Towards a Practical and Fair Rate Allocation for Multihop Wireless Networks based on a Simple Node Model

IEEE 802.11 is often considered as the underlying wireless technology of multihop wireless networks. But the use of 802.11 in such networks raises issues, like efficiency and/or fairness issues. Different kinds of solutions have been proposed to overcome these problems. One approach is to design new MAC protocols that provide alternatives to the IEEE 802.11 MAC protocol. Although these solutions are of some interest, it should probably take some time before new wireless network interface cards based on one of these solutions are developed and released. Another approach is to consider that 802.11 will remain the underlying wireless technology and to design solutions above it. Several solutions based on rate allocation have been proposed so far. The main drawback of the proposed solutions is that they rely on a radio medium sharing model that is difficult to compute in a wireless, distributed and mobile environment. Indeed, very few of these solutions have been derived into a network protocol. In this article, we propose a distributed and dynamic rate allocation solution that is based on a simple sharing model. Due to its simplicity, we can derive a network protocol that can be practically used in multihop wireless networks. This protocol provides a fair bandwidth sharing between end-to-end flows while maintaining an efficient overall throughput in the network. This solution has been implemented in NS2 and evaluated by simulations

Towards Optimal Distributed Node Scheduling in a Multihop Wireless Network through Local Voting

In a multihop wireless network, it is crucial but challenging to schedule transmissions in an efficient and fair manner. In this paper, a novel distributed node scheduling algorithm, called Local Voting, is proposed. This algorithm tries to semi-equalize the load (defined as the ratio of the queue length over the number of allocated slots) through slot reallocation based on local information exchange. The algorithm stems from the finding that the shortest delivery time or delay is obtained when the load is semi-equalized throughout the network. In addition, we prove that, with Local Voting, the network system converges asymptotically towards the optimal scheduling. Moreover, through extensive simulations, the performance of Local Voting is further investigated in comparison with several representative scheduling algorithms from the literature. Simulation results show that the proposed algorithm achieves better performance than the other distributed algorithms in terms of average delay, maximum delay, and fairness. Despite being distributed, the performance of Local Voting is also found to be very close to a centralized algorithm that is deemed to have the optimal performance

PACE: Simple Multi-hop Scheduling for Single-radio 802.11-based Stub Wireless Mesh Networks

IEEE 802.11-based Stub Wireless Mesh Networks (WMNs) are a cost-effective and flexible solution to extend wired network infrastructures. Yet, they suffer from two major problems: inefficiency and unfairness. A number of approaches have been proposed to tackle these problems, but they are too restrictive, highly complex, or require time synchronization and modifications to the IEEE 802.11 MAC. PACE is a simple multi-hop scheduling mechanism for Stub WMNs overlaid on the IEEE 802.11 MAC that jointly addresses the inefficiency and unfairness problems. It limits transmissions to a single mesh node at each time and ensures that each node has the opportunity to transmit a packet in each network-wide transmission round. Simulation results demonstrate that PACE can achieve optimal network capacity utilization and greatly outperforms state of the art CSMA/CA-based solutions as far as goodput, delay, and fairness are concerned

Topics in Routing and Network Coding for Wireless Networks

This dissertation presents topics in routing and network coding for wireless networks. We present a multipurpose multipath routing mechanism. We propose an efficient packet encoding algorithm that can easily integrate a routing scheme with network coding. We also discuss max-min fair rate allocation and scheduling algorithms for the flows in a wireless network that utilizes coding. We propose Polar Coordinate Routing (PCR) to create multiple paths between a source and a destination in wireless networks. Our scheme creates paths that are circular segments of different radii connecting source-destination pairs. We propose a non-euclidean distance metric that allows messages to travel along these paths. Using PCR it is possible to maintain a known separation among the paths, which reduces the interference between the nodes belonging to two separate routes. Our extensive simulations show that while PCR achieves a known separation between the routes, it does so with a small increase in overall hop count. Moreover, we demonstrate that the variances of average separation and hop count are lower for the paths created using PCR compared to the existing schemes, indicating a more reliable system. Existing multipath routing schemes in wireless networks do not perform well in the areas with obstacles or low node density. To overcome adverse areas in a network, we integrate PCR with simple robotic routing, which lets a message circumnavigate an obstacle and follow the multipath trajectory to the destination as soon as the obstacle is passed. Next we propose an efficient packet encoding algorithm to integrate a routing scheme with network coding. Note that this packet encoding algorithm is not dependent on PCR. In fact it can be coupled with any routing scheme in order to leverage the benefits offered by both an advanced routing scheme and an enhanced packet encoding algorithm. Our algorithm, based on bipartite graphs, lets a node exhaustively search its queue to identify the maximum set of packets that can be combined in a single transmission. We extend this algorithm to consider multiple next hop neighbors for a packet while searching for an optimal packet combination, which improves the likelihood of combining more packets in a single transmission. Finally, we propose an algorithm to assign max-min fair rates to the flows in a wireless network that utilizes coding. We demonstrate that when a network uses coding, a direct application of conventional progressive filling algorithm to achieve max-min fairness may yield incorrect or suboptimal results. To emulate progressive filling correctly for a wireless networks with coding, we couple a conflict graph based framework with a linear program. Our model helps us directly select a bottleneck flow at each iteration of the algorithm, eliminating the need of gradually increasing the rates of the flows until a bottleneck is found. We demonstrate the caveats in selecting the bottleneck flows and setting up transmission scheduling constraints in order to avoid suboptimal results. We first propose a centralized fair rate allocation algorithm assuming the global knowledge of the network. We also present a novel yet simple distributed algorithm that achieves the same results as the centralized algorithm. We also present centralized as well as distributed scheduling algorithms that help flows achieve their fair rates. We run our rate allocation algorithm on various topologies. We use various fairness metrics to show that our rate allocation algorithm outperforms existing algorithms (based on network utility maximization) in terms of fairness

Price-Based Optimal Resource Allocation in Multi-Hop Wireless Networks

Recent advances in wireless communications and digital electronics have enabled rapid development of a variety of wireless network technologies. The undeniable popularity of wireless network is due to its ubiquity and convenience, which is appreciated by the users. In this dissertation, we study the problem of resource allocation in multihop wireless networks (so called ad hoc networks). A wireless ad hoc network consists of a collection of wireless nodes without a fixed infrastructure. Two wireless nodes communicate with each other directly, if they are within the transmission range of each other. Otherwise, the communication is achieved through the relays of intermediate nodes. Compared with traditional wireline networks, the unique characteristics of wireless networks pose fundamental challenges to the design of effective resource allocation algorithms that are optimal with respect to resource utilization and fair across different network flows. Particularly, the following issues of wireless networks need fresh treatment: (1) Interference of wireless communication. Flows not only contend at the same node (contention in the time domain), but also compete for shared channel if they are within the interference ranges of each other (contention in the spatial domain). (2) Multiple resource usage. Sending data from one wireless node to another needs to consume multiple resources, most notably wireless bandwidth and battery energy. (3) Autonomous communication entities. The wireless nodes usually belong to different autonomous entities. They may lack the incentive to contribute to the network functionality in a cooperative way. (4) Rate diversity. Wireless nodes can adaptively change the transmission bit rate based on perceived channel conditions. This leads to a wireless network with rate diversity, where competing flows within the interference range transmit at different rates. None of the existing resource allocation algorithms in wireless ad hoc networks have realistically considered end-to-end flows spanning multiple hops. Moreover, strategies proposed for wireline networks are not applicable in the context of wireless ad hoc network, due to its unique characteristics. In this dissertation, we propose a new price-based resource allocation framework in wireless ad hoc networks to achieve optimal resource utilization and fairness among competing end-to-end flows. We build our pricing framework on the notion of maximal cliques in wireless ad hoc networks, as compared to individual links in traditional wide-area wireline networks. Based on such a price-based theoretical framework, we present a two-tier iterative algorithm. Distributed across wireless nodes, the algorithm converges to a global network optimum with respect to resource allocations. Further, we present a price pair mechanism to coordinate multiple resource allocations, and to provide incentives simultaneously such that cooperation is promoted and the desired global optimal network operating point is reached by convergence with a fully decentralized self-optimizing algorithm. Such desired network-wide global optimum is characterized with the concept of Nash bargaining solution, which not only provides the Pareto optimal point for the network, but is also consistent with the fairness axioms of game theory. Finally, we present a channel aware price generation scheme to decompose the bit rate adjustment and the flow rate allocation. The allocation result achieves channel time fairness where user fairness and channel utilization is balanced. The major achievements of this dissertation are outlined as follows. It models a system-wide optimal operation point of a wireless network, and outlines the solution space of resource allocation in a multihop wireless network; It presents a price-based distributed resource allocation algorithm to achieve this global optimal point; It presents a low overhead implementation of the price-based resource allocation algorithm; It presents an incentive mechanism that enables the resource allocation algorithm when users are selfish

Joint Head Selection and Airtime Allocation for Data Dissemination in Mobile Social Networks

Mobile social networks (MSNs) enable people with similar interests to interact without Internet access. By forming a temporary group, users can disseminate their data to other interested users in proximity with short-range communication technologies. However, due to user mobility, airtime available for users in the same group to disseminate data is limited. In addition, for practical consideration, a star network topology among users in the group is expected. For the former, unfair airtime allocation among the users will undermine their willingness to participate in MSNs. For the latter, a group head is required to connect other users. These two problems have to be properly addressed to enable real implementation and adoption of MSNs. To this aim, we propose a Nash bargaining-based joint head selection and airtime allocation scheme for data dissemination within the group. Specifically, the bargaining game of joint head selection and airtime allocation is first formulated. Then, Nash bargaining solution (NBS) based optimization problems are proposed for a homogeneous case and a more general heterogeneous case. For both cases, the existence of solution to the optimization problem is proved, which guarantees Pareto optimality and proportional fairness. Next, an algorithm, allowing distributed implementation, for join head selection and airtime allocation is introduced. Finally, numerical results are presented to evaluate the performance, validate intuitions and derive insights of the proposed scheme