2,937 research outputs found

    A theoretical and computational basis for CATNETS

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    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

    Resource Management in Grids: Overview and a discussion of a possible approach for an Agent-Based Middleware

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    14 pagesInternational audienceResource management and job scheduling are important research issues in computational grids. When software agents are used as resource managers and brokers in the Grid a number of additional issues and possible approaches materialize. The aim of this chapter is twofold. First, we discuss traditional job scheduling in grids, and when agents are utilized as grid middleware. Second, we use this as a context for discussion of how job scheduling can be done in the agent-based system under development

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

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    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

    Automated and dynamic multi-level negotiation framework applied to an efficient cloud provisioning

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    L’approvisionnement du Cloud est le processus de dĂ©ploiement et de gestion des applications sur les infrastructures publiques du Cloud. Il est de plus en plus utilisĂ© car il permet aux fournisseurs de services mĂ©tiers de se concentrer sur leurs activitĂ©s sans avoir Ă  gĂ©rer et Ă  investir dans l’infrastructure. Il comprend deux niveaux d’interaction : (1) entre les utilisateurs finaux et les fournisseurs de services pour l’approvisionnement des applications, et (2) entre les fournisseurs de services et les fournisseurs de ressources pour l’approvisionnement des ressources virtuelles. L’environnement Cloud est devenu un marchĂ© complexe oĂč tout fournisseur veut maximiser son profit monĂ©taire et oĂč les utilisateurs finaux recherchent les services les plus efficaces tout en minimisant leurs coĂ»ts. Avec la croissance de la concurrence dans le Cloud, les fournisseurs de services mĂ©tiers doivent assurer un approvisionnement efficace qui maximise la satisfaction de la clientĂšle et optimise leurs profits.Ainsi, les fournisseurs et les utilisateurs doivent ĂȘtre satisfaits en dĂ©pit de leurs besoins contradictoires. La nĂ©gociation est une solution prometteuse qui permet de rĂ©soudre les conflits en comblant le gap entre les capacitĂ©s des fournisseurs et les besoins des utilisateurs. Intuitivement, la nĂ©gociation automatique des contrats (SLA) permet d’aboutir Ă  un compromis qui satisfait les deux parties. Cependant, pour ĂȘtre efficace, la nĂ©gociation automatique doit considĂ©rer les propriĂ©tĂ©s de l’approvisionnement du Cloud et les complexitĂ©s liĂ©es Ă  la dynamicitĂ© (dynamicitĂ© de la disponibilitĂ© des ressources, dynamicitĂ© des prix). En fait ces critĂšres ont un impact important sur le succĂšs de la nĂ©gociation. Les principales contributions de cette thĂšse rĂ©pondant au dĂ©fi de la nĂ©gociation multi-niveau dans un contexte dynamique sont les suivantes: (1) Nous proposons un modĂšle de nĂ©gociateur gĂ©nĂ©rique qui considĂšre la nature dynamique de l’approvisionnement du Cloud et son impact potentiel sur les rĂ©sultats dĂ©cisionnels. Ensuite, nous construisons un cadre de nĂ©gociation multicouche fondĂ© sur ce modĂšle en l’instanciant entre les couches du Cloud. Le cadre comprend des agents nĂ©gociateurs en communication avec les modules en relation avec la qualitĂ© et le prix du service Ă  fournir (le planificateur, le moniteur, le prospecteur de marchĂ©). (2) Nous proposons une approche de nĂ©gociation bilatĂ©rale entre les utilisateurs finaux et les fournisseurs de service basĂ©e sur une approche d’approvisionnement existante. Les stratĂ©gies de nĂ©gociation sont basĂ©es sur la communication avec les modules d’approvisionnement (le planificateur et l’approvisionneur de machines virtuelles) afin d’optimiser les bĂ©nĂ©fices du fournisseur de service et de maximiser la satisfaction du client. (3) Afin de maximiser le nombre de clients, nous proposons une approche de nĂ©gociation adaptative et simultanĂ©e comme extension de la nĂ©gociation bilatĂ©rale. Nous proposons d’exploiter les changements de charge de travail en termes de disponibilitĂ© et de tarification des ressources afin de renĂ©gocier simultanĂ©ment avec plusieurs utilisateurs non acceptĂ©s (c’est-Ă -dire rejetĂ©s lors de la premiĂšre session de nĂ©gociation) avant la crĂ©ation du contrat SLA. (4) Afin de gĂ©rer toute violation possible de SLA, nous proposons une approche proactive de renĂ©gociation aprĂšs l’établissement de SLA. La renĂ©gociation est lancĂ©e lors de la dĂ©tection d’un Ă©vĂ©nement inattendu (par exemple, une panne de ressources) pendant le processus d’approvisionnement. Les stratĂ©gies de renĂ©gociation proposĂ©es visent Ă  minimiser la perte de profit pour le fournisseur et Ă  assurer la continuitĂ© du service pour le consommateur. Les approches proposĂ©es sont mises en Ɠuvre et les expĂ©riences prouvent les avantages d’ajouter la (re)nĂ©gociation au processus d’approvisionnement. L’utilisation de la (re)nĂ©gociation amĂ©liore le bĂ©nĂ©fice du fournisseur, le nombre de demandes acceptĂ©es et la satisfaction du client.Cloud provisioning is the process of deployment and management of applications on public cloud infrastructures. Cloud provisioning is used increasingly because it enables business providers to focus on their business without having to manage and invest in infrastructure. Cloud provisioning includes two levels of interaction: (1) between end-users and business providers for application provisioning; and (2) between business providers and resource providers for virtual resource provisioning.The cloud market nowadays is a complex environment where business providers need to maximize their monetary profit, and where end-users look for the most efficient services with the lowest prices. With the growth of competition in the cloud, business providers must ensure efficient provisioning that maximizes customer satisfaction and optimizes the providers’ profit. So, both providers and users must be satisfied in spite of their conflicting needs. Negotiation is an appealing solution to solve conflicts and bridge the gap between providers’ capabilities and users’ requirements. Intuitively, automated Service Level Agreement (SLA) negotiation helps in reaching an agreement that satisfies both parties. However, to be efficient, automated negotiation should consider the properties of cloud provisioning mainly the two interaction levels, and complexities related to dynamicity (e.g., dynamically-changing resource availability, dynamic pricing, dynamic market factors related to offers and demands), which greatly impact the success of the negotiation. The main contributions of this thesis tackling the challenge of multi-level negotiation in a dynamic context are as follows: (1) We propose a generic negotiator model that considers the dynamic nature of cloud provisioning and its potential impact on the decision-making outcome. Then, we build a multi-layer negotiation framework built upon that model by instantiating it among Cloud layers. The framework includes negotiator agents. These agents are in communication with the provisioning modules that have an impact on the quality and the price of the service to be provisioned (e.g, the scheduler, the monitor, the market prospector). (2) We propose a bilateral negotiation approach between end-users and business providers extending an existing provisioning approach. The proposed decision-making strategies for negotiation are based on communication with the provisioning modules (the scheduler and the VM provisioner) in order to optimize the business provider’s profit and maximize customer satisfaction. (3) In order to maximize the number of clients, we propose an adaptive and concurrent negotiation approach as an extension of the bilateral negotiation. We propose to harness the workload changes in terms of resource availability and pricing in order to renegotiate simultaneously with multiple non-accepted users (i.e., rejected during the first negotiation session) before the establishment of the SLA. (4) In order to handle any potential SLA violation, we propose a proactive renegotiation approach after SLA establishment. The renegotiation is launched upon detecting an unexpected event (e.g., resource failure) during the provisioning process. The proposed renegotiation decision-making strategies aim to minimize the loss in profit for the provider and to ensure the continuity of the service for the consumer. The proposed approaches are implemented and experiments prove the benefits of adding (re)negotiation to the provisioning process. The use of (re)negotiation improves the provider’s profit, the number of accepted requests, and the client’s satisfaction

    Proof-of-Concept Application - Annual Report Year 1

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    In this document the Cat-COVITE Application for use in the CATNETS Project is introduced and motivated. Furthermore an introduction to the catallactic middleware and Web Services Agreement (WS-Agreement) concepts is given as a basis for the future work. Requirements for the application of Cat-COVITE with in catallactic systems are analysed. Finally the integration of the Cat-COVITE application and the catallactic middleware is described. --Grid Computing

    Automated and dynamic multi-level negotiation framework applied to an efficient cloud provisioning

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    L’approvisionnement du Cloud est le processus de dĂ©ploiement et de gestion des applications sur les infrastructures publiques du Cloud. Il est de plus en plus utilisĂ© car il permet aux fournisseurs de services mĂ©tiers de se concentrer sur leurs activitĂ©s sans avoir Ă  gĂ©rer et Ă  investir dans l’infrastructure. Il comprend deux niveaux d’interaction : (1) entre les utilisateurs finaux et les fournisseurs de services pour l’approvisionnement des applications, et (2) entre les fournisseurs de services et les fournisseurs de ressources pour l’approvisionnement des ressources virtuelles. L’environnement Cloud est devenu un marchĂ© complexe oĂč tout fournisseur veut maximiser son profit monĂ©taire et oĂč les utilisateurs finaux recherchent les services les plus efficaces tout en minimisant leurs coĂ»ts. Avec la croissance de la concurrence dans le Cloud, les fournisseurs de services mĂ©tiers doivent assurer un approvisionnement efficace qui maximise la satisfaction de la clientĂšle et optimise leurs profits.Ainsi, les fournisseurs et les utilisateurs doivent ĂȘtre satisfaits en dĂ©pit de leurs besoins contradictoires. La nĂ©gociation est une solution prometteuse qui permet de rĂ©soudre les conflits en comblant le gap entre les capacitĂ©s des fournisseurs et les besoins des utilisateurs. Intuitivement, la nĂ©gociation automatique des contrats (SLA) permet d’aboutir Ă  un compromis qui satisfait les deux parties. Cependant, pour ĂȘtre efficace, la nĂ©gociation automatique doit considĂ©rer les propriĂ©tĂ©s de l’approvisionnement du Cloud et les complexitĂ©s liĂ©es Ă  la dynamicitĂ© (dynamicitĂ© de la disponibilitĂ© des ressources, dynamicitĂ© des prix). En fait ces critĂšres ont un impact important sur le succĂšs de la nĂ©gociation. Les principales contributions de cette thĂšse rĂ©pondant au dĂ©fi de la nĂ©gociation multi-niveau dans un contexte dynamique sont les suivantes: (1) Nous proposons un modĂšle de nĂ©gociateur gĂ©nĂ©rique qui considĂšre la nature dynamique de l’approvisionnement du Cloud et son impact potentiel sur les rĂ©sultats dĂ©cisionnels. Ensuite, nous construisons un cadre de nĂ©gociation multicouche fondĂ© sur ce modĂšle en l’instanciant entre les couches du Cloud. Le cadre comprend des agents nĂ©gociateurs en communication avec les modules en relation avec la qualitĂ© et le prix du service Ă  fournir (le planificateur, le moniteur, le prospecteur de marchĂ©). (2) Nous proposons une approche de nĂ©gociation bilatĂ©rale entre les utilisateurs finaux et les fournisseurs de service basĂ©e sur une approche d’approvisionnement existante. Les stratĂ©gies de nĂ©gociation sont basĂ©es sur la communication avec les modules d’approvisionnement (le planificateur et l’approvisionneur de machines virtuelles) afin d’optimiser les bĂ©nĂ©fices du fournisseur de service et de maximiser la satisfaction du client. (3) Afin de maximiser le nombre de clients, nous proposons une approche de nĂ©gociation adaptative et simultanĂ©e comme extension de la nĂ©gociation bilatĂ©rale. Nous proposons d’exploiter les changements de charge de travail en termes de disponibilitĂ© et de tarification des ressources afin de renĂ©gocier simultanĂ©ment avec plusieurs utilisateurs non acceptĂ©s (c’est-Ă -dire rejetĂ©s lors de la premiĂšre session de nĂ©gociation) avant la crĂ©ation du contrat SLA. (4) Afin de gĂ©rer toute violation possible de SLA, nous proposons une approche proactive de renĂ©gociation aprĂšs l’établissement de SLA. La renĂ©gociation est lancĂ©e lors de la dĂ©tection d’un Ă©vĂ©nement inattendu (par exemple, une panne de ressources) pendant le processus d’approvisionnement. Les stratĂ©gies de renĂ©gociation proposĂ©es visent Ă  minimiser la perte de profit pour le fournisseur et Ă  assurer la continuitĂ© du service pour le consommateur. Les approches proposĂ©es sont mises en Ɠuvre et les expĂ©riences prouvent les avantages d’ajouter la (re)nĂ©gociation au processus d’approvisionnement. L’utilisation de la (re)nĂ©gociation amĂ©liore le bĂ©nĂ©fice du fournisseur, le nombre de demandes acceptĂ©es et la satisfaction du client.Cloud provisioning is the process of deployment and management of applications on public cloud infrastructures. Cloud provisioning is used increasingly because it enables business providers to focus on their business without having to manage and invest in infrastructure. Cloud provisioning includes two levels of interaction: (1) between end-users and business providers for application provisioning; and (2) between business providers and resource providers for virtual resource provisioning.The cloud market nowadays is a complex environment where business providers need to maximize their monetary profit, and where end-users look for the most efficient services with the lowest prices. With the growth of competition in the cloud, business providers must ensure efficient provisioning that maximizes customer satisfaction and optimizes the providers’ profit. So, both providers and users must be satisfied in spite of their conflicting needs. Negotiation is an appealing solution to solve conflicts and bridge the gap between providers’ capabilities and users’ requirements. Intuitively, automated Service Level Agreement (SLA) negotiation helps in reaching an agreement that satisfies both parties. However, to be efficient, automated negotiation should consider the properties of cloud provisioning mainly the two interaction levels, and complexities related to dynamicity (e.g., dynamically-changing resource availability, dynamic pricing, dynamic market factors related to offers and demands), which greatly impact the success of the negotiation. The main contributions of this thesis tackling the challenge of multi-level negotiation in a dynamic context are as follows: (1) We propose a generic negotiator model that considers the dynamic nature of cloud provisioning and its potential impact on the decision-making outcome. Then, we build a multi-layer negotiation framework built upon that model by instantiating it among Cloud layers. The framework includes negotiator agents. These agents are in communication with the provisioning modules that have an impact on the quality and the price of the service to be provisioned (e.g, the scheduler, the monitor, the market prospector). (2) We propose a bilateral negotiation approach between end-users and business providers extending an existing provisioning approach. The proposed decision-making strategies for negotiation are based on communication with the provisioning modules (the scheduler and the VM provisioner) in order to optimize the business provider’s profit and maximize customer satisfaction. (3) In order to maximize the number of clients, we propose an adaptive and concurrent negotiation approach as an extension of the bilateral negotiation. We propose to harness the workload changes in terms of resource availability and pricing in order to renegotiate simultaneously with multiple non-accepted users (i.e., rejected during the first negotiation session) before the establishment of the SLA. (4) In order to handle any potential SLA violation, we propose a proactive renegotiation approach after SLA establishment. The renegotiation is launched upon detecting an unexpected event (e.g., resource failure) during the provisioning process. The proposed renegotiation decision-making strategies aim to minimize the loss in profit for the provider and to ensure the continuity of the service for the consumer. The proposed approaches are implemented and experiments prove the benefits of adding (re)negotiation to the provisioning process. The use of (re)negotiation improves the provider’s profit, the number of accepted requests, and the client’s satisfaction
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