Grid Computing in Extreme Situations: Reducing Risk and Creating Resilience for IT-Infrastructures

Recent turbulences in financial markets are not only a challenge for the actors in the front offices of the related institutions, but also represent a serious challenge for the IT departments in the back offices of banks etc. We present a simulation model that shows how Grid computing increases the resilience and quality-of-service of IT infrastructure in departmentalized enterprises in the presence of shocks. Grid computing also reduces the costs deriving from the cancellation of jobs in times with a high volatility of computational load. The model can be used to find the appropriate type of IT infrastructure for different financial service institutions. Our simulations\u27 findings are also likely to encourage the introduction of Grid computing for related business branches and applications

Utility-based reputation model for VO in GRIDs

In this paper we extend the existing utility-based reputation model for VOs in Grids by incorporating a statistical model of user behaviour (SMUB) that was previously developed for computer networks and distributed systems, and different functions to address threats scenarios in the area of trust and reputation management. These modifications include: assigning initial reputation to a new entity in VO, capturing alliance between consumer and resource, time decay function, and score function.В данной статье предложена модификация существующей модели репутаций для виртуальных организаций в Grid-системах, которая основана на оценке функции полезности. Модификация модели состоит в добавлении статистической модели поведения пользователя, которая ранее была разработана для компьютерных сетей и распределенных систем, а также компонентов, которые позволяют противостоять угрозам в области управления доверием и репутацией. К числу этих компонентов относятся: механизм присвоения начальной репутации для новых субъектов виртуальной организации; учет взаимосвязей между пользователями и ресурсами; функция учета времени; а также классификация предоставляемых сервисов в Grid-системе

Dual Constraint Problem Optimization Using A Natural Approach: Genetic Algorithm and Simulated Annealing

Constraint optimization problems with multiple constraints and a large solution domain are NP hard and span almost all industries in a variety of applications. One such application is the optimization of resource scheduling in a pay per use grid environment. Charging for these resources based on demand is often referred to as Utility Computing, where resource providers lease computing power with varying costs based on processing speed. Consumers using this resource have time and cost constraints associated with each job they submit. Determining the optimal way to divide the job among the available resources with regard to the time and cost constraints is tasked to the Grid Resource Broker (GRB). The GRB must use an optimization algorithm that returns an accurate result in a timely mam1er. The Genetic Algorithm and the Simulated Annealing algorithm can both be used to achieve this goal, although Simulated Annealing outperforms the Genetic Algorithm for use by the GRB. Determining optimal values for the variables used in each algorithm is often achieved through trial and error, and success depends upon the solution domain of the problem. Although this work outlines a specific grid resource allocation application, the results can be applied to any optimization problem based on dual constraints

Advances in Evolutionary Algorithms

With the recent trends towards massive data sets and significant computational power, combined with evolutionary algorithmic advances evolutionary computation is becoming much more relevant to practice. Aim of the book is to present recent improvements, innovative ideas and concepts in a part of a huge EA field

Uncertainty and uncertainty tolerance in service provisioning

PhDService, in general term is a type of economic activity where the consumers utilize labour and/or expertise of others to perform a specific task. The birth and continued growth of the Internet provide a new medium for services to be delivered, and enable services to become widely and readily available. In recent years, the Internet has become an important platform to provide services to the end users. Service provisioning, In the context of computing, is the process of providing users with access to data and technology resources. In a perfect operating environment, the entities involved can expect the system will perform as intended or up to an accepted level of quality. Unfortunately, disruptions or failures can occur which can affect the operation of the service. Thus, the entities involved, in particular the service requester faces a situation whereby the service requester’s belief towards certain process in the service provisioning life cycle is affected, i.e. deviates from the actual truth. This situation whereby the service requester’s belief is affected is referred as an uncertainty. in this thesis, we discuss and explore the issue of uncertainty throughout the service provisioning life cycle and provide a measure to tolerate uncertainty in service provisioning offer through the application of subjective probability framework. This thesis provides several key contributions to address the uncertainty issues in service provision- Ing system in particular, for a service requester to overcome the negative consequence of uncertainty. The key contributions are: (1) introduction to the issue of uncertainty in service provisioning system, (2) a new classification scheme for uncertainties in service provisioning system, (3) a unified view of uncertainty in service provisioning system based on temporal classification, which is linked to service requester’s view, (4) a concept of uncertainty tolerance for service provisioning, (5) an approach and framework for automated uncertainty tolerance in service provisioning offer. The approach and framework for uncertainty tolerance in service provisioning offer presented in this thesis is evaluated through an empirical study. The result from the study shows the viability of the approach and framework of the uncertainty tolerance Mechanism through the application of subjective probability theory. The result also shows the positive outcome of the mechanism in term of higher cumulative utility, and better acceptance rate for the service requester.UNIMAS(Universiti Malaysia Sarawak) Government of Malaysi

Quality of Service Aspects and Metrics in Grid Computing

Grid computing promises to become the future computing paradigm for enterprise application after having shown to be a quite e#ective computing paradigm for resource-intensive scientific applications. Large scale grids are complex systems, composed of a large number of components belonging to disjoint domains. Planning the capacity to guarantee quality of service (QoS) in these environments is a chal lenge because global Service Level Agreements (SLA) depend on local SLAs, i.e., SLAs established with components that make up the grid. These components are generally autonomous and join the grid as part of a loose federation. This paper investigates some of the relevant issues that must be considered in designing grid applications that deliver appropriate QoS: definition of metrics, relationship between resource allocation and SLAs, and QoS-related mechanisms