2 research outputs found
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Source-Routed Multicast Schemes for Large-Scale Cloud Data Center Networks
Data centers (DCs) have been witnessing unprecedented growth in size, number and complexity in recent years. They consist of tens of thousands of servers interconnected by fast network switches, hosting and enabling numerous applications with various traffic characteristics and requirements. As a result, DC networks have been presented with several unique challenges, pertaining to the scaling and allocation of network resources during the forwarding and moving of data across the different DC servers. Traffic routing in general and multicast routing in particular are important functions in DC networks, especially that modern cloud DCs tend to exhibit one-to-many communication traffic patterns. Unfortunately, recent multicast routing approaches that adopt IP multicast suffer from scalability and load balancing issues, and do not scale well with the number of supported multicast groups when used for cloud DC networks. In this thesis, we propose a set of new, complementary schemes that overcome these challenges. More specifically, firstly, we study existing DC network topologies, and propose Circulant Fat-Tree topology, an improvement over the traditional Fat-Tree topology with better properties to suit nowadays DC networks. Then, we review and classify recent studies that investigate and measure the traffic behavior of operational DC networks. We focus on the way they collect the traffic as well as on the key findings made in these studies.
Secondly, we propose Bert, a source-initiated multicast routing scheme for DCs. Bert scales well with both the number and the size of multicast groups, and does so through clustering, by dividing the members of the multicast group into a set of clusters with each cluster employing its own forwarding rules. In essence, Bert yields much lesser multicast traffic overhead than state-of-the-art schemes.
Thirdly, we propose, Ernie, a scalable and load-balanced multicast source routing scheme. Ernie introduces a novel method for scaling out the number of supported mul- ticast groups. In particular, it appropriately constructs and organizes multicast header information inside packets in a manner that allows core/root switches to only forward down the needed information. Ernie also introduces an effective multicast traffic load balancing technique across downstream links. Specifically, it prudently assigns multicast groups to core switches to ensure the evenness of load distribution across the downstream links
Resilient and Scalable Forwarding for Software-Defined Networks with P4-Programmable Switches
Traditional networking devices support only fixed features and limited configurability.
Network softwarization leverages programmable software and hardware platforms to remove those limitations.
In this context the concept of programmable data planes allows directly to program the packet processing pipeline of networking devices and create custom control plane algorithms.
This flexibility enables the design of novel networking mechanisms where the status quo struggles to meet high demands of next-generation networks like 5G, Internet of Things, cloud computing, and industry 4.0.
P4 is the most popular technology to implement programmable data planes.
However, programmable data planes, and in particular, the P4 technology, emerged only recently.
Thus, P4 support for some well-established networking concepts is still lacking and several issues remain unsolved due to the different characteristics of programmable data planes in comparison to traditional networking.
The research of this thesis focuses on two open issues of programmable data planes.
First, it develops resilient and efficient forwarding mechanisms for the P4 data plane as there are no satisfying state of the art best practices yet.
Second, it enables BIER in high-performance P4 data planes.
BIER is a novel, scalable, and efficient transport mechanism for IP multicast traffic which has only very limited support of high-performance forwarding platforms yet.
The main results of this thesis are published as 8 peer-reviewed and one post-publication peer-reviewed publication. The results cover the development of suitable resilience mechanisms for P4 data planes, the development and implementation of resilient BIER forwarding in P4, and the extensive evaluations of all developed and implemented mechanisms. Furthermore, the results contain a comprehensive P4 literature study.
Two more peer-reviewed papers contain additional content that is not directly related to the main results.
They implement congestion avoidance mechanisms in P4 and develop a scheduling concept to find cost-optimized load schedules based on day-ahead forecasts