Object-oriented Tools for Distributed Computing

Distributed computing systems are proliferating, owing to the availability of powerful, affordable microcomputers and inexpensive communication networks. A critical problem in developing such systems is getting application programs to interact with one another across a computer network. Remote interprogram connectivity is particularly challenging across heterogeneous environments, where applications run on different kinds of computers and operating systems. NetWorks! (trademark) is an innovative software product that provides an object-oriented messaging solution to these problems. This paper describes the design and functionality of NetWorks! and illustrates how it is being used to build complex distributed applications for NASA and in the commercial sector

A hierarchical group model for programming sensor networks

A hierarchical group model that decouples computation from hardware can characterize and aid in the construction of sensor network software with minimal overhead. Future sensor network applications will move beyond static, homogeneous deployments to include dynamic, heterogeneous elements. These sensor networks will also gain new users, including casual users who will expect intuitive interfaces to interact with sensor networks. To address these challenges, a new computational model and a system implementing the model are presented. This model ensures that computations can be readily reassigned as sensor nodes are introduced or removed. The model includes methods for communication to accommodate these dynamic elements. This dissertation presents a detailed description and design of a computational model that resolves these challenges using a hierarchical group mechanism. In this model, computation is tasked to logical groups and split into collective and local components that communicate hierarchically. Local computation is primarily used for data production and publishes data to the collective computation. Similarly, collective computation is primarily used for data aggregation and pushes results back to the local computation. Finally, the model includes data-processing functions interposed between local and collective functions that are responsible for data conversion. This dissertation also presents implementations and applications of the model. Implementations include Kensho, a C-based implementation of the hierarchical group model, that can be used for a variety of user applications. Another implementation, Tables, presents a spreadsheet-inspired view of the sensor network that takes advantage of hierarchical groups for both computation and communication. Users are able to specify both local and collective functions that execute on the sensor network via the spreadsheet interface. Applications of the model are also explored. One application, FUSN, provides a set of methods for constructing filesystem-based interfaces for sensor networks. This demonstrates the general applicability of the model as applied to sensor network programming and management interfaces. Finally, the model is applied to a novel privacy algorithm to demonstrate that the model isn\u27t strictly limited to programming interfaces

Leveraging simulation practice in industry through use of desktop grid middleware

This chapter focuses on the collaborative use of computing resources to support decision making in industry. Through the use of middleware for desktop grid computing, the idle CPU cycles available on existing computing resources can be harvested and used for speeding-up the execution of applications that have “non-trivial” processing requirements. This chapter focuses on the desktop grid middleware BOINC and Condor, and discusses the integration of commercial simulation software together with free-to-download grid middleware so as to offer competitive advantage to organizations that opt for this technology. It is expected that the low-intervention integration approach presented in this chapter (meaning no changes to source code required) will appeal to both simulation practitioners (as simulations can be executed faster, which in turn would mean that more replications and optimization is possible in the same amount of time) and the management (as it can potentially increase the return on investment on existing resources)

Domain-protocol mapping based middleware for distributed application development, A

2014 Spring.Includes bibliographical references.Distributed systems such as Internet of Things, Sensor Networks and Networked Control Systems are being used in various application domains, including industrial, environmental, medical and energy management domains. A distributed application in these domains may need to access data from different devices, where they may all be of the same type or a combination of different types. In addition, these devices may communicate through standardized protocols or proprietary interfaces. The development of such a distributed application may also require a team of developers with expertise in different disciplines. Therefore, the application development that involves heterogeneous devices and multidisciplinary teams can be made more effective by introducing an interface layer that shields developers from aspects of software and hardware heterogeneity. This work proposes a 'domain-protocol mapping' technique that is implemented as a middleware framework. The proposed mapping method maps the application data schema represented as object-oriented domain object to the appropriate communication protocol packet data and also updates the domain object from the response packet data. The middleware provides APIs for the domain experts to read the data from the device or to write the data to the device. The marshalling and unmarshalling process of the domain objects are hidden from the domain expert who may or may not be a software engineer. The use of the developed middleware is illustrated in two case-studies, one involving a simulation of distributed network controls for power system and the other involving integration of different types of power meters in power monitoring application

Advanced information processing system for advanced launch system: Avionics architecture synthesis

The Advanced Information Processing System (AIPS) is a fault-tolerant distributed computer system architecture that was developed to meet the real time computational needs of advanced aerospace vehicles. One such vehicle is the Advanced Launch System (ALS) being developed jointly by NASA and the Department of Defense to launch heavy payloads into low earth orbit at one tenth the cost (per pound of payload) of the current launch vehicles. An avionics architecture that utilizes the AIPS hardware and software building blocks was synthesized for ALS. The AIPS for ALS architecture synthesis process starting with the ALS mission requirements and ending with an analysis of the candidate ALS avionics architecture is described