From grids to clouds: a collective intelligence study for inter-cooperated infrastructures

Recently, more effort has been put into developing interoperable and distributed environments that offer users exceptional opportunities for utilizing resources over the internet. By utilising grids and clouds, resource consumers and providers, they gain significant benefits by either using or purchasing the computer processing capacities and the information provided by data centres. On the other hand, the collective intelligence paradigm is characterized as group based intelligence that emerges from the collaboration of many individuals, who in turn, define a coordinated knowledge model. It is envisaged that such a knowledge model could be of significant advantage if it is incorporated within the grid and cloud community. The dynamic load and access balancing of the grid and cloud data centres and the collective intelligence provides multiple opportunities, involving resource provisioning and development of scalable and heterogeneous applications. The contribution of this paper is that by utilizing grid and cloud resources, internal information stored within a public profile of each participant, resource providers as well as consumers, can lead to an effective mobilization of improved skills of members. We aim to unify the grid and cloud functionality as consumable computational power, for a) discussing the supreme advantages of such on-line resource utilization and provisioning models and b) analyzing the impact of the collective intelligence in the future trends of the aforementioned technologies

A trust based approach to mobile multi-agent systems.

This thesis undertakes to provide an architecture and understanding of the incorporation of trust into the paradigm of mobile multi-agent systems. Trust deliberation is a soft security approach to the problem of mobile agent security whereby an agent is protected from the malicious behaviour of others within the system. Using a trust approach capitalises on observing malicious behaviour rather than preventing it. We adopt an architectural approach to trust such than we do not provide a model in itself, numerous mathematical models for the calculation of trust based on a history of observations already exist. Rather we look to provide the framework enabling such models to be utilised by mobile agents. As trust is subjective we envisage a system whereby individual agents will use different trust models or different weighting mechanisms. Three architectures are provided. Centralised whereby the platform itself provides all of the services needed by an agent to make observations and calculate trust. Decentralised in which each individual agent is responsible for making observations, communicating trust and the calculation of its own trust in others. A hybrid architecture such that trust mechanisms are provided by the platform and additionally are embedded within the agents themselves. As an optimisation of the architectures proposed in this thesis, we introduce the notion of trust communities. A community is used as a means to represent the trust information in categorisations dependant upon various properties. Optimisation occurs in two ways; firstly with subjective communities and secondly with system communities. A customised implementation framework of the architectures is introduced in the form of our TEMPLE (Trust Enabled Mobile-agent PLatform Environment) and stands as the underpinning of a case-study implementation in order to provide empirical evidence in the form of scenario test-bed data as to the effectiveness of each architecture. The case study chosen for use in a trust based system is that of a fish market' as given the number of interactions, entities, and migration of agents involved in the system thus, providing substantial output data based upon the trust decisions made by agents. Hence, a good indicator of the effectiveness of equipping agents with trust ability using our architectures

Location Awareness in Multi-Agent Control of Distributed Energy Resources

The integration of Distributed Energy Resource (DER) technologies such as heat pumps, electric vehicles and small-scale generation into the electricity grid at the household level is limited by technical constraints. This work argues that location is an important aspect for the control and integration of DER and that network topology can inferred without the use of a centralised network model. It addresses DER integration challenges by presenting a novel approach that uses a decentralised multi-agent system where equipment controllers learn and use their location within the low-voltage section of the power system. Models of electrical networks exhibiting technical constraints were developed. Through theoretical analysis and real network data collection, various sources of location data were identified and new geographical and electrical techniques were developed for deriving network topology using Global Positioning System (GPS) and 24-hour voltage logs. The multi-agent system paradigm and societal structures were examined as an approach to a multi-stakeholder domain and congregations were used as an aid to decentralisation in a non-hierarchical, non-market-based approach. Through formal description of the agent attitude INTEND2, the novel technique of Intention Transfer was applied to an agent congregation to provide an opt-in, collaborative system. Test facilities for multi-agent systems were developed and culminated in a new embedded controller test platform that integrated a real-time dynamic electrical network simulator to provide a full-feedback system integrated with control hardware. Finally, a multi-agent control system was developed and implemented that used location data in providing demand-side response to a voltage excursion, with the goals of improving power quality, reducing generator disconnections, and deferring network reinforcement. The resulting communicating and self-organising energy agent community, as demonstrated on a unique hardware-in-the-loop platform, provides an application model and test facility to inspire agent-based, location-aware smart grid applications across the power systems domain

Towards Interoperable Research Infrastructures for Environmental and Earth Sciences

This open access book summarises the latest developments on data management in the EU H2020 ENVRIplus project, which brought together more than 20 environmental and Earth science research infrastructures into a single community. It provides readers with a systematic overview of the common challenges faced by research infrastructures and how a ‘reference model guided’ engineering approach can be used to achieve greater interoperability among such infrastructures in the environmental and earth sciences. The 20 contributions in this book are structured in 5 parts on the design, development, deployment, operation and use of research infrastructures. Part one provides an overview of the state of the art of research infrastructure and relevant e-Infrastructure technologies, part two discusses the reference model guided engineering approach, the third part presents the software and tools developed for common data management challenges, the fourth part demonstrates the software via several use cases, and the last part discusses the sustainability and future directions

Organization based multiagent architecture for distributed environments

[EN]Distributed environments represent a complex field in which applied solutions should be flexible and include significant adaptation capabilities. These environments are related to problems where multiple users and devices may interact, and where simple and local solutions could possibly generate good results, but may not be effective with regards to use and interaction. There are many techniques that can be employed to face this kind of problems, from CORBA to multi-agent systems, passing by web-services and SOA, among others. All those methodologies have their advantages and disadvantages that are properly analyzed in this documents, to finally explain the new architecture presented as a solution for distributed environment problems. The new architecture for solving complex solutions in distributed environments presented here is called OBaMADE: Organization Based Multiagent Architecture for Distributed Environments. It is a multiagent architecture based on the organizations of agents paradigm, where the agents in the architecture are structured into organizations to improve their organizational capabilities. The reasoning power of the architecture is based on the Case-Based Reasoning methology, being implemented in a internal organization that uses agents to create services to solve the external request made by the users. The OBaMADE architecture has been successfully applied to two different case studies where its prediction capabilities have been properly checked. Those case studies have showed optimistic results and, being complex systems, have demonstrated the abstraction and generalizations capabilities of the architecture. Nevertheless OBaMADE is intended to be able to solve much other kind of problems in distributed environments scenarios. It should be applied to other varieties of situations and to other knowledge fields to fully develop its potencial.[ES]Los entornos distribuidos representan un campo de conocimiento complejo en el que las soluciones a aplicar deben ser flexibles y deben contar con gran capacidad de adaptación. Este tipo de entornos está normalmente relacionado con problemas donde varios usuarios y dispositivos entran en juego. Para solucionar dichos problemas, pueden utilizarse sistemas locales que, aunque ofrezcan buenos resultados en términos de calidad de los mismos, no son tan efectivos en cuanto a la interacción y posibilidades de uso. Existen múltiples técnicas que pueden ser empleadas para resolver este tipo de problemas, desde CORBA a sistemas multiagente, pasando por servicios web y SOA, entre otros. Todas estas mitologías tienen sus ventajas e inconvenientes, que se analizan en este documento, para explicar, finalmente, la nueva arquitectura presentada como una solución para los problemas generados en entornos distribuidos. La nueva arquitectura aquí se llama OBaMADE, que es el acrónimo del inglés Organization Based Multiagent Architecture for Distributed Environments (Arquitectura Multiagente Basada en Organizaciones para Entornos Distribuidos). Se trata de una arquitectura multiagente basasa en el paradigma de las organizaciones de agente, donde los agentes que forman parte de la arquitectura se estructuran en organizaciones para mejorar sus capacidades organizativas. La capacidad de razonamiento de la arquitectura está basada en la metodología de razonamiento basado en casos, que se ha implementado en una de las organizaciones internas de la arquitectura por medio de agentes que crean servicios que responden a las solicitudes externas de los usuarios. La arquitectura OBaMADE se ha aplicado de forma exitosa a dos casos de estudio diferentes, en los que se han demostrado sus capacidades predictivas. Aplicando OBaMADE a estos casos de estudio se han obtenido resultados esperanzadores y, al ser sistemas complejos, se han demostrado las capacidades tanto de abstracción como de generalización de la arquitectura presentada. Sin embargo, esta arquitectura está diseñada para poder ser aplicada a más tipo de problemas de entornos distribuidos. Debe ser aplicada a más variadas situaciones y a otros campos de conocimiento para desarrollar completamente el potencial de esta arquitectura

Towards Interoperable Research Infrastructures for Environmental and Earth Sciences

This open access book summarises the latest developments on data management in the EU H2020 ENVRIplus project, which brought together more than 20 environmental and Earth science research infrastructures into a single community. It provides readers with a systematic overview of the common challenges faced by research infrastructures and how a ‘reference model guided’ engineering approach can be used to achieve greater interoperability among such infrastructures in the environmental and earth sciences. The 20 contributions in this book are structured in 5 parts on the design, development, deployment, operation and use of research infrastructures. Part one provides an overview of the state of the art of research infrastructure and relevant e-Infrastructure technologies, part two discusses the reference model guided engineering approach, the third part presents the software and tools developed for common data management challenges, the fourth part demonstrates the software via several use cases, and the last part discusses the sustainability and future directions

Journal of Telecommunications and Information Technology, 2014, nr 4

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