Service-Centric Networking for Distributed Heterogeneous Clouds

Abstract

Abstract-Optimal placement and selection of service instances in a distributed heterogeneous cloud is a complex trade-off between application requirements and resource capabilities that requires detailed information on the service, infrastructure constraints and the underlying IP network. In this article we first posit that from an analysis of a snapshot of today's centralized and regional data centre infrastructure, there is a sufficient number of candidate sites for deploying many services while meeting latency and bandwidth constraints. We then provide quantitative arguments why both network and hardware performance needs to be taken into account when selecting candidate sites to deploy a given service. Lastly, we propose a novel architectural solution for service-centric networking. The resulting system exploits the availability of fine-grained execution nodes across the Internet and uses knowledge of available computational and network resources for deploying, replicating and selecting instances to optimize Quality of Experience for a wide range of services. I. INTERACTIVE DEMANDING SERVICES IN THE CLOUDThere is vast diversity in cloud-hosted services today, ranging from mobile back-ends, over virtualized set-top boxes and gaming consoles to real-time services providing decision and control support for self-driving cars. These recent cloud services require a crisp experience and/or realtime processing of high data rate streams. High network delays and low throughput to a relatively small number of centralised remote data centres (DCs) may have a serious impact on the quality of experience (QoE). For instance, 30% of the US population has a too high latency to one of Amazon's EC2 DCs for cloud-based gaming [1]. Deploying such applications in distributed execution platforms closer to the users reduces network delays and is also the preferred approach for many data intensive applications. Shifting all the data to a centralised service could overwhelm the network and it is better to bring the computation logic closer to data sources and users at the network edge. As of today, Internet Service Providers (ISPs) already deploy Content Delivery Network (CDN) proxy servers in their network to save on transit costs and improve the quality of service for their customers [2].Service developers are thus confronted with the twofold challenge of service instance placement and selection. The central problem in service placement is to determine the cost-optimal set of geo-distributed datacenters where to deploy an instance, and to configure the appropriate scaling policies in each of these datacenters to adequately cope with the expected demand. These distributed nodes have heterogeneous hardware, as they are owned by different entities or deployed at different moments in time. Service instance selection refers to the anycast-style resolution of a service identifier to the network endpoint of the best replica, taking into account service availability, network metrics and the location of the requesting user. Service placemen...

Application of Quality of Experience in Networked Services: Review, Trend & Perspectives

“…fixed or wireless, network conditions such as available bandwidth, packet loss, terminal capabilities, CPU power, resolutions, codec and SLA with network or service operator, specific to service or application analysis of subjective and objective QoE for accuracy and service provision according to SLA (Moreno-Vozmediano et al 2017). The cloud and network based framework development for controlling QoE in the runtime environment and QoE optimization is also essential (Simoens et al 2017).…”

On the Feasibility of Using Current Data Centre Infrastructure for Latency-sensitive Applications

“…An important consideration is the impact of routing changes on end-to-end latency between users and data centres. In [28] we show that BGP updates can result in significant changes in network performance including latency to reach the same destination. For any major BGP storm there is an impact on RTT, which is transient as routing converges.…”

“…Replicating services in many data centres around the globe requires service providers to build relationships with many cloud service providers, which can be a significant barrier in terms of operational overhead, especially for SMEs. This can be alleviated by means of a cloud-broker operating as an orchestrator on behalf of individual service providers/application developers, who also offers a software platform for management of the service life cycle across distributed cloud nodes [28]. The service provider needs to expose to the broker some application metrics and how these are weighted to evaluate the feasibility of a data centre to host an instance.…”

“…In our view, resolution of service requests to service instances is best undertaken by ISPs, as they have a detailed view on the client's location and on the BGP routing path towards data centres in remote Autonomous Systems [28]. Besides improvement customer satisfaction, ISPs may be incentified to act as a service resolver as this would allow them to have more fine-grained control on their inter-AS transit traffic costs.…”

“…Such an infrastructure has started to be deployed to support virtualised network functions running as software components in ISP-provided data centres [10]. However, even when edge cloud nodes are widely deployed there is a significant management overhead required by service providers to provision and then manage widely replicated services in numerous edge node locations [28]. Moreover, these edge nodes are envisioned to be positioned in locations such as street cabinets or mobile base stations that impose restrictions on the physical size, power consumption and, hence, computational complexity of the edge cloud clusters.…”