Fragmentation of confidential objects for data processing security in distributed systems

This paper discusses how object orientation in application design enables confidentiality aspects to be handled more easily than in conventional approaches. The idea, based on object fragmentation at design time, is to reduce processing in confidential objects; the more non confidential objects can be produced at design-time, the more application objects can be processed on untrusted shared computers. Still confidential objects must be processed on non shared trusted workstations. Rules and limits of object fragmentation are discussed together with some criteria evaluating trade-offs between fragmentation and performance

Computing fuzzy rough approximations in large scale information systems

Rough set theory is a popular and powerful machine learning tool. It is especially suitable for dealing with information systems that exhibit inconsistencies, i.e. objects that have the same values for the conditional attributes but a different value for the decision attribute. In line with the emerging granular computing paradigm, rough set theory groups objects together based on the indiscernibility of their attribute values. Fuzzy rough set theory extends rough set theory to data with continuous attributes, and detects degrees of inconsistency in the data. Key to this is turning the indiscernibility relation into a gradual relation, acknowledging that objects can be similar to a certain extent. In very large datasets with millions of objects, computing the gradual indiscernibility relation (or in other words, the soft granules) is very demanding, both in terms of runtime and in terms of memory. It is however required for the computation of the lower and upper approximations of concepts in the fuzzy rough set analysis pipeline. Current non-distributed implementations in R are limited by memory capacity. For example, we found that a state of the art non-distributed implementation in R could not handle 30,000 rows and 10 attributes on a node with 62GB of memory. This is clearly insufficient to scale fuzzy rough set analysis to massive datasets. In this paper we present a parallel and distributed solution based on Message Passing Interface (MPI) to compute fuzzy rough approximations in very large information systems. Our results show that our parallel approach scales with problem size to information systems with millions of objects. To the best of our knowledge, no other parallel and distributed solutions have been proposed so far in the literature for this problem

Formal Specification and Testing of a Management Architecture

The importance of network and distributed systems management to supply and maintain services required by users has led to a demand for management facilities. Open network management is assisted by representing the system resources to be managed as objects, and providing standard services and protocols for interrogating and manipulating these objects. This paper examines the application of formal description techniques to the specification of managed objects by presenting a case study in the specification and testing of a management architecture. We describe a formal specification of a management architecture suitable for scheduling and distributing services across nodes in a distributed system. In addition, we show how formal specifications can be used to generate conformance tests for the management architecture

Model of evaluation of the efficiency of the ship’s diesel generator control system

The main trend in the development of control systems in industry is to transit from centralized to distributed intelligent systems based on network technologies. With the development of microprocessor technology and telecommunications, the opportunity has appeared to place the information processing means near the automation objects. It allows you to create effective control systems with locally distributed equipment – so called distributed control systems. Operation of power plants and many other objects determines the subject area of the control systems for such objects in real time

Brief Announcement: Wait-Free Universality of Consensus in the Infinite Arrival Model

In classical asynchronous distributed systems composed of a fixed number n of processes where some proportion may fail by crashing, many objects do not have a wait-free linearizable implementation (e.g. stacks, queues, etc.). It has been proved that consensus is universal in such systems, which means that this system augmented with consensus objects allows to implement any object that has a sequential specification. In this paper, we consider a more general system model called infinite arrival model where infinitely many processes may arrive and leave or crash during a run. We prove that consensus is still universal in this more general model. For that, we propose a universal construction based on a weak log that can be implementated using consensus objects

Geometric Aspects of Multiagent Systems

Recent advances in Multiagent Systems (MAS) and Epistemic Logic within Distributed Systems Theory, have used various combinatorial structures that model both the geometry of the systems and the Kripke model structure of models for the logic. Examining one of the simpler versions of these models, interpreted systems, and the related Kripke semantics of the logic $S5_n$ (an epistemic logic with $n$-agents), the similarities with the geometric / homotopy theoretic structure of groupoid atlases is striking. These latter objects arise in problems within algebraic K-theory, an area of algebra linked to the study of decomposition and normal form theorems in linear algebra. They have a natural well structured notion of path and constructions of path objects, etc., that yield a rich homotopy theory.Comment: 14 pages, 1 eps figure, prepared for GETCO200

Abstracting object interactions using composition filters

It is generally claimed that object-based models are very suitable for building distributed system architectures since object interactions follow the client-server model. To cope with the complexity of today's distributed systems, however, we think that high-level linguistic mechanisms are needed to effectively structure, abstract and reuse object interactions. For example, the conventional object-oriented model does not provide high-level language mechanisms to model layered system architectures. Moreover, we consider the message passing model of the conventional object-oriented model as being too low-level because it can only specify object interactions that involve two partner objects at a time and its semantics cannot be extended easily. This paper introduces Abstract Communication Types (ACTs), which are objects that abstract interactions among objects. ACTs make it easier to model layered communication architectures, to enforce the invariant behavior among objects, to reduce the complexity of programs by hiding the interaction details in separate modules and to improve reusability through the application of object-oriented principles to ACT classes. We illustrate the concept of ACTs using the composition filters model

A hierarchical distributed control model for coordinating intelligent systems

A hierarchical distributed control (HDC) model for coordinating cooperative problem-solving among intelligent systems is described. The model was implemented using SOCIAL, an innovative object-oriented tool for integrating heterogeneous, distributed software systems. SOCIAL embeds applications in 'wrapper' objects called Agents, which supply predefined capabilities for distributed communication, control, data specification, and translation. The HDC model is realized in SOCIAL as a 'Manager'Agent that coordinates interactions among application Agents. The HDC Manager: indexes the capabilities of application Agents; routes request messages to suitable server Agents; and stores results in a commonly accessible 'Bulletin-Board'. This centralized control model is illustrated in a fault diagnosis application for launch operations support of the Space Shuttle fleet at NASA, Kennedy Space Center

Integrating CLIPS applications into heterogeneous distributed systems

SOCIAL is an advanced, object-oriented development tool for integrating intelligent and conventional applications across heterogeneous hardware and software platforms. SOCIAL defines a family of 'wrapper' objects called agents, which incorporate predefined capabilities for distributed communication and control. Developers embed applications within agents and establish interactions between distributed agents via non-intrusive message-based interfaces. This paper describes a predefined SOCIAL agent that is specialized for integrating C Language Integrated Production System (CLIPS)-based applications. The agent's high-level Application Programming Interface supports bidirectional flow of data, knowledge, and commands to other agents, enabling CLIPS applications to initiate interactions autonomously, and respond to requests and results from heterogeneous remote systems. The design and operation of CLIPS agents are illustrated with two distributed applications that integrate CLIPS-based expert systems with other intelligent systems for isolating and mapping problems in the Space Shuttle Launch Processing System at the NASA Kennedy Space Center