José María Pérez

Applying RCM in large scale systems: a case study with railway networks

Abstract In 2000, the European Union founded a project named ‘RAIL: Reliability centered maintenance approach for the infrastructure and logistics of railway operation’ aimed to study the application of Reliability centered maintenance (RCM) techniques to the railway infrastructure. In this paper, we present the results obtained into the RAIL project, including a RCM methodology adapted to large infrastructure networks and a RCM toolkit to perform the RCM analysis, including cost aspects and maintenance planning guidance. This paper addresses the problem of applying RCM to large scale railway infrastructure networks to achieve an efficient and effective maintenance concept. Railways use nowadays very traditional preventive maintenance (PM) techniques, relying mostly on ‘blind’ periodic inspection and the ‘know-how’ of maintenance staff. RCM was seen as a promising technique from the beginning of the RAIL project because of several factors. First, technical insights obtained were better than the existing, so that several maintenance processes could be revised and adjusted. Second, the interdisciplinary approach used to make the analysis was very enriching and very encouraging for maintenance staff consulted. Third, using the RCM structured approach allowed to achieve well-documented analysis and clear decision diagrams. Our methodology includes some new features to overcome the problems of RCM observed in other projects. As a whole, our methodology and Computerized Maintenance Management Systems have produced two short-term benefits: reduction of time and paperwork because databases and tools are accessible through Internet, and creation of a permanent, accurate, and better collection of information. It will also have some long-term benefits: better PM will increase equipment life and will help to reduce corrective maintenance costs; Production will increase as unscheduled downtime decreases; purchase costs of parts and materials will be reduced; more effective and up-to-date record of inventory/stores reports; and better knowledge of the systems to help the company to chose those systems with the best LCC. The results have been corroborated with the application of our methodology to signal equipment in several railway network sections, as shown in this paper. Because of the successful conclusion of the project, the Spanish railway company (RENFE) and the German railway company (DB A.G.), not only decided to adopt RCM to enhance PM, but they have started a large project to implement Total Preventive Maintenance relying on the implantation of the RCM methodology.

Branch replication scheme: A new model for data replication in large scale data grids

Data replication is a practical and effective method to achieve efficient and fault-tolerant data access in grids. Traditionally, data replication schemes maintain an entire replica in each site where a file is replicated, providing a read-only model. These solutions require huge storage resources to store the whole set of replicas and do not allow efficient data modification to avoid the consistency problem. In this paper we propose a new replication method, called the Branch Replication Scheme (BRS), that provides three main advantages over traditional approaches: optimizing storage usage, by creating subreplicas; increasing data access performance, by applying parallel I/O techniques; and providing the possibility to modify the replicas, by maintaining consistency among updates in an efficient way. An analytical model of the replication scheme, naming system, and replica updating scheme are formally described in the paper. Using this model, operations such as reading, writing, or updating a replica are analyzed. Simulation results demonstrate the feasibility of BRS, as they show that the new replication algorithm increases data access performance, compared with popular replication schemes such as hierarchical and server-directed replication, which are commonly used in current data grids.

The Design of the Expand Parallel File System

This article describes an implementation of MPI-IO using a new parallel file system, called Expand (Expandable Parallel File System), which is based on NFS servers. Expand combines multiple NFS servers to create a distributed partition where files are striped. Expand requires no changes to the NFS server and uses RPC operations to provide parallel access to the same file. Expand is also independent of the clients, because all operations are implemented using RPC and NFS protocols. Using this system, we can join heterogeneous servers (Linux, Solaris, Windows 2000, etc.) to provide a parallel and distributed partition. The article describes the design, implementation and evaluation of Expand with MPI-IO. This evaluation has been made in Linux clusters and compares Expand and PVFS.

An Implementation of MPI-IO on Expand: A Parallel File System Based on NFS Servers

This paper describes an implementation of MPI-IO using a new parallel file system, called Expand (Expandable Parallel File System), that is based on NFS servers. Expand combines multiple NFS servers to create a distributed partition where files are declustered. Expand requires no changes to the NFS server and uses RPC operations to provide parallel access to the same file. Expand is also independent of the clients, because all operations are implemented using RPC and NFS protocol. The paper describes the design, the implementation and the evaluation of Expand with MPI-IO. This evaluation has been made in Linux clusters and compares Expand and PVFS.

Specifying use case behavior with interaction models.

Functional requirements for information systems can be modeled through use cases. Furthermore, use case models have been successfully used in broader contexts than software engineering, as systems engineering. Even if small systems may be modeled as a set of use cases, when large systems requirements are modeled with a plain use case model several difficulties arise. Traditionally, the behavior of use cases has been modeled through textual specifications. In this paper we present an alternate approach based on interaction modeling. The behavior modeling has two variants (one for UML 1.x and one for UML 2.0). We also integrate our behavior modeling with standard use case relationships.

A parallel and fault tolerant file system based on NFS servers

One important piece of system software for clusters is the parallel file system. All current parallel file systems and parallel I/O libraries for clusters do not use standard servers, thus it is very difficult to use these systems in heterogeneous environments. However why use proprietary or special-purpose servers on the server end of a parallel file system when you have most of the necessary functionality in NFS servers already? This paper describes the fault tolerance implemented in Expand (Expandable Parallel File System), a parallel file system based on NFS servers. Expand allows the transparent use of multiple NFS servers as a single file system, providing a single name space. The different NFS servers are combined to create a distributed partition where files are stripped. Expand requires no changes to the NFS server and uses RPC operations to provide parallel access to the same file. Expand is also independent of the clients, because all operations are implemented using RPC and NFS protocol. Using this system, we can join heterogeneous servers (Linux, Solaris, Windows 2000, etc.) to provide a parallel and distributed partition. Fault tolerance is achieved using RAID techniques applied to parallel files. The paper describes the design of Expand and the evaluation of a prototype of Expand, using the MPI-IO interface. This evaluation has been made in Linux clusters and compares Expand with PVFS.

Data allocation and load balancing for heterogeneous cluster storage systems

Distributed filesystems are a typical solution in networked environments as clusters and grids. Parallel filesystems are a typical solution in order to reach high performance I/O distributed environment, but those filesystems have some limitations in heterogeneous storage systems. Usually in distributed systems, load balancing is used as a solution to improve the performance, but typically the distribution is made between peer-to-peer computational resources and from the processor point of view. In heterogeneous systems, like heterogeneous clusters of workstations, the existing solutions do not work so well. However, the utilization of those systems is more extended every day, having an extreme example in the grid environment. In this paper we bring attention to those aspects of heterogeneous distributed data systems presenting a parallel file system that take into account heterogeneity of storage nodes, the dynamic addition of new storage nodes, and an algorithm to group requests in heterogeneous systems.

A fault tolerant MPI-IO implementation using the Expand parallel file system

Parallelism in file systems is obtained by using several independent server nodes supporting one or more secondary storage devices. This approach increases the performance and scalability of the system, but a fault in one single node can stop the whole system. To avoid this problem, data must be stored using some kind of redundant technique, so any data stored in a faulty element can be recovered. Fault tolerance can be provided in I/O systems using replication or RAID based schemes. However, most of the current systems apply the same technique for all files in the system. This paper describes the fault tolerance support provided by Expand, a parallel file system based on standard servers. Expand allows to define different fault-tolerant mechanisms at file level. The evaluation compares the performance of Expand with different configurations with PVFS using the FLASH-I/O benchmark.

A Model for Use Case Priorization Using Criticality Analysis

Modern UML based software development processes have use cases specification as a keystone of functional requirement modeling. Use cases have been used with success in broader contexts than software development as systems engineering. Not all the use cases are equally critical for the system to satisfy its goals. Criticality analysis allows to identify the critical elements of a system. Applying criticality analysis to functional requirements of a system allows to identify which are the critical functionalities of a system. In this paper we present a use case model structuring scheme. We apply a method to evaluate the criticality of use cases of a system to our structuring model. We also propose the requirements for an UML profile for criticality analysis of systems.

An adaptive cache coherence protocol specification for parallel input/output systems

Caching has been intensively used in memory and traditional file systems to improve system performance. However, the use of caching in parallel file systems and I/O libraries has been limited to I/O nodes to avoid cache coherence problems. We specify an adaptive cache coherence protocol that is very suitable for parallel file systems and parallel I/O libraries. This model exploits the use of caching, both at processing and I/O nodes, providing performance improvement mechanisms such as aggressive prefetching and delayed-write techniques. The cache coherence problem is solved by using a dynamic scheme of cache coherence protocols with different sizes and shapes of granularity. The proposed model is very appropriate for parallel I/O interfaces, such as MPI-IO. Performance results, obtained on an IBM SP2, are presented to demonstrate the advantages offered by the cache management methods proposed.