With the advent of new applications such as Cloud Computing, Blockchain, Big Data, and Machine Learning, modern data center network (DCN) architecture has been evolving to meet numerous challenging requirements such as scalability, agility, energy efficiency, and high performance. Among the new applications ones are expediting the convergence of high-performance computing and Data Centers. This convergence has prompted research into a single, converged data center architecture that unites computing, storage, and interconnect network in a synthetic system designed to reduce the total cost of ownership and result in greater efficiency and productivity. The interconnect network is a critical aspect of Data Centers, as it sets performance bounds and determines most of the total cost of ownership. The design of an interconnect network consists of three factors: topology, routing, and congestion control, and this thesis aims to satisfy the above challenging requirements. To address the challenges noted above, the communication patterns for emerging applications are investigated, and it is shown that the dynamic and diverse traffic patterns (denoted as *-cast), especially multi-cast, in-cast, broadcast (one-to-all), and all-to-all-cast, play a significant impact in the performance of emerging applications. Inspired by hypermesh topologies, this thesis presents a novel cost-efficient topology for large-scale Data Center Networks (DCNs), which is called HyperOXN. HyperOXN takes advantage of high-radix switch components leveraging state-of-the-art colorless wavelength division multiplexing technologies, effectively supports *-cast traffic, and at the same time meets the demands for high throughput, low latency, and lossless delivery. HyperOXN provides a non-blocking interconnect network with a relatively low overhead-cost. Through theoretical analysis, this thesis studies the topological properties of the proposed HyperOXN and compares it with other different types of interconnect networks such as Fat-Tree, Flattened Butterfly, and Hypercube-like topologies. Passive optical cross-connection networks are used in the HyperOXN topology, enabling economical, power-efficient, and reliable communication within DCNs. It is shown that HyperOXN outperforms a comparable Fat-Tree topology in cost, throughput, power consumption and cabling under a variety of workload conditions. A HyperOXN network provides multiple paths between the source and its destination to obtain high bandwidth and achieve fault tolerance. Inspired by a power-of-two-choices technique, a novel stochastic global congestion-aware load balancing algorithm, which can be used to achieve relatively optimal load balances amongst multiple shared paths is designed. It also guarantees low latency for short-lived mouse flows and high throughput for long-lasting elephant flows. Furthermore, the stability of the flow-scheduling algorithm is formally proven. Experimental results show that the algorithm successfully eliminated the interactions of the elephant and mouse DC flows, and ensured high network bandwidth utilization.