A FUNCTIONAL SKETCH FOR RESOURCES MANAGEMENT IN COLLABORATIVE SYSTEMS FOR BUSINESS

This paper presents a functional design sketch for the resource management module of a highly scalable collaborative system. Small and medium enterprises require such tools in order to benefit from and develop innovative business ideas and technologies. As computing power is a modern increasing demand and no easy and cheap solutions are defined, especially small companies or emerging business projects abide a more accessible alternative. Our work targets to settle a model for how P2P architecture can be used as infrastructure for a collaborative system that delivers resource access services. We are focused on finding a workable collaborative strategy between peers so that the system offers a cheap, trustable and quality service. Thus, in this phase we are not concerned about solutions for a specific type of task to be executed by peers, but only considering CPU power as resource. This work concerns the resource management module as a part of a larger project in which we aim to build a collaborative system for businesses with important resource demandsresource management, p2p, open-systems, service oriented computing, collaborative systems

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

A Utility-Based Reputation Model for Grid Resource Management System

In this paper we propose extensions to the existing utility-based reputation model for virtual organizations (VOs) in grids, and present a novel approach for integrating reputation into grid resource management system. The proposed extensions include: incorporation of statistical model of user behaviour (SMUB) to assess user reputation; a new approach for assigning initial reputation to a new entity in a VO; capturing alliance between consumer and resource; time decay and score functions. The addition of the SMUB model provides robustness and dynamics to the user reputation model comparing to the policy-based user reputation model in terms of adapting to user actions. We consider a problem of integrating reputation into grid scheduler as a multi-criteria optimization problem. A non-linear trade-off scheme is applied to form a composition of partial criteria to provide a single objective function. The advantage of using such a scheme is that it provides a Pareto-optimal solution partially satisfying criteria with corresponding weights. Experiments were run to evaluate performance of the model in terms of resource management using data collected within the EGEE Grid-Observatory project. Results of simulations showed that on average a 45 % gain in performance can be achieved when using a reputation-based resource scheduling algorithm

An efficient approach based on trust and reputation for secured selection of grid resources

Security is a principal concern in offering an infrastructure for the formation of general-purpose computational grids. A number of grid implementations have been devised to deal with the security concerns by authenticating the users, hosts and their interactions in an appropriate fashion. Resource management systems that are sophisticated and secured are inevitable for the efficient and beneficial deployment of grid computing services. The chief factors that can be problematic in the secured selection of grid resources are the wide range of selection and the high degree of strangeness. Moreover, the lack of a higher degree of confidence relationship is likely to prevent efficient resource allocation and utilisation. In this paper, we present an efficient approach for the secured selection of grid resources, so as to achieve secure execution of the jobs. This approach utilises trust and reputation for securely selecting the grid resources. To start with, the self-protection capability and reputation weightage of all the entities are computed, and based on those values, the trust factor (TF) of all the entities are determined. The reputation weightage of an entity is the measure of both the user’s feedback and other entities’ feedback. Those entities with higher TF values are selected for the secured execution of jobs. To make the proposed approach more comprehensive, a novel method is employed for evaluating the user’s feedback on the basis of the existing feedbacks available regarding the entities. This approach is proved to be scalable for an increased number of user jobs and grid entities. The experimentation portrays that this approach offers desirable efficiency in the secured selection of grid resources

E-infrastructures fostering multi-centre collaborative research into the intensive care management of patients with brain injury

Clinical research is becoming ever more collaborative with multi-centre trials now a common practice. With this in mind, never has it been more important to have secure access to data and, in so doing, tackle the challenges of inter-organisational data access and usage. This is especially the case for research conducted within the brain injury domain due to the complicated multi-trauma nature of the disease with its associated complex collation of time-series data of varying resolution and quality. It is now widely accepted that advances in treatment within this group of patients will only be delivered if the technical infrastructures underpinning the collection and validation of multi-centre research data for clinical trials is improved. In recognition of this need, IT-based multi-centre e-Infrastructures such as the Brain Monitoring with Information Technology group (BrainIT - www.brainit.org) and Cooperative Study on Brain Injury Depolarisations (COSBID - www.cosbid.de) have been formed. A serious impediment to the effective implementation of these networks is access to the know-how and experience needed to install, deploy and manage security-oriented middleware systems that provide secure access to distributed hospital based datasets and especially the linkage of these data sets across sites. The recently funded EU framework VII ICT project Advanced Arterial Hypotension Adverse Event prediction through a Novel Bayesian Neural Network (AVERT-IT) is focused upon tackling these challenges. This chapter describes the problems inherent to data collection within the brain injury medical domain, the current IT-based solutions designed to address these problems and how they perform in practice. We outline how the authors have collaborated towards developing Grid solutions to address the major technical issues. Towards this end we describe a prototype solution which ultimately formed the basis for the AVERT-IT project. We describe the design of the underlying Grid infrastructure for AVERT-IT and how it will be used to produce novel approaches to data collection, data validation and clinical trial design is also presented

A Brokering Framework for Assessing Legal Risks in Big Data and the Cloud

“Cloud computing” and “Big Data” are amongst the most hyped-up terms and buzzwords of the moment. After decades in which individuals and companies used to host their data and applications using their own IT infrastructure, the world has seen the stunning transformation of the Internet. Major shifts occurred when these infrastructures began to be outsourced to public Cloud providers to match commercial expectations. Storing, sharing and transferring data and databases over the Internet is convenient, yet legal risks cannot be eliminated. Legal risk is a fast-growing area of research and covers various aspects of law. Current studies and research on Cloud computing legal risk assessment have been, however, limited in scope and focused mainly on security and privacy aspects. There is little systematic research on the risks, threats and impact of the legal issues inherent to database rights and “ownership” rights of data. Database rights seem to be outdated and there is a significant gap in the scientific literature when it comes to the understanding of how to apply its provisions in the Big Data era. This means that we need a whole new framework for understanding, protecting and sharing data in the Cloud. The scheme we propose in this chapter is based on a risk assessment-brokering framework that works side by side with Service Level Agreements (SLAs). This proposed framework will provide better control for Cloud users and will go a long way to increase confidence and reinforce trust in Cloud computing transactions