Process migration has been added to the DEMOS/MP operating system. A process can be moved during its execution, and continue on another processor, with continuous access to all its resources. Messages are correctly delivered to the process's new location, and message paths are quickly updated to take advantage of the process's new location. No centralized algorithms are necessary to move a process.A number of characteristics of DEMOS/MP allowed process migration to be implemented efficiently and with no changes to system services. Among these characteristics are the uniform and location independent communication interface, and the fact that the kernel can participate in message send and receive operations in the same manner as a normal process.

Process migration in DEMOS/MP

A probabilistic measure of network fault tolerance expressed as the probability of a disconnection is proposed. Qualitative evaluation of this measure is presented. As expected, the single-node disconnection probability is the dominant factor irrespective of the topology under consideration. The authors derive an analytical approximation to the disconnection probability and verify it with a Monte Carlo simulation. On the basis of this model, the measures of network resilience and relative network resilience are proposed as probabilistic measures of network fault tolerance. These are used to evaluate the effects of the disconnection probability on the reliability of the system. >

Network resilience: a measure of network fault tolerance

A communication architecture for distributed processors is presented here. This architecture is based on a new topolgy we have developed, one which interconnects n nodes by using rn links where the maximum internode distance is logrn, and where each node has, at most, 2r, I/O ports. It is also shown that this network is fault-tolerant, being able to tolerate up to (r − 1) node failures.

A Fault-Tolerant Communication Architecture for Distributed Systems

The reliability of distributed processing systems can be expressed in terms of the reliability of the processing elements that run the programs, the reliability of the processing elements holding the required files, and the reliability of the communication links used in file transfers. The authors introduce two reliability measures, namely distributed program reliability and distributed system reliability, to accurately model the reliability of distributed systems. The first measure describes the probability of successful execution of a distributed program which runs on some processing elements and needs to communicate with other processing elements for remote files, while the second measure describes the probability that all the programs of a given set can run successfully. The notion of minimal file spanning trees is introduced to efficiently evaluate these reliability measures. Graph theory techniques are used to systematically generate file spanning trees that provide all the required connections. The technique is general and can be used in a dynamic environment for efficient reliability evaluation.

Distributed program reliability analysis

Maximizing the reliability of a system, that is, reducing the rate at which hardware and software components fail, is of prime importance to control systems designers. This is especially the case when systems must promise nonstop operation and on-line maintenance, as well as offer possibilities for expansion. Several methods of increasing system reliability have been proposed, 1-3 and, in general, researchers have preferred to consider reliability from the standpoint of a digital system as well as that of components and circuits.4'5 Until recently, however, reliable systems either performed poorly or cost too much to build, but the progress in LSI and optical transmission technologies has made it possible to reduce (rapidly) the cost of information processing, storage, and transmission. In addition, with the introduction of a decentralized approach to system design, the reliability of control systems now greatly exceeds that of comparable systems with centralized architectures. The autonomous, decentralized system described in this article is a highly reliable system; 6-9 more important, however, is the fact that this system is a large-scale, multifunctional engineering system, which performs the functions of both the control system and information system. To clarify the importance of this duplicity, we offer the following descriptions:

Autonomous Decentralized Computer Control Systems

Modular systems employing building-block VLSI circuits may provide fault tolerance to a variety of applications.

Rennels

Papers

Distributed Fault-Tolerant Computer Systems