Optical networks based on arrayed waveguide grating routers (AWGRs) offer significant advantages, including low latency, high bandwidth, and low power consumption. However, addressing the contention issues associated with AWGRs has become a primary concern in practical deployment. Previous research has focused on centralized control methods to address this challenge, but their scalability is often limited. Additionally, distributed time-slot strategies have been implemented, but fixed time-slot configurations can result in performance loss. To effectively overcome these challenges, we propose a distributed scheduling strategy called FlexLoop. Authorizations are issued by receiving nodes and passed between sending nodes via the software-defined networking (SDN) switches. The authorization holder is permitted to transmit a batch of data to the designated node. Each receiving node has the autonomy to define the authorization passing rules through SDN switch configurations. Similarly, each sending node retains the flexibility to either use the authorization to transmit data or forward it to other nodes. Therefore, FlexLoop operates in a fully distributed manner and shows adaptability to various traffic patterns. Experimental results demonstrate that FlexLoop reduces packet latency by up to 92.01% and improves throughput by up to 77.09% compared to NegotiaToR. Additionally, a prototype system was developed, which validates the practical feasibility of implementing FlexLoop.

Optical networks based on arrayed waveguide grating routers (AWGRs) present a promising solution for rapidly evolving data centers (DCs). However, the contention issue remains a significant challenge to their widespread adoption. Existing control strategies typically rely on time-slots that are both synchronized across the network and of fixed duration. This results in the fixed switching granularity. The determination of time-slot duration often involves a trade-off between flexibility and control overhead. In this paper, we propose Halo, a distributed control strategy that avoids contention without relying on time-slots. Halo decentralizes the scheduling tasks across the network. Each node independently issuesGrants, which are passed sequentially among source nodes with communication demands. The node holding theGrantis allowed to transmit a batch of data to the issuing node. Once the demand is no longer present, or the transmitted packet count exceeds a threshold, theGrantis forwarded to the next node. As a result, synchronization operations among nodes is unnecessary, allowing the switching granularity to become flexible. Experimental results demonstrate that Halo significantly outperforms existing control strategies. In trace-based simulations, it achieves up to a 75.13% reduction in flow completion time (FCT). Additionally, we developed a prototype system and executed several real applications to demonstrate the practical feasibility of the Halo.

Data center networks demand high-performance, robust, and scalable load balancing protocols. Despite progress, existing work still cannot meet these requirements well. Software defined networking (SDN) can bring considerable flexibility to the management of data center networks. In the software-defined data center network, we design, analyze, and evaluate RSLB, a robust and scalable load balancing protocol that overcomes these challenges. RSLB uses fine-grained flowcell as the transmission unit, and uses link delay as the congestion metric. It uses a three-step routing strategy to route flowcells to the path with the least congestion. Through global congestion awareness, RSLB reduces flow completion time (FCT), and is more robust to topological asymmetries compared to existing congestion-agnostic schemes. To collect and store congestion information, RSLB adopts a distributed control structure that monitors the congestion of the entire network through multiple controllers, which makes it much more scalable for implementation in large-scale networks compare to existing congestion-aware schemes. The simulation results show that RSLB can achieve lower FCT for mice flows and higher throughput for elephant flows than existing schemes, no matter in failure-free topology or asymmetric topology.