Fast and high capacity optical switching techniques have the potential to enable low latency and high throughput optical data center networks (DCNs) to afford the rapid increasing traffic boosted by multiple applications. Flexibility of the DCN is of key importance to provide adaptive and dynamic bandwidth and capacity to handle the variable traffic patterns of heterogeneous applications. Aiming at improving the network performance and the system flexibility of optical DCNs, we propose and investigate a novel optical DCN architecture named ROTOS based on reconfigurable optical top of rack (ToR) and fast optical switches. In the proposed DCN architecture, the novel optical flexible ToRs employing multiple transceivers (TRXs) and a wavelength selective switch (WSS) are reconfigured by the software-defined networking (SDN) control plane. The bandwidth can be dynamically allocated to the dedicated optical links on-demand according to the desired oversubscription (OV) and intra-/inter-cluster traffic matrix. Numerical investigations of the novel architecture under realistic traffic model indicate that dynamically allocating the TRXs and elastically controlling the WSS, a packet loss below 1E-5 and a server-to-server latency lower than 3 μs can be guaranteed for different traffic patterns at load of 0.4. With respect to the DCN with static interconnections, the average packet loss of ROTOS decreases two orders of magnitude and the average server-to-server latency performance improves by 21.5%. Scalability investigation to a large number of servers shows limited (11%) performance degradation as the network scale from 2560 to 40960 servers. Additionally, the dynamic bandwidth allocation of the DCN is experimentally validated. Network performance results show a packet loss of 0.05 and 5.85 μs end-to-end latency at the load of 0.8. Finally, investigations on the cost and power consumption confirm that the ROTOS DCN architecture has 28.4% lower cost and 35.0% better improvement for power efficiency with respect to the electrical switch based DCNs.

In elastic optical inter-datacenter networks, multiple software-defined networking (SDN) controllers have been used to improve scalability and reliability. The static controller deployment faces the problem of controller load imbalance under dynamic changes in network traffic. In response to this problem, existing research works proposed to use dynamic switch migration to achieve the controller load balancing. However, the efficiency of the existing switch migration is low, because the load balancing performance of controllers does not improve significantly after the switch migration and the migration activities can also cause additional migration costs. Thus the efficiency of switch migration has not yet been well resolved. In this work, we propose a highly-efficient switch migration (HESM) for controller load balancing. The proposed HESM method defines multiple load metrics to measure the load of controllers, and selects the optimal target controller with the largest remaining resource, which improves the load balancing performance. HESM selects switches based on minimizing migration costs, reducing additional migration costs. In addition, HESM can handle the load of multiple controllers in parallel during a switch migration activity, which improves the efficiency of migration. The simulation results show that HESM significantly improves load balancing performance of controllers and reduces the migration cost compared to existing solutions.

To solve the issues of low resource utilization and performance bottleneck in current server-centric data center networks (DCNs), we propose and experimentally demonstrate a disaggregated application-centric optical network (DACON) for data center infrastructures based on hybrid optical switches. DACON achieves flexible provision and dynamic reconfiguration of hardware nodes exploiting the softwared-define networking (SDN) orchestration plane. A four-node SDN-enabled disaggregated prototype is implemented with a field-programmable-gate-array-based controller of hardware nodes and nanosecond optical switches, performing a minimal node-to-node network latency of 378.6 ns and zero packet loss. Based on the unmodified Linux kernel and two different applications (distributed computing and a Memcached database), the application runtime of the disaggregated prototype is investigated and compared with the server-centric architecture. Experimental results show that the disaggregated prototype performs better with Memcached database applications, achieving a1.46×faster runtime than the server-centric network at a memory node access ratio of 0.9. Based on the customized control plane orchestrator and dynamic resource reallocation, the node-to-node latency is reduced by 21% when CPU nodes access memory nodes. The scalability of DACON is then numerically assessed based on experimentally measured parameters. Results show that the intra-rack node-to-node latency is less than 404.8 ns with a 6144-node network and memory node access ratio of 0.9. Finally, the cost and power consumption are also studied and compared with current DCN architectures. Results indicate DACON saves 13.4% of the cost of an interconnect network compared with current disaggregated architecture and consumes up to 31.1% less power with respect to server-centric DCN architectures.

Optical switching techniques have the potential to enable the optical data center network (DCN) interconnections providing high capacity and fast switching capabilities, overcoming thus the bandwidth and latency bottleneck of present electrical switch-based multi-tiered DCNs. The rapid growth of multi-tenant applications with heterogeneous traffic require specialized quality of service (QoS) in terms of packet loss and latency to the DCN infrastructure. Slicing the DCNs into dedicated pieces according to the deployed applications, the differentiated QoS and high resource utilization can be provided. However, slicing the optical DCNs still needs to be investigated because the Software-defined Networking (SDN) technique is developed for the electrical networks, not fully supporting the properties of the optical network. Additionally, Network Slices (NS) need to be automatically provisioned and reconfigured, to provide flexible slice interconnections in support of the multi-tenant applications to be deployed.

Maintaining high-performance operation under dynamic and nonuniform network traffic has been a technical challenge in current data center networks (DCNs). With the aim to provide better quality of service (QoS) for diverse applications, this work presents a dynamic and adaptive DCN reconfiguration framework based on deep reinforcement learning (DCR2L). The proposed framework is integrated into the SDN control plane of the DCN, implementing real-time and automatic DCN reconfiguration. Performance of the DCR2L framework is experimentally demonstrated in our DCN lab, including 4 racks and 16 servers. Experimental results show a network latency improvement of 6.9% based on the DCR2L at an average network bandwidth of 2.3 Gb/s. Based on measured traffic and physical parameters in the experiment, performance of the DCR2L framework is numerically assessed with the realistic traffic of diverse QoS requirements for both electrical and optical DCNs and for different data center scales. Leaf–spine electrical and OPSquare optical networks are set up in an OMNeT++ simulator. For a data plane network consisting of 16 racks and 320 servers, results indicate that the DCR2L framework improves the network latency of up to 16.4% under leaf–spine and up to 24.6% under OPSquare for the overall traffic with respect to the classical heuristic method. For a DCN scale of 10,240 servers, the DCR2L framework provides up to 12.5% lower latency for the leaf–spine electrical network and up to 17.8% latency improvement for the OPSquare optical network.

Aiming to solve the low utilization and high operational cost in current data centers and the diversified resource requirements for different application types, we propose and investigate what we believe to be a novel rack-scale disaggregated optical data center network (RDON). Different types of hardware resources (i.e., CPU, memory, and storage) are deployed in standalone resource pools of the RDON. The RDON architecture encompasses nanosecond distributed fast optical switches for the low latency and high bandwidth interconnects between the computing and memory nodes, while electrical packet switches are utilized to support the traffic of latency insensitivity and low bandwidth between memory nodes and storage nodes. By replacing the onboard data bus with a network interconnection, RDON architecture can provide a fine granularity hardware resource and relieve the constraints of server-centric architecture. To assess the performance of the RDON under realistic scenarios, statistics of diverse applications are captured from the data center lab. The RDON is modeled based on the OMNeT++ discrete event simulator and compared with the server-centric architecture. Numerical results show that the performance of the RDON is closely coupled with the type of deployed application. Compared to the server-centric architecture, the RDON can achieve up to 2.44 × faster running time when running a single application, whereas at most 2.25 × is the fastest running time under coexisting diverse types of applications. Finally, the analysis of costs and power consumption show that, with respect to server-centric architecture, the RDON requires 21.5% extra capital cost but 46.7% less power consumption.