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Resource allocation is used to allocate the available resources in an economical way in developing software system. Resource allocation problem occurs due to assigning available resources in inefficient manner. Before this in modular software resources are allocated on the basis of module priority. In this paper, we investigate an optimal resource algorithm to minimize the cost of software, time,...
Cloud computing has become increasingly popular due to deployment of cloud solutions that will enable enterprises to cost reduction and more operational flexibility. Reliability is a key metric for assessing performance in such systems. Fault tolerance methods are extensively used to enhance reliability in Cloud Computing Systems (CCS). However, these methods impose extra hardware and/or software...
Cloud computing is widely referred as the next generation of computing systems. Reliability is a key metric for assessing performance in such systems. Redundancy and diversity are prevalent approaches to enhance reliability in Cloud Computing Systems (CCS). Proper resource allocation is an alternative approach to reliability improvement in such systems. In contrast to redundancy, appropriate resource...
In this paper, we propose an ordinal optimization (OO) based algorithm for solving the resource allocation optimization problem of grid computing system to maximize the service reliability. An approximate model is firstly proposed to estimate the service reliability of a resource allocation design within a tolerable computation time. Next, we employ the proposed algorithm to solve the resource allocation...
SA-based software reliability estimation, which is applied in the early stage of software life cycle, is used to allocate resources to components to achieve the desired reliability effectively. This paper proposed an approach to predict reliability of the whole SA producing process by estimating and evaluating the different stages' reliability in SA producing process based on Markov chain. A case...
A probabilistic analytical framework for decentralized load balancing (LB) strategies for heterogeneous distributed-computing systems (DCSs) is presented with the overall goal of maximizing the service reliability in the presence of random failures. The service reliability of a DCS is defined as the probability of successfully serving a specified workload before all the computing nodes fail permanently...
In this paper we tackle several problems regarding efficient data replication in distributed systems. In the first part, we consider several theoretical offline data replication and reliability improvement problems, for which we present novel, efficient, algorithmic solutions (e.g. replication in tree networks and reliable replication strategies). In the second part we address a concrete data replication...
Virtual machine (VM) technology provides an additional layer of abstraction for resource management in high-performance computing (HPC) systems. In large-scale computing clusters, component failures become norms instead of exceptions, caused by the ever-increasing system complexity. VM construction and reconfiguration is a potent tool for efficient online system maintenance and failure resilience...
An early prediction of resource utilization and its impact on system performance and reliability can reduce the overall system cost, by allowing early correction of detected problems, or changes in development plans with minimized overhead. Nowadays, researchers are using both academic and commercial models to predict such attributes, by measuring them at earliest stages of system development. In...
In this paper, two problems of optimal resource allocation to modules during testing phase are studied: (1) maximization of the number of faults removed when the amount of testing-effort is fixed, and (2) maximization of the number of faults removed satisfying a certain percentage of initial faults to be removed with a fixed amount of testing-effort. These optimization problems are formulated as nonlinear...
To make the most effective application placement decisions on volatile large-scale heterogeneous Grids, schedulers must consider factors such as resource speed, load, and reliability. Including reliability requires availability predictors, which consider different periods of resource history, and use various strategies to make predictions about resource behavior. Prediction accuracy significantly...
Importance measures of a system provide a sense of the relative priorities of the components from a system reliability perspective. These measures can thus be used to identify critical components and to guide the allocation of resources so that the system reliability can be improved in a cost effective manner. Importance measures are widely used in many engineered hardware and electro-mechanical systems...
Nowadays, as the software systems become increasingly large and complex, the problem of allocating the limited testing-resource during the testing phase has become more and more difficult. In this paper, we propose to solve the testing-resource allocation problem (TRAP) using multi-objective evolutionary algorithms. Specifically, we formulate TRAP as two multi-objective problems. First, we consider...
Fault tolerance is an important aspect in real-time computing. In real-time control systems, tasks could be faulty due to various reasons. Faulty tasks may compromise the performance and safety of the whole system and even cause disastrous consequences. In this paper, we describe On-demand real-time guard (ORTEGA), a new software fault tolerance architecture for real-time control systems. ORTEGA has...
Failures and downtimes have severe impact on the performance of parallel programs in a large scale High Performance Computing (HPC) environment. There were several research efforts to understand the failure behavior of computing systems. However, the presence of multitude of hardware and software components required for uninterrupted operation of parallel programs make failure and reliability prediction...
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