Joint Routing and Scheduling in WiMAX-Based Mesh Networks

The problem of scheduling and tree routing in WiMAX/802.16 based mesh networks were not defined in the standard and are thus subject to extensive research. In this paper, we consider the problem of joint routing and scheduling in 802.16-based wireless mesh network, with the objective of determining a minimum length schedule that satisfies a given (uplink/downlink) end-to-end traffic demand. Minimizing the schedule length amounts to maximizing the spectrum spatial reuse by concurrently transmitting on as many links as possible, which we refer to as a transmission configuration (a group of links that can simultaneously transmit without violating the signal-to-interferenceplus- noise ratio (SINR) requirement). Our model is referred to as maximum spatial reuse (MSR). Since there is an overwhelming number of possible transmission configurations to be assigned to time slots, we adopt the column generation technique to construct our MSR model. We present two formulations for modeling MSR, namely the link-based column generation (CGLink) formulation and the path-based column generation (CGPath) formulation. These two formulations differ mainly in the number of routing decision variables. Our experimental results indicate that the path-based formulation needs much less computational (CPU) time than the link-based formulation in order to determine the (same) optimized solution with the same spatial reuse gain.

Wireless Mesh Networks offer a high-performance and low-cost solution to last-mile broadband Internet access. Routing and Scheduling play a critical role in determining the performance of a wireless mesh network. Efficiency of Routing and Scheduling algorithms is highly dependent on the availability of accurate traffic information. In this paper, we predict network traffic based on past data using ARIMA model, and provide that input to the routing and scheduling algorithm. Joint routing and scheduling results in significant performance improvement over the routing only algorithms. So, we provide predicted network traffic information to a Joint routing and scheduling algorithm known as Traffic Oblivious Routing and Scheduling. Traffic Oblivious Routing and Scheduling algorithm optimizes the worst case performance under traffic uncertainty but when accurate traffic information is available to the algorithm, its performance is enhanced. In the Traffic Oblivious Routing and Scheduling algorithm, computing the routing and the scheduling values is a one time overhead. In this paper, we present a system where we predict network traffic information using past data, then use the predicted information to formulate the input for the Traffic Oblivious routing and scheduling algorithm and finally we evaluate the performance of the algorithm using simulations.

This paper addresses, in the context of wireless network design, the problem of optimally partitioning the spectrum into a set of nonoverlapping channels with nonuniform spectrum widths. While narrower bands split the total available spectrum into more nonoverlapping channels allowing more parallel concurrent transmissions, wider spectrum bands yield links with larger transport capacity. Thus, we model the combinatorially complex problem of joint routing, link scheduling, and variable-width channel allocation in both single and multirate multihop wireless networks as a mixed integer linear program, and present a solution framework using the column generation decomposition approach. Given the nature and complexity of the resulting dual subproblem, we propose heuristic methods for partitioning the spectrum and allocating resources to each active links, and hence obtain solutions for larger network instances. We present several numerical results and engineering insights suggesting both spectrum width and transmission rates as effective tunable knobs for combatting interference and promoting spatial reuse and thus achieving superior performance in multihop settings.

Joint routing and scheduling in multi-Tx/Rx wireless mesh networks with random demands

We consider the problem of joint routing, scheduling and power control in multi-hop wireless networks. We use a linear relation between link capacity and signal to interference noise ratio in our formulation. In a previous work, using a duality approach, the optimal link scheduling and power control that minimizes the total average transmission power is found. We formulate this problem as a linear programming problem with exponential number of constraints. To cope with the exponential number of constraints, we propose an iterative algorithm based on the cutting plane method. The separation oracle for the cutting plane algorithm turns out to be an element-wise concave optimization problem that can be effectively solved using branch and bound algorithm. We extend the same method to find the optimal routing scheduling and power control. Simulation results show that this methodology is more efficient and scalable compare to the previously proposed algorithm.

Past approaches to routing in mesh networks either (i) do not account for the MAC-layer interactions between the links in a tractable manner, or (ii) are agnostic to load-balancing across gateways. Our answer to these problems is MaLB (MAC-aware and Load Balanced routing algorithm), a greedy, tractable, and distributed mesh routing algorithm. Since the underlying objective function has high combinatorial complexity, MaLB uses a greedy approach. MaLB finds an optimum routing forest (union of trees rooted at the gateways) by taking into account MAC-layer interaction between links, as well as optimum multi-hop association of mesh nodes to gateways. MaLB builds on top of ETP (Expected Through-Put), a recently proposed MAC-aware routing metric. We also propose a low complexity variant of MaLB called LB (Load Balanced routing algorithm) which performs load balancing in a MAC-agnostic manner. MaLB performs especially well in networks with skewed topologies that result from unplanned mesh network deployment, as well as in the presence of gateway failures. Simulations with an enhanced version of ns-2 show that MaLB results in up to 60% higher throughput than a shortest path algorithm with ETX (Expected Transmission Count). Furthermore, MaLB results in up to 30% improvement over the LB algorithm, as well as a shortest path algorithm with ETT (Expected Transmission Time).

Ad hoc network is an extensive research area in wireless communications nowadays, and is particularly studied under energy constraints, since energy consumption of the network should be minimized. The physical layer (power control), link layer (scheduling), and network layer (routing) are known to have great impact on network performance as well as on power consumption. In this paper, we present an optimization problem that there may exist a power vector that minimizes the overall transmission power of the network which at the same time supports a particular data rate on each link and satisfies the SINR and maximum transmission power constraints at each node. We also formulate an optimization problem where we use both the energy consumed of each node in the routing path and the delay associated on each link as link costs. We provide numerical examples for our schemes and relationships between the parameters. An overview of our intended routing algorithm for ad hoc networks is also given as a preliminary step towards our distributed joint scheduling, power control and routing algorithm for ad hoc networks using cross layer approach.

In Deep sub-micron design level, interconnect plays an important role in VLSI circuit designs. Traditional interconnects are facing several challenges such as delay and power dissipation. Graphene nanoribbons (GNRs) have been found to be potential alternative for both transistors and interconnects due to its outstanding electrical and thermal properties. The construction of minimum cost global routing trees is a key challenge in deep sub-micron design. The construction of such trees for traditional interconnects based on Required Arrival Time (RAT) has been reported in literature. The construction of global routing trees for GNR routing are different than that of traditional interconnects. In this paper, we propose an algorithm for the construction of cost effective global routing trees for GNR routing based on required arrival time. We formulate the GNR routing problem considering the minimization of the area of triangular grid such that delay from source to each of the sink terminals is within the given time budget. The algorithm is tested on a random set of data and the results obtained are quite encouraging.

We propose a Disruption Aware Routing and link Scheduling (DARS) scheme for multi-hop cognitive radio networks. The objective is to minimize disruptions to secondary user communication sessions due to channel switching and the resource consumption. We formulate the problem into an optimization problem and develop an efficient algorithm to solve the problem. The main idea is to monitor the data rate change of each communication session and then decide whether or not to change the routing and link scheduling. This eliminates unnecessary channel switching for secondary users. Simulation results demonstrate that DARS effectively reduces channel switching and disruptions to communication sessions.

Data gathering is a fundamental operation for various applications of wireless sensor networks (WSNs), where sensor nodes sense information and forward data to a sink node via multihop wireless communications. Typically, data in a WSN is relayed over a tree topology to the sink for effective data gathering. A number of tree-based data gathering schemes have been proposed in the literature, most of which aim at maximizing network lifetime. However, the timeliness and reliability of gathered data are also of great importance to many applications in WSNs. To achieve low-latency, high-reliability data gathering in WSNs, in this paper, we construct a data gathering tree based on a reliability model, schedule data transmissions for the links on the tree and assign transmitting power to each link accordingly. Since the reliability of a link is highly related to its signal to interference plus noise ratio (SINR), the SINR of all the currently used links on the data gathering tree should be greater than a threshold to guarantee high reliability. We formulate the joint problem of tree construction, link scheduling and power assignment for data gathering into an optimization problem, with the objective of minimizing data gathering latency. We show the problem is NP-hard and divide the problem into two subproblems: Construction of a low-latency data gathering tree; Jointly link scheduling and power assignment for the data gathering tree. We then propose a polynomial heuristic algorithm for each subproblem and conduct extensive simulations to verify the effectiveness of the proposed algorithms. Our simulation results show that the proposed algorithms achieve much lower data gathering latency than existing data gathering strategies while guaranteeing high reliability.

In this paper, we address the problem of computing the transport capacity of Wireless Mesh Networks dedicated to Internet access. Routing and transmission scheduling have a major impact on the capacity provided to the clients. A cross-layer optimization of these problems allows the routing to take into account contentions due to radio interferences. We develop exact linear programs and provide an efficient column generation process computing a relaxation of the problem. It allows to work around the combinatoric of simultaneously achievable transmissions, hence computing solutions on large networks. Our approach is validated through extensive simulations. Evolution of the capacity of a mesh network with its parameters, as well as the algorithmic complexity are then discussed. We conjecture that the problem can be solved in polynomial time and that the gateway placement problem is only subject to localized constraints.

A cross-layer framework for joint routing and rate adaptation in infrastructure Wireless Mesh Networks

Current works on the joint routing and channel assignment (JRC) problem in wireless mesh networks (WMNs) assume that all links operate at the base rate. In other words, they do not consider the presence of multiple bit-rates. However, in multi-rate WMNs, the achievable throughput of a link operating at higher rates could be much less than its bit-rate when it has to contend with low-rate links. This is also known as the multirate sharing problem. To address the problem, we first present a numerical formulation for estimating the dynamic link capacity, which can indicate the degree of the multi-rate sharing problem. Next, we propose an optimization model called MR <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> C, which solves the JRC problem by considering the dynamic link capacity in order to maximize the throughput in multi-rate, multi-radio, multi-channel WMNs. We then reformulate the primal problem as a Lagrangian dual problem, and apply the subgradient method to approach the dual. Finally, since each subproblem in the dual problem is also a non-linear problem, we design a polynomialtime algorithm to solve it. Our experiment results demonstrate that the proposed capacity formulation can approximate the actual link throughput. We compare MR <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> C with the base-rate JRC model via simulations. The results show that MR <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> C achieves throughput gains of 3-4 times and recover from network failure efficiently.

Tree-based routing protocols in low-rate wireless mesh networks usually have the detour problem in return for the no route discovery overhead. In this paper, we propose a novel algorithm, named Incremental Path Reduction (IPR), which incrementally shortens inefficient detoured path as more data packets are delivered. In IPR, data packets are delivered along the tree route in use by using 1-hop broadcast, enabling neighbor nodes to learn about the data packets' hop count. Using the hop counts, each node estimates their residual hop count to destination. As a result, each forwarder selects next hop node that has small residual hop count. In this way, IPR incrementally shortens the detoured route as more data packets are delivered. To verify our algorithm, we applied IPR to the representative tree routing protocols, and evaluated the path stretch and packet delivery ratio as well as control packet overhead. Simulation results show that IPR significantly enhances the overall routing metrics for any types of tree-based routing protocols.

Long-distance multi-hop wireless networks have been used in recent years to provide connectivity to rural areas. The salient features of such networks include TDMA channel access, nodes with multiple radios, and point-to-point long-distance wireless links established using high-gain directional antennas mounted on high towers. It has been demonstrated previously that in such network architectures, nodes can transmit concurrently on multiple radios, as well as receive concurrently on multiple radios. However, concurrent transmission on one radio, and reception on another radio causes interference. Under this scheduling constraint, given a set of source-destination demand rates, we consider the problem of satisfying the maximum fraction of each demand (also called the maximum concurrent flow problem). We give a novel joint routing and scheduling scheme for this problem, based on linear programming and graph coloring. We analyze our algorithm theoretically and prove that at least 50% of a satisfiable set of demands is satisfied by our algorithm for most practical networks (with maximum node degree at most 5).