Fuzzy Logic Based Negotiation in E-Commerce

The evolution of multi-agent system (MAS) presents new challenges in computer science and software engineering. A particularly challenging problem is the design of various forms of interaction among agents. Interaction may be aimed at enabling agents to coordinate their activities, cooperate to reach common objectives, or exchange resources to better achieve their individual objectives. This thesis is dealing with negotiation in e-commerce: a process through which multiple self-interested agents can reach agreement over the exchange of scarce resources. In particular, we present a fuzzy logic-based negotiation approach to automate multi-issue bilateral negotiation in e-marketplaces. In such frameworks issues to negotiate on can be multiple, interrelated, and may not be fixed in advance. Therefore, we use fuzzy inference system to model relations among issues and to allow agents express their preferences on them. We focus on settings where agents have limited or uncertain information, ruling them out from making optimal decisions. Since agents make decisions based on particular underlying reasons, namely their interests, beliefs then applying logic (by using fuzzy logic) over these reasons can enable agents to refine their decisions and consequently reach better agreements. I refer to this form of negotiation as: Fuzzy logic based negotiation in e-commerce. The contributions of the thesis begin with the use of fuzzy logic to design a reasoning model through which negotiation tactics and strategy are expressed throughout the process of negotiation. Then, an exploration of the differences between this approach and the more traditional bargaining-based approaches is presented. Strategic issues are then explored and a methodology for designing negotiation strategies is developed. Finally, the applicability of the framework is simulated using MATLAB toolbox

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

Fuzzy Logic Based Negotiation in E-Commerce

The evolution of multi-agent system (MAS) presents new challenges in computer science and software engineering. A particularly challenging problem is the design of various forms of interaction among agents. Interaction may be aimed at enabling agents to coordinate their activities, cooperate to reach common objectives, or exchange resources to better achieve their individual objectives. This thesis is dealing with negotiation in e-commerce: a process through which multiple self-interested agents can reach agreement over the exchange of scarce resources. In particular, we present a fuzzy logic-based negotiation approach to automate multi-issue bilateral negotiation in e-marketplaces. In such frameworks issues to negotiate on can be multiple, interrelated, and may not be fixed in advance. Therefore, we use fuzzy inference system to model relations among issues and to allow agents express their preferences on them. We focus on settings where agents have limited or uncertain information, ruling them out from making optimal decisions. Since agents make decisions based on particular underlying reasons, namely their interests, beliefs then applying logic (by using fuzzy logic) over these reasons can enable agents to refine their decisions and consequently reach better agreements. I refer to this form of negotiation as: Fuzzy logic based negotiation in e-commerce. The contributions of the thesis begin with the use of fuzzy logic to design a reasoning model through which negotiation tactics and strategy are expressed throughout the process of negotiation. Then, an exploration of the differences between this approach and the more traditional bargaining-based approaches is presented. Strategic issues are then explored and a methodology for designing negotiation strategies is developed. Finally, the applicability of the framework is simulated using MATLAB toolbox

Curvature-based sparse rule base generation for fuzzy rule interpolation

Fuzzy logic has been successfully widely utilised in many real-world applications. The most common application of fuzzy logic is the rule-based fuzzy inference system, which is composed of mainly two parts including an inference engine and a fuzzy rule base. Conventional fuzzy inference systems always require a rule base that fully covers the entire problem domain (i.e., a dense rule base). Fuzzy rule interpolation (FRI) makes inference possible with sparse rule bases which may not cover some parts of the problem domain (i.e., a sparse rule base). In addition to extending the applicability of fuzzy inference systems, fuzzy interpolation can also be used to reduce system complexity for over-complex fuzzy inference systems. There are typically two methods to generate fuzzy rule bases, i.e., the knowledge driven and data-driven approaches. Almost all of these approaches only target dense rule bases for conventional fuzzy inference systems. The knowledge-driven methods may be negatively affected by the limited availability of expert knowledge and expert knowledge may be subjective, whilst redundancy often exists in fuzzy rule-based models that are acquired from numerical data. Note that various rule base reduction approaches have been proposed, but they are all based on certain similarity measures and are likely to cause performance deterioration along with the size reduction. This project, for the first time, innovatively applies curvature values to distinguish important features and instances in a dataset, to support the construction of a neat and concise sparse rule base for fuzzy rule interpolation. In addition to working in a three-dimensional problem space, the work also extends the natural three-dimensional curvature calculation to problems with high dimensions, which greatly broadens the applicability of the proposed approach. As a result, the proposed approach alleviates the ‘curse of dimensionality’ and helps to reduce the computational cost for fuzzy inference systems. The proposed approach has been validated and evaluated by three real-world applications. The experimental results demonstrate that the proposed approach is able to generate sparse rule bases with less rules but resulting in better performance, which confirms the power of the proposed system. In addition to fuzzy rule interpolation, the proposed curvature-based approach can also be readily used as a general feature selection tool to work with other machine learning approaches, such as classifiers

A two-sided logistics matching method considering trading psychology and matching effort under a 4PL

As a supply chain integrator, a fourth party logistics (4PL) typically does not have its own logistics facilities, so the 4PL needs to match third party logistics (3PLs) and customers to meet customers' logistics service demands. An effective matching method can not only improve the efficiency of 4PL supply chain management, but also establish more long-term and stable cooperative relationships with customers and 3PLs. Therefore, we propose a novel two-sided logistics matching method considering the trading psychology and matching effort of matching subjects under the 4PL. First, based on considering the trading psychology, the concepts of blocking pair and stable matching are redefined. Then, based on the public values and matching effort of customers and 3PLs, the evaluation values of customers and 3PLs are calculated. And the trading possibilities of customers and 3PLs are calculated by considering the fairness threshold. Next, we consider different stable matching demands of customers and 3PLs and develop a bi-objective matching model to maximize the trading possibilities of both customers and 3PLs. Furthermore, the properties of the proposed method are discussed. Finally, a numerical example and comparison analysis are provided to prove the feasibility and effectiveness of the proposed method

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

A Free Exchange e-Marketplace for Digital Services

The digital era is witnessing a remarkable evolution of digital services. While the prospects are countless, the e-marketplaces of digital services are encountering inherent game-theoretic and computational challenges that restrict the rational choices of bidders. Our work examines the limited bidding scope and the inefficiencies of present exchange e-marketplaces. To meet challenges, a free exchange e-marketplace is proposed that follows the free market economy. The free exchange model includes a new bidding language and a double auction mechanism. The rule-based bidding language enables the flexible expression of preferences and strategic conduct. The bidding message holds the attribute-valuations and bidding rules of the selected services. The free exchange deliberates on attributes and logical bidding rules for automatic deduction and formation of elicited services and bids that result in a more rapid self-managed multiple exchange trades. The double auction uses forward and reverse generalized second price auctions for the symmetric matching of multiple digital services of identical attributes and different quality levels. The proposed double auction uses tractable heuristics that secure exchange profitability, improve truthful bidding and deliver stable social efficiency. While the strongest properties of symmetric exchanges are unfeasible game-theoretically, the free exchange converges rapidly to the social efficiency, Nash truthful stability, and weak budget balance by multiple quality-levels cross-matching, constant learning and informs at repetitive thick trades. The empirical findings validate the soundness and viability of the free exchange

Self-managed resources in network virtualisation environments

Network virtualisation is a promising technique for dealing with the resistance of the Internet to architectural changes, enabling a novel business model in which infrastructure management is decoupled from service provision. It allows infrastructure providers (InPs) who own substrate networks (SNs) to lease chunks of them out to service providers who then create virtual networks (VNs), which can then be re-leased out or used to provide services to end-users. However, the different VNs should be initialised, in which case virtual links and nodes must be mapped to substrate nodes and paths respectively. One of the challenges in the initialisation of VNs is the requirement of an efficient sharing of SN resources. Since the profitability of InPs depends on how many VNs are able to be allocated simultaneously onto the SN, the success of network virtualisation will depend, in part, on how efficiently VNs utilise physical network resources. This thesis contributes to efficient resource sharing in network virtualisation by dividing the problem into three sub-problems: (1) mapping virtual nodes and links to substrate nodes and paths i.e. virtual network embedding (VNE), (2) dynamic managing of the resources allocated to VNs throughout their lifetime (DRA), and (3) provisioning of backup resources to ensure survivability of the VNs. The constrained VNE problem is NP-Hard. As a result, to simplify the solution, many existing approaches propose heuristics that make assumptions (e.g. a SN with infinite resources), some of which would not apply in practical environments. This thesis proposes an improvement in VNE by proposing a one-shot VNE algorithm which is based on column generation (CG). The CG approach starts by solving a restricted version of the problem, and thereafter refines it to obtain a final solution. The objective of a one-shot mapping is to achieve better resource utilisation, while using CG significantly enhances the solution time complexity. In addition current approaches are static in the sense that after the VNE stage, the resources allocated are not altered for the entire lifetime of the VN. The few proposals that do allow for adjustments in original mappings allocate a fixed amount of node and link resources to VNs throughout their life time. Since network load varies with time due to changing user demands, allocating a fixed amount of resources based on peak load could lead to an inefficient utilisation of overall SN resources, whereby, during periods when some virtual nodes and/or links are lightly loaded, SN resources are still reserved for them, while possibly rejecting new VN requests. The second contribution of this thesis are a set of proposals that ensure that SN resources are efficiently utilised, while at the same making sure that the QoS requirements of VNs are met. For this purpose, we propose self-management algorithms in which the SN uses time-difference machine learning techniques to make autonomous decisions with respect to resource allocation. Finally, while some scientific research has already studied multi-domain VNE, the available approaches to survivable VNs have focused on the single InP environment. Since in the more practical situation a network virtualisation environment will involve multiple InPs, and because an extension of network survivability approaches from the single to multi domain environments is not trivial, this thesis proposes a distributed and dynamic approach to survivability in VNs. This is achieved by using a multi-agent-system that uses a multi-attribute negotiation protocol and a dynamic pricing model forming InPs coalitions supporting SNs resource backups. The ultimate objective is to ensure that virtual network operators maximise profitability by minimising penalties resulting from QoS violations.La virtualització de xarxes es una tècnica prometedora per afrontar la resistència d'Internet als canvis arquitectònics, que permet un nou model de negoci en el que la gestió de la infraestructura de xarxa es desacobla de la provisió del servei. Això permet als proveïdors de infraestructura (InPs), propietaris de la xarxa física substrat (SN), llogar segments d'aquesta als proveïdors dels serveis, que crearan xarxes virtuals (VNs) que a l'hora poden re-llogar-se o utilitzar-se per donar servei a usuaris finals. No obstant això, les diferents VNs s'han d'inicialitzar assignant els seus nodes i enllaços als del substrat. Un dels reptes d'aquest procés es el requisit de fer un ús eficient dels recursos de la SN. Donat que el benefici d'un InP depèn del nombre de xarxes virtuals que puguin allotjar-se simultàniament en la SN, l'èxit de la virtualització de xarxes depèn en part de quan eficient es l’ús dels recursos de la xarxa física per part de les VNs. Aquesta Tesi contribueix a la millora de l’eficiència en la compartició de recursos en la virtualització de xarxes dividint el problema en tres sots problemes: (1) assignació de nodes i enllaços virtuals a nodes i enllaços del substrat (VNE), (2) gestió dinàmica dels recursos assignats a les VNs al llarg de la seva vida útil (DRA) i (3) aprovisionament de recursos de backup per assegurar la supervivència de les VNs. La naturalesa del problema VNE el fa “NP-Hard". En conseqüència, per simplificar la solució, moltes de les propostes son heurístiques que es basen en hipòtesis (per exemple, SN amb recursos il•limitats) de difícil compliment en escenaris reals. Aquesta Tesi proposa una millora al problema VNE mitjan_cant un algorisme “one-shot VNE" basat en generació de columnes (CG). La solució CG comena resolent una versió restringida del problema, per tot seguit refinar-la i obtenir la solució final. L'objectiu del “one-shot VNE" es aconseguir millorar l’ús dels recursos, mentre que CG redueix significativament la complexitat temporal del procés. D'altre banda, les solucions actuals son estàtiques, ja que els recursos assignats en la fase VNE no es modifiquen durant tot el temps de vida útil de la VN. Les poques propostes que permeten reajustar l’assignació inicial, es basen en una assignació fixe de recursos a les VNs. No obstant això, degut a que la càrrega de la xarxa varia a conseqüència de la demanda canviant dels usuaris, assignar una quantitat fixe de recursos basada en situacions de càrrega màxima esdevé en ineficiència per infrautilització en períodes de baixa demanda, mentre que en tals períodes de demanda baixa, el tenir recursos reservats, pot originar rebutjos de noves VNs. La segona contribució d'aquesta Tesi es un conjunt de propostes que asseguren l’ús eficient dels recursos de la SN, garantint a la vegada els requeriments de qualitat de servei de totes les VNs. Amb aquesta finalitat es proposen algorismes d’autogestió en els que la SN utilitza tècniques d'aprenentatge de màquines per a materialitzar decisions autònomes en l’assignació dels recursos. Finalment, malgrat que diversos estudis han tractat ja el problema VNE en entorn multi-domini, les propostes actuals de supervivència de xarxes virtuals s'han limitat a contexts d'aprovisionament per part d'un sol InP. En canvi, a la pràctica, la virtualització de xarxes comportarà un entorn d'aprovisionament multi-domini, i com que l’extensió de solucions de supervivència d'un sol domini al multi-domini no es trivial, aquesta Tesi proposa una solució distribuïda i dinàmica per a la supervivència de VNs. Això s'aconsegueix amb un sistema multi-agent que utilitza un protocol de negociació multi-atribut i un model dinàmic de preus per formar coalicions d'InPs que proporcionaran backups als recursos de les SNs. L'objectiu últim es assegurar que els operadors de xarxes virtuals maximitzin beneficis minimitzant les penalitzacions per violació de la QoS.La virtualización de redes es una técnica prometedora para afrontar la resistencia de Internet a cambios arquitectónicos, que permite un nuevo modelo de negocio en el que la gestión de la infraestructura está desacoplada del aprovisionamiento del servicio. Esto permite a los proveedores de infraestructuras (InPs), propietarios de la red física subyacente (SN), alquilar segmentos de la misma a los proveedores de servicio, los cuales crearán redes virtuales (VNs), que a su vez pueden ser realquiladas o usadaspara proveer el servicio a usuarios finales. Sin embargo, las diferentes VNs deben inicializarse, mapeando sus nodos y enlaces en los del substrato. Uno de los retos de este proceso de inicialización es el requisito de hacer un uso eficiente de los recursos de la SN. Dado que el benecio de los InPs depende de cuantas VNs puedan alojarse simultáneamente en la SN, el éxito de la virtualización de redes depende, en parte, de cuan eficiente es el uso de los recursos de red físicos por parte de las VNs. Esta Tesis contribuye a la compartición eficiente de recursos para la virtualización de redes dividiendo el problema en tres sub-problemas: (1) mapeo de nodos y enlaces virtuales sobre nodos y enlaces del substrato (VNE), (2) gestión dinámica de los recursos asignados a las VNs a lo largo de su vida útil (DRA), y (3) aprovisionamiento de recursos de backup para asegurar la supervivencia de las VNs. La naturaleza del problema VNE lo hace “NP-Hard". En consecuencia, para simplificar la solución, muchas de las actuales propuestas son heurísticas que parten de unas suposiciones (por ejemplo, SN con recursos ilimitados) de difícil asumir en la práctica. Esta Tesis propone una mejora al problema VNE mediante un algoritmo “one-shot VNE" basado en generación de columnas (CG). La solución CG comienza resolviendo una versión restringida del problema, para después refinarla y obtener la solución final. El objetivo del “one-shot VNE" es mejorar el uso de los recursos, a la vez que con CG se reduce significativamente la complejidad temporal del proceso. Por otro lado,las propuestas actuales son estáticas, ya que los recursos asignados en la fase VNE no se alteran a lo largo de la vida útil de la VN. Las pocas propuestas que permiten reajustes del mapeado original ubican una cantidad fija de recursos a las VNs. Sin embargo, dado que la carga de red varía con el tiempo, debido a la demanda cambiante de los usuarios, ubicar una cantidad fija de recursos basada en situaciones de pico conduce a un uso ineficiente de los recursos por infrautilización de los mismos en periodos de baja demanda, mientras que en esta situación, al tener los recursos reservados, pueden rechazarse nuevas solicitudes de VNs. La segunda contribución de esta Tesis es un conjunto de propuestas para el uso eficiente de los recursos de la SN, asegurando al mismo tiempo la calidad de servicio de las VNs. Para ello se proponen algoritmos de auto-gestión en los que la SN usa técnicas de aprendizaje de máquinas para materializar decisiones autónomas en la asignación de recursos. Finalmente, aunque determinadas investigaciones ya han estudiado el problema multi-dominio VNE, las propuestas actuales de supervivencia de redes virtuales se han limitado a un entorno de provisión de infraestructura de un solo InP. Sin embargo, en la práctica, la virtualización de redes comportará un entorno de aprovisionamiento con múltiples InPs, y dado a que la extensión de las soluciones de supervivencia de un entorno único a uno multi-dominio no es trivial, esta Tesis propone una solución distribuida y dinámica a la supervivencia de VNs. Esto se consigue mediante un sistema multi-agente que usa un protocolo de negociación multi-atributo y un modelo dinámico de precios para conformar coaliciones de InPs para proporcionar backups a los recursos de las SNs. El objetivo último es asegurar que los operadores de VNs maximicen su beneficio minimizando la penalización por violación de la QoS