Automated Negotiation for Provisioning Virtual Private Networks Using FIPA-Compliant Agents

This paper describes the design and implementation of negotiating agents for the task of provisioning virtual private networks. The agents and their interactions comply with the FIPA specification and they are implemented using the FIPA-OS agent framework. Particular attention is focused on the design and implementation of the negotiation algorithms

Spatio-Temporal Context in Agent-Based Meeting Scheduling

Meeting scheduling is a common task for organizations of all sizes. It involves searching for a time and place when and where all the participants can meet. However, scheduling a meeting is generally difficult in that it attempts to satisfy the preferences of all participants. Negotiation tends to be an iterative and time consuming task. Proxy agents can handle the negotiation on behalf of the individuals without sacrificing their privacy or overlooking their preferences. This thesis examines the implications of formalizing meeting scheduling as a spatiotemporal negotiation problem. The “Children in the Rectangular Forest” (CRF) canonical model is applied to meeting scheduling. By formalizing meeting scheduling within the CRF model, a generalized problem emerges that establishes a clear relationship with other spatiotemporal distributed scheduling problems. The thesis also examines the implications of the proposed formalization to meeting scheduling negotiations. A protocol for meeting location selection is presented and evaluated using simulations

The Strategies for Quorum Satisfaction in Host-to-Host Meeting Scheduling Negotiation

This paper proposes two strategies for handling conflict schedule of two meetings which invite the same member of personnel at the same time through host-to-host negotiation scheme. The strategy is to let the member attend the other meeting under the condition that the group decision regarding the schedule is not changed and meeting quorum is fulfilled, namely release strategy. Other strategy is to substitute the absent personnel in order to keep the number of attendees above the quorum, namely substitute strategy. This paper adapts a mechanism design approach, namely Clarke Tax Mechanism, to satisfy incentive compatibility and individual rationality principal in meeting scheduling. By using a release strategy and substitute strategy, colliding meetings can still be held according to the schedule without the need for rescheduling. This paper shows the simulation result of using the strategies within some scenarios. It demonstrates that the number of meeting failures can be reduced with negotiation.       

A theoretical and computational basis for CATNETS

The main content of this report is the identification and definition of market mechanisms for Application Layer Networks (ALNs). On basis of the structured Market Engineering process, the work comprises the identification of requirements which adequate market mechanisms for ALNs have to fulfill. Subsequently, two mechanisms for each, the centralized and the decentralized case are described in this document. These build the theoretical foundation for the work within the following two years of the CATNETS project. --Grid Computing

Theoretical and Computational Basis for Economical Ressource Allocation in Application Layer Networks - Annual Report Year 1

This paper identifies and defines suitable market mechanisms for Application Layer Networks (ALNs). On basis of the structured Market Engineering process, the work comprises the identification of requirements which adequate market mechanisms for ALNs have to fulfill. Subsequently, two mechanisms for each, the centralized and the decentralized case are described in this document. --Grid Computing

Agent-based homeostatic control for green energy in the smart grid

With dwindling non-renewable energy reserves and the adverse effects of climate change, the development of the smart electricity grid is seen as key to solving global energy security issues and to reducing carbon emissions. In this respect, there is a growing need to integrate renewable (or green) energy sources in the grid. However, the intermittency of these energy sources requires that demand must also be made more responsive to changes in supply, and a number of smart grid technologies are being developed, such as high-capacity batteries and smart meters for the home, to enable consumers to be more responsive to conditions on the grid in real-time. Traditional solutions based on these technologies, however, tend to ignore the fact that individual consumers will behave in such a way that best satisfies their own preferences to use or store energy (as opposed to that of the supplier or the grid operator). Hence, in practice, it is unclear how these solutions will cope with large numbers of consumers using their devices in this way. Against this background, in this paper, we develop novel control mechanisms based on the use of autonomous agents to better incorporate consumer preferences in managing demand. These agents, residing on consumers' smart meters, can both communicate with the grid and optimise their owner's energy consumption to satisfy their preferences. More specifically, we provide a novel control mechanism that models and controls a system comprising of a green energy supplier operating within the grid and a number of individual homes (each possibly owning a storage device). This control mechanism is based on the concept of homeostasis whereby control signals are sent to individual components of a system, based on their continuous feedback, in order to change their state so that the system may reach a stable equilibrium. Thus, we define a new carbon-based pricing mechanism for this green energy supplier that takes advantage of carbon-intensity signals available on the internet in order to provide real-time pricing. The pricing scheme is designed in such a way that it can be readily implemented using existing communication technologies and is easily understandable by consumers. Building upon this, we develop new control signals that the supplier can use to incentivise agents to shift demand (using their storage device) to times when green energy is available. Moreover, we show how these signals can be adapted according to changes in supply and to various degrees of penetration of storage in the system. We empirically evaluate our system and show that, when all homes are equipped with storage devices, the supplier can significantly reduce its reliance on other carbon-emitting power sources to cater for its own shortfalls. By so doing, the supplier reduces the carbon emission of the system by up to 25% while the consumer reduces its costs by up to 14.5%. Finally, we demonstrate that our homeostatic control mechanism is not sensitive to small prediction errors and the supplier is incentivised to accurately predict its green production to minimise costs

Federated Robust Embedded Systems: Concepts and Challenges

The development within the area of embedded systems (ESs) is moving rapidly, not least due to falling costs of computation and communication equipment. It is believed that increased communication opportunities will lead to the future ESs no longer being parts of isolated products, but rather parts of larger communities or federations of ESs, within which information is exchanged for the benefit of all participants. This vision is asserted by a number of interrelated research topics, such as the internet of things, cyber-physical systems, systems of systems, and multi-agent systems. In this work, the focus is primarily on ESs, with their specific real-time and safety requirements. While the vision of interconnected ESs is quite promising, it also brings great challenges to the development of future systems in an efficient, safe, and reliable way. In this work, a pre-study has been carried out in order to gain a better understanding about common concepts and challenges that naturally arise in federations of ESs. The work was organized around a series of workshops, with contributions from both academic participants and industrial partners with a strong experience in ES development. During the workshops, a portfolio of possible ES federation scenarios was collected, and a number of application examples were discussed more thoroughly on different abstraction levels, starting from screening the nature of interactions on the federation level and proceeding down to the implementation details within each ES. These discussions led to a better understanding of what can be expected in the future federated ESs. In this report, the discussed applications are summarized, together with their characteristics, challenges, and necessary solution elements, providing a ground for the future research within the area of communicating ESs

Agent-Based System Design for Service Process Scheduling: Challenges, Approaches and Opportunities

Compared with traditional manufacturing scheduling, service process scheduling poses additional challenges attributable to the significant customer involvement in service processes. In services, there are typically no inventoried products, which make the service provider's capacity more sensitive to dynamic changes. Service process scheduling objectives are also more complicated due to the consideration of customer preferences, customer waiting costs and human resource costs. After describing the Unified Services Theory and analysing its scheduling implications, this paper reviews the research literature on service process scheduling system design with a particular emphasis on agent-based approaches. Major issues in agent-based service process scheduling systems design are discussed and research opportunities are identified. The survey of the literature reveals that despite of many domain-specific designs in agent-based service process scheduling, there is a lack of general problem formulations, classifications, solution frameworks, and test beds. Constructing these general models for service process scheduling system design will facilitate the collaboration of researchers in this area and guide the effective development of integrated service process scheduling systems

Multi-agent System Models for Distributed Services Scheduling

This thesis investigates the computational and modeling issues involved with developing solutions for distributed service scheduling problems. Compared with traditional manufacturing scheduling, service scheduling poses additional challenges due to the significant customer involvement in service processes. The first challenge is that the service scheduling environment is a distributed environment in which scheduling-related information is scattered among individual identities, such as service providers and customers. The second challenge is that the service scheduling environment is a dynamic environment. Uncertainty in customer demand, customer cancellations and no-shows make the scheduling of services a complex dynamic process. Service scheduling has to be robust and prepared to accommodate any contingencies caused by customer involvement in service production. The third challenge concerns customers’ private information. To compute optimal schedules, ideally, the scheduler should know the complete customer availability and preference information within the scheduling horizon. However, customers may act strategically to protect their private information. Therefore, service scheduling systems should be designed so that they are able to elicit enough of a customer’s private information that will make it possible to compute high quality schedules. The fourth challenge is that in a service scheduling environment, the objectives are complicated and they may even be in opposition. The distributed service scheduling environment enables each agent to have their own scheduling objectives. The objectives of these agents can vary from one to another. In addition to multiple objectives, since agents are self-interested, they are likely to behave strategically to achieve their own objectives without considering the global objectives of the system. Existing approaches usually deal with only a part of the challenges in a specific service domain. There is a need for general problem formulations and solutions that address service scheduling challenges in a comprehensive framework. In this thesis, I propose an integrated service scheduling framework for the general service scheduling problem. The proposed framework uses iterative auction as the base mechanism to tackle service scheduling challenges in distributed and dynamic environments. It accommodates customer’s private information by providing appropriate incentives to customers and it has the potential to accommodate dynamic events. This framework integrates customers’ preferences with the allocation of a provider’s capacity through multilateral negotiation between the provider and its customers. The framework can accommodate both price-based commercial settings and non-commercial service settings. Theoretical and experimental results are developed to verify the effectiveness of the proposed framework. The application of the framework to the mass customization of services and to appointment scheduling are developed to demonstrate the applicability of the general framework to specific service domains. A web-based prototype is designed and implemented to evaluate the scalability of the approach in a distributed environment

Stigmergic interoperability for autonomic systems: Managing complex interactions in multi-manager scenarios

The success of autonomic computing has led to its popular use in many application domains, leading to scenarios where multiple autonomic managers (AMs) coexist, but without adequate support for interoperability. This is evident, for example, in the increasing number of large datacentres with multiple managers which are independently designed. The increase in scale and size coupled with heterogeneity of services and platforms means that more AMs could be integrated to manage the arising complexity. This has led to the need for interoperability between AMs. Interoperability deals with how to manage multi-manager scenarios, to govern complex coexistence of managers and to arbitrate when conflicts arise. This paper presents an architecture-based stigmergic interoperability solution. The solution presented in this paper is based on the Trustworthy Autonomic Architecture (TAArch) and uses stigmergy (the means of indirect communication via the operating environment) to achieve indirect coordination among coexisting agents. Usually, in stigmergy-based coordination, agents may be aware of the existence of other agents. In the approach presented here in, agents (autonomic managers) do not need to be aware of the existence of others. Their design assumes that they are operating in 'isolation' and they simply respond to changes in the environment. Experimental results with a datacentre multi-manager scenario are used to analyse the proposed approach