Cross-layer rate optimization for proportional fairness in multihop wireless networks with random access

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.

Fair resource allocation for end-to-end flows is an important yet challenging problem in multi-hop wireless networks. Recent research on fair resource allocation mainly focuses on two directions: 1) theoretical methods for joint optimization of scheduling and rate allocation, which are inherently hard to implement; 2) heuristic rate allocation solutions, which are practical for implementation, but simplify the scope of resource sharing regions using different neighborhood models. One key question that remains unanswered is how well these heuristic neighborhood-aware rate allocation solutions approximate the fair point defined in the theoretical optimal resource allocation framework. To evaluate the impact of different neighborhood models on end-to-end fairness, we first establish a baseline fairness model (i.e., proportional fairness) using the price-based resource allocation framework. In this framework, price represents the cost of the resource usage incurred by unit flow. The rate of a flow is directly linked to its price, which is the aggregated price of the links it traverses. The link price is the sum of the prices of all the resource sharing regions which it belongs to. Obviously, when the resource sharing regions are approximated by different neighborhood models in the heuristic solutions, link prices will manifest as different values. To quantify the deviations of these heuristic neighborhood-aware solutions from the baseline proportional fairness model, we introduce a normalized fairness index model. Six different neighborhood models are evaluated. Our study makes two significant observations: 1) symmetric knowledge on the construction of a neighborhood is important in achieving fairness. Such a knowledge has not been considered in any of the existing neighborhood-aware rate allocation algorithms; 2) while 1-hop neighborhood information brings noticeable gain in fairness, the knowledge of 2-hop neighborhood information does not necessarily bring additional benefit.

In this chapter, we explore techniques for capacity estimation and throughput maximization in multi-hop wireless networks. The specific problem we investigate is the following: how can we characterize the set of all feasible end-to-end connection throughput rate vectors which can be supported by the network (i.e., what is the network capacity), and how can we design cross-layer algorithms at the scheduling, routing, and transport layers which are guaranteed to operate the network close to its capacity? We approach this problem from three distinct perspectives which have greatly influenced research in this field: (1) throughput scaling in random geometric graphs whose nodes are distributed uniformly in space, (2) geometric packing and linear programming-based techniques for arbitrary networks, and (3) the dynamic back-pressure scheme based on queueing theoretic principles for achieving network stability. A recurring theme throughout this chapter is the role of geometric insights into the design and analysis of provably good algorithms for multi-hop wireless networks. We also include a brief survey of related developments in the field of cross-layer algorithms for multi-hop wireless networks.

This paper addresses the flow allocation problem in multi-hop wireless networks. We define and formulate a new interference model, referred to as the Node-based Interference Model, to better capture the behavior of medium access control protocols and the physical layer interference issues. Based on this model, we formulate the problem as a cross-layer network utility maximization problem that considers the coordination of the transport, MAC and physical layers, and avoid the maximum clique or independent set enumeration approach as adopted in most of the existing work. The objective of the problem is to maximize the aggregate network throughput while maintaining the fairness among flows. We then propose a gradient-based flow allocation algorithm by using the duality approach, and analyze the rate of convergence to the optimum for the proposed algorithm. The simulation results show that the proposed algorithm can rapidly converge to the optimum, and can also rapidly adapt to the changes in network topology and routing paths in different flow scenarios.

This paper considers a proportional fairness of end-to-end session rates in a multihop wireless network through the rate control framework. In multihop wireless networks, there are two classes of rate control problem. One focuses in optimizing the transmission attempt probabilities at the lower layers, but not the transmit powers while other problem is closely related to jointly optimal congestion control and power control. Proportional fairness is a fundamental concept in flow control problems. In this paper, we give in-depth analysis and show that the optimal solutions of these problems are proportionally fair provided that the objective functions are suitably chosen.

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.

Link quality measurement (LQM), i.e. packet reception ratio (PRR) measurement, is becoming an indispensable component in multihop wireless networks. However, in all the existing LQM mechanisms, a common fact is that a node's knowledge about the forward PRR from itself to its neighbor is informed by the neighbor. On the one hand, this receiver- dependent measurement provides accurate and timely updates on the link quality. On the other hand, it opens up a door for a malicious node to easily report a false measurement result to mislead the routing decision and degrade the system performance. In this paper, we analyze the security vulnerabilities in the existing LQM mechanisms and propose an efficient broadcast- based secure LQM (SLQM) mechanism, which prevents the malicious receiver from reporting a higher PRR than the actual one. We analyze the security strength and the cost of the proposed mechanism. Simulation results show that even when there are only 10% malicious nodes in the network, the average end-to-end throughput can be degraded by 50% compared with the normally operated network, which demonstrates the importance of employing SLQM mechanisms. To the best of our knowledge, this is the first work addressing the SLQM problem in multihop wireless networks.

A useful optimization problem to help solve various base station layout problems in multihop wireless networks is formulated. By solving the proposed generalized formula, the relation between the permissible largest number of hops and the minimum base station density necessary to cover an entire service area while guaranteeing a specified QoS is easily calculated. Our formula is extendable to other allocation problems by replacing parameters. The energy-cost transformation and scope of the multihop effect are also presented.

In this paper, we study the exposed terminal problem in multi-hop wireless networks with log-normal shadowing channels. Assuming that location information is known, we first calculate the success probability for the concurrent transmissions from exposed nodes. We then propose a new MAC protocol which schedules concurrent transmissions in the presence of log- normal shadowing, thus mitigating the exposed terminal problem and increasing network throughput. The performance of the proposed protocol is evaluated with ns-2 simulations, and it is shown to achieve considerable improvements in both end-to-end throughput and delay over the IEEE 802.11 MAC.

MIMO links enable concurrent transmissions of multiple independent data streams between a pair of nodes, which can significantly improve network throughput. In this paper, we study the stream control and scheduling problems in multihop wireless networks with MIMO links. We present a constant factor approximation algorithm as well as an efficient heuristic algorithm for stream control. Moreover, we extend the results to incorporate TDMA-based scheduling and present effective heuristic algorithms to solve the joint Stream Control and Scheduling Problem (SCSP), whose efficiency is justified by simulation results.

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

A basic problem in radio networks is the distributed setting of transmission schedules which allow collision free reuse of the same frequency. The common principle of existing transmission scheduling protocols is the time oriented, cyclic, assignment of transmission rights. Such protocols assume that nodes use same cycle, which is globally known. We introduce the concept of local cycles, and present the local cycle assignment algorithm. The local cycle of each node is a function of its neighborhood, so that no global knowledge is required. The algorithm is simple and thus practical for implementation. Supplementing its simplicity, the algorithm also exhibits provable properties: (1) The cycle length at each node is at most twice the optimal. (2) The delay of a message sent on the shortest hops path is a linear function of the number of nodes in the two hops neighborhood of the path.

Achieving optimal transmission throughput in data networks is known as a fundamental but hard problem. The situation is exacerbated in multi-hop wireless networks due to the interference among local wireless transmissions. In this paper, we propose a general modeling and solution framework for the throughput optimization problem in wireless networks. In our framework, data routing, wireless medium contention and network coding are jointly considered to achieve the optimal network performance. The primal-dual solution method in the framework represents a cross-layer optimization approach. It decomposes the original problem into data routing sub-problems at the network layer, and power allocation sub-problems at the physical layer. Various effective solutions are discussed for each sub-problem, verifying that our framework may handle the throughput optimization problem in an efficient and distributed fashion for a broad range of wireless network scenarios.

A selection problem is among the basic communication primitives in networks. In this problem at most k participating stations have to broadcast successfully their messages. This problem is especially important in packet radio networks, where simultaneous transmissions of many neighbors result in interference among delivered messages. This work focuses on a single-hop radio networks with n-stations, also called a multiple access channel, and considers both static and dynamic versions of the selection problem. We construct a family of efficient oblivious deterministic protocols based on selectors, one of them with selection time cO(klog(n/k)), and the second explicit construction with selection time cO(k polylog n). The first construction matches the lower bound Ω(klog(n/k)) on deterministic oblivious selection, while the second one is the first known explicit construction better than Θ(k2). In the dynamic case we introduce the model of dynamic requests, called k-streams, which generalizes the static model and the dynamic requests with at most k participants. We prove that each oblivious deterministic protocol has latency Ω(k2/log k), and on the other hand we prove the existence of the oblivious deterministic protocol with latency cO(k2log n). In view of the existence of the randomized oblivious protocol with expected latency cO(klog(n/k)), this shows that randomization is substantially better than determinism for dynamic setting. Selection problem can be applied to implement other communication primitives --- we demonstrate it in the example of broadcast problem in multi-hop ad-hoc radio networks. In particular, we design an adaptive deterministic protocol broadcasting in time cO(nlog D) in every D-hop radio network of n-stations.

In multi-hop wireless networks, we often encounter a situation where there are some candidate paths between source node S and destination node D, and have to choose a path from the candidates. Although ordinary routing protocols select paths with minimum hops, QoS (quality of service) routing protocols evaluate paths using measures of QoS, such as expected transmission count (ETX). In multi-hop wireless networks with QoS routing, it is an important issue to identify and characterize the best path from the viewpoint of network design. To do this, we proposed an approximate method to theoretically compute minimum route ETX in static one-dimensional random multi-hop wireless networks, and we theoretically identified the best path and gave an exact formula to compute minimum route ETX in static lattice multi-hop wireless networks. In this paper, we propose a new approximate method to theoretically analyze minimum route ETX in a two-dimensional random network. In this method, we extend the approximate method proposed to be used for two-dimensional random networks. We show this approximate method well describes minimum route ETX by comparing the numerical results of the theoretical methods and simulation results.