How to correctly use the protocol interference model for multi-hop wireless networks

This paper addresses the Quality of Service (QoS) degradation problem of wireless relay node failures in multihop Worldwide interoperable Microwave Access (WiMAX) and Long Term Evolution (LTE) networks. In general, node protection in a communication network increases the reliability of the traffic flow from source to destination. For wireless networks, implementing the traditional 1+1 protection scheme increases the capital cost, as resources cannot be fully utilized. On the other hand, the design and implementation of the 1:N protection scheme in wireless networks for greater value of N (> 2) is very difficult, due to wireless network coverage and the physical layer design. To overcome the above drawbacks, a technique based on network coding is proposed for node protection in multihop wireless networks. In multihop wireless networks, few research efforts are concentrated on node protection schemes using network coding. Moreover, to best of our knowledge, no reports have been published on measuring the QoS performance for node protection in 4G wireless networks using network coding. In this paper, we first describe the node protection scheme using XOR network coding for multihop 4G wireless networks. Then, we measure the QoS performance, such as packet delivery ratio (PDR), latency and jitter, for different scenarios. The scenarios include a failure of a single relay node and failures of two relay nodes with and without our protection scheme and user's mobility. The simulation results show that the QoS performance with protection against a single relay node failure and failures of two relay nodes are very close to that of no failure scenario, while the network reliability increases due to the protection mechanism. Also, we report a decoding problem in multihop wireless networks using XOR network coding.

The efficient scheduling of transmission links in a wireless network with a certain optimization objective and subject to the interference and network flow constraints plays a central role in wireless networking research. As an alternative to traditional mathematical analysis, data-driven learning methods have shown promise in solving difficult problems by extracting knowledge from experiences and inspired applications of machine learning in wireless networking. In this paper, we focus on tackling the fundamental scheduling issue in multi-hop wireless networks with machine learning, facing the great challenges of the involvement of non-differentiable operations and the consideration of variable network topologies. To address these issues, we propose a reinforcement learning-based method to solve a class of network flow problems under the protocol interference model. Learning from experience, the proposed approach develops a strategy to sequentially select optimum subsets of links to transmit simultaneously to maximize the system throughput without causing interference. The model structure is designed in a way that incorporates network topological information to allow a flexible number of network nodes, and allows non-differentiable decision operation to pass informative gradient information. Experiments with synthetic and real-world deployment data demonstrate that the proposed algorithm achieves close-to-optimum performance at a significantly reduced time cost.

Gossiping is to broadcast the message of every node to all the other nodes in multi-hop wireless networks (MWNs). This operation plays an important role and is widely used in MWNs. Interference-aware gossiping scheduling (IAGS) aims to provide an interference-free scheduling for gossiping with the minimum latency. Previous work on IAGS mostly assumes that nodes are always active, and thus is not suitable for duty-cycled scenarios. In this paper, we investigate the IAGS problem in uncoordinated duty-cycled multi-hop wireless networks (IAGS-UDC problem) under protocol interference model and unbounded-size message model. We prove that the IAGS-UDC problem is NP-hard. We propose a novel approximation algorithm called MILD for this problem. The MILD algorithm achieves an approximation ratio of 3β 2(Δ + 6)|T|, where β is \(\lceil \frac{2}{3}(\alpha+2)\rceil\), α denotes the ratio of the interference radius to the transmission radius, Δ denotes the maximum node degree of the network, and |T| denotes the number of time-slots in a scheduling period. Moreover, the number of transmissions scheduled by the MILD algorithm is at most 3 times as large as the minimum number of transmissions.KeywordsGossiping schedulinginterferenceduty cyclemulti-hop wireless networks

Fractional Link scheduling is one of the most fundamental problems in wireless networks. The prevailing approach for shortest fractional link scheduling is based on a reduction to the maximum-weighted independent set problem, which itself may not admit efficient approximation algorithms. In addition, except for the wireless networks under the protocol interference model, none of the existing scheduling algorithms can produce a link schedule with explicit upper bounds on its length in terms of the link demands. As the result, the polynomial approximate capacity regions in these networks remain blank. This paper develops a purely combinatorial paradigm for fractional link scheduling in wireless networks. In addition to the superior efficiency, it is able to provide explicit upper bounds on the lengths of the produced link schedule. By exploiting these upper bounds, polynomial approximate capacity regions are derived. The effectiveness of this new paradigm is demonstrated by its applications in wireless networks under the physical interference model and wireless MIMO networks under the protocol interference model.

Wireless multi-hop local area networks use in general scheduling schemes that assume the network capacity to be known. Indeed in most of the throughput-optimal algorithms the sources are assumed to send at a rate within the capacity region. However, measurements made on real deployments show that the network capacity is usually difficult to characterize and also time-varying. It is therefore important to understand how the network behaves when the sources attempt to transmit at a rate above capacity. Toward this goal, we show 3-phase regime in the effect of the input rate λ on the end-to-end throughput μ of a multi-hop network. First, when λ is smaller than a threshold λ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> , μ is an increasing function of λ. Second, when λ is larger than another threshold λ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> > λ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> , μ is independent of λ. Third, when λ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> <; λ <; λ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> , μ decreases with λ. To understand this phenomenon, we capture the relation between the end-to-end throughput and the queue stability with a mathematical model that allows us to explain and derive the exact values of the transition points λi. We then validate experimentally our simulation results with measurements on a testbed composed of five wireless routers.

Connected dominating set (CDS) has a wide range of applications in multihop wireless networks. The Minimum CDS problem has been studied extensively in multihop wireless networks with uniform communication ranges. However, in practice, the nodes may have different communication ranges either because of the heterogeneity of the nodes, or due to interference mitigation, or due to a chosen range assignment for energy conservation. In this paper, we present a greedy approximation algorithm for computing a Minimum CDS in multihop wireless networks with disparate communications ranges and prove that its approximation ratio is better than the best one known in the literature. Our analysis utilizes a tighter relation between the independence number and the connected domination number.

In this study we investigate the interaction between TCP and MAC layer in a wireless multi-hop network. This type of network has traditionally found applications in the military (automated battlefield), law enforcement (search and rescue) and disaster recovery (flood, earthquake), where there is no fixed wired infrastructure. Wireless "ad-hoc" multi-hop networks have previously been proposed for nomadic computing applications. Key requirements in all the above applications are reliable data transfer and congestion control, features that are generally supported by TCP. Unfortunately, TCP performs on wireless in a much less predictable way than on wired protocols. Using simulation, we provide new insight into two critical problems of TCP over wireless multi-hop. The first is the conflict between data packets and ACKs, which causes TCP performance to degrade for window sizes greater than 1 packet. The second is the interaction between MAC and TCP layer backoff timers which causes severe unfairness and capture conditions. In the paper, we identify these problems in several representative simulation runs on various topologies and traffic patterns and indicate possible remedies to improve TCP efficiency over a wireless multi-hop network.

The increasing use of multi-hop wireless networks and the growing demand of bandwidth-intensive multimedia applications are the driving force to explore innovative techniques that can enhance the capacity of multi-hop wireless networks. The commonly used omni-directional antennas limit the spatial reusability of the wireless channel and hence reduce the available capacity of wireless networks. On the contrary, bandforming antennas, that enable directional transmissions and receptions, can overcome the aforementioned limitation. With the recent advances in signed processing and antenna technologies, smart beamforming antennas have become feasible in compact sizes and suitable prices and hence pertinent to multi-hop wireless networks. However, lack of appropriate control over the antenna beamforming may deteriorate the overall performance even below the level achieved by omni-directional antennas. Moreover, beamforming antennas introduce unprecedented challenges including deafness and directional hidden terminal problems. Hence, it is important to design efficient mechanisms for both Medium Access Control (MAC) and routing to deal with these challenges that hinder the full exploitation of spatial reusability offered by smart beamforming antennas. In this dissertation, we develop an analytical framework for modeling directional contention-based MAC protocols, which is, up to our knowledge, the first model to include deafness in the analysis. We show that deafness can severely limit the network capacity. Based on the insights gained from our analysis of the limitations of the existing solutions, we propose a novel opportunistic directional MAC protocol for multi-hop wireless networks with beamforming antennas. The proposed MAC protocol employs a new backoff mechanism that aims at minimizing the unnecessary idle waiting time, which is a key factor in leveraging the spatial reuse. Through extensive simulations, we demonstrate that the proposed MAC protocol enhances the performance in terms of throughput, delay, packet delivery ratio and fairness. We have also addressed the question about the theoretical capacity gain achieved by beamforming antennas. We derive a generic interference model that can accommodate any antenna radiation pattern and show that the capacity gain is significant even when realistic antenna radiation patterns are used. Since smart beamforming antennas can significantly spare the network resources, they can be utilized to provide Quality of Service (QoS) guarantees. We study the bandwidth-guaranteed routing problem in contention-based multi-hop wireless networks with beamforming antennas. We first present an analysis for the wireless links interdependencies in a contention-based environment in the presence of beamforming, which helps in our formulation of the QoS routing problem as a mixed-integer non-linear optimization problem. We then propose a routing and admission control algorithm for its solution. Our simulation results demonstrate the accuracy of our analysis and the ability of our proposed algorithm to find bandwidth-guaranteed routes. In summary, the analysis and design approaches, adopted in this dissertation, enhance the throughput of multi-hop wireless networks by grasping the transmission opportunities offered by smart beamforming antennas while dealing with the beamforming-related challenges at the MAC and network layers, which otherwise limit the spatial reusability of the wireless channel.

In time division multiple access (TDMA)-based wireless mesh networks, interference relationships should be considered when time slots are assigned to links. In graph theory-based time slot assignment algorithms, the protocol interference model is widely used to determine radio interference information, although it is an inaccurate model of actual radio interference. On the other hand, the signal-to-interference-plus-noise-ratio model (SINR model) gives more accurate interference relationships but is difficult to apply to time slot assignment algorithms since the radio interference information cannot be determined before time slot assignment. In this paper, we investigate the effect of the parameters of the protocol interference model on the accuracy of the interference relationships determined using this model. Specifically, after assigning time slots to links based on the protocol interference model with various interference ratios, which is the major parameter of the protocol interference model, we compare the interference relationship among links in the protocol interference and SINR models. Through simulation experiments, we show that accuracy of the protocol interference model is improved by up to 15% by adjusting the interference ratios of the protocol interference model.

Connected dominating set (CDS) has a wide range of applications in mutihop wireless networks. The Minimum CDS problem has been studied extensively in mutihop wireless networks with uniform communication ranges. However, in practice the nodes may have different communication ranges either because of the heterogeneity of the nodes, or due to interference mitigation, or due to a chosen range assignment for energy conservation. In this paper, we present a greedy approximation algorithm for computing a Minimum CDS in multihop wireless networks with disparate communications ranges and prove that its approximation ratio is better than the best one known in the literature. Our analysis utilizes a tighter relation between the independence number and the connected domination number.

Beaconing is a primitive communication task in which every node locally broadcasts a packet to all its neighbors within a fixed distance. Assume that all communications proceed in synchronous time-slots and each node can transmit at most one fixed-size packet in each time-slot. The problem Minimum-latency beaconing schedule (MLBS) in multihop wireless networks seeks a shortest schedule for beaconing subject to the interference constraint. MLBS has been intensively studied since the mid-1980s, but all assume the protocol interference model with uniform interference radii. In this paper, we first present a constant-approximation algorithm for MLBS under the protocol interference model with arbitrary interference radii. Then, we develop a constant-approximation algorithm for MLBS under the physical interference model. Both approximation algorithms have efficient implementations in a greedy first-fit manner.

Information-theoretic broadcast channels (BCs) and multiple-access channels (MACs) enable a single node to transmit data simultaneously to multiple nodes, and multiple nodes to transmit data simultaneously to a single node, respectively. In this paper, we address the problem of link scheduling in multihop wireless networks containing nodes with BC and MAC capabilities. We first propose an interference model that extends protocol interference models, originally designed for point-to-point channels, to include the possibility of BCs and MACs. Due to the high complexity of optimal link schedulers, we introduce the Multiuser Greedy Maximum Weight algorithm for link scheduling in multihop wireless networks containing BCs and MACs. Given a network graph, we develop new local pooling conditions and show that the performance of our algorithm can be fully characterized using the associated parameter, the multiuser local pooling factor. We provide examples of some network graphs, on which we apply local pooling conditions and derive the multiuser local pooling factor. We prove optimality of our algorithm in tree networks and show that the exploitation of BCs and MACs improve the throughput performance considerably in multihop wireless networks.

In this paper, we present experimental studies on Multi-channel Multi-radio Multi-hop (M3) wireless networks. The interference of multiple channels and multiple radios is studied. The result may help to understand effect of multi-channel and multi-radio in real system and is useful as reference for network performance optimization. We evaluate the coexistence of real-time traffic and best-effort traffic in multi-hop wireless networks. Our experiments show that coordination among wireless nodes is critical for optimal network performance, especially in the scenarios with quality of service (QoS) requirements. To perform the experiments, an M3 testbed with 32 nodes is built. The testbed is based on Windows operating system and provides convenient programming interface and management tools. The architecture and key modules of the testbed design are described.

MaxWeight algorithm, a.k.a., back-pressure algorithm, has received much attention as a viable solution for dynamic link scheduling in multi-hop wireless networks. The basic principle of the MaxWeight algorithm is to select a set of interference-free links with the maximum overall link weights in the network, where the link weight is determined by the queue difference between the transmitter and the receiver. While the throughput-optimality of the MaxWeight algorithm is well understood in the literature, the energy consumption induced by the MaxWeight algorithm is less studied, which is of great interest in energy-constrained wireless networks such as wireless sensor networks. In this paper, we propose an energy-conserving scheduling scheme, a.k.a., minimum energy scheduling (MES) algorithm for multi-hop wireless networks with stochastic traffic arrivals and time-varying channel conditions. We show that our algorithm is energy optimal in the sense that the proposed MES algorithm can achieve an energy consumption which is arbitrarily close to the global minimum solution. Moreover, the energy efficiency of the MES algorithm is achieved without losing the throughput- optimality. In other words, the proposed MES algorithm is still throughput optimal whereas the average consumed energy in the network is significantly reduced, as compared to the traditional MaxWeight algorithm. The theoretical results are substantiated via simulations.

MaxWeight algorithm, a.k.a., back-pressure algorithm [1]-[4], has received much attention as a viable solution for dynamic link scheduling in multi-hop wireless networks. The basic principle of the MaxWeight algorithm is to select a set of interference-free links with the maximum overall link weights in the network, where the link weight is determined by the queue difference between the transmitter and the receiver. While the throughput-optimality of the MaxWeight algorithm is well understood in the literature, the energy consumption induced by the MaxWeight algorithm is less studied, which is of great interest in energy-constrained wireless networks such as wireless sensor networks. In this paper, we propose a minimum energy scheduling (MES) algorithm for multi-hop wireless networks with stochastic traffic arrivals and time-varying channel conditions. We show that our algorithm is energy optimal in the sense that the proposed MES algorithm can achieve an energy consumption which is arbitrarily close to the global minimum solution. Moreover, the energy efficiency of the MES algorithm is achieved without losing the throughput-optimality. In other words, the proposed MES algorithm is still throughput optimal whereas the average consumed energy in the network is significantly reduced, as compared to the traditional MaxWeight algorithm. The theoretical results are substantiated via simulations.