Millimeter wave (mmWave) communications in the 60 GHz band can provide multi-gigabit rates for emerging bandwidth-intensive applications, and has thus gained considerable interest recently. In this paper, we investigate the problem of efficient scheduling in mmWave wireless personal area networks (WPAN). We develop a frame-based scheduling directional MAC protocol, termed FDMAC, to achieve the goal of leveraging collision-free concurrent transmissions to fully exploit spatial reuse in mmWave WPANs. The high efficiency of FDMAC is achieved by amortizing the scheduling overhead over multiple concurrent, back-to-back transmissions in a row. The core of FDMAC is a graph coloring-based scheduling algorithm, termed greedy coloring (GC) algorithm, that can compute near-optimal schedules with respect to the total transmission time with low complexity. The proposed FDMAC is analyzed and evaluated under various traffic models and patterns. Its superior performance is validated with extensive simulations.

We investigate the challenging problem of joint topology design and load balancing in FSO networks. Important factors such as FSO link characteristics, cost constraints, traffic characteristics, traffic demand, and QoS requirements are considered in the problem formulation, along with objective functions of network-wide average traffic load and delay. We develop a fast heuristic algorithm to provide highly competitive solutions. The heuristic algorithm iteratively perturbs the current topology and computes network flows for the new topology, thus progressively improving the configuration and load balancing of the FSO network. Our simulation results show that the heuristic algorithm can achieve an optimality gap close to that of a branch-and-bound algorithm developed in our prior work, with significantly reduced computation time. The heuristic algorithm is complementary to the branch-and-bound algorithm. Jointly applying the algorithms can make the FSO network dynamically reconfigurable and adaptive to events occurring at both large and small timescales.

Free space optical networks have emerged as a viable technology for broadband wireless backbone networks. In this paper, we investigate the challenging problem of joint topology design and load balancing in FSO networks. We consider FSO link characteristics, cost constraints, traffic characteristics, traffic demand, and QoS requirements in the formulation, along with various objective functions including network-wide average load and delay. We apply the Reformulation-Linearization Technique (RLT) to obtain linear programming (LP) relaxations of the original complex problem, and then incorporate the LP relaxations into a branch-and-bound framework. The proposed algorithm can produce highly competitive solutions with performance guarantees in the form of bounded optimality gap. The RLT-based branch-and-bound algorithm is evaluated with extensive simulations and is shown to be highly suitable for jointly optimizing topology and load balancing in FSO networks.

Although having high potential for broadband wireless access, wireless mesh networks are known to suffer from throughput and fairness problems, and are thus hard to scale to large size. To this end, hierarchical architectures provide a solution to this scalability problem. In this paper, we address the problem of design and optimization of a tiered wireless access network. At the lower tier, mesh routers are clustered based on traffic demands and delay requirements. The cluster heads are equipped with wireless optical transceivers and form the upper tier free space optical (FSO) network. We first present a plane sweeping and clustering algorithm aiming to minimize the number of clusters. PSC sweeps the network area and captures cluster members under delay and traffic load constraints. We then present an algebraic connectivity-based formulation for FSO network topology optimization and develop a greedy edge-appending algorithm that iteratively inserts edges to maximize algebraic connectivity. The proposed algorithms are analyzed and evaluated via simulations, and are shown to be highly effective as compared to the performance bounds derived in this paper.