Remote Procedure Call (RPC)

Mobile applications must operate in environments which experience rapid and significant fluctuations in the quality of service (QoS) offered by their underlying communications infrastructure. These fluctuations may be the result of explicit changes between networks, increased competition for network resources or degradation of service due to environmental factors. In order to continue to operate effectively mobile applications must be capable

The authors present the design and implementation of an asynchronous remote operation execution facility, futures, that retains the benefits of the remote procedure call (RPC) abstraction but allows execution to proceed locally in parallel with remote execution and provides extensive support for managing replies. It is shown how this facility can be easily used to support many common interprocess communication

Remote procedure call (RPC) systems have been proven to be a practical basis for building distributed applications. The RPC technique abstracts a typical communication pattern to an ordinary procedure call. Compared with an ordinary procedure call, however, the conventional RPC technique has one evident restriction; pointers (addresses) cannot be passed to remote procedures without the explicit and nontrivial programming effort. This paper presents VMRPC, a lightweight RPC framework specifically designed for VMs that leverages the heap and stack sharing mechanism to circumvent unnecessary data copy and serialization/deserialization. Our evaluation shows that the performance of VMRPC is an order of magnitude better than traditional RPC systems and existing alternative inter-domain communication optimization systems.

This Scientific paper focuses on employment of artificial neural network techniques to develop in-network "intelligent computation" capability for wireless sensor networks to improve their functionality, utility and survival aspects. The main purpose is to introduce computational intelligence capability for the wireless sensor networks to become adaptive to changes within a variety of operational contexts and to exhibit intelligent behavior. Paradigms of computational intelligence (CI) have been successfully used in recent years to address various challenges such as data aggregation and fusion, energy aware routing, task scheduling, security, optimal deployment and localization. CI provides adaptive mechanisms that exhibit intelligent behavior in complex and dynamic environments like WSNs. CI brings about flexibility, autonomous behavior, and robustness against topology changes, communication failures and scenario changes. However, WSN developers are usually not or not completely aware of the potential CI algorithms offer. On the other side, CI researchers are not familiar with all real problems and subtle requirements of WSNs. This mismatch makes collaboration and development difficult. This paper intends to close this gap and foster collaboration by offering a detailed introduction to WSNs and their properties. An extensive survey of CI applications to various problems in WSNs from various research areas and publication venues is presented in the paper.

When distributed systems first appeared, they were programmed in traditional sequential languages, usually with the addition of a few library procedures for sending and receiving messages. As distributed applications became more commonplace and more sophisticated, this ad hoc approach became less satisfactory. Researchers all over the world began designing new programming languages specifically for implementing distributed applications. These languages and their history, their underlying principles, their design, and their use are the subject of this paper. We begin by giving our view of what a distributed system is, illustrating with examples to avoid confusion on this important and controversial point. We then describe the three main characteristics that distinguish distributed programming languages from traditional sequential languages, namely, how they deal with parallelism, communication, and partial failures. Finally, we discuss 15 representative distributed languages to give ...

Distributed or parallel software with synchronous communication via rendezvous is found in client-server systems and in proposed open distributed systems, in implementation environments such as Ada, V, remote procedure call systems, in transputer systems, and in specification techniques such as CSP, CCS and LOTOS. The delays induced by rendezvous can cause serious performance problems, which are not easy to estimate using conventional models which focus on hardware contention, or on a restricted view of the parallelism which ignores implementation constraints. Stochastic rendezvous networks are queueing networks of a new type which have been proposed as a modelling framework for these systems. They incorporate the two key phenomena of included service and a second phase of service. This paper extends the model to also incorporate different services or entries associated with each task. Approximations to arrival-instant probabilities are employed with a mean-value analysis framework, to give approximate performance estimates. The method has been applied to moderately large industrial software systems

Rover is a software toolkit that supports the construction of both mobile-transparent and mobile-aware applications. The objective of the mobile-transparent approach is to develop proxies for system services that hide the mobile characteristics of the environment from applications. Since applications can be run without alteration, the mobile-transparent approach is appealing. However, to excel, applications operating in the harsh conditions of a mobile environment must often be aware of and take an active part in mitigating those conditions. The Rover toolkit supports a set of programming and communication abstractions that enable the construction of both mobile-transparent and mobile-aware applications. Using the Rover abstractions, applications obtain increased availability, concurrency, resource allocation efficiency, fault tolerance, consistency, and adaptation. Experimental evaluation of a suite of mobile applications built with the toolkit demonstrates that such application-le...

Summary Component-based Software Development is an approach that has many benefits, such as improving application developer productivity, reducing costs and complexity. Programming within this approach is like assembly rather than development, which reduce skill requirements, and allow expertise focus on domain problems. The foundation of any CBSD methodology is its underlying component model, which defines what components are, how they can be constructed, and specifies the standards and conventions that are needed to enable composition of independently developed component. This paper presents a survey of the current available component technologies with focus on the technical perspective of each component model in order to have better understanding for developing a new component model. We have categorized them based on Distributed Application Support and Interaction mechanism.

Abstract This paper deals with the integration of an efficient asynchronous remote procedure call mechanism into a programming language. It describes a new data type called a promise that was designed to support asynchronous calls. Promises allow a caller to run in parallel ...

Hadoop Remote Procedure Call (RPC) is increasingly used in many data centers of known technology companies such as Facebook and Yahoo together with other data middleware centers like MapReduce, HDFS (Hadoop Distributed File System) and Hbase. Due to its simplicity, efficiency, high performance use of RPC systems, it is essential to achieve dense data storage and low latency and high throughput. This thesis describes how to improve data storage, throughput, and latency performance for big data. E.Sivaraman Dr.R.Manickachezian(2014) said systems are becoming increasingly data-intensive due to the explosion of data and the need to process it, therefore ,the application performance is vital to storage management in data-intensive computing systems. The author mentioned above highligted that researchers believe that applications sensitive areas are advancing in storing large volume of data. As data volumes continue to grow, the movement of data from memory to storage systems has become a critical performance bottleneck for many data centers. However, data management on such multi-server storage systems is yet under studies to ascertain on how to utilize various storages for efficient data movement is an important research topic in RPC data perception. In this research, we propose an adoptive Heartbeat system, data-aware distribution that efficiently manages storage systems to coordinate multiple concurrent data-intensive applications. Extensive experiments are conducted and the results show that this method can significantly improve the network throughput performance and data-intensive storage of Hadoop in HDFS clusters. The thesis discusses the background of RPC, huge data application storage systems, related work and technologies, Hadoop installation, adaptive model mechanisms, evaluation and performance analysis of big data architecture and its server interfaces. The reason to focus on storage improvements is because of the great need to store information globally. A large class of communication-intensive distributed applications and software components have been ported to virtual machines, such as highperformance storage systems. This method dynamically adjusts the RPC configuration between the NameNode and the DataNode by sensing the data characters stored in the DataNode. This method can effectively reduce the processing pressure of the NameNode and improve the network throughput generated by the information transmission between the NameNode and the DataNode.

Many new remote procedure calls (RPC) systems are being built to meet different application requirements, and much development effort has been spent on redoing significant parts of the RPC system. This paper describes URPC, a toolkit for prototyping ...

Large scale distributed systems like Grids are difficult to study only from theoretical models and simulators. Most Grids deployed at large scale are production platforms that are inappropriate research tools because of their limited reconfiguration, control and monitoring capabilities. In this paper, we present Grid'5000, a 5000 CPUs nation-wide infrastructure for research in Grid computing. Grid'5000 is designed to provide a scientific tool for computer scientists similar to the large-scale instruments used by physicists, astronomers and biologists. We describe the motivations, design, architecture, configuration examples of Grid'5000 and performance results for the reconfiguration subsystem.