3.1 Interprocess Communication
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Remote Procedure Calls
Lectures on distributed systems Remote Procedure Calls Paul Krzyzanowski Introduction, or what’s wrong with sockets? OCKETS are a fundamental part of client-server networking. They provide a S relatively easy mechanism for a program to establish a connection to another program, either on a remote or local machine and send messages back and forth (we can even use read and write system calls). This interface, however, forces us to design our distributed applications using a read/write (input/output) inter- face which is not how we generally design non-distributed applications. In design- ing centralized applications, the procedure call is usually the standard interface model. If we want to make distributed computing look like centralized comput- ing, input-output-based communications is not the way to accomplish this. In 1984, Birrell and Nelson devised a mechanism to allow programs to call procedures on other machines. A process on machine A can call a procedure on machine B. The process on A is suspended and execution continues on B. When B returns, the return value is passed to A and A continues execution. This mechanism is called the Remote Procedure Call (RPC). To the programmer, the goal is that it should appear as if a normal procedure call is taking place. Obvi- ously, a remote procedure call is different from a local one in the underlying implementation. Steps in a remote procedure call Clearly, there is no architectural support for making remote procedure calls. A local procedure call generally involves placing the calling parameters on the stack and executing some form of a call instruction to the address of the proce- dure. -
Efficient Inter-Core Communications on Manycore Machines
ZIMP: Efficient Inter-core Communications on Manycore Machines Pierre-Louis Aublin Sonia Ben Mokhtar Gilles Muller Vivien Quema´ Grenoble University CNRS - LIRIS INRIA CNRS - LIG Abstract—Modern computers have an increasing num- nication mechanisms enabling both one-to-one and one- ber of cores and, as exemplified by the recent Barrelfish to-many communications. Current operating systems operating system, the software they execute increasingly provide various inter-core communication mechanisms. resembles distributed, message-passing systems. To sup- port this evolution, there is a need for very efficient However it is not clear yet how these mechanisms be- inter-core communication mechanisms. Current operat- have on manycore processors, especially when messages ing systems provide various inter-core communication are intended to many recipient cores. mechanisms, but it is not clear yet how they behave In this report, we study seven communication mech- on manycore processors. In this report, we study seven anisms, which are considered state-of-the-art. More mechanisms, that are considered state-of-the-art. We show that these mechanisms have two main drawbacks that precisely, we study TCP, UDP and Unix domain sock- limit their efficiency: they perform costly memory copy ets, pipes, IPC and POSIX message queues. These operations and they do not provide efficient support mechanisms are supported by traditional operating sys- for one-to-many communications. We do thus propose tems such as Linux. We also study Barrelfish message ZIMP, a new inter-core communication mechanism that passing, the inter-process communication mechanism of implements zero-copy inter-core message communications and that efficiently handles one-to-many communications. -
D-Bus, the Message Bus System Training Material
Maemo Diablo D-Bus, The Message Bus System Training Material February 9, 2009 Contents 1 D-Bus, The Message Bus System 2 1.1 Introduction to D-Bus ......................... 2 1.2 D-Bus architecture and terminology ................ 3 1.3 Addressing and names in D-Bus .................. 4 1.4 Role of D-Bus in maemo ....................... 6 1.5 Programming directly with libdbus ................. 9 1 Chapter 1 D-Bus, The Message Bus System 1.1 Introduction to D-Bus D-Bus (the D originally stood for "Desktop") is a relatively new inter process communication (IPC) mechanism designed to be used as a unified middleware layer in free desktop environments. Some example projects where D-Bus is used are GNOME and Hildon. Compared to other middleware layers for IPC, D-Bus lacks many of the more refined (and complicated) features and for that reason, is faster and simpler. D-Bus does not directly compete with low level IPC mechanisms like sock- ets, shared memory or message queues. Each of these mechanisms have their uses, which normally do not overlap the ones in D-Bus. Instead, D-Bus aims to provide higher level functionality, like: Structured name spaces • Architecture independent data formatting • Support for the most common data elements in messages • A generic remote call interface with support for exceptions (errors) • A generic signalling interface to support "broadcast" type communication • Clear separation of per-user and system-wide scopes, which is important • when dealing with multi-user systems Not bound to any specific programming language (while providing a • design that readily maps to most higher level languages, via language specific bindings) The design of D-Bus benefits from the long experience of using other mid- dleware IPC solutions in the desktop arena and this has allowed the design to be optimised. -
Distributed Objects in C
Rochester Institute of Technology RIT Scholar Works Theses 2006 Distributed Objects in C# Xiaoyun Xie Follow this and additional works at: https://scholarworks.rit.edu/theses Recommended Citation Xie, Xiaoyun, "Distributed Objects in C#" (2006). Thesis. Rochester Institute of Technology. Accessed from This Master's Project is brought to you for free and open access by RIT Scholar Works. It has been accepted for inclusion in Theses by an authorized administrator of RIT Scholar Works. For more information, please contact [email protected]. Rochester Institute of Technology Department of Computer Science Master of Science Project Distributed Objects System in C# Submitted By: Xie, Xiaoyun (Sherry) Date: February 2004 Chairman: Dr. Axel T. Schreiner Reader: Dr. Hans-Peter Bischof Observer: Dr. James Heliotis 2 ABSTRACT Today more and more programs run over a collection of autonomous computers linked by a network and are designed to produce an integrated computing facility. Java Distributed Objects (JDO) proposed by Dr. Axel T. Schreiner [1] builds an infrastructure which allows distributed program components to communicate over a network in a transparent, reliable, efficient, and generic way. JDO was originally intended as a teaching device to assess design parameters for distributed objects. This project focuses on porting JDO, which is implemented in Java on Sun’s JDK, to C# on Microsoft’s .NET. On one hand, it builds an infrastructure in C# that simplifies the construction of distributed programs by hiding the distributed nature of remote objects. On the other hand, it generates insights into the differences between two platforms, namely, Java on Sun and C# on .NET, in the distributed objects area. -
Message Passing Model
Message Passing Model Giuseppe Anastasi [email protected] Pervasive Computing & Networking Lab. (PerLab) Dept. of Information Engineering, University of Pisa PerLab Based on original slides by Silberschatz, Galvin and Gagne Overview PerLab Message Passing Model Addressing Synchronization Example of IPC systems Message Passing Model 2 Operating Systems Objectives PerLab To introduce an alternative solution (to shared memory) for process cooperation To show pros and cons of message passing vs. shared memory To show some examples of message-based communication systems Message Passing Model 3 Operating Systems Inter-Process Communication (IPC) PerLab Message system – processes communicate with each other without resorting to shared variables. IPC facility provides two operations: send (message ) – fixed or variable message size receive (message ) If P and Q wish to communicate, they need to: establish a communication link between them exchange messages via send/receive The communication link is provided by the OS Message Passing Model 4 Operating Systems Implementation Issues PerLab Physical implementation Single-processor system Shared memory Multi-processor systems Hardware bus Distributed systems Networking System + Communication networks Message Passing Model 5 Operating Systems Implementation Issues PerLab Logical properties Can a link be associated with more than two processes? How many links can there be between every pair of communicating processes? What is the capacity of a link? Is the size of a message that the link can accommodate fixed or variable? Is a link unidirectional or bi-directional? Message Passing Model 6 Operating Systems Implementation Issues PerLab Other Aspects Addressing Synchronization Buffering Message Passing Model 7 Operating Systems Overview PerLab Message Passing Model Addressing Synchronization Example of IPC systems Message Passing Model 8 Operating Systems Direct Addressing PerLab Processes must name each other explicitly. -
Message Passing
COS 318: Operating Systems Message Passing Jaswinder Pal Singh Computer Science Department Princeton University (http://www.cs.princeton.edu/courses/cos318/) Sending A Message Within A Computer Across A Network P1 P2 Send() Recv() Send() Recv() Network OS Kernel OS OS COS461 2 Synchronous Message Passing (Within A System) Synchronous send: u Call send system call with M u send system call: l No buffer in kernel: block send( M ) recv( M ) l Copy M to kernel buffer Synchronous recv: u Call recv system call M u recv system call: l No M in kernel: block l Copy to user buffer How to manage kernel buffer? 3 API Issues u Message S l Buffer (addr) and size l Message type, buffer and size u Destination or source send(dest, msg) R l Direct address: node Id, process Id l Indirect address: mailbox, socket, recv(src, msg) channel, … 4 Direct Addressing Example Producer(){ Consumer(){ ... ... while (1) { for (i=0; i<N; i++) produce item; send(Producer, credit); recv(Consumer, &credit); while (1) { send(Consumer, item); recv(Producer, &item); } send(Producer, credit); } consume item; } } u Does this work? u Would it work with multiple producers and 1 consumer? u Would it work with 1 producer and multiple consumers? u What about multiple producers and multiple consumers? 5 Indirect Addressing Example Producer(){ Consumer(){ ... ... while (1) { for (i=0; i<N; i++) produce item; send(prodMbox, credit); recv(prodMbox, &credit); while (1) { send(consMbox, item); recv(consMbox, &item); } send(prodMbox, credit); } consume item; } } u Would it work with multiple producers and 1 consumer? u Would it work with 1 producer and multiple consumers? u What about multiple producers and multiple consumers? 6 Indirect Communication u Names l mailbox, socket, channel, … u Properties l Some allow one-to-one mbox (e.g. -
Configuring PGM Host and Router Assist
Configuring PGM Host and Router Assist Note Support for the PGM Host feature has been removed. Use of this feature is not recommended. This module describes the PGM Host and Router Assist feature. PGM Host and Router Assist enables Cisco routers to support multicast applications that operate at the PGM transport layer and the PGM network layer, respectively. The PGM Reliable Transport Protocol itself is implemented on the hosts of the customer. For information on PGM Reliable Transport Protocol, refer to the Internet Engineering Task Force (IETF) protocol specification draft named PGM Reliable Transport Protocol Specification. For a complete description of the PGM Router Assist commands in this module, see the Cisco IOS IP Multicast Command Reference. To locate documentation of other commands that appear in this module, use the command reference master index, or search online. To identify the hardware platform or software image information associated with a feature, use the Feature Navigator on Cisco.com to search for information about the feature or refer to the software release notes for a specific release. PGM Overview Pragmatic General Multicast (PGM) is a reliable multicast transport protocol for multicast applications that require reliable, ordered, duplicate-free multicast data delivery from multiple sources to multiple receivers. PGM guarantees that a receiver in a multicast group either receives all data packets from transmissions and retransmissions, or can detect unrecoverable data packet loss. PGM is intended as a solution for multicast applications with basic reliability requirements. PGM has two main parts: a host element (also referred to as the transport layer of the PGM protocol) and a network element (also referred to as the network layer of the PGM protocol). -
More Efficient Serialization and RMI for Java
To appear in: Concurrency: Practice & Experience, Vol. 11, 1999. More Ecient Serialization and RMI for Java Michael Philippsen, Bernhard Haumacher, and Christian Nester Computer Science Department, University of Karlsruhe Am Fasanengarten 5, 76128 Karlsruhe, Germany [phlippjhaumajnester]@ira.u ka.de http://wwwipd.ira.uka.de/JavaPa rty/ Abstract. In current Java implementations, Remote Metho d Invo ca- tion RMI is to o slow, esp ecially for high p erformance computing. RMI is designed for wide-area and high-latency networks, it is based on a slow ob ject serialization, and it do es not supp ort high-p erformance commu- nication networks. The pap er demonstrates that a much faster drop-in RMI and an ecient drop-in serialization can b e designed and implemented completely in Java without any native co de. Moreover, the re-designed RMI supp orts non- TCP/IP communication networks, even with heterogeneous transp ort proto cols. We demonstrate that for high p erformance computing some of the ocial serialization's generality can and should b e traded for sp eed. Asaby-pro duct, a b enchmark collection for RMI is presented. On PCs connected through Ethernet, the b etter serialization and the improved RMI save a median of 45 maximum of 71 of the runtime for some set of arguments. On our Myrinet-based ParaStation network a cluster of DEC Alphas wesave a median of 85 maximum of 96, compared to standard RMI, standard serialization, and Fast Ethernet; a remote metho d invo cation runs as fast as 80 s round trip time, compared to ab out 1.5 ms. -
Bimodal Multicast1
Bimodal Multicast1 Kenneth P. Birman, Mark Hayden, Oznur Ozkasap, Zhen Xiao, Mihai Budiu, Yaron Minsky There are many methods for making a multicast protocol "reliable". At one end of the spectrum, a reliable multicast protocol might offer atomicity guarantees, such as all-or- nothing delivery, delivery ordering, and perhaps additional properties such as virtually synchronous addressing. At the other are protocols that use local repair to overcome transient packet loss in the network, offering “best effort” reliability. Yet none of this prior work has treated stability of multicast delivery as a basic reliability property, such as might be needed in an internet radio, TV, or conferencing application. This paper looks at reliability with a new goal: development of a multicast protocol which is reliable in a sense that can be rigorously quantified and includes throughput stability guarantees. We characterize this new protocol as a "bimodal multicast" in reference to its reliability model, which corresponds to a family of bimodal probability distributions. Here, we introduce the protocol, provide a theoretical analysis of its behavior, review experimental results, and discuss some candidate applications. These confirm that bimodal multicast is reliable, scalable, and that the protocol provides remarkably stable delivery throughput. Keywords: Bimodal Multicast, probabilistic multicast reliability, scalable group communications, isochronous protocols, internet media transmission. Encamped on the hilltops overlooking the enemy fortress, the commanding general prepared for the final battle of the campaign. Given the information he was gathering about enemy positions, his forces could prevail. Indeed, if most of his observations could be communicated to most of his forces the battle could be won even if some reports reached none or very few of his troupes. -
Multiprocess Communication and Control Software for Humanoid Robots Neil T
IEEE Robotics and Automation Magazine Multiprocess Communication and Control Software for Humanoid Robots Neil T. Dantam∗ Daniel M. Lofaroy Ayonga Hereidx Paul Y. Ohz Aaron D. Amesx Mike Stilman∗ I. Introduction orrect real-time software is vital for robots in safety-critical roles such as service and disaster response. These systems depend on software for Clocomotion, navigation, manipulation, and even seemingly innocuous tasks such as safely regulating battery voltage. A multi-process software design increases robustness by isolating errors to a single process, allowing the rest of the system to continue operating. This approach also assists with modularity and concurrency. For real-time tasks such as dynamic balance and force control of manipulators, it is critical to communicate the latest data sample with minimum latency. There are many communication approaches intended for both general purpose and real-time needs [19], [17], [13], [9], [15]. Typical methods focus on reliable communication or network-transparency and accept a trade-off of increased mes- sage latency or the potential to discard newer data. By focusing instead on the specific case of real-time communication on a single host, we reduce communication latency and guarantee access to the latest sample. We present a new Interprocess Communication (IPC) library, Ach,1 which addresses this need, and discuss its application for real-time, multiprocess control on three humanoid robots (Fig. 1). There are several design decisions that influenced this robot software and motivated development of the Ach library. First, to utilize decades of prior development and engineering, we implement our real-time system on top of a POSIX-like Operating System (OS)2. -
Remote Procedure Call (RPC)
Remote Procedure Call (RPC) RPC – RMI - Web Services 1 Complexity of the distributed applications . The programming of distributed applications is difficult. In addition to the usual tasks, programmers who build clients and servers must deal with the complex issues of communication. Although many of the needed functions are supplied by a standard API such as the socket interface, the socket calls require the programmer to specify many low level details as names ,addresses,protocols and ports. Moreover, asinchronous communications models are complex to implement. Distributed implementations tend to use the same standard API (e.g.,the socket interface). As a consequence most of the detailed code found in one program is replicated in others RPC – RMI - Web Services 2 . For example, all client programs that use a connection oriented transport must create a socket, specify the server’s endpoint address, open a connection to the server, send requests,receive responses and close the connection when interaction is complete. Tools (software that generates all or part of a computer program) have been created to construct clients and servers. Tools cannot eliminate all programming: a programmer must supply the code that perform the computation for the particular service. However, a tool can handle the communication details. As a result the code contains fever bugs. RPC – RMI - Web Services 3 . RPC = Remote Procedure Call . The basic model has been proposed by Birrell e Nelson in 1984. The essence of this technique is to allow programs on different machines to interact using simple procedure call/return semantics, just as if the two programs were in the same computer . -
Inter Process Communication with Message Passing
Operating systems (vimia219) Collaboration of Tasks Tamás Kovácsházy, PhD 13rd Topic Inter Process Communication with Message Passing Budapest University of Technology and Economics Department of Measurement and Information Systems Looking back, communication solutions . Using shared memory(RAM or PRAM model): o Among threads running in the context of a process (shared memory of the process) . Messages: o No shared memory • Among processes running inside an operating system • Distributed system (network communication) o Microkernel based operating system . Inter Process Communication, IPC © BME-MIT 2014, All Rights Reserved 2. lap Messages . Different from the same word used in computer networks o We consider a more generic notion of message . Message passing . For example: o System call o TCP/IP connection (TCP) or message (UDP) for internal (localhost) or external communication (among machines) . Most cases they are implemented as OS API function/method calls resulting a system call . The operating system implements them by its services © BME-MIT 2014, All Rights Reserved 3. lap Some notes . Semaphore, Critical section object, and Mutex are also implemented by the OS and handled by system calls o Threads running in the context of a process communicate using shared memory (fast, low resource utilization) o Mutual exclusion and synchronization are solved by messages (using system calls). o It has some overhead: • Experiments: Lockless programming, transactional memory etc. • There is no good solution, but we can pick a better one than