Taming Energy Costs of Large Enterprise Systems Through Adaptive Provisioning

One of the most pressing concerns in modern datacenter management is the rising cost of operation. Therefore, reducing variable expense, such as energy cost, has become a number one priority. However, reducing energy cost in large distributed enterprise system is an open research topic. These systems are commonly subjected to highly volatile workload processes and characterized by complex performance dependencies. This paper explicitly addresses this challenge and presents a novel approach to Taming Energy Costs of Larger Enterprise Systems (Tecless). Our adaptive provisioning methodology combines a low-level technical perspective on distributed systems with a high-level treatment of workload processes. More concretely, Tecless fuses an empirical bottleneck detection model with a statistical workload prediction model. Our methodology forecasts the system load online, which enables on-demand infrastructure adaption while continuously guaranteeing quality of service. In our analysis we show that the prediction of future workload allows adaptive provisioning with a power saving potential of up 25 percent of the total energy cost

Multi-capacity bin packing with dependent items and its application to the packing of brokered workloads in virtualized environments

Providing resource allocation with performance predictability guarantees is increasingly important in cloud platforms, especially for data-intensive applications, in which performance depends greatly on the available rates of data transfer between the various computing/storage hosts underlying the virtualized resources assigned to the application. Existing resource allocation solutions either assume that applications manage their data transfer between their virtualized resources, or that cloud providers manage their internal networking resources. With the increased prevalence of brokerage services in cloud platforms, there is a need for resource allocation solutions that provides predictability guarantees in settings, in which neither application scheduling nor cloud provider resources can be managed/controlled by the broker. This paper addresses this problem, as we define the Network-Constrained Packing (NCP) problem of finding the optimal mapping of brokered resources to applications with guaranteed performance predictability. We prove that NCP is NP-hard, and we define two special instances of the problem, for which exact solutions can be found efficiently. We develop a greedy heuristic to solve the general instance of the NCP problem , and we evaluate its efficiency using simulations on various application workloads, and network models.This work was done while author was at Boston University. It was partially supported by NSF CISE awards #1430145, #1414119, #1239021 and #1012798. (1430145 - NSF CISE; 1414119 - NSF CISE; 1239021 - NSF CISE; 1012798 - NSF CISE

Network-constrained packing of brokered workloads in virtualized environments

Providing resource allocation with performance predictability guarantees is increasingly important in cloud platforms, especially for data-intensive applications, in which performance depends greatly on the available rates of data transfer between the various computing/storage hosts underlying the virtualized resources assigned to the application. Existing resource allocation solutions either assume that applications manage their data transfer between their virtualized resources, or that cloud providers manage their internal networking resources.With the increased prevalence of brokerage services in cloud platforms, there is a need for resource allocation solutions that provides predictability guarantees in settings, in which neither application scheduling nor cloud provider resources can be managed/controlled by the broker. This paper addresses this problem, as we define the Network-Constrained Packing (NCP)problem of finding the optimal mapping of brokered resources to applications with guaranteed performance predictability. We prove that NCP is NP-hard, and we define two special instances of the problem, for which exact solutions can be found efficiently. We develop a greedy heuristic to solve the general instance of the NCP problem, and we evaluate its efficiency using simulations on various application workloads, and network models.This work is supported by NSF CISE CNS Award #1347522, # 1239021, # 1012798

Achieving Adaptation Through Live Virtual Machine Migration in Two-Tier Clouds

This thesis presents a model-driven approach for application deployment and management in two-tier heterogeneous cloud environments. For application deployment, we introduce the architecture, the services and the domain specific language that abstract common features of multi-cloud deployments. By leveraging the architecture and the language, application deployers author a deployment model that captures the high-level structure of the application. The deployment model is then translated into deployment workflows on specific clouds. As a use case, we introduce a live VM migration framework that maintains the application quality of services through VM migrations across two tier-clouds. The proposed framework can monitor the performance of the applications and their underlying infrastructure and plan and executes VM migrations to eliminate hotspots in a datacenter. We evaluate both the application deployment architecture and the live migration on public clouds

Orchestrating datacenters and networks to facilitate the telecom cloud

In the Internet of services, information technology (IT) infrastructure providers play a critical role in making the services accessible to end-users. IT infrastructure providers host platforms and services in their datacenters (DCs). The cloud initiative has been accompanied by the introduction of new computing paradigms, such as Infrastructure as a Service (IaaS) and Software as a Service (SaaS), which have dramatically reduced the time and costs required to develop and deploy a service. However, transport networks become crucial to make services accessible to the user and to operate DCs. Transport networks are currently configured with big static fat pipes based on capacity over-provisioning aiming at guaranteeing traffic demand and other parameters committed in Service Level Agreement (SLA) contracts. Notwithstanding, such over-dimensioning adds high operational costs for DC operators and service providers. Therefore, new mechanisms to provide reconfiguration and adaptability of the transport network to reduce the amount of over-provisioned bandwidth are required. Although cloud-ready transport network architecture was introduced to handle the dynamic cloud and network interaction and Elastic Optical Networks (EONs) can facilitate elastic network operations, orchestration between the cloud and the interconnection network is eventually required to coordinate resources in both strata in a coherent manner. In addition, the explosion of Internet Protocol (IP)-based services requiring not only dynamic cloud and network interaction, but also additional service-specific SLA parameters and the expected benefits of Network Functions Virtualization (NFV), open the opportunity to telecom operators to exploit that cloud-ready transport network and their current infrastructure, to efficiently satisfy network requirements from the services. In the telecom cloud, a pay-per-use model can be offered to support services requiring resources from the transport network and its infrastructure. In this thesis, we study connectivity requirements from representative cloud-based services and explore connectivity models, architectures and orchestration schemes to satisfy them aiming at facilitating the telecom cloud. The main objective of this thesis is demonstrating, by means of analytical models and simulation, the viability of orchestrating DCs and networks to facilitate the telecom cloud. To achieve the main goal we first study the connectivity requirements for DC interconnection and services on a number of scenarios that require connectivity from the transport network. Specifically, we focus on studying DC federations, live-TV distribution, and 5G mobile networks. Next, we study different connectivity schemes, algorithms, and architectures aiming at satisfying those connectivity requirements. In particular, we study polling-based models for dynamic inter-DC connectivity and propose a novel notification-based connectivity scheme where inter-DC connectivity can be delegated to the network operator. Additionally, we explore virtual network topology provisioning models to support services that require service-specific SLA parameters on the telecom cloud. Finally, we focus on studying DC and network orchestration to fulfill simultaneously SLA contracts for a set of customers requiring connectivity from the transport network.En la Internet de los servicios, los proveedores de recursos relacionados con tecnologías de la información juegan un papel crítico haciéndolos accesibles a los usuarios como servicios. Dichos proveedores, hospedan plataformas y servicios en centros de datos. La oferta plataformas y servicios en la nube ha introducido nuevos paradigmas de computación tales como ofrecer la infraestructura como servicio, conocido como IaaS de sus siglas en inglés, y el software como servicio, SaaS. La disponibilidad de recursos en la nube, ha contribuido a la reducción de tiempos y costes para desarrollar y desplegar un servicio. Sin embargo, para permitir el acceso de los usuarios a los servicios así como para operar los centros de datos, las redes de transporte resultan imprescindibles. Actualmente, las redes de transporte están configuradas con conexiones estáticas y su capacidad sobredimensionada para garantizar la demanda de tráfico así como los distintos parámetros relacionados con el nivel de servicio acordado. No obstante, debido a que el exceso de capacidad en las conexiones se traduce en un elevado coste tanto para los operadores de los centros de datos como para los proveedores de servicios, son necesarios nuevos mecanismos que permitan adaptar y reconfigurar la red de forma eficiente de acuerdo a las nuevas necesidades de los servicios a los que dan soporte. A pesar de la introducción de arquitecturas que permiten la gestión de redes de transporte y su interacción con los servicios en la nube de forma dinámica, y de la irrupción de las redes ópticas elásticas, la orquestación entre la nube y la red es necesaria para coordinar de forma coherente los recursos en los distintos estratos. Además, la explosión de servicios basados el Protocolo de Internet, IP, que requieren tanto interacción dinámica con la red como parámetros particulares en los niveles de servicio además de los habituales, así como los beneficios que se esperan de la virtualización de funciones de red, representan una oportunidad para los operadores de red para explotar sus recursos y su infraestructura. La nube de operador permite ofrecer recursos del operador de red a los servicios, de forma similar a un sistema basado en pago por uso. En esta Tesis, se estudian requisitos de conectividad de servicios basados en la nube y se exploran modelos de conectividad, arquitecturas y modelos de orquestación que contribuyan a la realización de la nube de operador. El objetivo principal de esta Tesis es demostrar la viabilidad de la orquestación de centros de datos y redes para facilitar la nube de operador, mediante modelos analíticos y simulaciones. Con el fin de cumplir dicho objetivo, primero estudiamos los requisitos de conectividad para la interconexión de centros de datos y servicios en distintos escenarios que requieren conectividad en la red de transporte. En particular, nos centramos en el estudio de escenarios basados en federaciones de centros de datos, distribución de televisión en directo y la evolución de las redes móviles hacia 5G. A continuación, estudiamos distintos modelos de conectividad, algoritmos y arquitecturas para satisfacer los requisitos de conectividad. Estudiamos modelos de conectividad basados en sondeos para la interconexión de centros de datos y proponemos un modelo basado en notificaciones donde la gestión de la conectividad entre centros de datos se delega al operador de red. Estudiamos la provisión de redes virtuales para soportar en la nube de operador servicios que requieren parámetros específicos en los acuerdos de nivel de servicio además de los habituales. Finalmente, nos centramos en el estudio de la orquestación de centros de datos y redes con el objetivo de satisfacer de forma simultánea requisitos para distintos servicios.Postprint (published version

Analyzing Data-center Application Performance Via Constraint-based Models

Hyperscale Data Centers (HDCs) are the largest distributed computing machines ever constructed. They serve as the backbone for many popular applications, such as YouTube, Netflix, Meta, and Airbnb, which involve millions of users and generate billions in revenue. As the networking infrastructure plays a pivotal role in determining the performance of HDC applications, understanding and optimizing their networking performance is critical. This thesis proposes and evaluates a constraint-based approach to characterize the networking performance of HDC applications. Through extensive evaluations conducted in both controlled settings and real-world case studies within a production HDC, I demonstrated the effectiveness of the constraint-based approach in handling the immense volume of performance data in HDCs, achieving tremendous dimension reduction, and providing very useful interpretability.Doctor of Philosoph