Large Grid systems not only provide massive aggregated computing power but also an unprecedented amount of distributed storage space. Unfortunately, the dynamic behavior of the Grid, caused by varying resource availability, unpredictable data updates, and the impact of local site policies make it difficult to exploit the full capabilities of Data Grids. We present

We consider the consistency control problem for replicated data in a distributed computing system (DCS) and propose a new algorithm to dynamically regenerate copies of data objects in response to node failures and network partitioning in the system. The DCS is assumed to have strict consistency constraints for data object copies. The new algorithm combines the advantages of voting based algorithms and regeneration mechanisms to maintain mutual consistency of replicated data objects in the case of node failures and network partitioning. Our algorithm extends the feasibility of regeneration to DCS on wide area networks, and is able to satisfy user queries as long as there is one current partition in the system. A stochastic availability analysis of our algorithm shows that it provides improved availability as compared to previously proposed dynamic voting algorithms. 1 Introduction In a distributed computing environment, two types of failures may occur: the processor at a given site may...

We consider the class of mobile computing applications with periodically connected clients. These clients wish to share data; however, due to the expense of mobile communication, they only connect periodically -- and not necessarily synchronously -- to a common network. Traditionally, a continuouslyconnected server, containing an aggregate of client data, facilitates sharing amongst clients by allowing the clients to upload local updates and download updates submitted by other clients. The server computes and retransmits these updates on a client-by-client basis; consequently, the complexity of these operations is on the order of the number of clients, limiting scalability. Recent research proposes exploiting client data overlap by grouping updates according to how the data is shared amongst clients (data-centric) instead of on a client-by-client basis (client-centric). By grouping, update operation distribution is computed only once per group, irrespective of the number of cl...

This paper proposes an agent-based distributed replica allocation and management technique, where each agent maximizes its own benefit, such as, user access time, latency and communication cost. The technique gathers inspiration from market economy and game theoretical mechanism designs. In such mechanisms the agents do not have a global view of the system, which makes the optimization process highly localized. This local optimization may encourage these agents to alter the output of the resource allocation mechanism in their favor and act selfishly. The proposed technique guarantees a global optimal solution even though the system acts in a distributed fashion operated by self-motivated selfish agents. The mechanism is extensively evaluated against some well-known replica placement algorithms such as greedy, branch and bound, game theoretical auctions and genetic algorithms. The experimental results reveal that the mechanism provides excellent solution quality, while maintaining fast execution time. 1.

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

Replicating data over geographically dispersed web servers reduces network traffic, server load, and more importantly the user-perceived access delays. This paper proposes a unique replica placement technique using the concepts of a supergame. The supergame allows the agents who represent the data objects to continuously compete for the limited available server memory space, so as to acquire the rights to place data objects at the servers. At any given instance in time, the supergame is represented by a game which is a collection of subgames, played concurrently at each server in the system. We derive a resource allocation mechanism which acts as a platform at the subgame level for the agents to compete. This approach allows us to transparently monitor the actions of the agents, who in a noncooperative environment strategically place the data objects to reduce the user access time, latency, which in turn adds reliability and fault-tolerance to the system. We show that this mechanism exhibits Nash equilibrium at the subgame level which in turn conforms to games and supergame Nash equilibrium, respectively, guaranteeing the entire system to be in a continuous self-evolving and selfrepairing mode. The mechanism is extensively evaluated against some well-known algorithms, such as: greedy, branch and bound, game theoretical auctions and genetic algorithms. The experimental results reveal that the mechanism provides excellent solution quality, while maintaining fast execution time. Povzetek: Opisana je metoda za multipliciranje internetnih strani. 1

Suppose you got an excellent dynamic file assignment algorithm. But, how to proceed dynamically from the current to the optimal file allocation? Imagine replication of your files and some sort of voting strategy --- the question then is, how to maintain consistency if the current and the optimal file assignment differ not only in the location of the files but also in the number of replicas? This paper tries to answer these questions and introduces the basic relocation protocols which preserve consistency during relocation, as well as a priority-driven, storage capacity-based approach to bring the basic relocation protocols in an optimal sequence in order to move quickly and as close as possible towards the optimal file assignment. 1 Introduction We consider a mathematical model of an information network of jRj nodes, some of which contain copies of our jDj data files. The degree of replicas has not to be fixed. Within this network, every node is able to communicate with every other no...

Abstract. Replicating data over geographically dispersed web servers reduces network traffic, server load, and more importantly the user-perceived access delays. This paper proposes a unique replica placement technique using the concepts of a “supergame”. The supergame allows the agents who represent the data objects to continuously compete for the limited available server memory space, so as to acquire the rights to place data objects at the servers. At any given instance in time, the supergame is represented by a game which is a collection of subgames, played concurrently at each server in the system. We derive a resource allocation mechanism which acts as a platform at the subgame level for the agents to compete. This approach allows us to transparently monitor the actions of the agents, who in a non-cooperative environment strategically place the data objects to reduce user access time and latency which in turn, adds reliability and fault-tolerance to the system. We show that this mechanism exhibits Nash equilibrium at the subgame level which in turn conforms to games and supergame Nash equilibrium, respectively. The mechanism is extensively evaluated against some well-known algorithms, such as: greedy, branch and bound, game theoretical auctions and genetic algorithms. The experimental results reveal that the mechanism provides excellent solution quality, while maintaining fast execution time. 1

This work addresses a files allocation problem (FAP) in distributed computing systems. This FAP attempts to minimize the expected data transfer time for a specific program that must access several data files from non-perfect computer sites. We assume that communication capacity can be reserved; hence, the data transmission behavior is modeled as a many-to-one multi-commodity flow problem. A new critical-cut method is proposed to solve this reduced multi-commodity flow problem. Based on this method, two algorithms which use branch-and-bound are proposed for this FAP. The proposed algorithms are able to allocate data files having single copies or multiple replicated copies. Simulation results are presented to demonstrate the performance of the algorithms.

The problem of allocating high-volume multimedia files on a virtual circuit network with the objective of maximizing channel throughput (and minimizing data transmission time) is addressed. The problem is formulated as a multicommodity flow problem. We present both the optimal and suboptimal solutions to the problem using novel approaches.