Financial evaluation of SLA-based VM scheduling strategies for cloud federations

In recent years, cloud federations have gained popularity. Small as well as big cloud service providers (CSPs) join federations to reduce their costs, and also cloud management software like OpenStack offers support for federations. In a federation, individual CSPs cooperate such that they can move load to partner clouds at high peaks and possibly offer a wider range of services to their customers. Research in this area addresses the organization of such federations and strategies that CSPs can apply to increase their profit. In this paper we present the latest extensions to the FederatedCloudSim framework that considerably improve the simulation and evaluation of cloud federations. These simulations include service-level agreements (SLAs), scheduling and brokering strategies on various levels, the use of real-world cloud workload traces and a fine-grained financial evaluation using the new CloudAccount module. We use FederatedCloudSim to compare scheduling and brokering strategies on the federation level. Among them are new strategies that conduct auctions or consult a reliance factor to select an appropriate federated partner for running outsourced virtual machines. Our results show that choosing the right strategy has a significant impact on SLA compliance and revenue

Security in Cloud Computing: Evaluation and Integration

Au cours de la dernière décennie, le paradigme du Cloud Computing a révolutionné la manière dont nous percevons les services de la Technologie de l’Information (TI). Celui-ci nous a donné l’opportunité de répondre à la demande constamment croissante liée aux besoins informatiques des usagers en introduisant la notion d’externalisation des services et des données. Les consommateurs du Cloud ont généralement accès, sur demande, à un large éventail bien réparti d’infrastructures de TI offrant une pléthore de services. Ils sont à même de configurer dynamiquement les ressources du Cloud en fonction des exigences de leurs applications, sans toutefois devenir partie intégrante de l’infrastructure du Cloud. Cela leur permet d’atteindre un degré optimal d’utilisation des ressources tout en réduisant leurs coûts d’investissement en TI. Toutefois, la migration des services au Cloud intensifie malgré elle les menaces existantes à la sécurité des TI et en crée de nouvelles qui sont intrinsèques à l’architecture du Cloud Computing. C’est pourquoi il existe un réel besoin d’évaluation des risques liés à la sécurité du Cloud durant le procédé de la sélection et du déploiement des services. Au cours des dernières années, l’impact d’une efficace gestion de la satisfaction des besoins en sécurité des services a été pris avec un sérieux croissant de la part des fournisseurs et des consommateurs. Toutefois, l’intégration réussie de l’élément de sécurité dans les opérations de la gestion des ressources du Cloud ne requiert pas seulement une recherche méthodique, mais aussi une modélisation méticuleuse des exigences du Cloud en termes de sécurité. C’est en considérant ces facteurs que nous adressons dans cette thèse les défis liés à l’évaluation de la sécurité et à son intégration dans les environnements indépendants et interconnectés du Cloud Computing. D’une part, nous sommes motivés à offrir aux consommateurs du Cloud un ensemble de méthodes qui leur permettront d’optimiser la sécurité de leurs services et, d’autre part, nous offrons aux fournisseurs un éventail de stratégies qui leur permettront de mieux sécuriser leurs services d’hébergements du Cloud. L’originalité de cette thèse porte sur deux aspects : 1) la description innovatrice des exigences des applications du Cloud relativement à la sécurité ; et 2) la conception de modèles mathématiques rigoureux qui intègrent le facteur de sécurité dans les problèmes traditionnels du déploiement des applications, d’approvisionnement des ressources et de la gestion de la charge de travail au coeur des infrastructures actuelles du Cloud Computing. Le travail au sein de cette thèse est réalisé en trois phases.----------ABSTRACT: Over the past decade, the Cloud Computing paradigm has revolutionized the way we envision IT services. It has provided an opportunity to respond to the ever increasing computing needs of the users by introducing the notion of service and data outsourcing. Cloud consumers usually have online and on-demand access to a large and distributed IT infrastructure providing a plethora of services. They can dynamically configure and scale the Cloud resources according to the requirements of their applications without becoming part of the Cloud infrastructure, which allows them to reduce their IT investment cost and achieve optimal resource utilization. However, the migration of services to the Cloud increases the vulnerability to existing IT security threats and creates new ones that are intrinsic to the Cloud Computing architecture, thus the need for a thorough assessment of Cloud security risks during the process of service selection and deployment. Recently, the impact of effective management of service security satisfaction has been taken with greater seriousness by the Cloud Service Providers (CSP) and stakeholders. Nevertheless, the successful integration of the security element into the Cloud resource management operations does not only require methodical research, but also necessitates the meticulous modeling of the Cloud security requirements. To this end, we address throughout this thesis the challenges to security evaluation and integration in independent and interconnected Cloud Computing environments. We are interested in providing the Cloud consumers with a set of methods that allow them to optimize the security of their services and the CSPs with a set of strategies that enable them to provide security-aware Cloud-based service hosting. The originality of this thesis lies within two aspects: 1) the innovative description of the Cloud applications’ security requirements, which paved the way for an effective quantification and evaluation of the security of Cloud infrastructures; and 2) the design of rigorous mathematical models that integrate the security factor into the traditional problems of application deployment, resource provisioning, and workload management within current Cloud Computing infrastructures. The work in this thesis is carried out in three phases

A service broker for Intercloud computing

This thesis aims at assisting users in finding the most suitable Cloud resources taking into account their functional and non-functional SLA requirements. A key feature of the work is a Cloud service broker acting as mediator between consumers and Clouds. The research involves the implementation and evaluation of two SLA-aware match-making algorithms by use of a simulation environment. The work investigates also the optimal deployment of Multi-Cloud workflows on Intercloud environments

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

L’approvisionnement du Cloud est le processus de déploiement et de gestion des applications sur les infrastructures publiques du Cloud. Il est de plus en plus utilisé car il permet aux fournisseurs de services métiers de se concentrer sur leurs activités sans avoir à gérer et à 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 marché complexe où tout fournisseur veut maximiser son profit monétaire et où les utilisateurs finaux recherchent les services les plus efficaces tout en minimisant leurs coûts. Avec la croissance de la concurrence dans le Cloud, les fournisseurs de services métiers doivent assurer un approvisionnement efficace qui maximise la satisfaction de la clientèle et optimise leurs profits.Ainsi, les fournisseurs et les utilisateurs doivent être satisfaits en dépit de leurs besoins contradictoires. La négociation est une solution prometteuse qui permet de résoudre les conflits en comblant le gap entre les capacités des fournisseurs et les besoins des utilisateurs. Intuitivement, la négociation automatique des contrats (SLA) permet d’aboutir à un compromis qui satisfait les deux parties. Cependant, pour être efficace, la négociation automatique doit considérer les propriétés de l’approvisionnement du Cloud et les complexités liées à la dynamicité (dynamicité de la disponibilité des ressources, dynamicité des prix). En fait ces critères ont un impact important sur le succès de la négociation. Les principales contributions de cette thèse répondant au défi de la négociation multi-niveau dans un contexte dynamique sont les suivantes: (1) Nous proposons un modèle de négociateur générique qui considère la nature dynamique de l’approvisionnement du Cloud et son impact potentiel sur les résultats décisionnels. Ensuite, nous construisons un cadre de négociation multicouche fondé sur ce modèle en l’instanciant entre les couches du Cloud. Le cadre comprend des agents négociateurs en communication avec les modules en relation avec la qualité et le prix du service à fournir (le planificateur, le moniteur, le prospecteur de marché). (2) Nous proposons une approche de négociation bilatérale entre les utilisateurs finaux et les fournisseurs de service basée sur une approche d’approvisionnement existante. Les stratégies de négociation sont basées sur la communication avec les modules d’approvisionnement (le planificateur et l’approvisionneur de machines virtuelles) afin d’optimiser les bénéfices du fournisseur de service et de maximiser la satisfaction du client. (3) Afin de maximiser le nombre de clients, nous proposons une approche de négociation adaptative et simultanée comme extension de la négociation bilatérale. Nous proposons d’exploiter les changements de charge de travail en termes de disponibilité et de tarification des ressources afin de renégocier simultanément avec plusieurs utilisateurs non acceptés (c’est-à-dire rejetés lors de la première session de négociation) avant la création du contrat SLA. (4) Afin de gérer toute violation possible de SLA, nous proposons une approche proactive de renégociation après l’établissement de SLA. La renégociation est lancée lors de la détection d’un événement inattendu (par exemple, une panne de ressources) pendant le processus d’approvisionnement. Les stratégies de renégociation proposées visent à minimiser la perte de profit pour le fournisseur et à assurer la continuité du service pour le consommateur. Les approches proposées sont mises en œuvre et les expériences prouvent les avantages d’ajouter la (re)négociation au processus d’approvisionnement. L’utilisation de la (re)négociation améliore le bénéfice du fournisseur, le nombre de demandes acceptées 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

FLA-SLA aware cloud collation formation using fuzzy preference relationship multi-decision approach for federated cloud

Cloud Computing provides a solution to enterprise applications in resolving their services at all level of Software, Platform, and Infrastructure. The current demand of resources for large enterprises and their specific requirement to solve critical issues of services to their clients like avoiding resources contention, vendor lock-in problems and achieving high QoS (Quality of Service) made them move towards the federated cloud. The reliability of the cloud has become a challenge for cloud providers to provide resources at an instance request satisfying all SLA (Service Level Agreement) requirements for different consumer applications. To have better collation among cloud providers, FLA (Federated Level Agreement) are given much importance to get consensus in terms of various KPI’s (Key Performance Indicator’s) of the individual cloud providers. This paper proposes an FLA-SLA Aware Cloud Collation Formation algorithm (FS-ACCF) considering both FLA and SLA as major features affecting the collation formation to satisfy consumer request instantly. In FS-ACCF algorithm, fuzzy preference relationship multi-decision approach was used to validate the preferences among cloud providers for forming collation and gaining maximum profit. Finally, the results of FS-ACCF were compared with S-ACCF (SLA Aware Collation Formation) algorithm for 6 to 10 consecutive requests of cloud consumers with varied VM configurations for different SLA parameters like response time, process time and availability

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

L’approvisionnement du Cloud est le processus de déploiement et de gestion des applications sur les infrastructures publiques du Cloud. Il est de plus en plus utilisé car il permet aux fournisseurs de services métiers de se concentrer sur leurs activités sans avoir à gérer et à 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 marché complexe où tout fournisseur veut maximiser son profit monétaire et où les utilisateurs finaux recherchent les services les plus efficaces tout en minimisant leurs coûts. Avec la croissance de la concurrence dans le Cloud, les fournisseurs de services métiers doivent assurer un approvisionnement efficace qui maximise la satisfaction de la clientèle et optimise leurs profits.Ainsi, les fournisseurs et les utilisateurs doivent être satisfaits en dépit de leurs besoins contradictoires. La négociation est une solution prometteuse qui permet de résoudre les conflits en comblant le gap entre les capacités des fournisseurs et les besoins des utilisateurs. Intuitivement, la négociation automatique des contrats (SLA) permet d’aboutir à un compromis qui satisfait les deux parties. Cependant, pour être efficace, la négociation automatique doit considérer les propriétés de l’approvisionnement du Cloud et les complexités liées à la dynamicité (dynamicité de la disponibilité des ressources, dynamicité des prix). En fait ces critères ont un impact important sur le succès de la négociation. Les principales contributions de cette thèse répondant au défi de la négociation multi-niveau dans un contexte dynamique sont les suivantes: (1) Nous proposons un modèle de négociateur générique qui considère la nature dynamique de l’approvisionnement du Cloud et son impact potentiel sur les résultats décisionnels. Ensuite, nous construisons un cadre de négociation multicouche fondé sur ce modèle en l’instanciant entre les couches du Cloud. Le cadre comprend des agents négociateurs en communication avec les modules en relation avec la qualité et le prix du service à fournir (le planificateur, le moniteur, le prospecteur de marché). (2) Nous proposons une approche de négociation bilatérale entre les utilisateurs finaux et les fournisseurs de service basée sur une approche d’approvisionnement existante. Les stratégies de négociation sont basées sur la communication avec les modules d’approvisionnement (le planificateur et l’approvisionneur de machines virtuelles) afin d’optimiser les bénéfices du fournisseur de service et de maximiser la satisfaction du client. (3) Afin de maximiser le nombre de clients, nous proposons une approche de négociation adaptative et simultanée comme extension de la négociation bilatérale. Nous proposons d’exploiter les changements de charge de travail en termes de disponibilité et de tarification des ressources afin de renégocier simultanément avec plusieurs utilisateurs non acceptés (c’est-à-dire rejetés lors de la première session de négociation) avant la création du contrat SLA. (4) Afin de gérer toute violation possible de SLA, nous proposons une approche proactive de renégociation après l’établissement de SLA. La renégociation est lancée lors de la détection d’un événement inattendu (par exemple, une panne de ressources) pendant le processus d’approvisionnement. Les stratégies de renégociation proposées visent à minimiser la perte de profit pour le fournisseur et à assurer la continuité du service pour le consommateur. Les approches proposées sont mises en œuvre et les expériences prouvent les avantages d’ajouter la (re)négociation au processus d’approvisionnement. L’utilisation de la (re)négociation améliore le bénéfice du fournisseur, le nombre de demandes acceptées 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

A Survey of Resource Management Challenges in Multi-cloud Environment: Taxonomy and Empirical Analysis

Cloud computing has seen a great deal of interest by researchers and industrial firms since its first coined. Different perspectives and research problems, such as energy efficiency, security and threats, to name but a few, have been dealt with and addressed from cloud computing perspective. However, cloud computing environment still encounters a major challenge of how to allocate and manage computational resources efficiently. Furthermore, due to the different architectures and cloud computing networks and models used (i.e., federated clouds, VM migrations, cloud brokerage), the complexity of resource management in the cloud has been increased dramatically. Cloud providers and service consumers have the cloud brokers working as the intermediaries between them, and the confusion among the cloud computing parties (consumers, brokers, data centres and service providers) on who is responsible for managing the request of cloud resources is a key issue. In a traditional scenario, upon renting the various cloud resources from the providers, the cloud brokers engage in subletting and managing these resources to the service consumers. However, providers’ usually deal with many brokers, and vice versa, and any dispute of any kind between the providers and the brokers will lead to service unavailability, in which the consumer is the only victim. Therefore, managing cloud resources and services still needs a lot of attention and effort. This paper expresses the survey on the systems of the cloud brokerage resource management issues in multi-cloud environments

From geographically dispersed data centers towards hierarchical edge computing

Internet scale data centers are generally dispersed in different geographical regions. While the main goal of deploying the geographically dispersed data centers is to provide redundancy, scalability and high availability, the geographic dispersity provides another opportunity for efficient employment of global resources, e.g., utilizing price-diversity in electricity markets or utilizing locational diversity in renewable power generation. In other words, an efficient approach for geographical load balancing (GLB) across geo-dispersed data centers not only can maximize the utilization of green energy but also can minimize the cost of electricity. However, due to the different costs and disparate environmental impacts of the renewable energy and brown energy, such a GLB approach should tap on the merits of the separation of green energy utilization maximization and brown energy cost minimization problems. To this end, the notion of green workload and green service rate, versus brown workload and brown service rate, respectively, to facilitate the separation of green energy utilization maximization and brown energy cost minimization problems is proposed. In particular, a new optimization framework to maximize the profit of running geographically dispersed data centers based on the accuracy of the G/D/1 queueing model, and taking into consideration of multiple classes of service with individual service level agreement deadline for each type of service is developed. A new information flow graph based model for geo-dispersed data centers is also developed, and based on the developed model, the achievable tradeoff between total and brown power consumption is characterized. Recently, the paradigm of edge computing has been introduced to push the computing resources away from the data centers to the edge of the network, thereby reducing the communication bandwidth requirement between the sources of data and the data centers. However, it is still desirable to investigate how and where at the edge of the network the computation resources should be provisioned. To this end, a hierarchical Mobile Edge Computing (MEC) architecture in accordance with the principles of LTE Advanced backhaul network is proposed and an auction-based profit maximization approach which effectively facilitates the resource allocation to the subscribers of the MEC network is designed. A hierarchical capacity provisioning framework for MEC that optimally budgets computing capacities at different hierarchical edge computing levels is also designed. The proposed scheme can efficiently handle the peak loads at the access point locations while coping with the resource poverty at the edge. Moreover, the code partitioning problem is extended to a scheduling problem over time and the hierarchical mobile edge network, and accordingly, a new technique that leads to the optimal code partitioning in a reasonable time even for large-sized call trees is proposed. Finally, a novel NOMA augmented edge computing model that captures the gains of uplink NOMA in MEC users\u27 energy consumption is proposed