectively enhances the network lifetime of wireless sensor networks.
A secure service provisioning framework for cyber physical cloud computing sy...ijdpsjournal
Cyber physical systems (CPS) are mission critical systems engineered by combination of cyber and
physical systems respectively. These systems are tightly coupled, resource constrained systems and have
dynamic real time applications. Due to the limitation of resources, and in order to improve the efficiency of
the CPS systems, they are combined with cloud computing architecture, and are called as Cyber Physical
Cloud Computing Systems (CPCCS). These CPCCS have critical care applications where security of the
systems is a major concern. Therefore, we propose a Secure Service provisioning architecture for Cyber
Physical Cloud Computing Systems (CPCCS), which includes the combination of technologies such as
CPS, Cloud Computing and Wireless Sensor Networks. In addition to this, we also highlight various
threats/attacks; security requirements and mechanisms that are applicable to CPCCS at different layers
and propose two security models that can be adapted in a layered architectural format.
The document discusses thesis topics related to wireless sensor networks (WSN), providing examples of 5 potential WSN thesis ideas that focus on energy efficient transmission, dependability analysis, secure data outsourcing to cloud-WSN systems, uneven clustering algorithms, and energy optimized routing. It also lists the typical sections included in a WSN thesis, such as introductions, statements of proposed work, research goals, methodologies, results, and conclusions. Contact information is provided for getting guidance on WSN or other network simulation tool related theses.
Deep learning and feature extraction for time series forecastingPavel Filonov
This document outlines the use of deep learning and feature extraction techniques for time series forecasting. It discusses using artificial neural networks like RNNs on raw time series data and on extracted features. RNNs can be used for anomaly detection and forecasting. The document also discusses modeling quasi-periodic time series using RNNs with LSTM units, extracting features through clustering, and evaluating models on forecast horizons of minutes to segments.
This document discusses security protocols for high performance grid computing architectures. It analyzes the different network layers in grid computing protocols and identifies various security disciplines. It also analyzes various security suites available in the TCP/IP protocol architecture. The paper aims to define security disciplines at different levels of cluster computing architecture and propose applicable security suites from the TCP/IP security protocol suite. Grid computing allows sharing and aggregation of distributed computing resources to enable more powerful applications. Security is an important consideration in grid computing due to sharing resources across administrative domains.
Machine Learning (ML) in Wireless Sensor Networks (WSNs)mabualsh
Wireless sensor networks (WSNs) and the Internet of Things (IoT) monitor dynamic environments that change rapidly over time. This dynamic behavior is either caused by external factors or initiated by the system designers themselves. WSNs and IoT often adopt machine learning to eliminate the need for unnecessary redesign. Machine learning inspires many practical solutions that maximize resource utilization and prolong the network's lifespan. These slides present an extensive literature review of machine learning methods to address common issues in WSNs and IoT.
Edal an energy efficient, delay-aware, and lifetime-balancing data collection...LogicMindtech Nologies
NS2 Projects for M. Tech, NS2 Projects in Vijayanagar, NS2 Projects in Bangalore, M. Tech Projects in Vijayanagar, M. Tech Projects in Bangalore, NS2 IEEE projects in Bangalore, IEEE 2015 NS2 Projects, WSN and MANET Projects, WSN and MANET Projects in Bangalore, WSN and MANET Projects in Vijayangar
Biological Immunity and Software Resilience: Two Faces of the Same Coin?SERENEWorkshop
The document discusses the similarities between biological immunity and software resilience. It proposes that biological systems are resilient, with the immune system being a prime example due to its ability to adapt, make decisions through distributed agents, and defend the body through learning. An actor-based model is presented as a way to engineer resilience into software by drawing inspiration from immune system principles like replication, containment, and delegation. A bio-inspired architecture is described that uses supervisor actors to detect changes and spawn helper/killer actors to address issues while maintaining system function. Future work areas are identified like automatic failure recognition, dynamic learning, and multi-layer management of failures.
In this deck from the Stanford HPC Conference, Peter Dueben from the European Centre for Medium-Range Weather Forecasts (ECMWF) presents: Machine Learning for Weather Forecasts.
"I will present recent studies that use deep learning to learn the equations of motion of the atmosphere, to emulate model components of weather forecast models and to enhance usability of weather forecasts. I will than talk about the main challenges for the application of deep learning in cutting-edge weather forecasts and suggest approaches to improve usability in the future."
Peter is contributing to the development and optimization of weather and climate models for modern supercomputers. He is focusing on a better understanding of model error and model uncertainty, on the use of reduced numerical precision that is optimised for a given level of model error, on global cloud- resolving simulations with ECMWF's forecast model, and the use of machine learning, and in particular deep learning, to improve the workflow and predictions. Peter has graduated in Physics and wrote his PhD thesis at the Max Planck Institute for Meteorology in Germany. He worked as Postdoc with Tim Palmer at the University of Oxford and has taken up a position as University Research Fellow of the Royal Society at the European Centre for Medium-Range Weather Forecasts (ECMWF) in 2017.
Watch the video: https://youtu.be/ks3fkRj8Iqc
Learn more: https://www.ecmwf.int/
and
http://www.hpcadvisorycouncil.com/events/2020/stanford-workshop/
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
The document lists generic technology project titles from 2011 across several domains including mobile computing, networks, software engineering, wireless networks, cloud computing, network security, data mining, and grid computing. It includes titles such as "A Privacy-Preserving Location Monitoring System for Wireless Sensor Networks", "Supporting Efficient and Scalable Multicasting over Mobile Ad Hoc Networks", "A Unified Approach to Optimizing Performance in Networks serving Heterogeneous Flows", and "Secure and Practical Outsourcing of Linear Programming in Cloud Computing". It also lists some non-IEEE project titles from 2011 related to domains like voice, image processing and other applications.
ENERGY EFFICIENT MULTIHOP QUALITY PATH BASED DATA COLLECTION IN WIRELESS SENS...Editor IJMTER
In recent years there has been an increased focus on the use of sensor networks to sense and measure
the environment. This leads to a wide variety of theoretical and practical issues on appropriate protocols for data
sensing and transfer. Recent work shows sink mobility can improve the energy efficiency in wireless sensor
networks (WSNs). However, data delivery latency often increases due to the speed limit of mobile sink. Most of
them exploit mobility to address the problem of data collection in WSNs. The WSNs with MS (mobile Sink) and
provide a comprehensive taxonomy of their architectures, based on the role of the MS. An overview of the data
collection process in such a scenario, and identify the corresponding issues and challenges. A protocol named
weighted rendezvous planning (WRP) which is a heuristic method that finds a near-optimal traveling tour that
minimizes the energy consumption of sensor nodes. Focus on the path selection problem in delay-guaranteed
sensor networks with a path-constrained mobile sink. Concentrate an efficient data collection scheme, which
simultaneously improves the total amount of data and reduces the energy consumption. The optimal path is chosen
to meet the requirement on delay as well as minimize the energy consumption of entire network. Predictable sink
mobility is exploited to improve energy efficiency of sensor networks.
Presentation by Steffen Zeuch, Researcher at German Research Center for Artificial Intelligence (DFKI) and Post-Doc at TU Berlin (Germany), at the FogGuru Boot Camp training in September 2018.
Modeling Uncertainty For Middleware-based Streaming Power Grid ApplicationsJenny Liu
The document describes modeling uncertainty in middleware-based streaming applications for power grids. It presents a discrete-event model built in Ptolemy II to capture uncertainty from sources like middleware latency, network delays, and number of sensor streams. Monte Carlo simulations are run over this model by varying parameters like middleware concurrency and sensor streams. Regression analysis is then used to understand the relationship between these influential parameters and the end-to-end application run time.
This document provides an introduction and overview of wireless visual sensor networks (WVSNs) and the coverage problem in WVSNs. It begins with defining WVSNs as sensor networks equipped with camera sensors that can send visual data to enable applications in wildlife observation and security surveillance. It then covers the hardware components of WVSNs, applications of WVSNs, how WVSNs differ from traditional wireless sensor networks, sensing models in WVSNs, major design issues in WVSNs including coverage, and principles for enhancing coverage in WVSNs. It concludes by stating that coverage is a central design issue for visual monitoring applications using WVSNs.
4 TeraGrid Sites Have Focal Points:
SDSC – The Data Place
Large-scale and high-performance data analysis/handling
Every Cluster Node is Directly Attached to SAN
NCSA – The Compute Place
Large-scale, Large Flops computation
Argonne – The Viz place
Scalable Viz walls
Caltech – The Applications place
Data and flops for applications – Especially some of the GriPhyN Apps
Specific machine configurations reflect this
Reinventing the Share Button for Physical SpacesDarren Carlson
This document presents the Ambient Dynamix framework, which allows browser-based apps to access sensor and device context from the physical environment. The framework includes a web extension that gives apps access to plug-ins for various sensors and devices through a central repository. This allows apps to gain awareness of their physical context and enable ad-hoc interactions. The presentation demonstrates the framework enabling a web app to control lights and projectors in the environment based on user context. It provides examples of plug-ins for various sensors and devices that could be accessed through the framework.
Positioning University of California Information Technology for the Future: S...Larry Smarr
05.02.15
Invited Talk
The Vice Chancellor of Research and Chief Information Officer Summit
“Information Technology Enabling Research at the University of California”
Title: Positioning University of California Information Technology for the Future: State, National, and International IT Infrastructure Trends and Directions
Oakland, CA
OOFELIE::Multiphysics is a 3D multiphysics simulation software that allows for the design and analysis of microsystems, such as MEMS and MOEMS devices. It uses strongly coupled finite element analysis to obtain accurate results for increasingly smaller components in a timely manner. The software automates design space exploration through parametric studies and optimization to identify the best design. It also links with CAD and EDA tools to facilitate the design flow from concept to fabrication. OOFELIE::Multiphysics was used by ONERA to simulate a vibrating inertial accelerometer and optimize its performance.
A Survey on Secure Alternate Path Selection for Enhanced Network Lifetime in ...IRJET Journal
This document summarizes a research paper that proposes techniques to enhance the lifetime of wireless sensor networks. It discusses how sensor nodes closer to the sink node consume more energy transmitting data, creating hotspots and shortening the network's lifetime. To address this, the paper proposes using alternate shortest paths to route data and relocating the sink node when the energy of alternate paths gets low. It also uses elliptic curve cryptography and a hybrid encryption method using AES and ECC to securely transmit data and further increase the network lifetime. Evaluation results show the proposed energy-aware sink relocation technique effectively enhances the network lifetime of wireless sensor networks.
A secure service provisioning framework for cyber physical cloud computing sy...ijdpsjournal
Cyber physical systems (CPS) are mission critical systems engineered by combination of cyber and
physical systems respectively. These systems are tightly coupled, resource constrained systems and have
dynamic real time applications. Due to the limitation of resources, and in order to improve the efficiency of
the CPS systems, they are combined with cloud computing architecture, and are called as Cyber Physical
Cloud Computing Systems (CPCCS). These CPCCS have critical care applications where security of the
systems is a major concern. Therefore, we propose a Secure Service provisioning architecture for Cyber
Physical Cloud Computing Systems (CPCCS), which includes the combination of technologies such as
CPS, Cloud Computing and Wireless Sensor Networks. In addition to this, we also highlight various
threats/attacks; security requirements and mechanisms that are applicable to CPCCS at different layers
and propose two security models that can be adapted in a layered architectural format.
The document discusses thesis topics related to wireless sensor networks (WSN), providing examples of 5 potential WSN thesis ideas that focus on energy efficient transmission, dependability analysis, secure data outsourcing to cloud-WSN systems, uneven clustering algorithms, and energy optimized routing. It also lists the typical sections included in a WSN thesis, such as introductions, statements of proposed work, research goals, methodologies, results, and conclusions. Contact information is provided for getting guidance on WSN or other network simulation tool related theses.
Deep learning and feature extraction for time series forecastingPavel Filonov
This document outlines the use of deep learning and feature extraction techniques for time series forecasting. It discusses using artificial neural networks like RNNs on raw time series data and on extracted features. RNNs can be used for anomaly detection and forecasting. The document also discusses modeling quasi-periodic time series using RNNs with LSTM units, extracting features through clustering, and evaluating models on forecast horizons of minutes to segments.
This document discusses security protocols for high performance grid computing architectures. It analyzes the different network layers in grid computing protocols and identifies various security disciplines. It also analyzes various security suites available in the TCP/IP protocol architecture. The paper aims to define security disciplines at different levels of cluster computing architecture and propose applicable security suites from the TCP/IP security protocol suite. Grid computing allows sharing and aggregation of distributed computing resources to enable more powerful applications. Security is an important consideration in grid computing due to sharing resources across administrative domains.
Machine Learning (ML) in Wireless Sensor Networks (WSNs)mabualsh
Wireless sensor networks (WSNs) and the Internet of Things (IoT) monitor dynamic environments that change rapidly over time. This dynamic behavior is either caused by external factors or initiated by the system designers themselves. WSNs and IoT often adopt machine learning to eliminate the need for unnecessary redesign. Machine learning inspires many practical solutions that maximize resource utilization and prolong the network's lifespan. These slides present an extensive literature review of machine learning methods to address common issues in WSNs and IoT.
Edal an energy efficient, delay-aware, and lifetime-balancing data collection...LogicMindtech Nologies
NS2 Projects for M. Tech, NS2 Projects in Vijayanagar, NS2 Projects in Bangalore, M. Tech Projects in Vijayanagar, M. Tech Projects in Bangalore, NS2 IEEE projects in Bangalore, IEEE 2015 NS2 Projects, WSN and MANET Projects, WSN and MANET Projects in Bangalore, WSN and MANET Projects in Vijayangar
Biological Immunity and Software Resilience: Two Faces of the Same Coin?SERENEWorkshop
The document discusses the similarities between biological immunity and software resilience. It proposes that biological systems are resilient, with the immune system being a prime example due to its ability to adapt, make decisions through distributed agents, and defend the body through learning. An actor-based model is presented as a way to engineer resilience into software by drawing inspiration from immune system principles like replication, containment, and delegation. A bio-inspired architecture is described that uses supervisor actors to detect changes and spawn helper/killer actors to address issues while maintaining system function. Future work areas are identified like automatic failure recognition, dynamic learning, and multi-layer management of failures.
Considering Execution Environment Resilience: A White-Box ApproachSERENEWorkshop
The document discusses an approach called semi-purification for automatically generating unit test cases from source code. Semi-purification replaces dependencies like global variables and database calls in the source code with function parameters. This allows existing automated test case generation tools to be used by treating the semi-purified code as if it were pure. Challenges discussed include handling shared subroutines, loops, and concurrency. The goal is to increase test coverage for complex, distributed systems with frequent changes like those used at CERN.
This document summarizes a presentation on system-level concurrent error detection. It discusses specifying reliability constraints in system specifications, design methodologies that provide error detection capabilities through redundancy, and a two-level hardware/software partitioning approach that first considers traditional costs and then analyzes reliability constraints. The goal is to adopt design for reliability approaches earlier in the system design process to significantly impact costs like timing, energy and area.
Hot Stand-By Disaster Recovery Solutions for Ensuring the Resilience of Railw...SERENEWorkshop
Specifications of modern railway control systems often include resilience requirements in order to quickly and safely recovery from disasters (e.g. system-level failures). To that aim, spatial redundancy is required, with main and backup systems installed in fully isolated buildings, together with very short switchover times from main to backup systems in case of disasters. In order to fulfil those requirements, Ansaldo STS has developed a system-level hot stand-by solution allowing to quickly and smoothly switch from the main system to the back-up one, ensuring the necessary continuity of service and transparency to train supervisors and other operators. The functional architecture of such a solution is able to keep aligned the safety-critical nucleuses, typically based on N-modular redundancy (i.e. ‘KooM’ voting), of the main and the back-up systems. Such a coherent alignment must be kept in terms of both interfaced field devices (e.g. interlocking signals, track circuits, switch points, etc.) – on the ‘bottom’ level – and control room Human Machine Interfaces (HMI) – on the ‘top’ level. The solution is based on heterogeneous and redundant network links (copper/fiber Ethernet/HyperRing) at different levels of system architecture. In this speech, the reference architecture and the fault-tolerance functionalities for disaster recovery are provided, considering the requirements of real railway and mass-transit installations.
Serene 2015
Davide Scaramuzza
Abstract: With drones becoming more and more popular, safety is a big concern. A critical situation occurs when a drone temporarily loses its GPS position information, which might lead it to crash. This can happen, for instance, when flying close to buildings where GPS signal is lost. In such situations, it is desirable that the drone can rely on fall-back systems and regain stable flight as soon as possible. In this talk, I will present novel methods to automatically recover and stabilize a quadrotor from any initial condition or execute emergency landing. On the one hand, this new technology will allow quadrotors to be launched by simply tossing them in the air, like a “baseball ball”. On the other hand, it will allow them to recover back into stable flight or land on a safe area after a system failure. Since this technology does not rely on any external infrastructure, such as GPS, it enables the safe use of drones in both indoor and outdoor environments. Thus, it can become relevant for commercial use of drones, such as parcel delivery.
Recent videos:
Automatic failure recovery without GPS: https://youtu.be/pGU1s6Y55JI
Autonomous Landing-site detection and landing: https://youtu.be/phaBKFwfcJ4
SERENE 2014 Workshop: Paper "Adaptive Domain-Specific Service Monitoring"SERENEWorkshop
- An adaptive service monitoring approach that considers domain-specific errors, such as codec errors for streamed media, in addition to generic errors.
- The approach adapts the monitoring frequency for a particular service and error type based on the historical error rate to reduce monitoring costs.
- An evaluation using real-world data from Smart TV services found that the adaptive approach reduced monitoring costs by 30% with negligible impact on error detection quality.
SERENE 2014 Workshop: Paper "Advanced Modelling, Simulation and Verification ...SERENEWorkshop
SERENE 2014 - 6th International Workshop on Software Engineering for Resilient Systems
http://serene.disim.univaq.it/
Session 3: Verification and Validation
Paper 3: Advanced Modelling, Simulation and Verification for Future Traffic Regulation Optimisation
SERENE 2014 Workshop: Paper "Combined Error Propagation Analysis and Runtime ...SERENEWorkshop
SERENE 2014 - 6th International Workshop on Software Engineering for Resilient Systems
http://serene.disim.univaq.it/
Session 4: Monitoring
Paper 3: Combined Error Propagation Analysis and Runtime Event Detection in Process-driven Systems
SERENE 2014 Workshop: Paper "Simulation Testing and Model Checking: A Case St...SERENEWorkshop
SERENE 2014 - 6th International Workshop on Software Engineering for Resilient Systems
http://serene.disim.univaq.it/
Session 3: Verification and Validation
Paper 2: Simulation Testing and Model Checking: A Case Study Comparing these Approaches
SERENE 2014 Workshop: Paper "Using Instrumentation for Quality Assessment of ...SERENEWorkshop
SERENE 2014 - 6th International Workshop on Software Engineering for Resilient Systems
http://serene.disim.univaq.it/
Session 4: Monitoring
Paper 1: Using Instrumentation for Quality Assessment of Resilient Software in Embedded Systems
SERENE 2014 Workshop: Paper "Verification and Validation of a Pressure Contro...SERENEWorkshop
SERENE 2014 - 6th International Workshop on Software Engineering for Resilient Systems
http://serene.disim.univaq.it/
Session 3: Verification and Validation
Paper 1: Verification and Validation of a Pressure Control Unit for Hydraulic Systems
SERENE 2014 Workshop: Panel on "Views on Runtime Resilience Assessment of Dyn...SERENEWorkshop
The document summarizes a panel discussion on views of runtime resilience assessment of dynamic software systems held at SERENE 2014 in Budapest, Hungary. The panelists represented different domains related to resilience assessment, software engineering, dynamic systems design, and dependable computing. They discussed key challenges around metrics for characterizing resilience, defining dynamic workloads and changeloads, monitoring unbounded and dynamic systems, maintaining accurate runtime models, and standardizing resilience assessment techniques. The panelists emphasized the need for predictive monitoring and adaptation, rather than just detection, to ensure resilience in increasingly complex and evolving software systems.
Kevin Sullivan from the University of Virginia presented: "Cyber-Social Learning Systems: Take-Aways from First Community Computing Consortium Workshop on Cyber-Social Learning Systems" as part of the Cognitive Systems Institute Speaker Series.
SERENE 2014 Workshop: Paper "Formal Fault Tolerance Analysis of Algorithms fo...SERENEWorkshop
SERENE 2014 - 6th International Workshop on Software Engineering for Resilient Systems
http://serene.disim.univaq.it/
Session 2: Analysis of Resilience
Paper : Formal Fault Tolerance Analysis of Algorithms for Redundant Systems in Early Design Stages
SERENE 2014 School: Resilience in Cyber-Physical Systems: Challenges and Oppo...SERENEWorkshop
SERENE 2014 School on Engineering Resilient Cyber Physical Systems
Talk: Resilience in Cyber-Physical Systems: Challenges and Opportunities, by Gabor Karsai
Architectures for Cyber-Physical Systems, or Why Ivan Doesn’t Want to GraduateIvan Ruchkin
A fresh multidisciplinary research and engineering area of Cyber-Physical Systems (CPSs) lies on an intersection of more traditional fields, like mechanical and electrical engineering, and newer approaches from AI, ubiquitous computing, and software engineering. Although modeling is a core method in these areas, the concrete mindsets and methods for it are very diverse, which makes system-level reasoning across models more complicated. For instance, it is difficult to predict how smoothing a control algorithm represented in Simulink would affect schedulability guarantees provided by a rate-monotonic analysis model. Conveniently, software architecture is well-known for reconciling concerns by loosening up model semantics, which makes it a promising tool for model-based design of CPSs. This talk discusses several examples from the automotive and robotics domains to expose the challenges of using heterogeneous models and how software architecture might help alleviate those. All these considerations will be linked to the mysterious second part of the title.
The document introduces the new mainframe and its capabilities. It outlines that mainframes are used by large organizations to host commercial databases and applications requiring high security and availability. Mainframes can process large volumes of different workloads concurrently. Typical mainframe roles include system programmers, operators, developers and administrators. Common operating systems are z/OS, z/VM, VSE, and Linux for zSeries.
AIST Super Green Cloud: lessons learned from the operation and the performanc...Ryousei Takano
This document discusses lessons learned from operating the AIST Super Green Cloud (ASGC), a fully virtualized high-performance computing (HPC) cloud system. It summarizes key findings from the first six months of operation, including performance evaluations of SR-IOV virtualization and HPC applications. It also outlines conclusions and future work, such as improving data movement efficiency across hybrid cloud environments.
3tera provides cloud computing services that allow information technology assets to be more private and secure in the cloud compared to traditional data centers. The cloud offers massive scalability on demand with computing, storage, and other services that users can access without knowledge of the underlying technology. This reduces capital expenditures by allowing resources to be shared and only paying for what is consumed. 3tera's cloud platform further reduces costs by handling hardware failures and providing a single management interface for resources, applications, and users. Cloud computing will continue to evolve and eventually all information technology, including legacy systems, web applications, and storage, will be hosted in the cloud, which will become the next great utility for IT.
This document discusses key aspects of enterprise cloud computing including definitions of cloud computing, the SPI model of cloud services, and architectural choices and challenges presented by cloud computing. Some of the main challenges mentioned are the need for elastic resources, stateless and asynchronous system designs, data sharding, and ensuring redundancy and high availability despite constant failures.
OpenNebula Conf 2014 | From private cloud to laaS public services for Catalan...NETWAYS
Nowadays, Catalan Academic and research institutions can enjoy self-service cloud infrastructure in order to meet their application needs in a flexible pay per use mode. An self-service platform is available for managing servers, networks and assigned storage from the Universities Consortium Data Centers, allowing users access to a customizable infrastructure with an orientation towards the so-call virtual DC.
OpenNebulaConf 2014 - From private cloud to laaS public services for Catalan ...OpenNebula Project
This document summarizes a presentation about moving a Catalan research and education community from a private cloud to public infrastructure as a service (IaaS) clouds.
The presentation discusses the evolution of the community's data center services from dedicated servers to virtual data centers and hybrid solutions using OpenNebula. It provides details on the new OpenNebula 4.8 installation including host configuration, networking, storage, and software ecosystem.
The presentation addresses some myths about cloudification including the relevance of the hypervisor and whether clouds need to always be on or can be hybrid. It concludes that the community now has IaaS services in their hands and should promote OpenNebula usage.
This document discusses virtualization techniques for embedded systems to enable the cloud of things (CoT). It begins by introducing CoT as the integration of the internet of things (IoT) and cloud computing to realize the vision of smart networked systems and societies. It then discusses fog computing as an extension of cloud computing that is better suited for IoT due to features like edge location. The document evaluates whether current embedded system hardware and virtualization techniques can support CoT/IoT and finds that full, para, and container virtualization as well as type-1 and type-2 hypervisors are appropriate options. Key frameworks like Xen and KVM that support ARM architecture are also mentioned.
This document discusses re-engineering engineering approaches from a top-down to a bottom-up model. It addresses issues facing CIOs like legacy systems, skills shortages, and changing business needs. The author advocates for evolvability, specialization, experimentation, and diversity to allow for continuous change and innovation. The road ahead is seen as requiring more modularity, adaptability, personalization and application interoperability to deal with increasing complexity. The future of computing is envisioned as autonomous systems that are self-healing, self-optimizing through technologies like SDN, NFV and platform-as-a-service models.
Virtualization plays a vital role in cloud computing by allowing for the efficient sharing of hardware resources. It involves the creation of virtual instances of operating systems, servers, storage, and networks. A hypervisor manages these virtual machines and allows multiple instances to run simultaneously on a single physical machine. Virtualization provides benefits like cost effectiveness, flexibility, and isolation of applications and operating systems. It is a key technology enabling cloud computing services like Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS).
Virtualization allows multiple virtual machines to run on a single physical machine. It relies on hardware advances like multi-core CPUs and networking improvements. Virtualization works by either emulating hardware, trapping privileged instructions and emulating them, dynamic binary translation, or paravirtualization where the guest OS is aware it is virtualized. I/O virtualization can emulate devices, use paravirtualized drivers, or directly assign devices to VMs. This enables server consolidation and efficient utilization of resources in cloud computing.
Storm is an open-source distributed real-time computation system. It provides a framework for processing unbounded streams of data reliably and fault-tolerantly. Storm allows data to be analyzed in real-time using spouts, bolts, and topologies. It is scalable, fault-tolerant, guarantees processing, and is easy to code. Storm powers many real-time systems at Twitter and is useful for applications like analytics, personalization, and ETL.
New Threats, New Approaches in Modern Data CentersIben Rodriguez
New Threats, New Approaches in Modern Data Centers - A Presentation by NPS at CENIC conference 11:00 am - 12:00 pm, Wednesday, March 22, 2017 – in San Diego, California
The standard approach to securing data centers has historically emphasized strong perimeter protection to keep threats on the outside of the network. However, this model is ineffective for handling new types of threats—including advanced persistent threats, insider threats, and coordinated attacks. A better model for data center security is needed: one that assumes threats can be anywhere and probably are everywhere and then, through automation, acts accordingly. Using micro-segmentation, fine-grained network controls enable unit-level trust, and flexible security policies can be applied all the way down to a network interface. In this joint presentation between customer, partner, and VMware, the fundamental tenants of micro-segmentation will be discussed. Presenters will describe how the Naval Postgraduate School has incorporated these principles into the architecture and design of a multi-tenant Cybersecurity Lab environment to deliver security training to national and international government personnel.
Edgar Mendoza, IT Specialist, Information Technology and Communications Services (ITACS) Naval Postgraduate School
Eldor Magat, Computer Specialist, ITACS, Naval Postgraduate School
Mike Monahan, Network Engineer, ITACS, Naval Postgraduate School
Iben Rodriguez, Brocade Resident SDN Delivery Consultant, ITACS, Naval Postgraduate School
Brian Recore, NSX Systems Engineer, VMware, Inc.
https://youtu.be/mYBbIbfKkGU?t=1h7m16s
Copied from the program with corrections - https://adobeindd.com/view/publications/b9fbbdf0-60f1-41dc-8654-3d2141b0bf54/nh4h/publication-web-resources/pdf/Conference_Agenda_2017_v1.pdf
This document compares Cisco and VMware's virtual networking technology solutions for SCANA Corporation. It defines virtual networking/software defined networking and explains how it works. VMware's solution (NSX) is software-based and overlays a virtual network, while Cisco's (ACI) is hardware-based. The document concludes that VMware would be a better fit for SCANA since they already use VMware's virtualization technology and would not need costly new Cisco hardware. Implementing a virtual networking solution would improve productivity by speeding up application/file transfers and simplifying network management.
The document discusses steps for an IoT to Big Data approach, including acquiring IoT data, edge streaming analytics, big data analytics for IoT, and hardware platforms for pilots. It describes successes with IoT projects in areas like connected healthcare. It outlines the IoT and big data landscape models and focuses on solutions for data visibility, critical situations, extracting value from IoT data, and infrastructure including networks and cloud computing. The presentation emphasizes how Dimension Data offers full-stack solutions across the IoT and big data models and can help clients do incredible things with IoT.
UnifiedSessionsManager Application of Virtualisation and CloudComputing for Development and Runtime Systems - Embedded World 2012 Session 16:Internet Technology and M2M I
Virtualization plays a key role in cloud computing by allowing for the efficient sharing of hardware resources. It allows a single physical machine to run multiple virtual machines, maximizing resource utilization. Common forms of virtualization include server, storage, network, desktop, and memory virtualization. A hypervisor manages virtual machines and provides an abstraction layer between hardware and software. Virtualization provides benefits like cost effectiveness, flexibility, and isolation of applications and operating systems. It is an important technology enabling cloud computing services.
The document discusses the Catalan Universities Services Consortium's (CSUC) transition from providing private cloud services to Infrastructure as a Service public cloud services for the Catalan research and education community. Specifically, it summarizes CSUC's installation of OpenNebula 4.8 on their infrastructure to provide virtual data centers, IaaS solutions, and public cloud services on-premise. It also addresses some myths about cloudification processes and hypervisor relevance, and concludes that CSUC has put the power to use their cloud services into the hands of their users.
OpenNebula TechDay Boston 2015 - Bringing Private Cloud Computing to HPC and ...OpenNebula Project
This document discusses bringing private cloud computing to high-performance computing (HPC) and science. It outlines the challenges of using cloud infrastructure for HPC workloads, including performance penalties from virtualization and input/output overhead. It then describes OpenNebula, an open-source tool for managing private clouds that addresses these challenges. Finally, it presents several case studies of research institutions that have implemented private HPC clouds using OpenNebula to gain efficiencies while supporting a variety of applications and user groups.
- The document discusses building a predictive anomaly detection model for network traffic using streaming data technologies.
- It proposes using Apache Kafka to ingest and process network packet and Netflow data in real-time, and Akka clustering to build predictive models that can guide human cybersecurity experts.
- The solution aims to more effectively guide human awareness of network threats by complementing localized rule-matching with predictive modeling of aggregate network behavior based on streaming metrics.
Similar to SERENE 2014 School: Measurement-Driven Resilience Design of Cloud-Based Cyber-Physical Systems (20)
Software Engineering and Project Management - Introduction, Modeling Concepts...Prakhyath Rai
Introduction, Modeling Concepts and Class Modeling: What is Object orientation? What is OO development? OO Themes; Evidence for usefulness of OO development; OO modeling history. Modeling
as Design technique: Modeling, abstraction, The Three models. Class Modeling: Object and Class Concept, Link and associations concepts, Generalization and Inheritance, A sample class model, Navigation of class models, and UML diagrams
Building the Analysis Models: Requirement Analysis, Analysis Model Approaches, Data modeling Concepts, Object Oriented Analysis, Scenario-Based Modeling, Flow-Oriented Modeling, class Based Modeling, Creating a Behavioral Model.
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...IJECEIAES
Medical image analysis has witnessed significant advancements with deep learning techniques. In the domain of brain tumor segmentation, the ability to
precisely delineate tumor boundaries from magnetic resonance imaging (MRI)
scans holds profound implications for diagnosis. This study presents an ensemble convolutional neural network (CNN) with transfer learning, integrating
the state-of-the-art Deeplabv3+ architecture with the ResNet18 backbone. The
model is rigorously trained and evaluated, exhibiting remarkable performance
metrics, including an impressive global accuracy of 99.286%, a high-class accuracy of 82.191%, a mean intersection over union (IoU) of 79.900%, a weighted
IoU of 98.620%, and a Boundary F1 (BF) score of 83.303%. Notably, a detailed comparative analysis with existing methods showcases the superiority of
our proposed model. These findings underscore the model’s competence in precise brain tumor localization, underscoring its potential to revolutionize medical
image analysis and enhance healthcare outcomes. This research paves the way
for future exploration and optimization of advanced CNN models in medical
imaging, emphasizing addressing false positives and resource efficiency.
Comparative analysis between traditional aquaponics and reconstructed aquapon...bijceesjournal
The aquaponic system of planting is a method that does not require soil usage. It is a method that only needs water, fish, lava rocks (a substitute for soil), and plants. Aquaponic systems are sustainable and environmentally friendly. Its use not only helps to plant in small spaces but also helps reduce artificial chemical use and minimizes excess water use, as aquaponics consumes 90% less water than soil-based gardening. The study applied a descriptive and experimental design to assess and compare conventional and reconstructed aquaponic methods for reproducing tomatoes. The researchers created an observation checklist to determine the significant factors of the study. The study aims to determine the significant difference between traditional aquaponics and reconstructed aquaponics systems propagating tomatoes in terms of height, weight, girth, and number of fruits. The reconstructed aquaponics system’s higher growth yield results in a much more nourished crop than the traditional aquaponics system. It is superior in its number of fruits, height, weight, and girth measurement. Moreover, the reconstructed aquaponics system is proven to eliminate all the hindrances present in the traditional aquaponics system, which are overcrowding of fish, algae growth, pest problems, contaminated water, and dead fish.
Discover the latest insights on Data Driven Maintenance with our comprehensive webinar presentation. Learn about traditional maintenance challenges, the right approach to utilizing data, and the benefits of adopting a Data Driven Maintenance strategy. Explore real-world examples, industry best practices, and innovative solutions like FMECA and the D3M model. This presentation, led by expert Jules Oudmans, is essential for asset owners looking to optimize their maintenance processes and leverage digital technologies for improved efficiency and performance. Download now to stay ahead in the evolving maintenance landscape.
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...IJECEIAES
Climate change's impact on the planet forced the United Nations and governments to promote green energies and electric transportation. The deployments of photovoltaic (PV) and electric vehicle (EV) systems gained stronger momentum due to their numerous advantages over fossil fuel types. The advantages go beyond sustainability to reach financial support and stability. The work in this paper introduces the hybrid system between PV and EV to support industrial and commercial plants. This paper covers the theoretical framework of the proposed hybrid system including the required equation to complete the cost analysis when PV and EV are present. In addition, the proposed design diagram which sets the priorities and requirements of the system is presented. The proposed approach allows setup to advance their power stability, especially during power outages. The presented information supports researchers and plant owners to complete the necessary analysis while promoting the deployment of clean energy. The result of a case study that represents a dairy milk farmer supports the theoretical works and highlights its advanced benefits to existing plants. The short return on investment of the proposed approach supports the paper's novelty approach for the sustainable electrical system. In addition, the proposed system allows for an isolated power setup without the need for a transmission line which enhances the safety of the electrical network
Use PyCharm for remote debugging of WSL on a Windo cf5c162d672e4e58b4dde5d797...shadow0702a
This document serves as a comprehensive step-by-step guide on how to effectively use PyCharm for remote debugging of the Windows Subsystem for Linux (WSL) on a local Windows machine. It meticulously outlines several critical steps in the process, starting with the crucial task of enabling permissions, followed by the installation and configuration of WSL.
The guide then proceeds to explain how to set up the SSH service within the WSL environment, an integral part of the process. Alongside this, it also provides detailed instructions on how to modify the inbound rules of the Windows firewall to facilitate the process, ensuring that there are no connectivity issues that could potentially hinder the debugging process.
The document further emphasizes on the importance of checking the connection between the Windows and WSL environments, providing instructions on how to ensure that the connection is optimal and ready for remote debugging.
It also offers an in-depth guide on how to configure the WSL interpreter and files within the PyCharm environment. This is essential for ensuring that the debugging process is set up correctly and that the program can be run effectively within the WSL terminal.
Additionally, the document provides guidance on how to set up breakpoints for debugging, a fundamental aspect of the debugging process which allows the developer to stop the execution of their code at certain points and inspect their program at those stages.
Finally, the document concludes by providing a link to a reference blog. This blog offers additional information and guidance on configuring the remote Python interpreter in PyCharm, providing the reader with a well-rounded understanding of the process.
Null Bangalore | Pentesters Approach to AWS IAMDivyanshu
#Abstract:
- Learn more about the real-world methods for auditing AWS IAM (Identity and Access Management) as a pentester. So let us proceed with a brief discussion of IAM as well as some typical misconfigurations and their potential exploits in order to reinforce the understanding of IAM security best practices.
- Gain actionable insights into AWS IAM policies and roles, using hands on approach.
#Prerequisites:
- Basic understanding of AWS services and architecture
- Familiarity with cloud security concepts
- Experience using the AWS Management Console or AWS CLI.
- For hands on lab create account on [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
# Scenario Covered:
- Basics of IAM in AWS
- Implementing IAM Policies with Least Privilege to Manage S3 Bucket
- Objective: Create an S3 bucket with least privilege IAM policy and validate access.
- Steps:
- Create S3 bucket.
- Attach least privilege policy to IAM user.
- Validate access.
- Exploiting IAM PassRole Misconfiguration
-Allows a user to pass a specific IAM role to an AWS service (ec2), typically used for service access delegation. Then exploit PassRole Misconfiguration granting unauthorized access to sensitive resources.
- Objective: Demonstrate how a PassRole misconfiguration can grant unauthorized access.
- Steps:
- Allow user to pass IAM role to EC2.
- Exploit misconfiguration for unauthorized access.
- Access sensitive resources.
- Exploiting IAM AssumeRole Misconfiguration with Overly Permissive Role
- An overly permissive IAM role configuration can lead to privilege escalation by creating a role with administrative privileges and allow a user to assume this role.
- Objective: Show how overly permissive IAM roles can lead to privilege escalation.
- Steps:
- Create role with administrative privileges.
- Allow user to assume the role.
- Perform administrative actions.
- Differentiation between PassRole vs AssumeRole
Try at [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
International Conference on NLP, Artificial Intelligence, Machine Learning an...gerogepatton
International Conference on NLP, Artificial Intelligence, Machine Learning and Applications (NLAIM 2024) offers a premier global platform for exchanging insights and findings in the theory, methodology, and applications of NLP, Artificial Intelligence, Machine Learning, and their applications. The conference seeks substantial contributions across all key domains of NLP, Artificial Intelligence, Machine Learning, and their practical applications, aiming to foster both theoretical advancements and real-world implementations. With a focus on facilitating collaboration between researchers and practitioners from academia and industry, the conference serves as a nexus for sharing the latest developments in the field.
Batteries -Introduction – Types of Batteries – discharging and charging of battery - characteristics of battery –battery rating- various tests on battery- – Primary battery: silver button cell- Secondary battery :Ni-Cd battery-modern battery: lithium ion battery-maintenance of batteries-choices of batteries for electric vehicle applications.
Fuel Cells: Introduction- importance and classification of fuel cells - description, principle, components, applications of fuel cells: H2-O2 fuel cell, alkaline fuel cell, molten carbonate fuel cell and direct methanol fuel cells.
SERENE 2014 School: Measurement-Driven Resilience Design of Cloud-Based Cyber-Physical Systems
1. Departmentof Measurementand InformationSystems
Budapest University of Technologyand Economics, Hungary
Measurement-Driven Resilience Design of Cloud-Based Cyber-Physical Systems
Imre Kocsis
ikocsis@mit.bme.hu
SERENE’14 AutumnSchool
2014.10.14.
3. Cyber-PhysicalSystems (CPSs)
3
Ubiquitousembeddedand networkedsystems thatcan monitor and control the physical world witha high level of intelligenceand dependabilityNetworkedembeddedsystemseverywhereClouds, „infusable” analytics, Big Data
7. Cyber-PhysicalSystems
Differentflavors
oNSF, EU, academia, industry…
Still: itis here
oFromsmartcities& IoTtoself- drivingcars
oScalable, reconfigurablebackendis a must
7
Health CareTransportationEnergy
8. „Classical” caseforcloudcomputing: a brainforaCPS
Video
surveillance
Citizen
devices
Env. sensors
…
Trafficcontrol
Situationalawareness
Deep analyticsNormaldayDisaster
See: Naphadeet. al(IBM), „SmarterCitiesand TheirInnovationChallanges”, Computer, 2011Elastic, reconfigurablecomputing Reconfiguration
17. Gartner, 2013
„For larger businesseswith existing internal data centers, well-managed virtualized infrastructure and efficient IT operations teams, IaaSfor steady-state workloads is often no less expensive, and may be more expensive, than an internal private cloud.”
„I needitnow, and needitfast…”?
18. Parallellizableloads
More and more embarrassinglyparallel, „scale- out” applicationcategoriesexist
NYT TimesMachine: publicdomainarchive
oConversiontoweb-friendlyformat: ApacheHadoop, a fewhundredVMs, 36 hours
Inthecloud: coststhesameaswithoneVM
Practically: „speedupforfree”
21. 1.) Big Data atRest
Distributedstorage
„Computationtodata”
„Atrest Big Data”
oNo update
oNo sampling
„Not true, but a very, very good lie!”
(T.Pratchett, Nightwatch)
49. Short transient faults –long recovery
8 sec platform overload
30 sec service outage
120 sec SLA violation
As if you unplug your desktop for a second...
50. Deterministic (?!) run-time in the public cloud...
Variance tolerable by overcapacity
Performance outage intolerable by overcapacity
56. Benchmarking (a pragmatictakeon)
(De-facto) standard applications
withwelldefinedexecutionmetrics
thatmayexercisespecificsubsystems
tocompareIT systemsviasaidmetrics.
Popularbenchmarks: e.g. PhoronixTest Suite
Benchmarking asa Service: cloudharmony.com
59. A performance featuremodel
+ exp. behavior, homogeneity, stability
Li, Z., OBrien, L., Cai, R., & Zhang, H. (2012). Towards a Taxonomy of Performance Evaluation of Commercial Cloud Services.
In 2012 IEEE Fifth International Conference on Cloud Computing (pp. 344–351). IEEE. doi:10.1109/CLOUD.2012.74
60. ModelingIaaSperformanceexperiments
Li, Z., OBrien, L., Cai, R., & Zhang, H. (2012). Towards a Taxonomy of Performance Evaluation of Commercial Cloud Services.
In 2012 IEEE Fifth International Conference on Cloud Computing (pp. 344–351). IEEE. doi:10.1109/CLOUD.2012.74
61. „Cloudmetrology” and itsapplication
Full stack instrumentationFull adaptive data acquisitionFine-grained storageExploratory Data AnalysisConfirmatory Data Analysis Mystery shoppers and routine excercisesApplication sensitivity model(Platform) fault modelPerformance/capacity modelStructural defensesDynamic defenses MONITORING BENCHMARKING
62. Example:characterizingVDI „CPU ReadyTime”
„Ready”: VM readytorun, butnotscheduled
oVDI: „stutter”
Rareevents
oSampling
Needsfinegranularity!
+ atleasta fewmonths
Very„wide” data
Result: ~QoEcapacity+ load
Big Data tooling
64. Workflow? (As of now)
Classical
tools
Slow EDA
On Big Data
Interactive EDA
On samples
statistics
on samples
Big Data
statistics
Hadoop,
Storm,
Cassandra,
…