Thomas Voith

Network-aware service placement in a distributed cloud environment

We consider a system of compute and storage resources geographically distributed over a large number of locations connected via a wide-area network. By distributing the resources, latency to users can be decreased, bandwidth costs reduced and availablility increased. The challenge is to distribute services with varying characteristics among the data centers optimally. Some services are very latency sensitive, others need vast amounts of storage, and yet others are computationally complex but do not require hard deadlines on execution. We propose efficient algorithms for the placement of services to get the maximum benefit from a distributed cloud systems. The algorithms need input on the status of the network, compute resources and data resources, which are matched to application requirements. This demonstration shows how a network-aware cloud can combine all three resource types - computation, storage, and network connectivity - in distributed cloud environments. Our dynamic service placement algorithm monitors the network and data center resources in real-time. Our prototype uses the information gathered to place or migrate services to provide the best user experience for a service.

A Real-time Service Oriented Infrastructure

The advancements in distributed computing have driven the emergence of service-based infrastructures that allow for on-demand provision of ICT assets. Taking into consideration the complexity of distributed environments, significant challenges exist in providing and managing the offered on-demand resources with the required level of Quality of Service (QoS), especially for real-time interactive and streaming applications. In this paper we propose an approach for providing real-time QoS guarantees by enhancing service oriented infrastructures with coherent and consistent real-time attributes at various levels (application, network, storage, processing). The approach considers the full lifecycle of service-based systems including service engineering, Service Level Agreement (SLA) negotiation and management, service provisioning and monitoring. QoS parameters at application, platform and infrastructure levels are given specific attention as the basis for provisioning policies in the context of temporal constraints

Network virtualization: The missing piece

Current service platforms or frameworks, e.g., cloud solutions, do not take the infrastructure, necessary for the execution of the service, sufficiently into consideration. They take resources like network connectivity for granted and do not provide an integrated networking approach considering quality of service (QoS) or other real-time aspects of the message exchange between possibly thousands of components. This paper presents the concept of a fully managed network virtualization framework to provide the required connectivity between components within a virtualized service platform respecting all service requirements, e.g. as expressed by interactive real-time services, on transport layer.

Virtualised e-Learning with real-time guarantees on the IRMOS platform

In this paper we focus on how Quality of Service guarantees are provided to virtualised applications in the Cloud Computing infrastructure that is being developed in the context of the IRMOS1 European Project. Provisioning of proper timeliness guarantees to distributed real-time applications involves the careful use of real-time scheduling mechanisms at the virtual-machine hypervisor level, of QoS-aware networking protocols and of proper design methodologies and tools for stochastic modelling of the application. The paper focuses on how we applied these techniques to a case-study involving a real e-Learning mobile content delivery application that has been integrated into the IRMOS platform and its achieved performance.

Quality of service provisioning for distributed data center inter-connectivity enabled by network virtualization

Todays service platform or Cloud service models, such as Infrastructure-as-a-Service (IaaS), enable customers to deploy and execute applications on an on-demand available infrastructure. Such platforms reduce operational expenses for the service provider and lower the entry barrier for small and medium enterprises. However, current commercial solutions do not provide sufficient quality of service (QoS) guarantees for some applications. For example, they do not support various interactive real-time applications. In this paper, we introduce a way overcome these current Cloud service limitations. We show how to provide and guarantee quality of service requirements for resource networks within an IaaS framework. Our work has focused on methods for network resource management and flow control as well as QoS models. We have developed a framework that enables QoS support for real-time services executing within an IaaS environment.

Virtualised e-Learning on the IRMOS real-time Cloud

This paper presents the real-time virtualised Cloud infrastructure that was developed in the context of the IRMOS European Project. The paper shows how different concepts, such as real-time scheduling, QoS-aware network protocols, and methodologies for stochastic modelling and run-time provisioning were practically combined to provide strong performance guarantees to soft real-time interactive applications in a virtualised environment. The efficiency of the IRMOS Cloud is demonstrated by two real interactive e-Learning applications, an e-Learning mobile content delivery application and a Virtual World e-Learning application.

Monitoring and abstraction for networked clouds

We consider the problem of building tightly coupled network and cloud management systems for “carrier clouds” based on an abstract view of the dynamic network state. Optimized resource placement in distributed clouds requires information about the internal network topology and state, in addition to other data center information. We present a distributed cloud system that accesses such data in an abstract way using the Application Layer Traffic Optimization (ALTO) protocol. The demonstration addresses how dynamic networking information can be gathered, how it can be abstracted and coupled with other data such as data center load, how it can be exposed, and how it can be integrated into a cloud management system. Our distributed cloud solution demonstrates that ALTO is well-suited for infrastructure-to-application information exposure.

Dynamic VPN Optimization by ALTO Guidance

Virtual Private Networks (VPNs) are a key component of cloud computing systems, since they provide isolated connectivity between geographically separated users. The elasticity in cloud computing and new usage patterns such as cloud bursting require VPNs to be more dynamic than traditional solutions used by network service providers. Managing and optimizing the topology of VPNs requires insight into the underlying wide area network topology and benefits from new network interfaces currently discussed for Software Defined Networks (SDN). This paper presents the use of the Application-Layer Traffic Optimization (ALTO) protocol for VPN optimization. ALTO is a standardized solution for exposure of abstract topology information to a variety of applications, including cloud management systems. We demonstrate the use of ALTO in determining how to scale-out a VPN on demand. We also present a prototype of an ALTO-based dynamic VPN management, which is based on a carrier-grade network management system. Our results show that ALTO is a powerful topology abstraction approach that enables informed VPN scale-out decisions by applications.

The network aspect of Infrastructure-as-a-Service

Current service platform offers that provide Infrastructure as a Service (IaaS) do not adequately meet the requirements expressed by interactive real-time services. Online application response times can not yet be enforced in virtual infrastructures without service level objectives (SLOs) that meet virtual machine interconnection constraints. This paper presents a framework spanning from the service description model over the IaaS platform interface for service level agreement (SLA) negotiation to the management of virtual network resources in an IaaS environment.

Network-Aware Instance Scheduling in OpenStack

Cloud computing systems require a placement logic that decides where to allocate resources. In state-of-the-art platforms such as OpenStack, this scheduler takes into account multiple constraints when starting a new instance, including in particular the required computational and memory resources. However, this scheduling mechanism typically neither considers network requirements of Virtual Machines nor the networking resources that are actually available. In this paper we present an extension of the OpenStack scheduler that enables a network-aware placement of instances by taking into account bandwidth constraints to and from nodes. Our solution keeps track of host-local network resource allocation, and it can be combined with bandwidth enforcement mechanisms such as rate limiting. We present a prototype that requires only very few changes in the OpenStack open source software. Testbed measurement results demonstrate the benefit of our solution compared to the OpenStack default approach.