Generic Methods for Adaptive Management of Service Level Agreements in Cloud Computing

The adoption of cloud computing to build and deliver application services has been nothing less than phenomenal. Service oriented systems are being built using disparate sources composed of web services, replicable datastores, messaging, monitoring and analytics functions and more. Clouds augment these systems with advanced features such as high availability, customer affinity and autoscaling on a fair pay-per-use cost model. The challenge lies in using the utility paradigm of cloud beyond its current exploit. Major trends show that multi-domain synergies are creating added-value service propositions. This raises two questions on autonomic behaviors, which are specifically ad- dressed by this thesis. The first question deals with mechanism design that brings the customer and provider(s) together in the procurement process. The purpose is that considering customer requirements for quality of service and other non functional properties, service dependencies need to be efficiently resolved and legally stipulated. The second question deals with effective management of cloud infrastructures such that commitments to customers are fulfilled and the infrastructure is optimally operated in accordance with provider policies. This thesis finds motivation in Service Level Agreements (SLAs) to answer these questions. The role of SLAs is explored as instruments to build and maintain trust in an economy where services are increasingly interdependent. The thesis takes a wholesome approach and develops generic methods to automate SLA lifecycle management, by identifying and solving relevant research problems. The methods afford adaptiveness in changing business landscape and can be localized through policy based controls. A thematic vision that emerges from this work is that business models, services and the delivery technology are in- dependent concepts that can be finely knitted together by SLAs. Experimental evaluations support the message of this thesis, that exploiting SLAs as foundations for market innovation and infrastructure governance indeed holds win-win opportunities for both cloud customers and cloud providers

The Semantic Grid: A future e-Science infrastructure

e-Science offers a promising vision of how computer and communication technology can support and enhance the scientific process. It does this by enabling scientists to generate, analyse, share and discuss their insights, experiments and results in an effective manner. The underlying computer infrastructure that provides these facilities is commonly referred to as the Grid. At this time, there are a number of grid applications being developed and there is a whole raft of computer technologies that provide fragments of the necessary functionality. However there is currently a major gap between these endeavours and the vision of e-Science in which there is a high degree of easy-to-use and seamless automation and in which there are flexible collaborations and computations on a global scale. To bridge this practice–aspiration divide, this paper presents a research agenda whose aim is to move from the current state of the art in e-Science infrastructure, to the future infrastructure that is needed to support the full richness of the e-Science vision. Here the future e-Science research infrastructure is termed the Semantic Grid (Semantic Grid to Grid is meant to connote a similar relationship to the one that exists between the Semantic Web and the Web). In particular, we present a conceptual architecture for the Semantic Grid. This architecture adopts a service-oriented perspective in which distinct stakeholders in the scientific process, represented as software agents, provide services to one another, under various service level agreements, in various forms of marketplace. We then focus predominantly on the issues concerned with the way that knowledge is acquired and used in such environments since we believe this is the key differentiator between current grid endeavours and those envisioned for the Semantic Grid

Building a Semantic Tendering System

In the new B2B e-commerce arena, applications such as auctions and data exchange are growing rapidly. However, Web content is currently designed for human consumption rather than computer manipulation. This limits the possibility of Web automation. Fortunately, the new development of the Semantic Web that allows Web pages to provide information not only in terms of their content, but also in terms of the properties of that content, can be used for automation. Electronic tendering systems are among the successfully commercial systems that can tremendously benefit from the availability of Semantic Web. This study proposes an e-tendering system that uses the Semantic Web to investigate the automatic negotiation process. The system is built in a P2P environment to simulate a two-player negotiation. It is found that the ontology of semantic information can be used to locate qualified suppliers and precede negotiation. The bargaining power of each party is then determined by the relative magnitude of the negotiators’ respective costs of haggling and the utility that varies with the degree of risk preference. Our experiments showed that applying automatic negotiation strategies to e-tendering system in semantic web can reflect the risk preference of the participants

Multiple Issue Action and Market Algorithms for the World Wide Web

The Internet is quickly changing the way business-to-consumer and business-to-business commerce is conducted in the world. The Electronic Revolution has also spawned a trend of price wars and, in some instances, chaos because of the zero-sum nature of the electronic channel. The technology has created an opportunity to get beyond the lose-lose nature of single issue price wars by determining sellers' and buyers' preferences across multiple issues and encouraging negotiations, thereby creating possible joint gains for all parties. We develop simple multiple issue algorithms and heuristics that could be used in electronic auctions and electronic markets, to match business to business and consumers based on dovetailing underlying interests and preferences. We provide arguments that such dovetailed matches should help stabilize markets and make them more efficient

Towards an Agent-Based Approach for Multimarket Package e-Procurement

While most e-commerce research focuses on one market based problems, less work has been done on multimarket aggregation. Nowadays it is important to address the multimarket package e-procurement problem if we want to acquire a combination of goods and services from different suppliers and service providers. To achieve this, one should address the issues pertaining to identifying of a company's needs, discovering potential partners and suppliers, gathering distributed information and conducting combined negotiations, creating a seamless of information flow with different heterogeneous markets, suppliers, and partners, and finally concluding transactions. Several commercial e-procurement applications already automate some aspects of the procurement processes, helping decision makers and employees complete their purchasing activity. But none take into account the key aspects of combining goods and services into one aggregated package. Agent-based systems are well equipped to address the challenges of multimarket package e-procurement. Indeed, goal driven autonomous agents aim to satisfy user requirements and preferences while being flexible enough to deal with the diversity of semantics amongst markets, suppliers, service providers, partners and individual sellers. A distributed common shared space, called infospace, comprised of the negotiation exchanges and states, allows for agent coordination, market aggregation, and packages construction. This paper presents some issues and challenges faced in multimarket package e-procurement, and puts forward an agent-based approach to deal with them. La plupart des recherches sur le commerce électronique s'intéressent aux problèmes reliés à des marchés uniques. Moins de travaux ont été réalisés autour de l'approvisionnement multimarché. Le problème d'approvisionnement électronique (e-procurement) multimarché d'un paquet consiste en l'acquisition d'une combinaison d'objets à partir de différents fournisseurs de biens et services. Afin d'y parvenir, nous devons identifier les besoins de l'entreprise, découvrir les fournisseurs et partenaires potentiels, extraire de l'information distribuée et eventuellement gérer des négociations combinées, gérer le flux d'information circulant entre des marchés hétérogènes, vendeurs et partenaires, et finalement conclure des transactions. Il existe un certain nombre d'applications commerciales d'approvisionnement électronique qui automatisent quelques aspects du processus d'approvisionnement pour les entreprises, en aidant les preneurs de décisions et les employés dans leurs activités d'achats et d'approvisionnement. Mais aucune de ces applications ne tient en compte l'aspect de combinaison d'objets en un paquet agrégé. Les systèmes à base d'agents représentent une approche adéquate pour faire face aux problématiques posées de l'approvisionnement électronique multimarché d'un paquet. En effet, les agents autonomes essayent de satisfaire les besoins et préférences de l'utilisateur en étant assez flexibles pour gérer la diversité sémantique entre marchés, vendeurs, et fournisseurs de services. Un espace commun et partagé, appelé InfoSpace, contenant les échanges de données et les états des négociations, assure la coordination des agents, l'agrégation des marchés et la construction des paquets. Ce papier présente quelques problématiques et défis reliés à l'approvisionnement électronique multimarché de paquets, et expose une approche basée sur les agents pour y faire face.Markets, e-Procurement, Combined Negotiations, Multi-agent Systems, Marchés, e-procurement, négociations combinées, systèmes à base d'agents

An Agent Based Market Design Methodology for Combinatorial Auctions

Auction mechanisms have attracted a great deal of interest and have been used in diverse e-marketplaces. In particular, combinatorial auctions have the potential to play an important role in electronic transactions. Therefore, diverse combinatorial auction market types have been proposed to satisfy market needs. These combinatorial auction types have diverse market characteristics, which require an effective market design approach. This study proposes a comprehensive and systematic market design methodology for combinatorial auctions based on three phases: market architecture design, auction rule design, and winner determination design. A market architecture design is for designing market architecture types by Backward Chain Reasoning. Auction rules design is to design transaction rules for auctions. The specific auction process type is identified by the Backward Chain Reasoning process. Winner determination design is about determining the decision model for selecting optimal bids and auctioneers. Optimization models are identified by Forward Chain Reasoning. Also, we propose an agent based combinatorial auction market design system using Backward and Forward Chain Reasoning. Then we illustrate a design process for the general n-bilateral combinatorial auction market. This study serves as a guideline for practical implementation of combinatorial auction markets design.Combinatorial Auction, Market Design Methodology, Market Architecture Design, Auction Rule Design, Winner Determination Design, Agent-Based System

A model of preference elicitation: The case of distributed resource allocation

Market mechanisms are deemed promising for distributed resource allocation settings by explicitly involving users into the allocation process. The market considers the users’ and providers’ valuations to generate efficient resource allocations and prices. In theory, valuations are assumed to be known to the user. In practice, however, this is not the case. It is a complex burden for both users and providers to assess their true valuation for a certain combination of resources and services and to efficiently communicate this valuation to the market. This paper contributes to the theory of designing distributed allocation models in that (i) we propose a model for preference elicitation, which allows users and providers to assess their valuations as a function of their resource requirements and strategic considerations, (ii) we show how this model can be encoded within so-called bidding agents which interact with the market on behalf of the user, and (iii) we evaluate our approach in a numerical experiment to illustrate how the bidding agent adapts to the dynamic market situation. As this evaluation shows, the model outperforms technical schedulers and can thus be used for decision support in electronic markets