A file storage scheme is proposed for networks containing heterogeneous clients. In the scheme, the performance measured by file-retrieval delays degrades gracefully under increasingly serious faulty circumstances. The scheme combines coding with storage for better performance. The problem is NP-hard for general networks; and this paper focuses on tree networks with asymmetric edges between adjacent nodes. A polynomial-time memory-allocation algorithm is presented, which determines how much data to store on each node, with the objective of minimizing the total amount of data stored in the network. Then a polynomial-time data-interleaving algorithm is used to determine which data to store on each node for satisfying the quality-of-service requirements in the scheme. By combining the memory-allocation algorithm with the data-interleaving algorithm, an optimal solution to realize the file storage scheme in tree networks is established.

Dealing with the large amounts of data generated by longrunning parallel applications is one of the most challenging aspects of Grid Computing. Periodic checkpoints might be taken to guarantee application progression, producing even more data. The classical approach is to employ highthroughput checkpoint servers connected to the computational nodes by high speed networks. In the case of Opportunistic Grid Computing, we do not want to be forced to rely on such dedicated hardware. Instead, we want to use the shared Grid nodes to store application data in a distributed fashion. In this work, we evaluate several strategies to store checkpoints on distributed non-dedicated repositories. We consider the tradeoff among computational overhead, storage overhead, and degree of fault-tolerance of these strategies. We compare the use of replication, parity information, and information dispersal (IDA). We used InteGrade, an objectoriented Grid middleware, to implement the storage strategies and perform evaluation experiments. Categories and Subject Descriptors C.2.4 [Computer-communication Networks]: Distributed Systems—distributed applications; C.4 [Performance

Abstract: Storing multiple copies of files is crucial for ensuring quality of service for data storage in mobile networks. This paper proposes a new scheme, called the K-out-of-N file distribution scheme, for the placement of files. In this scheme files are splitted, and Reed-Solomon codes or other maximum distance seperable (MDS) codes are used to produce file segments containing parity information. Multiple copies of the file segments are stored on gateways in the network in such a way that every gateway can retrieve enough file segments from itself and its neighbors within a certain amount of hops for reconstructing the orginal files. The goal is to minimize the maximum number of hops it takes for any gateway to get enough file segments for the file reconstruction. We formulate the K-out-of-N file distribution scheme as a coloring problem we call diversity coloring. A diversity coloring is defined to be optimal if it uses the smallest number of colors. Upper and lower bounds on the performance of diversity coloring for general graphs are studied. Diversity coloring algorithms for several special classes of graphs—trees, rings and tori—are presented, all of which have linear time complexity. Both the algorithm for trees and the algorithm for rings output optimal diversity colorings. The algorithm for tori guarantees to output optimal diversity coloring when the sizes of tori are sufficiently large. Index Terms: Data storage, diversity coloring, file assignment problem (FAP), graph coloring, K-out-of-N scheme, maximum distance seperable (MDS) codes, mobile computing, Quality of Service

In a largely distributed data storage system, high data availability becomes a major issue of concern. Storage server failure increases with the number of servers, or data objects get inadvertently deleted or corrupted. Maintaining highly available data storage service in a distributed environment is an acute problem. We propose a novel scheme by which highly available and dependable data service is achieved. The proposed scheme stripes a file into data blocks and distributes them over distributed storage servers. To retrieve the original file, the data blocks are downloaded from the storage servers in parallel and then merged. The scheme employs a reconfigurable architecture consisting of a cluster of distributed data servers. The reconfiguration of the storage is performed in order to recover missing data blocks by a coding method and to relocate these onto operational backup servers for continuous data availability. keywords: Distributed Systems, Availability, Coding, Reliability...

Opportunistic grids are a class of computational grids that can leverage the idle processing and storage capacity of shared workstations in laboratories, companies, and universities to perform useful computation. OppStore is a middleware that allows using the free disk space of machines from an opportunistic grid for the distributed storage of application data. But when machines depart from the grid, it is necessary to reconstruct the fragments that were stored in that machines. Depending on the amount of stored data and the rate of machine departures, the generated traffic may make the distributed storage of data infeasible. In this work we present and evaluate a fragment recovery mechanism that makes viable to achieve redundancy and large data scale in a dynamic environment. Categories andSubjectDescriptors C.4 [Performance of Systems]: Reliability, availability, and serviceability