This document discusses developing low-memory-footprint programs for iSeries. It explains that programs use memory when activated from disk by a loader. It then covers understanding program activation and the memory equation that determines usage. Key factors that influence memory usage are the object size, static storage, and dependencies of main and service programs. The document provides tips for optimizing static storage usage such as reducing variable declarations and using dynamic memory allocation when possible.
An Efficient Decentralized Load Balancing Algorithm in Cloud ComputingAisha Kalsoom
This document proposes a new efficient decentralized load balancing algorithm for cloud computing. It consists of two phases: 1) a request sequencing phase where incoming user requests are sequenced to minimize wait times, and 2) a load transferring phase where a load balancer calculates resource utilization of each VM and transfers tasks to less utilized VMs. This algorithm aims to improve load balancing performance and achieve more efficient resource utilization in cloud computing environments.
This document discusses Dimensions Computation (DC), a solution for handling massive real-time data streams. DC extracts meaningful statistics and identifies trends over time by isolating the effect of different variables. It works by splitting data into tuples containing dimensions and measures. Dimensions are variables that can impact measures. DC produces aggregations of measures using dimension combinations. It is implemented using Apache Apex, which allows building distributed, fault-tolerant applications on Hadoop for real-time streaming data. DC is available through Data Torrent and resources for learning more are provided.
This document summarizes a major project on dynamically scaling web applications in a virtualized cloud computing environment. The project is submitted by Mallika Malhotra and Sanya Kapoor to Mr. Prakash Kumar. The project proposes an algorithm and architecture to dynamically add or remove virtual machines based on resource usage to efficiently scale the system and reduce costs. Key technologies used include the Xen hypervisor, Java, Apache, Python, and Tomcat.
A Spanish city council implemented power management software on 3000 computers to automatically put computers into low-power sleep states during periods of inactivity. The software tracked computer power states and user activity every second. It found that after implementing the software, computers spent more time in low-power sleep states, saving an estimated 53.9 kWh per computer per year. This was within 1.1% of projections, meeting the customer's goal of less than 20% deviation from projected savings.
This document provides definitions and explanations related to high performance computing (HPC). It defines HPC as utilizing custom-designed, high-performance processors or parallel, distributed, and grid computing techniques to solve large problems faster than possible on single commodity systems. Parallel computing involves multiple processors working on the same problem, distributed computing involves loosely coupled systems working on related problems, and grid computing tightly couples systems to work together on single or related problems. The document notes HPC has had tremendous impact across many fields by enabling solutions to problems that were previously impossible to solve.
EC2 Masterclass from the AWS User Group Scotland MeetupIan Massingham
The document provides an overview of Amazon Elastic Compute Cloud (EC2) including what EC2 is, how it works, instance types, pricing models, and how to launch instances. Specifically:
- EC2 provides resizable compute capacity in the cloud and allows users to run and manage application servers and workloads.
- Users have complete control over their instances and can choose from different instance types optimized for compute, memory, storage or GPU.
- EC2 offers several pricing models including on-demand, reserved, and spot instances to provide flexibility and cost savings based on usage levels and predictability.
This Chapter provides a Background Review of Parallel and Distributed Computing. a focus is made on the concept of SISD, SIMD, MISD, MIMD.
It also gives an understanding of the notion of HPC (High-Performance Computing). A survey is done using some case studies to show why parallelism is needed. The chapter discusses the Amdahl's Law and the limitations. Gustafson's Law is also discussed.
This document discusses developing low-memory-footprint programs for iSeries. It explains that programs use memory when activated from disk by a loader. It then covers understanding program activation and the memory equation that determines usage. Key factors that influence memory usage are the object size, static storage, and dependencies of main and service programs. The document provides tips for optimizing static storage usage such as reducing variable declarations and using dynamic memory allocation when possible.
An Efficient Decentralized Load Balancing Algorithm in Cloud ComputingAisha Kalsoom
This document proposes a new efficient decentralized load balancing algorithm for cloud computing. It consists of two phases: 1) a request sequencing phase where incoming user requests are sequenced to minimize wait times, and 2) a load transferring phase where a load balancer calculates resource utilization of each VM and transfers tasks to less utilized VMs. This algorithm aims to improve load balancing performance and achieve more efficient resource utilization in cloud computing environments.
This document discusses Dimensions Computation (DC), a solution for handling massive real-time data streams. DC extracts meaningful statistics and identifies trends over time by isolating the effect of different variables. It works by splitting data into tuples containing dimensions and measures. Dimensions are variables that can impact measures. DC produces aggregations of measures using dimension combinations. It is implemented using Apache Apex, which allows building distributed, fault-tolerant applications on Hadoop for real-time streaming data. DC is available through Data Torrent and resources for learning more are provided.
This document summarizes a major project on dynamically scaling web applications in a virtualized cloud computing environment. The project is submitted by Mallika Malhotra and Sanya Kapoor to Mr. Prakash Kumar. The project proposes an algorithm and architecture to dynamically add or remove virtual machines based on resource usage to efficiently scale the system and reduce costs. Key technologies used include the Xen hypervisor, Java, Apache, Python, and Tomcat.
A Spanish city council implemented power management software on 3000 computers to automatically put computers into low-power sleep states during periods of inactivity. The software tracked computer power states and user activity every second. It found that after implementing the software, computers spent more time in low-power sleep states, saving an estimated 53.9 kWh per computer per year. This was within 1.1% of projections, meeting the customer's goal of less than 20% deviation from projected savings.
This document provides definitions and explanations related to high performance computing (HPC). It defines HPC as utilizing custom-designed, high-performance processors or parallel, distributed, and grid computing techniques to solve large problems faster than possible on single commodity systems. Parallel computing involves multiple processors working on the same problem, distributed computing involves loosely coupled systems working on related problems, and grid computing tightly couples systems to work together on single or related problems. The document notes HPC has had tremendous impact across many fields by enabling solutions to problems that were previously impossible to solve.
EC2 Masterclass from the AWS User Group Scotland MeetupIan Massingham
The document provides an overview of Amazon Elastic Compute Cloud (EC2) including what EC2 is, how it works, instance types, pricing models, and how to launch instances. Specifically:
- EC2 provides resizable compute capacity in the cloud and allows users to run and manage application servers and workloads.
- Users have complete control over their instances and can choose from different instance types optimized for compute, memory, storage or GPU.
- EC2 offers several pricing models including on-demand, reserved, and spot instances to provide flexibility and cost savings based on usage levels and predictability.
This Chapter provides a Background Review of Parallel and Distributed Computing. a focus is made on the concept of SISD, SIMD, MISD, MIMD.
It also gives an understanding of the notion of HPC (High-Performance Computing). A survey is done using some case studies to show why parallelism is needed. The chapter discusses the Amdahl's Law and the limitations. Gustafson's Law is also discussed.
Deployment Checkup: How to Regularly Tune Your Cloud Environment - RightScale...RightScale
The document discusses the importance of regularly tuning cloud environments through deployment checkups. It highlights key areas to focus on during checkups, including cost optimization by identifying unused resources, ensuring optimal server utilization, implementing high availability and disaster recovery strategies, addressing security issues, and following best practices. Regular checkups help avoid inefficiencies that can arise over time and ensure deployments are optimized for cost, performance, availability and security.
Parallel computing involves solving computational problems simultaneously using multiple processors. It breaks problems into discrete parts that can be solved concurrently rather than sequentially. Parallel computing provides benefits like reduced time/costs to solve large problems and ability to model complex real-world phenomena. Common forms include bit-level, instruction-level, data, and task parallelism. Parallel resources can include multiple cores/processors in a single computer or networks of computers.
This chapter discusses various classification attributed to parallel architectures. It also introduces related parallel programming models and presents the actions of these models on parallel architectures. Notions such as Data parallelism Task parallelism, Tighty and Coupled system, UMA/NUMA, Multicore computing, Symmetric multiprocessing, Distributed Computing, Cluster computing, Shared memory without thread/Thread, etc..
An efficient approach for load balancing using dynamic ab algorithm in cloud ...bhavikpooja
This document outlines a proposed approach for efficient load balancing using a dynamic Ant-Bee algorithm in cloud computing. It discusses limitations of existing ant colony and bee colony algorithms for load balancing. The author aims to develop a new AB algorithm approach that combines aspects of ant colony optimization and bee colony algorithms to improve load balancing optimization and overcome issues like slow convergence and tendency to stagnate in ant colony algorithms. The proposed approach would leverage both the dynamic path finding of ants and pheromone updating of bees for more effective load balancing in cloud environments.
Multi objective vm placement using cloudsimKhalidAnsari60
This document presents a multi-objective virtual machine (VM) placement approach using Particle Swarm Optimization (PSO) and CloudSim. PSO is applied to optimize multiple objectives like energy consumption, load balancing, and resource utilization when placing VMs on physical machines in a cloud computing environment. CloudSim, a cloud simulation tool, is used to test the PSO-based VM placement approach without using real cloud infrastructure and resources. The approach involves initializing VM demands and particle positions, evaluating fitness values, and updating particle velocities and positions through iterations to determine the optimal VM placement solution.
CloneCloud proposes a flexible architecture that seamlessly uses cloud resources to augment mobile applications in an energy-efficient manner. It clones a mobile app and partitions it at runtime to migrate computation-heavy threads to the clone in the cloud. This allows threads to leverage faster CPUs and hardware accelerations remotely while keeping other functionality local. A static analyzer identifies legal partitions, a dynamic profiler collects execution data to build cost models, and an optimization solver picks optimal partitions to minimize time and energy. The prototype delivers significant speedups and energy reductions without requiring programmer involvement in partitioning. However, it does not give programmers flexibility over partitioning and may not cover all parameter combinations.
MapReduce is a programming model and an implementation for processing and generating big data sets with parallel & distributed algorithms on a cluster. It is a programming paradigm that enables massive scalability across hundreds or thousands of servers in a cluster for distributed computing of jobs. It is a Distributed Data Processing Algorithm mainly inspired by Functional Programming. In the MapReduce process, big tasks are split into smaller tasks and then they are assigned to several systems for processing. Introduced by Google, it is a reliable and efficient way to process data sets in cluster environments. MapReduce runs in the background to provide scalability, simplicity, speed, recovery and easy solutions for data processing.
Weather and Climate Visualization softwareRahul Gupta
The document describes a software project to develop a visualization tool for weather and climate data analysis. The tool will read netCDF files and allow users to analyze the data, perform statistical operations, generate interpolated spatial maps and images, and visualize shapefiles. The software will be developed using Java and JavaFX for the graphical user interface. It will implement design patterns like MVC and work with data formats like netCDF, shapefile, and others. The goal is to provide an easy to use tool for scientists to perform complex climate and weather data analysis and visualization without needing to write scripts.
This document provides an overview of cloud computing and the Eucalyptus platform. It defines cloud computing as a large-scale distributed computing paradigm that delivers dynamically scalable computing resources as a service over the Internet. It then describes Eucalyptus as an open-source software that implements cloud computing on computer clusters and is compatible with Amazon EC2. The document outlines the Eucalyptus cloud architecture including components like the Cloud Controller, Cluster Controller, Node Controller, Storage Controller, and Walrus storage. It provides examples of deploying data mining applications on Eucalyptus and Amazon EC2 clouds.
Load Balancing In Cloud Computing newpptUtshab Saha
The document discusses various load balancing algorithms for cloud computing including round robin, first come first serve (FCFS), and simulated annealing. It provides implementations of each algorithm in CloudSim and compares the results. Round robin and FCFS showed similar overall response times, data center processing times, and maximum/minimum values. Simulated annealing had slightly lower average overall response time. The document proposes using a genetic algorithm for host-side optimization to select the best host for virtual machine requests.
Oracle optimizer is very complex and is getting more complex with every version. This presentation covers some new optimizer behavior and how to deal with it
The document introduces the MapReduce programming model. It explains that MapReduce handles parallelization and distributed computing tasks like multi-threading, failure handling, and I/O behind the scenes. Developers focus on defining two functions: the mapper which splits input into key-value pairs, and the reducer which aggregates the output of mappers by keys. MapReduce processes large datasets by splitting input files into blocks, running the mapper function on each block in parallel, shuffling and sorting the outputs, and running the reducer to aggregate the results.
GECon2017_High-volume data streaming in azure_ Aliaksandr LaishaGECon_Org Team
The session will be focused on solutions that require high-throughput ingestion & streaming of data in real-time. You'll get familiar with different business uses-cases and architecture examples to get a common idea as well as understand the concepts of stream processing systems. Next, you'll get deep insights into functional and non-functional capabilities of Azure Event Hub service to see how it fits into the whole picture. Moreover we’ll take a look how to leverage Azure CosmosDB for high-throughput streaming when Event Hub is not suitable by different reasons.
This document describes the system architecture and modules of a smart home system called MyHome. The key modules are:
1. Hardware sensors and actuators that communicate wirelessly with the Central Unit and can turn lights on/off, detect motion, etc.
2. A Central Unit (Raspberry Pi) that communicates with the sensors/actuators via XBee, stores data in the cloud database, and receives commands from the mobile app.
3. A cloud database implemented with Google App Engine that stores home/device data and allows communication between the Central Unit and mobile app.
4. An Android mobile app that users can use to monitor cameras, control lights, and view the state of
Mobile Saturday. Тема 2. Особенности тестирования приложения на Android: Spec...GoIT
21 ноября GoITClub совместно с Zeo Alliance провели ивент, посвященный тестированию мобильных приложений.
Рассмотрели 2 самых популярных ОС - Andoird и iOS
Блок Android
1. Особенности операционной системы Android - Иван Мурзак (Android developer, Co-Founder&CTO at Capitan Inc.)
2. Особенности тестирования приложения на Android (Specific functional, Performance, Device park selection) - Михаил Железнов (QC Engineer at SoftServe)
3. Особенности тестирования приложения на Android (Human Interface Guideline, Tools) - Юлия Смирнова (QC Engineer at SoftServe)
4. Автоматизация тестирования верстки - Александр Хотемской (Senior Client Automation QA Enginner at Wargaming)
Блок iOS
1. Особенности операционной системы iOS - Ольга Макаревич (QA Engineer at EPAM)
2. Особенности тестирования приложений на iOS - Александр Буратынский ( Senior QA Analysyt at Global Logic)
3. Тестирование с использованием инструментов xCode - Максим Гонтар (Mobile Developer, Lead Engineer at Global Logic) - презентация отутствуе, было живой показ программы.
Видеозапись мероприятия можно посмотреть на официальном канале GoIT на Youtube
"Going Offline", one of the hottest mobile app trendsDerek Baron
One of the hottest trends in mobile is "going offline", yet organizations are faced with a tripling of time and cost when adding offline functionality to a business app. According to Forrester Research, the ability to work offline is "the most important and difficult mobile feature...and will be a consideration for nearly every modern application".
Meteor is a platform for building modern web applications using JavaScript. It allows developers to build real-time applications using a single language across client and server. Some key features of Meteor include latency compensation, reactivity across all layers of an application, and support for mobile development. The presentation provided an overview of Meteor's principles and architecture, including data on the wire, one language, database everywhere, and latency compensation. It also demonstrated building a simple topic voting app in Meteor.
How to Lower Android Power Consumption Without Affecting Performancerickschwar
The document discusses various ways mobile app developers can lower the power consumption of their apps without affecting performance. It begins by explaining that most apps do not efficiently use system resources like the processor, cellular radio, and display, wasting power and reducing battery life. It then provides tips for optimizing specific areas of power consumption, such as using the cellular radio efficiently by bundling network traffic, offloading tasks to hardware accelerators like the DSP to reduce CPU usage, and managing the display to minimize brightness. The document stresses that measuring power consumption is key, and provides tools developers can use to profile and optimize the power impact of their apps.
Mobile Synchronization Patterns for Large Volumes of DataOutSystems
Do your mobile business apps require large amounts of data? Is the complexity of "offline" causing you to lose sleep? Come and learn "4 Best Practices," and their supporting patterns, for dealing with the synchronization of large data volumes in mobile apps built with OutSystems. In addition, we will discuss how to avoid the problems that can pop up whenever dealing with these kinds of applications.
Deployment Checkup: How to Regularly Tune Your Cloud Environment - RightScale...RightScale
The document discusses the importance of regularly tuning cloud environments through deployment checkups. It highlights key areas to focus on during checkups, including cost optimization by identifying unused resources, ensuring optimal server utilization, implementing high availability and disaster recovery strategies, addressing security issues, and following best practices. Regular checkups help avoid inefficiencies that can arise over time and ensure deployments are optimized for cost, performance, availability and security.
Parallel computing involves solving computational problems simultaneously using multiple processors. It breaks problems into discrete parts that can be solved concurrently rather than sequentially. Parallel computing provides benefits like reduced time/costs to solve large problems and ability to model complex real-world phenomena. Common forms include bit-level, instruction-level, data, and task parallelism. Parallel resources can include multiple cores/processors in a single computer or networks of computers.
This chapter discusses various classification attributed to parallel architectures. It also introduces related parallel programming models and presents the actions of these models on parallel architectures. Notions such as Data parallelism Task parallelism, Tighty and Coupled system, UMA/NUMA, Multicore computing, Symmetric multiprocessing, Distributed Computing, Cluster computing, Shared memory without thread/Thread, etc..
An efficient approach for load balancing using dynamic ab algorithm in cloud ...bhavikpooja
This document outlines a proposed approach for efficient load balancing using a dynamic Ant-Bee algorithm in cloud computing. It discusses limitations of existing ant colony and bee colony algorithms for load balancing. The author aims to develop a new AB algorithm approach that combines aspects of ant colony optimization and bee colony algorithms to improve load balancing optimization and overcome issues like slow convergence and tendency to stagnate in ant colony algorithms. The proposed approach would leverage both the dynamic path finding of ants and pheromone updating of bees for more effective load balancing in cloud environments.
Multi objective vm placement using cloudsimKhalidAnsari60
This document presents a multi-objective virtual machine (VM) placement approach using Particle Swarm Optimization (PSO) and CloudSim. PSO is applied to optimize multiple objectives like energy consumption, load balancing, and resource utilization when placing VMs on physical machines in a cloud computing environment. CloudSim, a cloud simulation tool, is used to test the PSO-based VM placement approach without using real cloud infrastructure and resources. The approach involves initializing VM demands and particle positions, evaluating fitness values, and updating particle velocities and positions through iterations to determine the optimal VM placement solution.
CloneCloud proposes a flexible architecture that seamlessly uses cloud resources to augment mobile applications in an energy-efficient manner. It clones a mobile app and partitions it at runtime to migrate computation-heavy threads to the clone in the cloud. This allows threads to leverage faster CPUs and hardware accelerations remotely while keeping other functionality local. A static analyzer identifies legal partitions, a dynamic profiler collects execution data to build cost models, and an optimization solver picks optimal partitions to minimize time and energy. The prototype delivers significant speedups and energy reductions without requiring programmer involvement in partitioning. However, it does not give programmers flexibility over partitioning and may not cover all parameter combinations.
MapReduce is a programming model and an implementation for processing and generating big data sets with parallel & distributed algorithms on a cluster. It is a programming paradigm that enables massive scalability across hundreds or thousands of servers in a cluster for distributed computing of jobs. It is a Distributed Data Processing Algorithm mainly inspired by Functional Programming. In the MapReduce process, big tasks are split into smaller tasks and then they are assigned to several systems for processing. Introduced by Google, it is a reliable and efficient way to process data sets in cluster environments. MapReduce runs in the background to provide scalability, simplicity, speed, recovery and easy solutions for data processing.
Weather and Climate Visualization softwareRahul Gupta
The document describes a software project to develop a visualization tool for weather and climate data analysis. The tool will read netCDF files and allow users to analyze the data, perform statistical operations, generate interpolated spatial maps and images, and visualize shapefiles. The software will be developed using Java and JavaFX for the graphical user interface. It will implement design patterns like MVC and work with data formats like netCDF, shapefile, and others. The goal is to provide an easy to use tool for scientists to perform complex climate and weather data analysis and visualization without needing to write scripts.
This document provides an overview of cloud computing and the Eucalyptus platform. It defines cloud computing as a large-scale distributed computing paradigm that delivers dynamically scalable computing resources as a service over the Internet. It then describes Eucalyptus as an open-source software that implements cloud computing on computer clusters and is compatible with Amazon EC2. The document outlines the Eucalyptus cloud architecture including components like the Cloud Controller, Cluster Controller, Node Controller, Storage Controller, and Walrus storage. It provides examples of deploying data mining applications on Eucalyptus and Amazon EC2 clouds.
Load Balancing In Cloud Computing newpptUtshab Saha
The document discusses various load balancing algorithms for cloud computing including round robin, first come first serve (FCFS), and simulated annealing. It provides implementations of each algorithm in CloudSim and compares the results. Round robin and FCFS showed similar overall response times, data center processing times, and maximum/minimum values. Simulated annealing had slightly lower average overall response time. The document proposes using a genetic algorithm for host-side optimization to select the best host for virtual machine requests.
Oracle optimizer is very complex and is getting more complex with every version. This presentation covers some new optimizer behavior and how to deal with it
The document introduces the MapReduce programming model. It explains that MapReduce handles parallelization and distributed computing tasks like multi-threading, failure handling, and I/O behind the scenes. Developers focus on defining two functions: the mapper which splits input into key-value pairs, and the reducer which aggregates the output of mappers by keys. MapReduce processes large datasets by splitting input files into blocks, running the mapper function on each block in parallel, shuffling and sorting the outputs, and running the reducer to aggregate the results.
GECon2017_High-volume data streaming in azure_ Aliaksandr LaishaGECon_Org Team
The session will be focused on solutions that require high-throughput ingestion & streaming of data in real-time. You'll get familiar with different business uses-cases and architecture examples to get a common idea as well as understand the concepts of stream processing systems. Next, you'll get deep insights into functional and non-functional capabilities of Azure Event Hub service to see how it fits into the whole picture. Moreover we’ll take a look how to leverage Azure CosmosDB for high-throughput streaming when Event Hub is not suitable by different reasons.
This document describes the system architecture and modules of a smart home system called MyHome. The key modules are:
1. Hardware sensors and actuators that communicate wirelessly with the Central Unit and can turn lights on/off, detect motion, etc.
2. A Central Unit (Raspberry Pi) that communicates with the sensors/actuators via XBee, stores data in the cloud database, and receives commands from the mobile app.
3. A cloud database implemented with Google App Engine that stores home/device data and allows communication between the Central Unit and mobile app.
4. An Android mobile app that users can use to monitor cameras, control lights, and view the state of
Mobile Saturday. Тема 2. Особенности тестирования приложения на Android: Spec...GoIT
21 ноября GoITClub совместно с Zeo Alliance провели ивент, посвященный тестированию мобильных приложений.
Рассмотрели 2 самых популярных ОС - Andoird и iOS
Блок Android
1. Особенности операционной системы Android - Иван Мурзак (Android developer, Co-Founder&CTO at Capitan Inc.)
2. Особенности тестирования приложения на Android (Specific functional, Performance, Device park selection) - Михаил Железнов (QC Engineer at SoftServe)
3. Особенности тестирования приложения на Android (Human Interface Guideline, Tools) - Юлия Смирнова (QC Engineer at SoftServe)
4. Автоматизация тестирования верстки - Александр Хотемской (Senior Client Automation QA Enginner at Wargaming)
Блок iOS
1. Особенности операционной системы iOS - Ольга Макаревич (QA Engineer at EPAM)
2. Особенности тестирования приложений на iOS - Александр Буратынский ( Senior QA Analysyt at Global Logic)
3. Тестирование с использованием инструментов xCode - Максим Гонтар (Mobile Developer, Lead Engineer at Global Logic) - презентация отутствуе, было живой показ программы.
Видеозапись мероприятия можно посмотреть на официальном канале GoIT на Youtube
"Going Offline", one of the hottest mobile app trendsDerek Baron
One of the hottest trends in mobile is "going offline", yet organizations are faced with a tripling of time and cost when adding offline functionality to a business app. According to Forrester Research, the ability to work offline is "the most important and difficult mobile feature...and will be a consideration for nearly every modern application".
Meteor is a platform for building modern web applications using JavaScript. It allows developers to build real-time applications using a single language across client and server. Some key features of Meteor include latency compensation, reactivity across all layers of an application, and support for mobile development. The presentation provided an overview of Meteor's principles and architecture, including data on the wire, one language, database everywhere, and latency compensation. It also demonstrated building a simple topic voting app in Meteor.
How to Lower Android Power Consumption Without Affecting Performancerickschwar
The document discusses various ways mobile app developers can lower the power consumption of their apps without affecting performance. It begins by explaining that most apps do not efficiently use system resources like the processor, cellular radio, and display, wasting power and reducing battery life. It then provides tips for optimizing specific areas of power consumption, such as using the cellular radio efficiently by bundling network traffic, offloading tasks to hardware accelerators like the DSP to reduce CPU usage, and managing the display to minimize brightness. The document stresses that measuring power consumption is key, and provides tools developers can use to profile and optimize the power impact of their apps.
Mobile Synchronization Patterns for Large Volumes of DataOutSystems
Do your mobile business apps require large amounts of data? Is the complexity of "offline" causing you to lose sleep? Come and learn "4 Best Practices," and their supporting patterns, for dealing with the synchronization of large data volumes in mobile apps built with OutSystems. In addition, we will discuss how to avoid the problems that can pop up whenever dealing with these kinds of applications.
redpill Mobile Case Study (Salvation Army)Peter Presnell
Case study that summarizes key findings by Red Pill Development as they built a mobile interface for Notes applications at Salvation Army. Using asymmetric modernization a mobile interface can be delivered for an entire portfolio of applications in a few days.
SaaS Enablement of your existing application (Cloud Slam 2010)Nati Shalom
The document discusses enabling existing applications to run on the cloud using GigaSpaces' elastic middleware platform. It provides examples of how the platform has been used to enable batch processing and real-time transactional applications as software-as-a-service (SaaS) on the cloud with benefits like linear scalability, multi-tenancy, auto-scaling and high availability. The key aspects of GigaSpaces' approach are virtualizing resources, providing elastic middleware as a service, and fine-grained multi-tenancy while avoiding vendor lock-in.
An in-building multi-server cloud system based on shortest Path algorithm dep...IOSR Journals
This document summarizes a proposed in-building multi-server cloud system based on the shortest path algorithm. The system would allow for mobile client nodes to upload and access data from the closest of multiple upload stations located throughout an office building. It describes using Bluetooth as the wireless transmission medium between nodes and stations. The stations would be interconnected to allow data access from any station. An application would determine the nearest station for each upload and encrypt data during transmission and storage for security.
This document describes a proposed multi-server cloud system within a building based on determining the nearest server using the shortest path algorithm. The system has multiple upload stations that act as servers, and client nodes that can be mobile. When a client tries to upload data, the system intelligently finds the nearest upload station based on the client's location and measured signal strength. Data is encrypted during transmission and storage for security. The design includes a client application that allows users to login, access files and more. Data structures like dictionaries and lists are used to store user and file information in text files on the upload stations.
Unit-I Introduction to Cloud Computing.pptxgarkhot123
Cloud computing involves delivering computing resources such as servers, storage, databases, networking, software, analytics and more over the internet ("the cloud"). Key aspects include on-demand self-service, broad network access, resource pooling, rapid elasticity and measured service. Major cloud computing service providers include Amazon Web Services, Microsoft Azure and Google Cloud. Cloud computing offers advantages like reduced costs, increased collaboration and flexibility.
The document discusses stream processing models. It describes the key components as data sources, stream processing pipelines, and data sinks. Data sources refer to the inputs of streaming data, pipelines are the processing applied to the streaming data, and sinks are the outputs where the results are stored or sent. Stateful stream processing requires ensuring state is preserved over time and data consistency even during failures. Frameworks like Apache Spark use sources and sinks to connect to streaming data sources like Kafka and send results to other systems, acting as pipelines between different distributed systems.
Collection of tips & tricks that makes the difference between a good app and a "wow-affect" app. Relevant to product managers and developers (including some code samples)
As presented in DroidCon Tel Aviv 2014 by:
Ran Nachmany, MobiliUp
http://il.droidcon.com
Microsoft Sync Framework (part 1) ABTO Software Lecture GarntsarikABTO Software
The document discusses Microsoft Sync Framework, which is a comprehensive synchronization platform that enables collaboration and offline access for applications. It allows synchronization of any type of data stored in any format using any protocol across any network configuration. Key capabilities include support for offline scenarios, synchronization of changes between different endpoints like devices and servers, and handling conflicts that may arise during synchronization. The document provides examples of how to implement synchronization between a local database cache and remote data sources using Sync Framework along with Windows Communication Foundation (WCF) services.
A Review And Research Towards Mobile Cloud ComputingSuzanne Simmons
This document provides an overview of mobile cloud computing (MCC), including its advantages and challenges. MCC integrates cloud computing with mobile environments to provide mobile users access to rich computing resources and applications. Key advantages include extending battery life by offloading processing to cloud servers, improving data storage capacity and processing power by storing data in the cloud, and improving reliability through data backup in the cloud. However, challenges exist due to limitations of mobile devices like processing power, storage and battery life. Additionally, the quality of wireless communication introduces issues like variable bandwidth and delays. Dividing applications between mobile devices and cloud servers also requires optimization techniques to determine the most efficient distribution of processing tasks.
IBM IMPACT 2014 AMC-1866 Introduction to IBM Messaging CapabilitiesPeter Broadhurst
IBM Messaging provides market-leading capabilities for anywhere-to-anywhere integration across mobile, cloud, and enterprise platforms - from the simplest pair of applications requiring basic connectivity and data exchange, to the most complex business process management environments. Come to this session to understand the value and rationale of message/queuing and the IBM Messaging family of products; its key features and functions; and how it can be used to build a secure, flexible, and scalable messaging backbone for a business.
A Scalable Network Monitoring and Bandwidth Throttling System for Cloud Compu...Nico Huysamen
This document summarizes a scalable network monitoring and bandwidth throttling system for cloud computing. The system monitors network usage of users on a cloud to identify those abusing bandwidth. It uses a client-server model where virtual machines run client software to monitor their own traffic and report to servers monitoring each cluster. When bandwidth thresholds are exceeded, servers calculate new bandwidth limits for abusive users to normalize network usage across the cloud. The system was tested on Amazon EC2 using over a million simulated clients to evaluate its scalability.
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?Speck&Tech
ABSTRACT: A prima vista, un mattoncino Lego e la backdoor XZ potrebbero avere in comune il fatto di essere entrambi blocchi di costruzione, o dipendenze di progetti creativi e software. La realtà è che un mattoncino Lego e il caso della backdoor XZ hanno molto di più di tutto ciò in comune.
Partecipate alla presentazione per immergervi in una storia di interoperabilità, standard e formati aperti, per poi discutere del ruolo importante che i contributori hanno in una comunità open source sostenibile.
BIO: Sostenitrice del software libero e dei formati standard e aperti. È stata un membro attivo dei progetti Fedora e openSUSE e ha co-fondato l'Associazione LibreItalia dove è stata coinvolta in diversi eventi, migrazioni e formazione relativi a LibreOffice. In precedenza ha lavorato a migrazioni e corsi di formazione su LibreOffice per diverse amministrazioni pubbliche e privati. Da gennaio 2020 lavora in SUSE come Software Release Engineer per Uyuni e SUSE Manager e quando non segue la sua passione per i computer e per Geeko coltiva la sua curiosità per l'astronomia (da cui deriva il suo nickname deneb_alpha).
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...SOFTTECHHUB
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
Full-RAG: A modern architecture for hyper-personalizationZilliz
Mike Del Balso, CEO & Co-Founder at Tecton, presents "Full RAG," a novel approach to AI recommendation systems, aiming to push beyond the limitations of traditional models through a deep integration of contextual insights and real-time data, leveraging the Retrieval-Augmented Generation architecture. This talk will outline Full RAG's potential to significantly enhance personalization, address engineering challenges such as data management and model training, and introduce data enrichment with reranking as a key solution. Attendees will gain crucial insights into the importance of hyperpersonalization in AI, the capabilities of Full RAG for advanced personalization, and strategies for managing complex data integrations for deploying cutting-edge AI solutions.
How to Get CNIC Information System with Paksim Ga.pptxdanishmna97
Pakdata Cf is a groundbreaking system designed to streamline and facilitate access to CNIC information. This innovative platform leverages advanced technology to provide users with efficient and secure access to their CNIC details.
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...Neo4j
Leonard Jayamohan, Partner & Generative AI Lead, Deloitte
This keynote will reveal how Deloitte leverages Neo4j’s graph power for groundbreaking digital twin solutions, achieving a staggering 100x performance boost. Discover the essential role knowledge graphs play in successful generative AI implementations. Plus, get an exclusive look at an innovative Neo4j + Generative AI solution Deloitte is developing in-house.
Best 20 SEO Techniques To Improve Website Visibility In SERPPixlogix Infotech
Boost your website's visibility with proven SEO techniques! Our latest blog dives into essential strategies to enhance your online presence, increase traffic, and rank higher on search engines. From keyword optimization to quality content creation, learn how to make your site stand out in the crowded digital landscape. Discover actionable tips and expert insights to elevate your SEO game.
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.
TrustArc Webinar - 2024 Global Privacy SurveyTrustArc
How does your privacy program stack up against your peers? What challenges are privacy teams tackling and prioritizing in 2024?
In the fifth annual Global Privacy Benchmarks Survey, we asked over 1,800 global privacy professionals and business executives to share their perspectives on the current state of privacy inside and outside of their organizations. This year’s report focused on emerging areas of importance for privacy and compliance professionals, including considerations and implications of Artificial Intelligence (AI) technologies, building brand trust, and different approaches for achieving higher privacy competence scores.
See how organizational priorities and strategic approaches to data security and privacy are evolving around the globe.
This webinar will review:
- The top 10 privacy insights from the fifth annual Global Privacy Benchmarks Survey
- The top challenges for privacy leaders, practitioners, and organizations in 2024
- Key themes to consider in developing and maintaining your privacy program
Communications Mining Series - Zero to Hero - Session 1DianaGray10
This session provides introduction to UiPath Communication Mining, importance and platform overview. You will acquire a good understand of the phases in Communication Mining as we go over the platform with you. Topics covered:
• Communication Mining Overview
• Why is it important?
• How can it help today’s business and the benefits
• Phases in Communication Mining
• Demo on Platform overview
• Q/A
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
Driving Business Innovation: Latest Generative AI Advancements & Success StorySafe Software
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdfMalak Abu Hammad
Discover how MongoDB Atlas and vector search technology can revolutionize your application's search capabilities. This comprehensive presentation covers:
* What is Vector Search?
* Importance and benefits of vector search
* Practical use cases across various industries
* Step-by-step implementation guide
* Live demos with code snippets
* Enhancing LLM capabilities with vector search
* Best practices and optimization strategies
Perfect for developers, AI enthusiasts, and tech leaders. Learn how to leverage MongoDB Atlas to deliver highly relevant, context-aware search results, transforming your data retrieval process. Stay ahead in tech innovation and maximize the potential of your applications.
#MongoDB #VectorSearch #AI #SemanticSearch #TechInnovation #DataScience #LLM #MachineLearning #SearchTechnology
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
Climate Impact of Software Testing at Nordic Testing DaysKari Kakkonen
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
2. Major Concerns Addressed 1 of 2
From the App User and Device Resource view point the
following are some of the critical factors a cloud backed
mobile engineering team should consider.
• Smart Disk space usage - A lot of apps including some
popular social media apps abuse device disk space. Every time the
apps sync with the cloud counter part they bring down fresh data.
Apps should be considerate of device user and should come up with
some clean-up mechanism.
3. Major Concerns Addressed 2 of 2
• Smart Network usage – Be it upstream or downstream sync
i.e. apps as well as the cloud counter parts should be designed to be
very frugal about the number of bytes sent over the wire as well as
the number of network calls as it directly impacts the data usage and
hence the device user.
• Smart Battery consumption -
For instance
• Apps which broadcast real time user activities should smartly club
syncs to reduce multiple device pings
• Location and geo fence based apps should use the right strategy to
avoid draining device battery.
6. On-Start-up - online
• First time fetch of current Location
• Instantiate N/W Connection receiver. (Wifi/Data)
• “All” data if new device or “Newer” data
deals since last sync date, if used device.
• Clean up older disk cache records. (Cache date <
Current date and un synchronized)
• Any other Metadata sync or change in Business rules or
disclaimers etc..
7. On-Start-up - offline
• If new device change to offline mode and provide an option
to retry N/W connection
• Active fetch of current Location.
• If used device use last synced data
• Clean up older disk cache records. (Cache date <
Current date and synched)
8. On-Sign in
• User data later than last sync if already used device -
Something like getting the newer emails from the server since
last sync. Using the app in Multiple devices doesn’t affect this
part of the sync. But it does affects the synch of user specific
settings/ preferences.
• User specific notifications – offers or expiry notices etc.
Since there could be multiple devices in which user could login
from, every device will have to maintain last sign in timestamp
and Cloud will maintain last synchronization timestamp at levels
desired. Every time during sign-in If these 2 time stamps vary
then it calls for Synching all user specific settings data
• User specific app settings and preferences
9. On-Sign in - offline
• show the message and continue as guest in offline mode.
10. On-Demand Sync – 2 Way
• All data listing screens shall support on-Demand sync.
Using a pull down or swipe down gesture user can initiate sync.
• During swipe down n/w state will be first checked before
making the Sync call. If offline appropriate message shall be
shown.
Best real life example would be your Gmail app.
Try to “star” an email and Swipe down. Your “star” should
reflect in your server (try and open gmail in another device or
PC) and if you had new emails that would be in your device too.
So 2 way cloud sync.
13. On-UITransition
• All user activities shall be stored at disk first and synced on the
next UI based action like a UI Transition. The approach is
disk first and asynchronous calls to cloud. The stored data shall look
something like below. Choice of storage could be disk caches like
SQLLite or something similar.
Data Cache Date Sync Status
{“test”:”data”} 2014-08-01:00:00:00 Sync Progress
{“test”:”data”} 2014-08-01:00:00:00 Sync Complete
{“test”:”data”} 2014-08-01:00:00:00 To be Synced
15. Offline mode
As a part of the strategy make sure all deal breaking features
(whichever possible) are supported in offline mode for the
success of the app. This might require some careful planning
and some extra processing / storing required data in the
device.