Routing-as-a-Service (RaaS): A Framework for Tenant-Directed Route Control in Data Center

In a multi-tenant data center environment, the current paradigm for route control customization involves a labor-intensive ticketing process where tenants submit route control requests to the landlord. This results in tight coupling between tenants and the landlord, extensive human resource deployment, and long ticket resolution time. We propose Routing-as-a-Service (RaaS), a framework for tenant-directed route control in data centers. We show that RaaS-based implementation provides a route control platform where multiple tenants can perform route control independently with little administrative involvement, and the landlord can set the overall network policies. RaaS-based solutions can run on commercial off-the-shelf (COTS) hardware and leverage existing technologies, so it can be implemented in existing networks without major infrastructural overhaul. We present the design of RaaS, introduce its components, and evaluate a prototype based on RaaS

Self adaptive controlling mechanism to optimize the efficiency of network implementing Routing –as-a-Service

In today's Internet, clients can pick their neighborhood Internet specialist co-ops (ISPs), yet once their bundles have entered the system, they have little control over the general courses their parcels take. It gives a client the capacity to pick between supplier level courses, the capability of encouraging ISP rivalry to offer upgraded benefit and enhancing end-to-end execution and unwavering quality. Its gives client the capacity to pick the succession of suppliers his parcels take. Another system is intended to present the parts, and assess a model in light of RaaS (Routing-as-a-Service). The new structure addresses a wide scope of issues, including commonsense supplier pay, versatile course revelation, effective course representation, quick course bomb over, and security. It underpins client decision without running a worldwide connection state directing convention. It breaks a conclusion to-end course into a sender part and a recipient part and gives the client to give include according to the necessity. A client can indicate a course with just a source and a goal address, and switch courses by exchanging input. The structure is assessed utilizing a mix of system estimation, reproduction, and investigation

Routing-as-a-Service (RaaS): A framework for tenant-directed route control in data center

In a multi-tenant data center environment, the current paradigm for route control customization involves a labor-intensive ticketing process where tenants submit route control requests to the landlord. This results in tight coupling between tenants and the landlord, extensive human resource deployment, and long ticket resolution time. We propose Routing-as-a-Service (RaaS), a framework for tenant-directed route control in data centers. We show that RaaS-based implementation provides a route control platform where multiple tenants can perform route control independently with little administrative involvement, and the landlord can set the overall network policies. RaaS-based solutions can run on commercial off-the-shelf (COTS) hardware and leverage existing technologies, so it can be implemented in existing networks without major infrastructural overhaul. We present the design of RaaS, introduce its components, and evaluate a prototype based on RaaS

Alocação de Máquinas Virtuais em Ambientes de Computação em Nuvem Baseada em Requisitos de Service Level Agreement

A computação em nuvem teve um avanço considerável nos últimos anos, trazendo grandes benefícios incluindo escalabilidade, flexibilidade, acessibilidade global, melhor utilização de recursos e redução de custos, entre outros. Apesar de todos os benefícios, esta adesão e crescimento trás consigo grandes desafios como otimização do uso de recursos computacionais, redução de custos, garantia da qualidade de serviço (Quality of Service (QoS)), segurança, etc. As garantias da qualidade de serviço são estabelecidas através de Service Level Agreements (SLAs), que são contratos estabelecidos entre o cliente e o fornecedor do serviço de computação em nuvem, visando especificar de forma mensurável as metas de nível de serviço a serem cumpridas, além dos papéis e responsabilidades das partes envolvidas. Este trabalho apresenta um estudo sobre cumprimento de SLAs por algoritmos de alocação de máquinas virtuais em ambientes de computação em nuvem. O trabalho tem em consideração métricas como disponibilidade, custo, tempo de conclusão de uma aplicação (task completion time) e nível de tolerância a faltas, avaliando o cumprimento de tais métricas em diferentes cenários. O estudo é realizado utilizando o framework CloudSim Plus para modelação e execução de simulações de computação em nuvem. São introduzidos dois módulos no framework visando: (i) especificação de SLAs e templates de máquinas virtuais em formato JavaScript Object Notation (JSON), seguindo padrões do Amazon Elastic Compute Cloud (Amazon EC2); (ii) injeção de faltas aleatórias, permitindo avaliar como os SLAs são afetados perante o surgimento de faltas nos servidores. Por fim, o trabalho apresenta uma proposta para automação da criação e alocação de máquinas virtuais, visando cumprir os SLAs e libertar o cliente da necessidade de especificar a quantidade mínima de máquinas virtuais para atendimento dos níveis de serviço exigidos. Mesmo com todo o nível de automação que os fornecedores de computação em nuvem possam oferecer, os resultados obtidos mostram que é possível melhorar a automação destes serviços, reduzindo a necessidade de intervenção do cliente e as violações de SLA devido a uma inadequada configuração de máquinas virtuais realizada pelo cliente.Cloud computing has made considerable progress in recent years, bringing great benefits including scalability, flexibility, global accessibility, improved resource utilization and cost savings, among others. Despite all the benefits, this adhesion and growth carries with it great challenges such as optimization of the use of computational resources, reduction of costs, Quality of Service (QoS) assurance, security, etc. Guarantees are provided through Service Level Agreements (SLAs), which are agreements between the customer and the cloud computing service provider to measurably specify the service level goals to be fulfilled, as well as the roles and responsibilities of the parties involved. This work presents a study on compliance with service level agreements by algorithms for allocating virtual machines in cloud computing environments. The work takes into account metrics such as availability, cost, task completion time and level of fault tolerance, evaluating the compliance of such metrics in different scenarios. The study is conducted using the CloudSim Plus framework for modeling and running cloud computing simulations. Two modules are introduced in the framework about: (i) specification of SLAs and virtual machine templates in JSON format, following Amazon Elastic Compute Cloud (Amazon EC2) standards; (ii) injection of random faults, allowing to evaluate how the SLAs are affected by the occurrence of faults in servers. Finally, this work presents a proposal for automation of the creation and allocation of virtual machines, aiming to comply with the SLAs and free the client from the need to specify the minimum number of virtual machines to meet the required service levels. Even with all the automation level provided by cloud service providers, the obtained results show it is possible to further improve the automation of these services by reducing the need for customer intervention and SLA violations due to an inadequate configuration of virtual machines performed by the client

Reducing the Cost of Operating a Datacenter Network

Datacenters are a significant capital expense for many enterprises. Yet, they are difficult to manage and are hard to design and maintain. The initial design of a datacenter network tends to follow vendor guidelines, but subsequent upgrades and expansions to it are mostly ad hoc, with equipment being upgraded piecemeal after its amortization period runs out and equipment acquisition is tied to budget cycles rather than changes in workload. These networks are also brittle and inflexible. They tend to be manually managed, and cannot perform dynamic traffic engineering. The high-level goal of this dissertation is to reduce the total cost of owning a datacenter by improving its network. To achieve this, we make the following contributions. First, we develop an automated, theoretically well-founded approach to planning cost-effective datacenter upgrades and expansions. Second, we propose a scalable traffic management framework for datacenter networks. Together, we show that these contributions can significantly reduce the cost of operating a datacenter network. To design cost-effective network topologies, especially as the network expands over time, updated equipment must coexist with legacy equipment, which makes the network heterogeneous. However, heterogeneous high-performance network designs are not well understood. Our first step, therefore, is to develop the theory of heterogeneous Clos topologies. Using our theory, we propose an optimization framework, called LEGUP, which designs a heterogeneous Clos network to implement in a new or legacy datacenter. Although effective, LEGUP imposes a certain amount of structure on the network. To deal with situations when this is infeasible, our second contribution is a framework, called REWIRE, which using optimization to design unstructured DCN topologies. Our results indicate that these unstructured topologies have up to 100-500\% more bisection bandwidth than a fat-tree for the same dollar cost. Our third contribution is two frameworks for datacenter network traffic engineering. Because of the multiplicity of end-to-end paths in DCN fabrics, such as Clos networks and the topologies designed by REWIRE, careful traffic engineering is needed to maximize throughput. This requires timely detection of elephant flows---flows that carry large amount of data---and management of those flows. Previously proposed approaches incur high monitoring overheads, consume significant switch resources, or have long detection times. We make two proposals for elephant flow detection. First, in the Mahout framework, we suggest that such flows be detected by observing the end hosts' socket buffers, which provide efficient visibility of flow behavior. Second, in the DevoFlow framework, we add efficient stats-collection mechanisms to network switches. Using simulations and experiments, we show that these frameworks reduce traffic engineering overheads by at least an order of magnitude while still providing near-optimal performance

Internet of Things From Hype to Reality

The Internet of Things (IoT) has gained significant mindshare, let alone attention, in academia and the industry especially over the past few years. The reasons behind this interest are the potential capabilities that IoT promises to offer. On the personal level, it paints a picture of a future world where all the things in our ambient environment are connected to the Internet and seamlessly communicate with each other to operate intelligently. The ultimate goal is to enable objects around us to efficiently sense our surroundings, inexpensively communicate, and ultimately create a better environment for us: one where everyday objects act based on what we need and like without explicit instructions