This document discusses epidemic algorithms and their application to distributed systems. Epidemic algorithms were inspired by epidemiology and how diseases spread among populations. They work by having nodes periodically exchange information with random peer nodes in a manner similar to how diseases infect individuals. This allows information to spread quickly and reliably throughout the distributed system. Specific applications discussed include data replication, aggregation, and peer sampling services.
This document discusses distributed systems and their evolution. It defines a distributed system as a collection of networked computers that communicate and coordinate actions by passing messages. Distributed systems have several advantages over centralized systems, including better utilization of resources and the ability to share information among distributed users. The document describes several models of distributed systems including mini computer models, workstation models, workstation-server models, processor pool models, and hybrid models. It also discusses why distributed computing systems are gaining popularity due to their ability to effectively manage large numbers of distributed resources and handle inherently distributed applications.
Checkpointing and Rollback Recovery Algorithms for Fault Tolerance in MANETs:...Eswar Publications
This document summarizes and reviews various checkpointing and rollback recovery algorithms that have been proposed to provide fault tolerance in mobile ad hoc networks (MANETs). It begins with background information on MANETs and checkpointing. Checkpointing techniques take snapshots of process states and store them to allow recovery from failures without restarting from the beginning. The document then describes different types of checkpointing, including uncoordinated, coordinated, communication-induced, and hybrid approaches. Several specific algorithms for MANETs checkpointing are then analyzed, including flooding-based, concurrent checkpointing, cluster-based, and mobility-aware approaches. The document concludes by stating that checkpointing presents challenges for MANETs due to their dynamic topology and limited
Grokking Techtalk #39: Gossip protocol and applicationsGrokking VN
Gossip là một giao thức trao đổi thông tin phổ biến trong các hệ thống phân tán giúp cho các máy chủ duy trì trạng thái đồng nhất với nhau cũng như thực hiện các nhiệm vụ có chủ đích. Điểm mạnh của nó là khả năng phát tán thông tin ở tốc độ cao cũng như không hề có single point of failure. Trong bài talk này, Anh Nguyễn Anh Tú, thành viên của Grokking sẽ chia sẻ một số thông tin về giao thức Gossip cũng như điểm qua một vài ứng dụng thực tiễn của nó.
- Về diễn giả: Anh Nguyễn Anh Tú hiện đang là Staff Software Engineer tại Axon Vietnam, đồng thời là thành viên của Grokking Vietnam.
MPI provides point-to-point and collective communication capabilities. Point-to-point communication includes synchronous and asynchronous send/receive functions. Collective communication functions like broadcast, reduce, scatter, and gather efficiently distribute data among processes. MPI also supports irregular data packaging using packing/unpacking functions and derived datatypes.
This document discusses different distributed computing system (DCS) models:
1. The minicomputer model consists of a few minicomputers with remote access allowing resource sharing.
2. The workstation model consists of independent workstations scattered throughout a building where users log onto their home workstation.
3. The workstation-server model includes minicomputers, diskless and diskful workstations, and centralized services like databases and printing.
It provides an overview of the key characteristics and advantages of different DCS models.
This document discusses two common models for distributed computing communication: message passing and remote procedure calls (RPC). It describes the basic primitives and design issues for each model. For message passing, it covers synchronous vs asynchronous and blocking vs non-blocking primitives. For RPC, it explains the client-server model and how stubs are used to convert parameters and return results between machines. It also discusses binding, parameter passing techniques, and ensuring error handling and execution semantics.
In this presentation, you will learn the fundamentals of Multi Processors and Multi Computers in only a few minutes.
Meanings, features, attributes, applications, and examples of multiprocessors and multi computers.
So, let's get started. If you enjoy this and find the information beneficial, please like and share it with your friends.
This document provides an overview of Linux internals and networking concepts covered in 3 sentences or less:
It introduces Linux internals topics like processes, memory management, and virtual file systems. It also discusses networking concepts and provides a brief history of operating systems development. The document contains various sections on Linux components, kernel subsystems, virtual file systems, and transitioning to systems programming.
This document discusses distributed systems and their evolution. It defines a distributed system as a collection of networked computers that communicate and coordinate actions by passing messages. Distributed systems have several advantages over centralized systems, including better utilization of resources and the ability to share information among distributed users. The document describes several models of distributed systems including mini computer models, workstation models, workstation-server models, processor pool models, and hybrid models. It also discusses why distributed computing systems are gaining popularity due to their ability to effectively manage large numbers of distributed resources and handle inherently distributed applications.
Checkpointing and Rollback Recovery Algorithms for Fault Tolerance in MANETs:...Eswar Publications
This document summarizes and reviews various checkpointing and rollback recovery algorithms that have been proposed to provide fault tolerance in mobile ad hoc networks (MANETs). It begins with background information on MANETs and checkpointing. Checkpointing techniques take snapshots of process states and store them to allow recovery from failures without restarting from the beginning. The document then describes different types of checkpointing, including uncoordinated, coordinated, communication-induced, and hybrid approaches. Several specific algorithms for MANETs checkpointing are then analyzed, including flooding-based, concurrent checkpointing, cluster-based, and mobility-aware approaches. The document concludes by stating that checkpointing presents challenges for MANETs due to their dynamic topology and limited
Grokking Techtalk #39: Gossip protocol and applicationsGrokking VN
Gossip là một giao thức trao đổi thông tin phổ biến trong các hệ thống phân tán giúp cho các máy chủ duy trì trạng thái đồng nhất với nhau cũng như thực hiện các nhiệm vụ có chủ đích. Điểm mạnh của nó là khả năng phát tán thông tin ở tốc độ cao cũng như không hề có single point of failure. Trong bài talk này, Anh Nguyễn Anh Tú, thành viên của Grokking sẽ chia sẻ một số thông tin về giao thức Gossip cũng như điểm qua một vài ứng dụng thực tiễn của nó.
- Về diễn giả: Anh Nguyễn Anh Tú hiện đang là Staff Software Engineer tại Axon Vietnam, đồng thời là thành viên của Grokking Vietnam.
MPI provides point-to-point and collective communication capabilities. Point-to-point communication includes synchronous and asynchronous send/receive functions. Collective communication functions like broadcast, reduce, scatter, and gather efficiently distribute data among processes. MPI also supports irregular data packaging using packing/unpacking functions and derived datatypes.
This document discusses different distributed computing system (DCS) models:
1. The minicomputer model consists of a few minicomputers with remote access allowing resource sharing.
2. The workstation model consists of independent workstations scattered throughout a building where users log onto their home workstation.
3. The workstation-server model includes minicomputers, diskless and diskful workstations, and centralized services like databases and printing.
It provides an overview of the key characteristics and advantages of different DCS models.
This document discusses two common models for distributed computing communication: message passing and remote procedure calls (RPC). It describes the basic primitives and design issues for each model. For message passing, it covers synchronous vs asynchronous and blocking vs non-blocking primitives. For RPC, it explains the client-server model and how stubs are used to convert parameters and return results between machines. It also discusses binding, parameter passing techniques, and ensuring error handling and execution semantics.
In this presentation, you will learn the fundamentals of Multi Processors and Multi Computers in only a few minutes.
Meanings, features, attributes, applications, and examples of multiprocessors and multi computers.
So, let's get started. If you enjoy this and find the information beneficial, please like and share it with your friends.
This document provides an overview of Linux internals and networking concepts covered in 3 sentences or less:
It introduces Linux internals topics like processes, memory management, and virtual file systems. It also discusses networking concepts and provides a brief history of operating systems development. The document contains various sections on Linux components, kernel subsystems, virtual file systems, and transitioning to systems programming.
The document appears to be about agent programs and intelligent agents. It discusses how agent programs take in percepts from sensors and output actions through actuators. It also discusses how intelligent agents perceive their environment through sensors, take actions through actuators, and strive to achieve goals. The document contains diagrams illustrating the architecture of agent programs and how they interact with the environment.
Inter process communication using Linux System Callsjyoti9vssut
This document discusses various methods of inter-process communication (IPC) in Linux using system calls and standard APIs. It describes pipes, FIFOs, message queues, and shared memory as common IPC methods. For each method, it provides details on the relevant system calls and functions, and includes code examples of producer-consumer implementations using message queues and shared memory.
This document discusses implementing a parallel merge sort algorithm using MPI (Message Passing Interface). It describes the background of MPI and how it can be used for communication between processes. It provides details on the dataset used, MPI functions for initialization, communication between processes, and summarizes the results which show a decrease in runtime when increasing the number of processors.
The document provides an overview of operating system concepts, including:
- The role of an operating system in managing computer hardware resources and facilitating the use of applications.
- Key operating system functions like process management, memory management, storage management, I/O management, and security/protection.
- Computer system organization involving CPUs, memory, I/O devices, and the bus connecting them.
- Operating system structures for multiprogramming/timesharing and memory management in these environments.
- The hierarchy of storage devices from fastest/smallest memory to slower/larger secondary storage.
- Computing environments involving traditional systems, networks, and client-server models.
The document discusses various inter-process communication (IPC) mechanisms in Linux including pipes, FIFOs, messages, shared memory, and sockets. It provides detailed explanations of how pipes and FIFOs are implemented in the Linux kernel, including how they are created, read from, and written to via system calls. It also summarizes the use of System V IPC features like semaphores, messages, and shared memory for communication between processes.
Remote Procedure Call in Distributed SystemPoojaBele1
Presentation to give description about the remote procedure call in distributed systems
Presentation covers some points on remote procedure call in distributed systems
This document provides an introduction to POSIX threads (Pthreads) programming. It discusses what threads are, how they differ from processes, and how Pthreads provide a standardized threading interface for UNIX systems. The key benefits of Pthreads for parallel programming are improved performance from overlapping CPU and I/O work and priority-based scheduling. Pthreads are well-suited for applications that can break work into independent tasks or respond to asynchronous events. The document outlines common threading models and emphasizes that programmers are responsible for synchronizing access to shared memory in multithreaded programs.
This chapter discusses operating system structures and concepts. It describes the services operating systems provide to users and processes, such as user interfaces, program execution, I/O operations, file manipulation, communications, and error detection. It also discusses how operating systems ensure efficient resource sharing through resource allocation, accounting, protection and security. The chapter covers system calls, which are the programming interface to OS services, and how system calls are typically implemented and accessed through APIs rather than direct calls.
The document discusses key concepts related to process management in Linux, including process lifecycle, states, memory segments, scheduling, and priorities. It explains that a process goes through creation, execution, termination, and removal phases repeatedly. Process states include running, stopped, interruptible, uninterruptible, and zombie. Process memory is made up of text, data, BSS, heap, and stack segments. Linux uses a O(1) CPU scheduling algorithm that scales well with process and processor counts.
UNIT II PROCESS MANAGEMENT
Processes-Process Concept, Process Scheduling, Operations on Processes, Interprocess Communication; Threads- Overview, Multicore Programming, Multithreading Models; Windows 7 - Thread and SMP Management. Process Synchronization - Critical Section Problem, Mutex Locks, Semophores, Monitors; CPU Scheduling and Deadlocks.
This document provides an overview of an upcoming lecture on real-time operating systems (RTOS) for embedded systems. It includes the syllabus, which covers operating system basics, types of operating systems, tasks/processes/threads, multiprocessing/multitasking, task scheduling, and how to choose an RTOS. The document discusses the architecture and services of general operating systems and real-time kernels, including task management, scheduling, synchronization, and time management.
Computer Communication Networks- Introduction to Transport layerKrishna Nanda
The document summarizes the key functions and services of the transport layer:
1) The transport layer provides process-to-process communication between applications on different hosts using addressing that identifies processes via port numbers in addition to IP addresses.
2) It implements services like multiplexing/demultiplexing, flow control, error control, and reliable data transfer to ensure reliable end-to-end delivery of data between applications.
3) Transport layer protocols encapsulate and decapsulate messages, adding headers that include sequence numbers and acknowledgments to implement functions like error detection and retransmission.
This document provides an overview of network security. It discusses security attacks like passive attacks (eavesdropping) and active attacks (modifying data). It outlines security services like confidentiality, authentication, integrity, non-repudiation, and access control. It also discusses methods of defense against attacks, including encryption, software/hardware controls, security policies, and physical controls. The document defines key security terms and concepts.
The document summarizes a presentation on network security and Linux security. The presentation covered introduction to security, computer security, and network security. It discussed why security is needed, who is vulnerable, common security attacks like dictionary attacks, denial of service attacks, TCP attacks, and packet sniffing. It also covered Linux security topics like securing the Linux kernel, file and filesystem permissions, password security, and network security using firewalls, IPSEC, and intrusion detection systems. The presentation concluded with a reference to an ID-CERT cybercrime report and a call for questions.
This document discusses key aspects of distributed file systems including file caching schemes, file replication, and fault tolerance. It describes different cache locations, modification propagation techniques, and methods for replica creation. File caching schemes aim to reduce network traffic by retaining recently accessed files in memory. File replication provides increased reliability and availability through independent backups. Distributed file systems must also address being stateful or stateless to maintain information about file access and operations.
This document compares message passing and shared memory architectures for parallel computing. It defines message passing as processors communicating through sending and receiving messages without a global memory, while shared memory allows processors to communicate through a shared virtual address space. The key difference is that message passing uses explicit communication through messages, while shared memory uses implicit communication through memory operations. It also discusses how the programming model and hardware architecture can be separated, with message passing able to support shared memory and vice versa.
The document discusses the Linux kernel architecture. The kernel manages resources and arbitrates access between users and applications. It includes functions like file systems, process management, device drivers, memory management, and networking. The kernel space runs kernel processes while the user space runs user applications, which interact with the kernel through system calls. The kernel presents a consistent view of data stored on devices using a virtual file system.
Synchronization in distributed computingSVijaylakshmi
Synchronization in distributed systems is achieved via clocks. The physical clocks are used to adjust the time of nodes. Each node in the system can share its local time with other nodes in the system. The time is set based on UTC (Universal Time Coordination).
Chord is a peer-to-peer lookup service that maps keys to nodes in a distributed system. It addresses problems like load balancing, decentralization, scalability, and availability that arise from nodes frequently joining and leaving the network. Chord uses consistent hashing to assign keys to nodes, and each node maintains a finger table with pointers to other nodes to efficiently route lookup requests. When nodes join or leave, only a few keys are redistributed and finger tables are updated through a stabilization protocol to maintain correctness.
The document describes the PULP protocol, a hybrid push-pull protocol for disseminating messages from multiple sources across a network. It uses an initial exponential growth phase using push to quickly inform nodes, followed by a quadratic shrinking pull phase to limit redundant messages. Nodes maintain message histories and trading windows to drive useful pulls. Evaluation shows the protocol achieves high coverage with low latency and bandwidth costs, and adapts well to changes in message frequency and network churn.
The document appears to be about agent programs and intelligent agents. It discusses how agent programs take in percepts from sensors and output actions through actuators. It also discusses how intelligent agents perceive their environment through sensors, take actions through actuators, and strive to achieve goals. The document contains diagrams illustrating the architecture of agent programs and how they interact with the environment.
Inter process communication using Linux System Callsjyoti9vssut
This document discusses various methods of inter-process communication (IPC) in Linux using system calls and standard APIs. It describes pipes, FIFOs, message queues, and shared memory as common IPC methods. For each method, it provides details on the relevant system calls and functions, and includes code examples of producer-consumer implementations using message queues and shared memory.
This document discusses implementing a parallel merge sort algorithm using MPI (Message Passing Interface). It describes the background of MPI and how it can be used for communication between processes. It provides details on the dataset used, MPI functions for initialization, communication between processes, and summarizes the results which show a decrease in runtime when increasing the number of processors.
The document provides an overview of operating system concepts, including:
- The role of an operating system in managing computer hardware resources and facilitating the use of applications.
- Key operating system functions like process management, memory management, storage management, I/O management, and security/protection.
- Computer system organization involving CPUs, memory, I/O devices, and the bus connecting them.
- Operating system structures for multiprogramming/timesharing and memory management in these environments.
- The hierarchy of storage devices from fastest/smallest memory to slower/larger secondary storage.
- Computing environments involving traditional systems, networks, and client-server models.
The document discusses various inter-process communication (IPC) mechanisms in Linux including pipes, FIFOs, messages, shared memory, and sockets. It provides detailed explanations of how pipes and FIFOs are implemented in the Linux kernel, including how they are created, read from, and written to via system calls. It also summarizes the use of System V IPC features like semaphores, messages, and shared memory for communication between processes.
Remote Procedure Call in Distributed SystemPoojaBele1
Presentation to give description about the remote procedure call in distributed systems
Presentation covers some points on remote procedure call in distributed systems
This document provides an introduction to POSIX threads (Pthreads) programming. It discusses what threads are, how they differ from processes, and how Pthreads provide a standardized threading interface for UNIX systems. The key benefits of Pthreads for parallel programming are improved performance from overlapping CPU and I/O work and priority-based scheduling. Pthreads are well-suited for applications that can break work into independent tasks or respond to asynchronous events. The document outlines common threading models and emphasizes that programmers are responsible for synchronizing access to shared memory in multithreaded programs.
This chapter discusses operating system structures and concepts. It describes the services operating systems provide to users and processes, such as user interfaces, program execution, I/O operations, file manipulation, communications, and error detection. It also discusses how operating systems ensure efficient resource sharing through resource allocation, accounting, protection and security. The chapter covers system calls, which are the programming interface to OS services, and how system calls are typically implemented and accessed through APIs rather than direct calls.
The document discusses key concepts related to process management in Linux, including process lifecycle, states, memory segments, scheduling, and priorities. It explains that a process goes through creation, execution, termination, and removal phases repeatedly. Process states include running, stopped, interruptible, uninterruptible, and zombie. Process memory is made up of text, data, BSS, heap, and stack segments. Linux uses a O(1) CPU scheduling algorithm that scales well with process and processor counts.
UNIT II PROCESS MANAGEMENT
Processes-Process Concept, Process Scheduling, Operations on Processes, Interprocess Communication; Threads- Overview, Multicore Programming, Multithreading Models; Windows 7 - Thread and SMP Management. Process Synchronization - Critical Section Problem, Mutex Locks, Semophores, Monitors; CPU Scheduling and Deadlocks.
This document provides an overview of an upcoming lecture on real-time operating systems (RTOS) for embedded systems. It includes the syllabus, which covers operating system basics, types of operating systems, tasks/processes/threads, multiprocessing/multitasking, task scheduling, and how to choose an RTOS. The document discusses the architecture and services of general operating systems and real-time kernels, including task management, scheduling, synchronization, and time management.
Computer Communication Networks- Introduction to Transport layerKrishna Nanda
The document summarizes the key functions and services of the transport layer:
1) The transport layer provides process-to-process communication between applications on different hosts using addressing that identifies processes via port numbers in addition to IP addresses.
2) It implements services like multiplexing/demultiplexing, flow control, error control, and reliable data transfer to ensure reliable end-to-end delivery of data between applications.
3) Transport layer protocols encapsulate and decapsulate messages, adding headers that include sequence numbers and acknowledgments to implement functions like error detection and retransmission.
This document provides an overview of network security. It discusses security attacks like passive attacks (eavesdropping) and active attacks (modifying data). It outlines security services like confidentiality, authentication, integrity, non-repudiation, and access control. It also discusses methods of defense against attacks, including encryption, software/hardware controls, security policies, and physical controls. The document defines key security terms and concepts.
The document summarizes a presentation on network security and Linux security. The presentation covered introduction to security, computer security, and network security. It discussed why security is needed, who is vulnerable, common security attacks like dictionary attacks, denial of service attacks, TCP attacks, and packet sniffing. It also covered Linux security topics like securing the Linux kernel, file and filesystem permissions, password security, and network security using firewalls, IPSEC, and intrusion detection systems. The presentation concluded with a reference to an ID-CERT cybercrime report and a call for questions.
This document discusses key aspects of distributed file systems including file caching schemes, file replication, and fault tolerance. It describes different cache locations, modification propagation techniques, and methods for replica creation. File caching schemes aim to reduce network traffic by retaining recently accessed files in memory. File replication provides increased reliability and availability through independent backups. Distributed file systems must also address being stateful or stateless to maintain information about file access and operations.
This document compares message passing and shared memory architectures for parallel computing. It defines message passing as processors communicating through sending and receiving messages without a global memory, while shared memory allows processors to communicate through a shared virtual address space. The key difference is that message passing uses explicit communication through messages, while shared memory uses implicit communication through memory operations. It also discusses how the programming model and hardware architecture can be separated, with message passing able to support shared memory and vice versa.
The document discusses the Linux kernel architecture. The kernel manages resources and arbitrates access between users and applications. It includes functions like file systems, process management, device drivers, memory management, and networking. The kernel space runs kernel processes while the user space runs user applications, which interact with the kernel through system calls. The kernel presents a consistent view of data stored on devices using a virtual file system.
Synchronization in distributed computingSVijaylakshmi
Synchronization in distributed systems is achieved via clocks. The physical clocks are used to adjust the time of nodes. Each node in the system can share its local time with other nodes in the system. The time is set based on UTC (Universal Time Coordination).
Chord is a peer-to-peer lookup service that maps keys to nodes in a distributed system. It addresses problems like load balancing, decentralization, scalability, and availability that arise from nodes frequently joining and leaving the network. Chord uses consistent hashing to assign keys to nodes, and each node maintains a finger table with pointers to other nodes to efficiently route lookup requests. When nodes join or leave, only a few keys are redistributed and finger tables are updated through a stabilization protocol to maintain correctness.
The document describes the PULP protocol, a hybrid push-pull protocol for disseminating messages from multiple sources across a network. It uses an initial exponential growth phase using push to quickly inform nodes, followed by a quadratic shrinking pull phase to limit redundant messages. Nodes maintain message histories and trading windows to drive useful pulls. Evaluation shows the protocol achieves high coverage with low latency and bandwidth costs, and adapts well to changes in message frequency and network churn.
The document discusses the gossip protocol, which is a simple, masterless communication protocol inspired by gossip in social networks. It describes how gossip protocols work by having nodes randomly share information with other nodes to propagate data throughout the entire network. They are useful for building reliable distributed systems that can tolerate failures of individual nodes.
Cassandra is a distributed, decentralized, wide column store NoSQL database modeled after Amazon's Dynamo and Google's Bigtable. It provides high availability with no single point of failure, elastic scalability and tunable consistency. Cassandra uses consistent hashing to partition and distribute data across nodes, vector clocks to track data versions for consistency, and Merkle trees to detect and repair inconsistencies between replicas.
The document provides an introduction to Cassandra presented by Nick Bailey. It discusses key Cassandra concepts like cluster architecture, data modeling using CQL, and best practices. Examples are provided to illustrate how to model time-series data and denormalize schemas to support different queries. Tools for testing Cassandra implementations like CCM and client drivers are also mentioned.
Cassandra is a distributed database management system designed to handle large amounts of data across many commodity servers. It provides high availability with no single points of failure and linear scalability as nodes are added. Cassandra uses a peer-to-peer distributed architecture and tunable consistency levels to achieve high performance and availability without requiring strong consistency. It is based on Amazon's Dynamo and Google's Bigtable papers and provides a combination of their features.
Apache Cassandra is a free, distributed, open source, and highly scalable NoSQL database that is designed to handle large amounts of data across many commodity servers. It provides high availability with no single point of failure, linear scalability, and tunable consistency. Cassandra's architecture allows it to spread data across a cluster of servers and replicate across multiple data centers for fault tolerance. It is used by many large companies for applications that require high performance, scalability, and availability.
This presentation shortly describes key features of Apache Cassandra. It was held at the Apache Cassandra Meetup in Vienna in January 2014. You can access the meetup here: http://www.meetup.com/Vienna-Cassandra-Users/
IDMEF, the universal format for security alerts, OW2con'16, Paris. OW2
The constant growth of cybercrime requires that nations are organizing to unite their defense and protection. In the area of cyber-detection federation requires standardizing in two fields:
- Communications between the various tools and security solutions in order to consolidate and correlate information simply, we will call this communication “intra” Security Centers.
- Communications between different Security Centers Teams to share information on incidents, we will call this communications “inter” Security Centers (between CSIRT).
Both recognized standards at IETF in this field are:
- IDMEF (Intrusion Detection Message Exchange Format) – RFC 4765
- IODEF (Incident Object Description Exchange Format) – RFC 5070
These two standards are still relatively new and insufficiently deployed on a market still dominated by proprietary formats.
Prelude is a SIEM (Security Information & Event Management). This is a security control tool that fully use IDMEF. Prelude collects and centralizes the company security information of to provide a central point of steering. Thanks to the analysis and correlation of logs, Prelude alerts in real time of intrusion attempts and threats on the network. Prelude offers several tools of investigation and reporting on your big data to identify the weak signals which may prefigure of advanced persistent threats (APT). Finally, Prelude has all the tools to help the operation to simplify operators’ work and risk management.
This document provides biographical information on Eric Wildi including his awards, patents, publications, and technical experience. It highlights that Eric Wildi has received several prestigious awards including the GE CR&D Dushman Award and Science Digest Top 100 Award. He also holds over 20 patents related to semiconductor devices and integrated circuits. Wildi has extensive experience in high-voltage integrated circuits and power electronics and has published widely with papers in conferences and journals.
The document discusses a cloud platform called SOARWare for service-oriented software development. SOARWare aims to improve software development productivity through reusable services over the internet. It provides tools for requirements specification, software development, service management, composition, and runtime management. SOARWare has been applied successfully in various domains including e-government, satellites, remote sensing, health, and geology through 7 applications developed by 12 collaborating organizations. The Trustie project, a key Chinese research initiative, focuses on producing highly trustworthy software using service-oriented approaches and SOARWare supports this through tools for design, development, and runtime support of services.
A Hahn Golf Academia & Club hivatalos megnyitójára 2009. július 16-án csütörtökön kerül sor Gödön a Pólus Palace Thermal Hotelben. A prezentáció erre az alkalomra készült.
The XLcloud project strives to establish the demonstration of a High Performance Cloud Computing (HPCC) platform based on OpenStack that is designed to run a representative set of compute intensive workloads. Two Use Cases will be demonstrated during this presentation. First, the interventional radiology use case of the XLCloud project has the goal to show that the XLCLoud platform can be used to leverage an application requiring both interaction and high performance computing. This simulator, developed by CEA and Esprimed, allows medical staff to prepare or replay an intervention in a 3D interactive environment (manipulation of the radiological system, position of people and their protections) while having the benefit of precise estimation of the dose they are exposed to through a 3D monte carlo simulation optimized in order to provide results in interactive time. The second use case will be based on cloud gaming and 3D visualization. XLcloud is a three-year long collaborative project funded by the French FSN (Fonds national pour la Société Numérique) programme.
A new interface between smart device and web using html5 web socket and qr codeMatthew Chang
This document proposes a new interface between smart devices and the web using HTML5 WebSocket and QR codes. The author developed a remote soccer game demo where users can control gameplay on their smart devices and view it through a web browser on their laptop or desktop. HTML5 WebSockets allow for two-way communication between the server and clients, enabling real-time updates between the game and controllers. The author used technologies like Node.js, Socket.io and QR codes to link smart devices to the game interface on the web.
TDC 2012 - Métricas de código na arquiteturaLeandro Daniel
O documento discute métricas de código e como elas podem ser usadas para melhorar o design de software e testes. Ele explica conceitos como complexidade ciclomática e acoplamento e como métricas como essas podem guiar a tomada de decisões de design. Ferramentas para análise de métricas também são apresentadas.
Big data and mass analytical processing have gained a prime position over the past years in business and have touched almost all domains of society. According to the famous Gartner “3Vs” definition, big data deals with Volume, Velocity and Variety. It enables organizations to exploit information that was previously ignored because there was no reasonable way to process it. One talks about the big data revolution but underpinning this revolution is the capacity to process unstructured data such as written documents, images, audio and videos which make up more than 80 percent of available data today. The WebLab platform aims at building systems providing intelligence solutions from the processing of open source data. Such systems face three major challenges: • Managing large amounts of unstructured data, • Managing the data diversity with the appropriate combination of processing tools , • Allowing the most effective tools to be selected for each processing step. Like Big Data, WebLab addresses intelligence needs and deals with Volume, Variety and Velocity. Can we therefore say that Big Data and WebLab face the same challenges? In fact, it can be argued that Big Data and WebLab are complementary. How can we benefit, then, from the best of both worlds?
The document discusses the complex structure of the US federal tax law, which results from competing objectives in developing tax policy. It outlines various economic, social, equity and political considerations that influence tax law. It also describes the key agencies and sources of tax law, including the Internal Revenue Code, Treasury regulations, revenue rulings, judicial precedents and more. Finally, it discusses tax research and the process of identifying, assessing and applying relevant tax law authorities to arrive at solutions to tax issues.
The document discusses information flow processing and different related models. It describes how information flow processing engines can process live data streams in real-time without persistent storage. It also summarizes two main competing models - Data Stream Management Systems (DSMS) which are an evolution of database management systems, and Complex Event Processing (CEP) which focuses on detecting complex patterns in event streams. Finally, it outlines several ways of modeling information flow processing including functional, processing, time, data, rule, language, and deployment models.
The document describes the Chubby lock service, which provides a centralized lock service using Paxos consensus. Chubby maintains a simple database replicated across servers (replicas), with one server elected as the master via Paxos. Clients can perform read and write operations on the database by communicating only with the master server. The lock service provides reliability and availability rather than high performance. It was used in Google systems like GFS, Bigtable to coordinate processes and ensure only one acts on a shared resource at a time.
The document discusses deadlocks that can occur in a multiprocessing system where multiple processes compete for limited resources. A deadlock occurs when a process is waiting for a resource held by another waiting process, resulting in a circular wait. The document outlines the four conditions required for deadlock and describes methods to prevent deadlocks, including imposing a total ordering of resource requests and avoiding holding resources while waiting for additional resources.
The document discusses process synchronization techniques, including semaphores. It describes semaphores as a synchronization tool that provides more sophisticated ways for processes to synchronize activities than mutex locks. Semaphores use wait() and signal() operations to decrement and increment an integer value to control access to shared resources. The document also discusses potential issues with semaphores like deadlock, starvation, and priority inversion, and how monitors provide an alternative approach.
Time, clocks and the ordering of eventsAmir Payberah
The document discusses modeling distributed systems. It defines a distributed system as a set of nodes connected by a network that appear as a single system to users. It describes modeling nodes as state machines that can send/receive messages and do computations. The document also discusses modeling message passing between nodes and the network connecting them.
The document discusses various security threats to computer systems, including breaches of confidentiality, integrity, availability, and denial of service. It describes common attack methods like masquerading, replay attacks, and man-in-the-middle attacks. Specific threats discussed in more detail include Trojan horses, trap doors, logic bombs, stack and buffer overflows, and viruses. Security needs to be implemented at the physical, human, operating system, and network levels to be effective.
This document presents a mathematical model for analyzing the spread of computer viruses through a network. It modifies an existing epidemic model by incorporating a range of parameters rather than constant values. The model classifies computers into four groups: susceptible, exposed, infected, and immunized. It uses differential equations to model how the population in each group changes over time and analyzes the epidemic threshold. The document estimates parameter values based on studies of real computer viruses. It aims to help understand virus spreading and determine measures to control viral epidemics.
Modeling and Threshold Sensitivity Analysis of Computer Virus EpidemicIOSR Journals
This document presents a mathematical model for analyzing the spread of computer viruses through a network. It modifies an existing epidemic model by incorporating a range of parameters rather than constant values. The model classifies computers into four groups: susceptible, exposed, infected, and immunized. It uses differential equations to model how the population in each group changes over time and analyzes the epidemic threshold. The document estimates parameter values based on studies of real computer viruses. It aims to help understand virus spreading and determine measures to control viral epidemics.
This document provides a summary of Andrew Heuze's education and career experience. He received a BSc in Biological Sciences in 2001 and has over 20 years of experience in life sciences research, primarily in assay development and high-throughput screening. His career includes roles at AstraZeneca from 1996-2012 developing cell-based and biochemical assays and running primary screens of over 1 million compounds. He currently works at Thermo Fisher Scientific running biochemical screens for pharmaceutical companies.
Applying principles of chaos engineering to serverless (ServerlessCPH)Yan Cui
Chaos engineering is a discipline that focuses on improving system resilience through experiments that expose the inherent chaos and failure modes in our system, in a controlled fashion, before these failure modes manifest themselves like a wildfire in production and impact our users.
Netflix is undoubtedly the leader in this field, but much of the publicised tools and articles focus on killing EC2 instances, and the efforts in the serverless community has been largely limited to moving those tools into AWS Lambda functions.
But how can we apply the same principles of chaos to a serverless architecture built around AWS Lambda functions?
These serverless architectures have more inherent chaos and complexity than their serverful counterparts, and, we have less control over their runtime behaviour. In short, there are far more unknown unknowns with these systems.
Can we adapt existing practices to expose the inherent chaos in these systems? What are the limitations and new challenges that we need to consider?
Join us in this talk as Yan Cui shares his thought experiments, and actual experiments, in his pursuit to understand how we can apply the principles of chaos to a serverless architecture. A word of warning though, you’re guaranteed to walk away with more questions than answers!
AUDIO CRYPTOGRAPHY VIA ENHANCED GENETIC ALGORITHMijma
As communication technologies surged recently, the secrecy of shared information between communication parts has gained tremendous attention. Many Cryptographic techniques have been proposed/implemented to secure multimedia data and to allay public fears during communication. This paper expands the scope of audio data security via an enhanced genetic algorithm. Here, each individual (audio sample) is genetically engineered to produce new individuals. The enciphering process of the proposed technology acquires, conditions, and transforms each audio sample into bit strings. Bits fission, switching, mutation, fusion, and deconditioning operations are then applied to yield cipher audio signals. The original audio sample is recovered at the receiver's end through a deciphering process without the loss of any inherent message. The novelty of the proposed technique resides in the integration of fission and fusion into the traditional genetic algorithm operators and the use of a single (rather than two) individual(s) for reproduction. The effectiveness of the proposed cryptosystem is demonstrated through simulations and performance analyses.
Introduction to Operating Systems - Part1Amir Payberah
This document provides an introduction to an operating systems course. It outlines the course objectives, which are to teach the design of operating systems and cover topics like process management, memory management, file systems, I/O management, and security. It also lists the course textbooks and explains that the course grade will be based on midterm and final exams as well as programming assignments done in groups of three students.
Introduction into Fault-tolerant Distributed Algorithms and their Modeling (P...Iosif Itkin
The document discusses the challenges of modeling and verifying fault-tolerant distributed algorithms. It notes that subtle bugs can hide in complex concurrent systems even with extensive testing. It advocates using a precise high-level description of a design and sound verification methods to analyze these algorithms more thoroughly. The key challenges identified include modeling diverse fault models, parameterized systems, and the interplay of safety and liveness properties.
SIP Flooding Attack Detection Using Hybrid Detection AlgorithmEditor IJMTER
The session initiation protocol is the signalling protocol,for controlling voice and video
communication over the internet protocol.SIP is however designed with open structure vulnerable
to security attak.The SIP flooding attack is the most severe attack becouse it is easy to launch and
capable of quickly draining the resources of both network and node. The existing flooding
detection schemes are either anomaly based or misuse based.The anomaly based scheme can detect
unknown attack it does not need the proir knowledge of the attack,but it generates some false
alarm,suffers from accuracy problem and gives false positive.Similarly the misuse based schemes
have high detection accuracy,no false positive but it cannot detect unknown attack.To overcome
problems in both detection schemes a hybrid detection scheme is proposed.the proposed hybrid
scheme consist features of both anomaly based scheme and misuse based scheme,and it gives fast
response,increase accuracy of detection and no false alarm
The document discusses the two generals' problem and the replicated state machine problem, where agreement between nodes is challenging due to asynchrony and failures. It introduces the two-phase commit protocol as a solution to reach consensus in distributed systems. The two-phase commit protocol involves a prepare phase where nodes vote to commit or abort, and a commit phase where based on the votes the coordinator decides on a final outcome. The document also discusses handling timeouts and failures during the protocol.
Probabilistic models for anomaly detection based on usage of network trafficAlexander Decker
This document discusses probabilistic models for anomaly detection based on network traffic usage. It introduces several probabilistic methods and statistical models that can be used for network traffic anomaly detection, including Bayesian theorem, mean and standard deviation models, point and interval estimations, multivariate regression models, Markov processes, and time series models. As an example, it describes modeling the spread of computer worms using epidemiological models such as linear, exponential, logistic, and differential equation models. It also discusses the different possible scenarios an intrusion detection system can encounter and how to calculate probabilities of outcomes using Bayesian theorem.
Random Keying Technique for Security in Wireless Sensor Networks Based on Mem...ijcsta
The document proposes a random keying technique combined with memetics concepts to provide security in wireless sensor networks. It involves randomly selecting keys from ranges distributed from the base station to cluster heads and nodes. When a node communicates, it selects keys that undergo crossover and mutation to generate header and trailer keys. The receiving node verifies packets by applying the same operations to the header keys and comparing the results to the trailer keys. Simulations showed this technique effectively combats spoofing attacks while being energy efficient compared to cryptographic methods.
The document discusses Pregel, a graph-parallel processing platform developed at Google for large-scale graph processing. Pregel is inspired by the bulk synchronous parallel (BSP) model and uses a vertex-centric programming model where computation is viewed as messages passed between graph vertices. In Pregel, applications run as a series of supersteps where vertices can update themselves and pass messages to other vertices, with global synchronization between supersteps. This model is better suited for graph problems compared to more general data-parallel systems.
The document discusses peer-to-peer (P2P) content distribution systems like BitTorrent and Spotify. It describes how BitTorrent works by breaking files into pieces that are distributed among peers using a tracker. Peers select rare pieces first and cooperate through a tit-for-tat approach. Spotify's P2P system supplements streaming from servers by also getting pieces from other users' devices to improve performance and scalability.
The document discusses cloud computing concepts including definitions, characteristics, service models, and deployment models. Cloud computing refers to applications and services delivered over the internet (SaaS) as well as the underlying hardware and software (utility computing). There are three main service models - Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS) - which provide different levels of control over computing resources, analogous to building a new house, buying an empty house, and renting a hotel room, respectively. The four deployment models define the scope and access of cloud infrastructure - public, private, community, and hybrid clouds.
The document discusses data intensive computing frameworks. It provides background on big data, how it is stored and processed at scale. Specifically, it discusses distributed file systems like HDFS, databases including relational and NoSQL approaches, and data processing frameworks like MapReduce. It aims to explain challenges in big data and how these tools address issues like scalability, fault tolerance and distributed computation.
The Stratosphere Big Data Analytics PlatformAmir Payberah
The document discusses the Stratosphere platform for distributed data analysis. Stratosphere is built on HDFS and YARN and focuses on ease of programming. It extends the MapReduce model with additional operators and supports complex data flows and iterative algorithms. The execution engine uses a master-worker architecture and provides fault tolerance through backup task deployment and recovery from intermediate results.
This document discusses the Spark big data analytics platform. It begins with an introduction to Spark and Scala. It then covers Spark concepts like RDDs and transformations. It describes how to process big data using techniques like scaling out. Finally, it outlines concepts like streaming and graph analytics that can be done with Spark and provides an agenda for the document.
The document discusses computer protection models. It describes a model where a computer consists of objects that can be uniquely named and accessed through defined operations. The protection problem is to ensure each object is only accessed correctly by allowed processes. It also discusses principles of protection like least privilege and separation of policy and mechanism. Different types of protection domains like users, processes, and procedures are described along with examples of UNIX and Multics domain implementations using access matrices.
This document provides an introduction to Linux kernel modules and device drivers. It discusses what kernel modules are, how they are loaded and unloaded, and provides examples of "Hello World" kernel modules. It also discusses device drivers, specifically character device drivers, and how they interface with the kernel via file operations structures. Major and minor numbers are introduced as how devices are identified. The document is intended to teach the basics of Linux kernel module and device driver programming.
The document discusses input/output (I/O) systems. It describes how I/O devices connect to computers through ports, busses, and device controllers. Device drivers present a uniform interface to access devices. Common I/O hardware concepts are discussed, including polling and interrupt-driven interactions between processors and controllers. Interrupt vectors route interrupts to specific handler routines. Interrupts are also used for exceptions and system calls.
The document discusses various techniques for implementing file systems, including on-disk and in-memory data structures. On-disk structures include boot blocks, volume blocks, directory structures, and file control blocks. In-memory structures include mount tables, directory trees, open file tables, and buffered file system blocks. The document also discusses virtual file systems, directory implementations using lists and hashes, allocation methods, and free space management techniques like bit vectors, linked lists, grouping, counting, and space maps.
The document discusses the motivation and design of file system implementations. It describes how file systems map the logical structure to physical storage, using various on-disk and in-memory data structures. These include boot blocks, superblocks, directories, inodes/file control blocks, buffer caches, open file tables, and more. Common operations like creating, opening, reading and closing files are also outlined.
The document discusses file systems and file operations. It states that for most users, the file system is the most visible part of an operating system as it provides mechanisms to access data and programs stored on devices. The file system consists of files organized in a directory structure. Files have attributes like name, size, permissions. Common file operations are create, read, write, delete. Information about open files is tracked in tables. The document also discusses file locking, structures, and the stat system call for retrieving file metadata.
The document discusses secondary storage and disk drives. It describes how magnetic disks work, including disk platters, tracks, sectors, and cylinders. It explains disk addressing and structures, as well as different types of disk attachment like host-attached storage, network-attached storage, and storage area networks. The document also covers disk scheduling algorithms like first-come first-served, shortest seek time first, SCAN, and C-SCAN that are used to determine the service order of requests to optimize disk performance.
The document discusses virtual memory and techniques for allocating frames to processes. It covers:
- Fixed allocation schemes like equal allocation and proportional allocation that split frames among processes.
- Priority allocation that gives more frames to higher priority processes.
- Global and local page replacement policies for determining which process's frame to replace on a page fault.
- Thrashing that occurs when a process does not have enough frames for its current locality or working set of pages. Locality and working set models are discussed for determining how many frames a process needs to avoid thrashing.
The document discusses virtual memory and demand paging. It motivates virtual memory by explaining how programs can exceed physical memory limits and how virtual memory allows programs to run partially loaded. Demand paging is introduced as a technique where pages are swapped into memory on demand when accessed, rather than pre-loading the entire program. This reduces I/O and allows multiple programs to share memory.
The document discusses paging in computer memory management. Paging divides both physical and logical memory into fixed-size blocks called frames and pages, respectively. It allows processes to have non-contiguous physical address spaces by mapping pages to available frames using a page table. While this avoids external fragmentation, it still suffers from internal fragmentation. Other topics covered include TLBs to reduce translation time, page sizes tradeoffs, memory protection using valid-invalid bits, and address space identifiers.
Main memory is a large array of bytes that each have their own address. Programs must be loaded into main memory from disk in order to run. The CPU fetches instructions from main memory based on the program counter value. Main memory access takes many CPU cycles, so cache is used to reduce access time. Memory management units map virtual addresses used by programs to physical addresses in main memory through address translation.
The document discusses CPU scheduling for real-time systems. It describes two types of latencies that affect real-time performance: interrupt latency, which is the time from when an interrupt occurs to when it is serviced, and dispatch latency, which is the time to switch from the current process to a higher priority one. For hard real-time systems, tasks must be serviced by their deadline to avoid missing events. The document also mentions periodic processes that require CPU access at constant intervals.
The document discusses CPU scheduling in operating systems. It provides background on CPU scheduling, including its purpose in multiprogrammed operating systems. It describes basic concepts like the CPU-I/O burst cycle and CPU burst distributions. It then covers the CPU scheduler, dispatcher, and different criteria used for scheduling like CPU utilization, throughput, turnaround time, waiting time, and response time. Finally, it introduces some common scheduling algorithms like first-come first-served, shortest-job-first, priority scheduling, round-robin, multilevel queue scheduling, and multilevel feedback queue scheduling.
The document discusses process synchronization and the producer-consumer problem. It describes how concurrent access to shared data by processes may result in data inconsistency issues. It then presents a solution to the producer-consumer problem using a counter to track the number of full buffers. The document also discusses the critical section problem, where a section of code containing shared resources can only be accessed by one process at a time. It presents Peterson's algorithm as a solution to the critical section problem for two processes.
The document discusses threads and threading models. It defines a thread as a basic unit of CPU utilization. It describes how traditional processes have a single thread, while multiple threads in a process can perform more than one task simultaneously by sharing resources. The main threading models of many-to-one, one-to-one, and many-to-many are summarized. Key thread libraries like pthreads and differences between user and kernel threads are also outlined.
A Comprehensive Guide on Implementing Real-World Mobile Testing Strategies fo...kalichargn70th171
In today's fiercely competitive mobile app market, the role of the QA team is pivotal for continuous improvement and sustained success. Effective testing strategies are essential to navigate the challenges confidently and precisely. Ensuring the perfection of mobile apps before they reach end-users requires thoughtful decisions in the testing plan.
Orca: Nocode Graphical Editor for Container OrchestrationPedro J. Molina
Tool demo on CEDI/SISTEDES/JISBD2024 at A Coruña, Spain. 2024.06.18
"Orca: Nocode Graphical Editor for Container Orchestration"
by Pedro J. Molina PhD. from Metadev
Building API data products on top of your real-time data infrastructureconfluent
This talk and live demonstration will examine how Confluent and Gravitee.io integrate to unlock value from streaming data through API products.
You will learn how data owners and API providers can document, secure data products on top of Confluent brokers, including schema validation, topic routing and message filtering.
You will also see how data and API consumers can discover and subscribe to products in a developer portal, as well as how they can integrate with Confluent topics through protocols like REST, Websockets, Server-sent Events and Webhooks.
Whether you want to monetize your real-time data, enable new integrations with partners, or provide self-service access to topics through various protocols, this webinar is for you!
WWDC 2024 Keynote Review: For CocoaCoders AustinPatrick Weigel
Overview of WWDC 2024 Keynote Address.
Covers: Apple Intelligence, iOS18, macOS Sequoia, iPadOS, watchOS, visionOS, and Apple TV+.
Understandable dialogue on Apple TV+
On-device app controlling AI.
Access to ChatGPT with a guest appearance by Chief Data Thief Sam Altman!
App Locking! iPhone Mirroring! And a Calculator!!
Alluxio Webinar | 10x Faster Trino Queries on Your Data PlatformAlluxio, Inc.
Alluxio Webinar
June. 18, 2024
For more Alluxio Events: https://www.alluxio.io/events/
Speaker:
- Jianjian Xie (Staff Software Engineer, Alluxio)
As Trino users increasingly rely on cloud object storage for retrieving data, speed and cloud cost have become major challenges. The separation of compute and storage creates latency challenges when querying datasets; scanning data between storage and compute tiers becomes I/O bound. On the other hand, cloud API costs related to GET/LIST operations and cross-region data transfer add up quickly.
The newly introduced Trino file system cache by Alluxio aims to overcome the above challenges. In this session, Jianjian will dive into Trino data caching strategies, the latest test results, and discuss the multi-level caching architecture. This architecture makes Trino 10x faster for data lakes of any scale, from GB to EB.
What you will learn:
- Challenges relating to the speed and costs of running Trino in the cloud
- The new Trino file system cache feature overview, including the latest development status and test results
- A multi-level cache framework for maximized speed, including Trino file system cache and Alluxio distributed cache
- Real-world cases, including a large online payment firm and a top ridesharing company
- The future roadmap of Trino file system cache and Trino-Alluxio integration
🏎️Tech Transformation: DevOps Insights from the Experts 👩💻campbellclarkson
Connect with fellow Trailblazers, learn from industry experts Glenda Thomson (Salesforce, Principal Technical Architect) and Will Dinn (Judo Bank, Salesforce Development Lead), and discover how to harness DevOps tools with Salesforce.
Stork Product Overview: An AI-Powered Autonomous Delivery FleetVince Scalabrino
Imagine a world where instead of blue and brown trucks dropping parcels on our porches, a buzzing drove of drones delivered our goods. Now imagine those drones are controlled by 3 purpose-built AI designed to ensure all packages were delivered as quickly and as economically as possible That's what Stork is all about.
Why Apache Kafka Clusters Are Like Galaxies (And Other Cosmic Kafka Quandarie...Paul Brebner
Closing talk for the Performance Engineering track at Community Over Code EU (Bratislava, Slovakia, June 5 2024) https://eu.communityovercode.org/sessions/2024/why-apache-kafka-clusters-are-like-galaxies-and-other-cosmic-kafka-quandaries-explored/ Instaclustr (now part of NetApp) manages 100s of Apache Kafka clusters of many different sizes, for a variety of use cases and customers. For the last 7 years I’ve been focused outwardly on exploring Kafka application development challenges, but recently I decided to look inward and see what I could discover about the performance, scalability and resource characteristics of the Kafka clusters themselves. Using a suite of Performance Engineering techniques, I will reveal some surprising discoveries about cosmic Kafka mysteries in our data centres, related to: cluster sizes and distribution (using Zipf’s Law), horizontal vs. vertical scalability, and predicting Kafka performance using metrics, modelling and regression techniques. These insights are relevant to Kafka developers and operators.
14 th Edition of International conference on computer visionShulagnaSarkar2
About the event
14th Edition of International conference on computer vision
Computer conferences organized by ScienceFather group. ScienceFather takes the privilege to invite speakers participants students delegates and exhibitors from across the globe to its International Conference on computer conferences to be held in the Various Beautiful cites of the world. computer conferences are a discussion of common Inventions-related issues and additionally trade information share proof thoughts and insight into advanced developments in the science inventions service system. New technology may create many materials and devices with a vast range of applications such as in Science medicine electronics biomaterials energy production and consumer products.
Nomination are Open!! Don't Miss it
Visit: computer.scifat.com
Award Nomination: https://x-i.me/ishnom
Conference Submission: https://x-i.me/anicon
For Enquiry: Computer@scifat.com
The Rising Future of CPaaS in the Middle East 2024Yara Milbes
Explore "The Rising Future of CPaaS in the Middle East in 2024" with this comprehensive PPT presentation. Discover how Communication Platforms as a Service (CPaaS) is transforming communication across various sectors in the Middle East.
Consistent toolbox talks are critical for maintaining workplace safety, as they provide regular opportunities to address specific hazards and reinforce safe practices.
These brief, focused sessions ensure that safety is a continual conversation rather than a one-time event, which helps keep safety protocols fresh in employees' minds. Studies have shown that shorter, more frequent training sessions are more effective for retention and behavior change compared to longer, infrequent sessions.
Engaging workers regularly, toolbox talks promote a culture of safety, empower employees to voice concerns, and ultimately reduce the likelihood of accidents and injuries on site.
The traditional method of conducting safety talks with paper documents and lengthy meetings is not only time-consuming but also less effective. Manual tracking of attendance and compliance is prone to errors and inconsistencies, leading to gaps in safety communication and potential non-compliance with OSHA regulations. Switching to a digital solution like Safelyio offers significant advantages.
Safelyio automates the delivery and documentation of safety talks, ensuring consistency and accessibility. The microlearning approach breaks down complex safety protocols into manageable, bite-sized pieces, making it easier for employees to absorb and retain information.
This method minimizes disruptions to work schedules, eliminates the hassle of paperwork, and ensures that all safety communications are tracked and recorded accurately. Ultimately, using a digital platform like Safelyio enhances engagement, compliance, and overall safety performance on site. https://safelyio.com/
Transforming Product Development using OnePlan To Boost Efficiency and Innova...OnePlan Solutions
Ready to overcome challenges and drive innovation in your organization? Join us in our upcoming webinar where we discuss how to combat resource limitations, scope creep, and the difficulties of aligning your projects with strategic goals. Discover how OnePlan can revolutionize your product development processes, helping your team to innovate faster, manage resources more effectively, and deliver exceptional results.
Unlock the Secrets to Effortless Video Creation with Invideo: Your Ultimate G...The Third Creative Media
"Navigating Invideo: A Comprehensive Guide" is an essential resource for anyone looking to master Invideo, an AI-powered video creation tool. This guide provides step-by-step instructions, helpful tips, and comparisons with other AI video creators. Whether you're a beginner or an experienced video editor, you'll find valuable insights to enhance your video projects and bring your creative ideas to life.
Baha Majid WCA4Z IBM Z Customer Council Boston June 2024.pdfBaha Majid
IBM watsonx Code Assistant for Z, our latest Generative AI-assisted mainframe application modernization solution. Mainframe (IBM Z) application modernization is a topic that every mainframe client is addressing to various degrees today, driven largely from digital transformation. With generative AI comes the opportunity to reimagine the mainframe application modernization experience. Infusing generative AI will enable speed and trust, help de-risk, and lower total costs associated with heavy-lifting application modernization initiatives. This document provides an overview of the IBM watsonx Code Assistant for Z which uses the power of generative AI to make it easier for developers to selectively modernize COBOL business services while maintaining mainframe qualities of service.
Baha Majid WCA4Z IBM Z Customer Council Boston June 2024.pdf
Gossip-based algorithms
1. Epidemic Algorithms
Amir H. Payberah
amir@sics.se
Amirkabir University of Technology
(Tehran Polytechnic)
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 1 / 60
2. What is the Problem?
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 2 / 60
3. What is the Problem?
Application-level broadcast/multicast
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 3 / 60
4. What is the Problem?
Application-level broadcast/multicast
• Database replication
• Video streaming
• RSS feeds
• ...
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 3 / 60
6. Possible Solutions
Flooding
• Robust, but inefficient (O(n2
))
Tree
• Efficient (O(n)), but fragile
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 4 / 60
7. Possible Solutions
Flooding
• Robust, but inefficient (O(n2
))
Tree
• Efficient (O(n)), but fragile
Gossip
• Efficient (O(nlogn)) and robust, but has relative high latency
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 4 / 60
8. Possible Solutions
Flooding
• Robust, but inefficient (O(n2
))
Tree
• Efficient (O(n)), but fragile
Gossip
• Efficient (O(nlogn)) and robust, but has relative high latency
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 4 / 60
10. Introduction
Epidemiology studies the spread of a disease or infection in terms
of populations of infected/uninfected individuals and their rates of
change.
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 6 / 60
11. Introduction
Epidemiology studies the spread of a disease or infection in terms
of populations of infected/uninfected individuals and their rates of
change.
Nodes infect each other trough messages.
Total number of messages is less than O(n2).
No node is overloaded.
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 6 / 60
12. Introduction
Epidemiology studies the spread of a disease or infection in terms
of populations of infected/uninfected individuals and their rates of
change.
Nodes infect each other trough messages.
Total number of messages is less than O(n2).
No node is overloaded.
But
• No deterministic guarantee on reliability.
• Only probabilistic ones.
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 6 / 60
13. History of the Epidemic/Gossip Paradigm
First defined by Alan Demers et al. (1987)
90s: gossip applied to the information dissemination problem
00s: gossip beyond dissemination
2006: Workshop on the future of gossip (Leiden, the Netherlands)
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 7 / 60
14. History of the Epidemic/Gossip Paradigm (1987)
Database replicated at thousands of nodes.
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 8 / 60
15. History of the Epidemic/Gossip Paradigm (1987)
Database replicated at thousands of nodes.
Heterogeneous and unreliable network.
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 8 / 60
16. History of the Epidemic/Gossip Paradigm (1987)
Database replicated at thousands of nodes.
Heterogeneous and unreliable network.
Independent updates to single elements of the DB are injected at
multiple nodes.
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 8 / 60
17. History of the Epidemic/Gossip Paradigm (1987)
Database replicated at thousands of nodes.
Heterogeneous and unreliable network.
Independent updates to single elements of the DB are injected at
multiple nodes.
Updates must propagate to all nodes or be supplanted by later up-
dates of the same element.
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 8 / 60
18. History of the Epidemic/Gossip Paradigm (1987)
Database replicated at thousands of nodes.
Heterogeneous and unreliable network.
Independent updates to single elements of the DB are injected at
multiple nodes.
Updates must propagate to all nodes or be supplanted by later up-
dates of the same element.
Replicas become consistent after no more new updates.
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 8 / 60
19. History of the Epidemic/Gossip Paradigm (Today)
Amazon uses a gossip protocol to quickly spread information
throughout the S3 system.
Amazon’s Dynamo uses a gossip-based failure detection service.
The basic information exchange in BitTorrent is based on gossip.
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 9 / 60
20. SIR Model (1/2)
Kermack and McKendrick, 1927
An individual p can be:
• Susceptible: if p is not yet infected by the disease.
• Infective: if p is infected and capable to spread the disease.
• Removed: if p has been infected and has recovered from the disease.
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 10 / 60
21. SIR Model (2/2)
Initially, a single individual is infective.
Individuals get in touch with each other, spreading the disease.
Susceptible individuals are turned into infective ones.
Eventually, infective individuals will become removed.
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 11 / 60
22. From Epidemiology to Distributed Systems
The idea
• Disease spread quickly and robustly.
• Our goal is to spread an update as fast and as reliable as possible.
• Can we apply these ideas to distributed systems?
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 12 / 60
23. From Epidemiology to Distributed Systems
The idea
• Disease spread quickly and robustly.
• Our goal is to spread an update as fast and as reliable as possible.
• Can we apply these ideas to distributed systems?
SIR Model for database replication:
• Susceptible: if p has not yet received an update.
• Infective: if p has not yet received an update.
• Removed: if p has the update but is no longer willing to share it.
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 12 / 60
24. Two Styles of Epidemic Protocols
Anti-entropy
Rumor mongering
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 13 / 60
25. Anti-Entropy
Each node p periodically contacts a random partner q selected from
the current population.
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 14 / 60
26. Anti-Entropy
Each node p periodically contacts a random partner q selected from
the current population.
Then, p and q engage in an information exchange protocol, where
updates known to p but not to q are transferred from p to q (push),
or vice-versa (pull), or in both direction (push-pull).
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 14 / 60
27. Rumor Mongering
Nodes are initially ignorant.
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 15 / 60
28. Rumor Mongering
Nodes are initially ignorant.
When an update is learned by a node, it becomes a hot rumor.
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 15 / 60
29. Rumor Mongering
Nodes are initially ignorant.
When an update is learned by a node, it becomes a hot rumor.
While a node holds a hot rumor, it periodically chooses a random
node from the current population and sends (pushes) the rumor to
it.
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 15 / 60
30. Rumor Mongering
Nodes are initially ignorant.
When an update is learned by a node, it becomes a hot rumor.
While a node holds a hot rumor, it periodically chooses a random
node from the current population and sends (pushes) the rumor to
it.
Eventually, a node will lose interest in spreading the rumor.
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 15 / 60
33. Aggregation
Aggregation provides a summary of some global system property.
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 18 / 60
34. Aggregation
Aggregation provides a summary of some global system property.
It allows local access to global information.
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 18 / 60
35. Aggregation
Aggregation provides a summary of some global system property.
It allows local access to global information.
Examples of aggregation functions:
• The average load of nodes in a cluster.
• The sum of free space in a distributed storage.
• The total number of nodes in a P2P system.
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 18 / 60
36. Aggregation Generic Framework (1/3)
Executed by all processes:
repeat evert t time units:
q = selectRandomPeer() // Select a random neighbor
send <p, pullRequest, Sp> to q
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 19 / 60
37. Aggregation Generic Framework (2/3)
Executed by all processes:
upon receive<p, pullRequest, Sp> do:
send <q, pullResponse, Sq> to p
Sq = update(Sp, Sq)
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 20 / 60
38. Aggregation Generic Framework (2/3)
Executed by all processes:
upon receive<p, pullRequest, Sp> do:
send <q, pullResponse, Sq> to p
Sq = update(Sp, Sq)
update function:
• avg: return (Sp + Sq) / 2
• max: return max(Sp, Sq)
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 20 / 60
39. Aggregation Generic Framework (3/3)
Executed by all processes:
upon receive<q, pullResponse, Sq> do:
Sp = update(Sp, Sq)
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 21 / 60
40. Aggregation Generic Framework (3/3)
Executed by all processes:
upon receive<q, pullResponse, Sq> do:
Sp = update(Sp, Sq)
update function:
• avg: return (Sp + Sq) / 2
• max: return max(Sp, Sq)
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 21 / 60
41. Aggregation Example (1/5)
Taking the average of the numbers in the nodes.
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 22 / 60
42. Aggregation Example (2/5)
Taking the average of the numbers in the nodes.
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 23 / 60
43. Aggregation Example (3/5)
Taking the average of the numbers in the nodes.
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 24 / 60
44. Aggregation Example (4/5)
Taking the average of the numbers in the nodes.
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 25 / 60
45. Aggregation Example (5/5)
Taking the average of the numbers in the nodes.
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 26 / 60
46. Network Size Estimation
Any ideas?
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 27 / 60
47. Network Size Estimation
Any ideas?
All nodes set their states to 0.
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 27 / 60
48. Network Size Estimation
Any ideas?
All nodes set their states to 0.
The initiator sets its state to 1 and starts gossiping for the average.
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 27 / 60
49. Network Size Estimation
Any ideas?
All nodes set their states to 0.
The initiator sets its state to 1 and starts gossiping for the average.
Eventually all nodes converge to the avg = 1
N .
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 27 / 60
51. Epidemic Protocols
In a epidemic (gossip) protocol, each node in the system periodically
exchanges information with a subset of nodes.
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 29 / 60
52. Epidemic Protocols
In a epidemic (gossip) protocol, each node in the system periodically
exchanges information with a subset of nodes.
The choice of this subset is crucial.
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 29 / 60
53. Epidemic Protocols
In a epidemic (gossip) protocol, each node in the system periodically
exchanges information with a subset of nodes.
The choice of this subset is crucial.
Ideally, the nodes should be selected following a uniform random
sample of all nodes currently in the system.
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 29 / 60
54. Achieving a Uniform Random Sample
Each node may be assumed to know every other node in the system.
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 30 / 60
55. Achieving a Uniform Random Sample
Each node may be assumed to know every other node in the system.
Providing each node with a complete membership table is unrealistic
in a large scale dynamic system.
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 30 / 60
56. Peer Sampling
An alternative solution.
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 31 / 60
57. Peer Sampling
An alternative solution.
Every node maintains a relatively small local membership table that
provides a partial view on the complete set of nodes.
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 31 / 60
58. Peer Sampling
An alternative solution.
Every node maintains a relatively small local membership table that
provides a partial view on the complete set of nodes.
Periodically refreshes the table using a gossiping procedure.
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 31 / 60
59. Peer Sampling Generic Framework (1/4)
Executed by all processes:
repeat evert t time units:
q = selectPeer()
buf = ((myAddress, 0))
view.permute()
move oldest H items to the end of view
buf.append(view.head(c/2-1))
send <p, psRequest, buf> to q
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 32 / 60
60. Peer Sampling Generic Framework (2/4)
Executed by all processes:
upon receive<p, psRequest, bufp> do:
buf = ((myAddress, 0))
view.permute()
move oldest H items to the end of view
buf.append(view.head(c/2-1))
send <q, psResponse, buf> to p
view.select(c, H, S, bufp)
view.increaseAge()
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 33 / 60
61. Peer Sampling Generic Framework (3/4)
Executed by all processes:
upon receive<q, psResponse, bufq> do:
view.select(c, H, S, bufq)
view.increaseAge()
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 34 / 60
63. Gossip-based Peer Sampling (1/7)
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 36 / 60
64. Gossip-based Peer Sampling (2/7)
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 37 / 60
65. Gossip-based Peer Sampling (3/7)
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 38 / 60
66. Gossip-based Peer Sampling (4/7)
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 39 / 60
67. Gossip-based Peer Sampling (5/7)
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 40 / 60
68. Gossip-based Peer Sampling (6/7)
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 41 / 60
69. Gossip-based Peer Sampling (7/7)
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 42 / 60
70. Peer Sampling Design Space
Peer Selection
• Rand: uniform random
• Tail: highest age
View Propagation
• Push
• Push-Pull
View Selection
• Blind: H = 0, S = 0
• Healer: H = c/2
• Swapper: H = 0, S = c/2
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 43 / 60
71. Cyclon as a Peer Sampling Service
Peer Selection
• Rand: uniform random
• Tail: highest age
View Propagation
• Push
• Push-Pull
View Selection
• Blind: H = 0, S = 0
• Healer: H = c/2
• Swapper: H = 0, S = c/2
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 44 / 60
72. Cyclon (1/5)
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 45 / 60
73. Cyclon (2/5)
Pick the oldest node from my view and remove it from the view
(tail)
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 46 / 60
74. Cyclon (3/5)
Exchange some of the nodes in neighbours (push-pull)
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 47 / 60
75. Cyclon (4/5)
Exchange some of the nodes in neighbours (push-pull)
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 48 / 60
76. Cyclon (5/5)
Update the views (swapper)
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 49 / 60
78. T-Man
T-man is a protocol to construct and maintain any topology with
the help of a ranking function.
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 51 / 60
79. T-Man
T-man is a protocol to construct and maintain any topology with
the help of a ranking function.
The ranking function orders any set of nodes according to their
desirability to be neighbors of a given node.
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 51 / 60
80. T-Man Generic Framework (1/3)
Executed by all processes.
repeat evert t time units:
q = selectPeer()
myDescriptor = (myAddress, myProfile)
buf = merge(view, myDescriptor)
buf = merge(buf, view.rnd)
send <p, tmanRequest, buf> to q
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 52 / 60
81. T-Man Generic Framework (1/3)
Executed by all processes.
repeat evert t time units:
q = selectPeer()
myDescriptor = (myAddress, myProfile)
buf = merge(view, myDescriptor)
buf = merge(buf, view.rnd)
send <p, tmanRequest, buf> to q
selectPeer
• Sort all nodes in the view based on ranking.
• Pick randomly one node from the first half.
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 52 / 60
82. T-Man Generic Framework (1/3)
Executed by all processes.
repeat evert t time units:
q = selectPeer()
myDescriptor = (myAddress, myProfile)
buf = merge(view, myDescriptor)
buf = merge(buf, view.rnd)
send <p, tmanRequest, buf> to q
selectPeer
• Sort all nodes in the view based on ranking.
• Pick randomly one node from the first half.
view.rnd
• Provides a random sample of the nodes from the entire network,
e.g., using cyclon.
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 52 / 60
83. T-Man Generic Framework (2/3)
Executed by all processes.
upon receive<p, psRequest, bufp> do:
myDescriptor = (myAddress, myProfile)
buf = merge(view, myDescriptor)
buf = merge(buf, rnd.view)
send <q, tmanResponse, buf> to p
buf = merge(bufp, view)
view = selectView(buf)
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 53 / 60
84. T-Man Generic Framework (2/3)
Executed by all processes.
upon receive<p, psRequest, bufp> do:
myDescriptor = (myAddress, myProfile)
buf = merge(view, myDescriptor)
buf = merge(buf, rnd.view)
send <q, tmanResponse, buf> to p
buf = merge(bufp, view)
view = selectView(buf)
selectView
• Sort all nodes in buffer (about double size of the view).
• Pick out c highest ranked nodes.
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 53 / 60
85. T-Man Generic Framework (3/3)
Executed by all processes.
upon receive<q, tmanResponse, bufq> do:
buf = merge(bufq, view)
view = selectView(buf)
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 54 / 60
86. T-Man Generic Framework (3/3)
Executed by all processes.
upon receive<q, tmanResponse, bufq> do:
buf = merge(bufq, view)
view = selectView(buf)
selectView
• Sort all nodes in buffer (about double size of the view).
• Pick out c highest ranked nodes.
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 54 / 60
87. Ranking Function
Sample ranking functions:
• Line: d(a, b) = |a − b|
• Ring: d(a, b) = min(N − |a − b|, |a − b|)
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 55 / 60
91. References:
M. Jelasity, and A. Montresor, Epidemic-style proactive aggregation
in large overlay networks, ICDCS, 2004.
M. Jelasity, and O. Babaoglu, T-Man: Gossip-based overlay topol-
ogy management, Engineering Self-Organising Systems, 2006.
M. Jelasity et al., Gossip-based peer sampling, TOCS, 2007.
S. Voulgaris, D. Gavidia, and M. Van Steen, Cyclon: Inexpensive
membership management for unstructured P2P overlays, Journal of
Network and Systems Management, 2005.
A. Demers et al., Epidemic algorithms for replicated database main-
tenance, PODC, 1987.
Amir H. Payberah (Tehran Polytechnic) Epidemic Algorithms 1393/7/7 59 / 60