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Data Grids provide services and infrastructure for distributed data-intensive applications accessing massive geographically distributed datasets. An important technique to speed access in Data Grids is replication, which provides nearby data access. Much of the work on the replica placement problem has focused on average system performance and ignored quality assurance issues. In a data grid environment,...
This paper presents a mechanism of integrating the concept of reliability with trust management policy in the distributed scheduling algorithms. This algorithm focuses on the distributed computing systems involving collaborative computing. Trust management is achieved with the concept of bidirectional reputation points that are assigned to resource providers and resource consumers. Moreover, concept...
Data grids support distributed data-intensive applications that need to access massive datasets stored around the world. Ensuring efficient access to such datasets is hindered by the high latencies of wide-area networks. To speed up access, files can be replicated so a user can access a nearby replica. Replication also provides improved availability, decreased bandwidth use, increased fault tolerance,...
An e-Infrastructure allows end-user's applications to easily and securely access heterogeneous grid resources (e.g., computing and storage elements). Since e-Science applications are often characterized by huge data transfers and high computational loads, the selection and allocation of grid resources dramatically affect their performance. This paper proposes a distributed resource allocation algorithm,...
We developed a scalable distributed computing system using the Berkeley Open Interface for Network Computing (BOINC) to align next-generation sequencing (NGS) data quickly and accurately. NGS technology is emerging as a promising platform for gene expression analysis due to its high sensitivity compared to traditional genomic microarray technology. However, despite the benefits, NGS datasets can be...
In this paper, given a random distribution of sensor nodes, we pose the problem of finding maximum number of connected set covers such that each set can guarantee the required coverage of the region of interest. It requires just a one-time computation during initialization. Once the connected set covers are known, the sets may remain active in a round robin fashion to cover the region enhancing the...
A critical aspect of applications with WSNs is increase the sensor nodes lifetime. Power constrained WSNs are useable such as they can communicate sensed data to a processing node. Communication and sensing consume energy therefore energy saving and improving lifetime of WSNs can be achieved by scheduling of sensor nodes. In scheduling allow sensor nodes can interchange its state into idle, sleep...
This paper focuses on updating time varying demand matrices using real-time information. An Artificial Intelligence technique based on Distributed Evolutionary Algorithms (DEA), which is capable to exploit the use of grid computing, is developed. This EA-based demand estimation framework is implemented into a model that we call DynODE (Dynyamic O/D Estimator). DynODE provides a direct way of fusing...
Grid scheduling is one of optimally assigning jobs to resources to achieve maximizing the utilization of resources. We propose a distributed ant colony algorithm based on cross-entropy for multi-constraints scheduling. This is an extremely robust rare event simulation technique which may be employed to solve difficult combinatorial optimization problems. We tailor the CE-ANT method for the requirements...
Scheduling is an important issue in computational grid. In computational grid, computing resources are connected through networks. So, if we want to take advantage of computational grid, an efficient scheduling algorithm is necessary to assign jobs to the appropriate nodes. Our adaptive load sharing algorithms uses a timer to find a receiver/sender. If receiver does not find a sender it broadcasts...
Consider an orthogonal grid of streets and avenues in a Manhattan-like city populated by stationary sensor modules at some crossings and mobile robots that can serve as relays of information that the modules exchange. Both module-module and module-robot communication is limited to a straight line of sight along a row or a column of the grid. We present a number of distributed algorithms for the robots...
In this paper we review current and previous work in the field of modeling and simulation of large scale distributed systems. We propose a new taxonomy to analyze the most representative modeling instruments for such systems. Previous work has dealt with the more generic case of computing systems simulations, but we state that, based on their specific particularities, the simulators designed for such...
Computational grids have the potential for solving large-scale scientific problems using heterogeneous and geographically distributed resources. However, a number of major technical hurdles must be overcome before this potential can be realized. One problem that is critical to effective utilization of computational grids is the efficient scheduling of jobs. This work addresses this problem by describing...
Grid is commonly considered as next generation network. Resource discovery is the key requirements in large heterogeneous grid environments, and an effective and efficient resource discovery mechanism is crucial. Base on centering resource discovery and distributed resource discovery methods, a hierarchical resource discovery method is proposed. Agent technology is used in every layer. Resource adjacency...
Efficient, scalable and robust grid service provisioning is one of the cornerstones of next generation grid systems. In agreement with this vision, we propose a flexible grid service provisioning framework built on a two layer architecture. A lower layer provides membership management and basic communication upon a self-organized peer-to-peer overlay maintained and optimized using a fully distributed...
In a file system, critical sections are represented by means of read or write operations on useful data (i.e files) as well as metadata of the system. The processes must be synchronized to reach these shared resources, thanks to mutual exclusion algorithms which guarantee data consistency. In a grid environment, processes are compared to grid nodes and their synchronization is ensured by the sending...
Grid computing provides a platform for users to access the worldwide distributed resources. To meet the timing and quality requirements imposed by the tasks running on the grid, the resources required by the tasks needs to be carefully scheduled. In the last decade, a lot of scheduling algorithms have been proposed to squeeze the computing power from a grid. However, many of them do not consider the...
Model checking is a popular technique to systematically and automatically verify system properties. Unfortunately, the well-known state explosion problem often limits the extent to which it can be applied to realistic specifications, due to the huge resulting memory requirements. Distributed-memory model checkers exist, but have thus far only been evaluated on small-scale clusters, with mixed results...
This paper presents ldquoSelf-Chordrdquo, a bio-inspired P2P algorithm that can be profitably adopted to build the information service of distributed systems, in particular Computational Grids and Clouds. Self-Chord inherits the ability of Chord-like structured systems for the construction and maintenance of an overlay of peers, but features enhanced functionalities deriving from the activity of ant-inspired...
We investigate the effects of communication failures in grid-based, distributed genetic algorithms with various topologies. We evaluated the performance behavior of distributed GAs under varying levels of persistent communication failures, using the sorting network problem as a benchmark application. In this experiment, we find that distributed GA with larger population size is less affected by the...
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