Scalable Impairment-Aware Anycast Routing in Multi-Domain Optical Grid Networks

ABSTRACT In optical Grid networks, the main challenge is to account for not only network parameters, but also for resource availability. Anycast routing has previously been proposed as an effective solution to provide job scheduling services in optical Grids, offering a generic interface to access Grid resources and services. The main weakness of this approach is its limited scalability, especially in a multi-domain scenario. This paper proposes a novel anycast proxy architecture, which extends the anycast principle to a multi-domain scenario. The main purpose of the architecture is to perform aggregation of resource and network states, and as such improve computational scalability and reduce control plane traffic. Furthermore, the architecture has the desirable properties of allowing Grid domains to maintain their autonomy and hide internal configuration details from other domains. Finally, we propose an impairment-aware anycast routing algorithm that incorporates the main physical layer characteristics of large-scale optical networks into its path computation process. By integrating the proposed routing scheme into the introduced architecture we demonstrate significant network performance improvements. Keywords: Grid computing, routing algorithms, optical networks, physical impairments, anycast routing. INTRODUCTION Today, the need for network systems to support storage and computing services for science and business, is often satisfied by relatively isolated computing infrastructure (clusters). Migration to truly distributed and integrated applications requires optimization and (re)design of the underlying network technology to create a Grid platform for the cost and resource efficient delivery of network services with substantial data transfer, processing power and/or data storage requirements. Optical networks offer an undeniable potential for the Grid, given their proven track-record in the context of high-speed, long-haul, networking. Not only eScience applications dealing with large experimental data sets (e.g. particle physics) but also business/consumer oriented applications can benefit from optical Grid infrastructure [1]: both the high data rates typical of eScience applications and the low latency requirements of consumer/business applications (cf. interactivity) can effectively be addressed. When using transparent WDM as such network technology, signals are transported end-to-end optically without being converted to the electrical domain in between. Connection provisioning of all-optical connections (lightpaths) between source and destination nodes is based on specific routing and wavelength assignment algorithms (RWA). Traditional RWA schemes only account for network conditions such as connectivity and available capacity, without considering physical layer details. However, in transparent optical networks covering large geographical areas, the optical signal experiences the accumulation of physical impairments through transmission and switching, possibly resulting in unacceptable signal quality Another emerging and challenging task in distributed and heterogeneous computing environments, is job scheduling: when and where to execute a given Grid job, based on the requirements of the job (for instance a deadline and minimal computational power) and the current state of the network and resources. Traditionally, a local scheduler optimizes utilization and performance of a single Grid site, while a meta-scheduler is distributes workload across different sites. Current implementations of these (meta-)schedulers only account for Grid resource availability In this paper we propose a novel architecture to support impairment-aware anycast routing for large-scale optical Grid networks. Section 2 discusses general approaches to support multi-domain networks. We then proceed to introduce a novel architecture, which can provide anycast Grid services in a multi-domain scenario (Section 3). Simulation analysis is used to demonstrate the improved scalability without incurring significant performance loss. Furthermore, Section 4 shows how to incorporate physical layer impairments, to further improve the performance of optical Grid networks. Conclusions are presented in Section 5

Energy-efficient resource-provisioning algorithms for optical clouds

Rising energy costs and climate change have led to an increased concern for energy efficiency (EE). As information and communication technology is responsible for about 4% of total energy consumption worldwide, it is essential to devise policies aimed at reducing it. In this paper, we propose a routing and scheduling algorithm for a cloud architecture that targets minimal total energy consumption by enabling switching off unused network and/or information technology (IT) resources, exploiting the cloud-specific anycast principle. A detailed energy model for the entire cloud infrastructure comprising a wide-area optical network and IT resources is provided. This model is used to make a single-step decision on which IT end points to use for a given request, including the routing of the network connection toward these end points. Our simulations quantitatively assess the EE algorithm's potential energy savings but also assess the influence this may have on traditional quality-of-service parameters such as service blocking. Furthermore, we compare the one-step scheduling with traditional scheduling and routing schemes, which calculate the resource provisioning in a two-step approach (selecting first the destination IT end point and subsequently using unicast routing toward it). We show that depending on the offered infrastructure load, our proposed one-step calculation considerably lowers the total energy consumption (reduction up to 50%) compared to the traditional iterative scheduling and routing, especially in low-to medium-load scenarios, without any significant increase in the service blocking

Accepted for Photonic Network Communications

Abstract-When deploying Grid infrastructure, the problem of dimensioning arises: how many servers to provide, where to place them, and which network to install for interconnecting server sites and users generating Grid jobs? In contrast to classical optical network design problems, it is typical of optical Grids that the destination of traffic (jobs) is not known beforehand. This leads to so-called anycast routing of jobs. For network dimensioning, this implies the absence of a clearly defined (source,destination)-based traffic matrix, since only the origin of Grid jobs (and their data) is known, but not their destination. The latter depends not only on the state of Grid resources, including network, storage, and computational resources, but also the Grid scheduling algorithm used. We present a phased solution approach to dimension all these resources, and use it to evaluate various scheduling algorithms in two European network case studies. Results show that the Grid scheduling algorithm has a substantial impact on the required network capacity. This capacity can be minimized by appropriately choosing a (reasonably small) number of server site locations: an optimal balance can be found, in between the single server site case requiring a lot of network traffic to this single location, and an overly fragmented distribution of server capacity over too many sites without much statistical multiplexing opportunities, and hence a relatively large probability of not finding free servers at nearby sites

Time-varying Resilient Virtual Networking Mapping for Multi-location Cloud Data Centers

Abstract In the currently dominant cloud computing paradigm, applications are being served in data centers (DCs), which are connected to high capacity optical networks. For bandwidth and consequently cost efficiency reasons, in both DC and optical network domains, virtualization of the physical hardware is exploited. In a DC, it means that multiple so-called virtual machines (VMs) are being hosted on the same physical server. Similarly, the network is partitioned into separate virtual networks, thus providing isolation between distinct virtual network operators (VNOs). Thus, the problem of virtual network mapping arises: how to decide which physical resources to allocate for a particular virtual network? In this thesis, we study that problem in the context of cloud computing with multiple DC sites. This introduces additional flexibility, due to the anycast routing principle: we have the freedom to decide at what particular DC location to serve a particular application. We can exploit this choice to minimize the required resources when solving the virtual network mapping problem. This thesis solves a resilient virtual network mapping problem that optimally decides on the mapping of both network and data center resources, considering time-varying traffic conditions and protecting against possible failures of both network and DC resources. We consider the so-called VNO resilience scheme: rerouting under failure conditions is provided in the virtual network layer. To minimize physical resource capacity requirements, we allow reuse of both network and DC resources: we can reuse the same resources for the rerouting under failure scenarios that are assumed not to occur simultaneously. Since we also protect against DC failures, we allocate backup DC resources, and account for synchronization between primary and backup DCs. To deal with the time variations in the volume and geographical pattern of the application traffic, we investigate the potential benefits (in terms iii of overall bandwidth requirements) of reconfiguring the virtual network mapping from one time period to the next. We provide models with good scalability, and investigate different scenarios to check whether it is worth to change routing for service requirement between time periods. The results come up with our experiments show that the benefits for rerouting is very limited. Keywords: Cloud Computing, Optical Networks, Virtualization, Anycast, VNO resilienc