Jointly optimal congestion control, channel allocation and power control in multi-channel wireless multihop networks

In this paper, to increase end-to-end throughput and energy efficiency of the multi-channel wireless multihop networks, a framework of jointly optimize congestion control in the transport layer, channel allocation in the data link layer and power control in the physical layer is proposed. It models the network by a generalized network utility maximization (NUM) problem with elastic link data rate constraints. Through binary linearization and log-transformation, and after relaxing the binary constraints on channel allocation matrix, the NUM problem becomes a convex optimization problem, which can be solved by the gateway centralized through branch and bound algorithm with exponential time complexity. Then, a partially distributed near-optimal jointly congestion control, channel allocation and power control (DCCCAPC) algorithm based on Lagrangian dual decomposition technique is proposed. Performance is assessed through simulations in terms of network utility, energy efficiency and fairness index. Convergence of both centralized and distributed algorithms is proved through theoretic analysis and simulations. As the available network resources increase, the performance gain on network utility increases.     

Jointly optimized congestion control,forwarding strategy,and link scheduling in a named-data multihop wireless network

As a promising future network architecture, named data networking (NDN) has been widely considered as a very appropriate network protocol for the multihop wireless network (MWN). In named-data MWNs, congestion control is a critical issue. Independent optimization for congestion control may cause severe performance degradation if it can not cooperate well with protocols in other layers. Cross-layer congestion control is a potential method to enhance performance. There have been many cross-layer congestion control mechanisms for MWN with Internet Protocol (IP). However, these cross-layer mechanisms for MWNs with IP are not applicable to named-data MWNs because the communication characteristics of NDN are different from those of IP. In this paper, we study the joint congestion control, forwarding strategy, and link scheduling problem for named-data MWNs. The problem is modeled as a network utility maximization (NUM) problem. Based on the approximate subgradient algorithm, we propose an algorithm called ‘jointly optimized congestion control, forwarding strategy, and link scheduling (JOCFS)’ to solve the NUM problem distributively and iteratively. To the best of our knowledge, our proposal is the first cross-layer congestion control mechanism for named-dataMWNs. By comparison with the existing congestion control mechanism, JOCFS can achieve a better performance in terms of network throughput, fairness, and the pending interest table (PIT) size.     

A novel optimization-based bandwidth-aware minimum power multicast routing algorithm in green wireless networks

Multicast routing in wireless networks that possess the wireless multicast advantage could significantly reduce the power and energy consumption. However, this kind of multicast routing that only addresses the transmission radius coverage might not be able to meet the bandwidth requirement of the users. As a result, additional transmissions are required to incur more energy consumption and carbon dioxide emissions that make existing algorithms not applicable to bandwidth constrained applications. In this paper, for the first time, we address the bandwidth aware minimum power multicast routing problem in wireless networks where the objective function is to minimize the total power consumption subject to the users?? bandwidth requirements. This problem is a challenging cross-layer design problem that requires seamless and sophisticated integrated design in the network layer (multicast routing) and physical layer (bandwidth-aware wireless transmission and power control). We first formulate this problem as a mixed integer linear programming problem and then propose a Lagrangian relaxation based algorithm to solve this problem. Numerical results demonstrate that the proposed approach is a sound green networking algorithm that outperforms the existing power efficient multicast routing approaches under all tested cases, especially in large bandwidth request, fine radius granularity, large group size and sparse network.     

A multirate MAC protocol for reliable multicast in multihop wireless networks

Many multicast applications, such as audio/video streaming, file sharing or emergency reporting, are becoming quite common in wireless mobile environment, through the widespread deployment of 802.11-based wireless networks. However, despite the growing interest in the above applications, the current IEEE 802.11 standard does not offer any medium access control (MAC) layer support to the efficient and reliable provision of multicast services. It does not provide any MAC-layer recovery mechanism for unsuccessful multicast transmissions. Consequently, lost frames cannot be detected, hence retransmitted, causing a significant quality of service degradation. In addition, 802.11 multicast traffic is sent at the basic data rate, often resulting in severe throughput reduction.In this work, we address these issues by presenting a reliable multicast MAC protocol for wireless multihop networks, which is coupled with a lightweight rate adaptation scheme. Simulation results show that our schemes provide high packet delivery ratio and when compared with other state-of-the-art solutions, they also provide reduced control overhead and data delivery delay.     

基于QoS多播路由技术研究

随着Internet、移动网络和高性能网络的不断发展,在网络和不确定参数下具有QoS多播路由优化技术已成为网络及分布式系统领域的一个重要研究课题,这也是下一代Internet和高性能网络的难题。它吸引了许多爱好者。该文重点论述QoS多播路由需求,并简要阐明当前最新多目标优化问题的方法。定义了QoS多播路由作为多目标优化问题(即路由问题的网络模型)以及它是NP-复杂性问题。然后,重点讨论QoS多播路由的解决方法,包括约束多播树、多目标优化、计算智能和人工智能等。最后,文章建议一个约束多播路由结构和讨论一些将来的研究展望。     

Rate-lifetime tradeoff for reliable communication in wireless sensor networks

The network lifetime and application performance are two fundamental, yet conflicting, design objectives in wireless sensor networks. There is an intrinsic tradeoff between network lifetime maximization and application performance maximization, the latter being often correlated to the rate at which the application can send its data reliably in sensor networks. In this paper we study this tradeoff by investigating the interactions between the network lifetime maximization problem and the rate allocation problem with a reliable data delivery requirement. Severe bias on the allocated rates of some sensor nodes may exist if only the total throughput of the sensor network is maximized, hence we enforce fairness on source rates of sensor nodes by invoking the network utility maximization (NUM) framework. To guarantee reliable communication, we adopt the hop-by-hop retransmission scheme. We formulate the network lifetime maximization and fair rate allocation both as constrained maximization problems. We characterize the tradeoff between them, give the optimality condition, and derive a partially distributed algorithm to solve the problem. Furthermore, we propose an approximation of the tradeoff problem using NUM framework, and derive a fully distributed algorithm to solve the problem.     

Optimization-based resource allocation in communication networks

The continuously growing number of applications competing for resources in current communication networks highlights the necessity for efficient resource allocation mechanisms to maximize user satisfaction. Optimization Theory can provide the necessary tools to develop such mechanisms that will allocate network resources optimally and fairly among users. The aim of this paper is to provide a starting point for researchers interested in applying optimization techniques in the resource allocation problem for current communication networks. To achieve that we, first, describe the fundamental optimization theory tools necessary to design optimal resource allocation algorithms. Then, we describe the Network Utility Maximization (NUM) framework, a framework that has already found numerous applications in network optimization, along with some recent advancements of the initial NUM framework. Finally, we summarize some of our recent work in the area and discuss some of the remaining research challenges towards the development of a complete optimization-based resource allocation protocol.     

A joint maximum likelihood algorithm for simultaneous track correlation and sensorbias estimation

In this study a joint maximum likelihood （JML） algorithm was developed to solve problems re- garding interdependent and contradictory relationships between track correlation and sensor bias estimation in multi-sensor information fusion systems. First, the relationships between track correlation and sensor bias estimation of a multi-sensor system were analyzed. Then, based on these relationships, a JML function of the track correlation and sensor bias estimation was developed, while an iterative two-step optimization procedure was adopted to solve the JML function. In addition, transformation of sensor bias from Cartesian coordinates to polar coordinates and a complete design of track quality and ambiguity processing were provided. Finally, several Monte Carlo simulations were built to test the effect of target density and different sensor bias in the JML algorithm. Simulation results showed that the JML algorithm presented in this paper had a higher correct correlation rate and more accurate sensor bias estimation than traditional methods, demonstrating that the JML algorithm had good performance.     

无线多跳网络中吞吐量优化的多播路由算法研究

现有网络中提高多播吞吐量的算法通常是以提高链路速率为目的,但单纯地提高链路速率而忽略多播树的度也限制了多播吞吐量的提高。主要研究了多跳无线网络中多播吞吐量最优化问题,深入分析了无线多跳网络特点,并在综合考虑链路速率和多播树度对多播吞吐量影响的基础上,提出了应用于节点发射功率相同环境下的UUP_MTOA算法和应用于节点发射功率不同环境下的UNP_MTOA算法。通过仿真实验与同类近似最优化算法相比,UUP_MTOA算法和UNP_MTOA算法能够获得更高的吞吐量,更适应于多跳无线网络环境。     

Standard clock simulation and ordinal optimization applied to admission control in integrated communication networks

In this paper we apply the ideas of ordinal optimization and the technique of Standard Clock (SC) simulation to the voice-call admission-control problem in integrated voice/data multihop radio networks. This is an important problem in networking that is not amenable to exact analysis by means of the usual network modeling techniques. We first describe the use of the SC approach on sequential machines, and quantify the speedup in simulation time that is achieved by its use in a number of queueing examples. We then develop an efficient simulation model for wireless integrated networks based on the use of the SC approach, which permits the parallel simulation of a large number of admission-control policies, thereby reducing computation time significantly. This model is an extension of the basic SC approach in that it incorporates fixed-length data packets, whereas SC simulation is normally limited to systems with exponentially distributed interevent times. Using this model, we demonstrate the effectiveness of ordinal-optimization techniques, which provide a remarkably good ranking of admission-control policies after relatively short simulation runs, thereby facilitating the rapid determination of good policies. Moreover, we demonstrate that the use of crude, inaccurate analytical and simulation models can provide highly accurate policy rankings that can be used in conjunction with ordinal-optimization methods, provided that they incorporate the key aspects of system operation.     

Joint Source Coding and Network-Supported Distributed Error Control for Video Streaming in Wireless Multihop Networks

Real-time video communication over wireless multihop networks has gained significant interest in the last few years. In this paper, we focus our attentions on the problem of source coding and link adaptation for packetized video streaming in wireless multihop networks when network nodes are media-aware. We consider a system where source coding is employed at the video encoder by selecting the encoding mode of each individual macro-block, while error control is exercised through application-layer retransmissions at each media-aware network node. For this system model, the contribution of each communication link on the end-to-end video distortion is considered separately in order to achieve globally optimal source coding and ARQ error control. To reach the globally optimal solution, we formulate the problem of joint source and distributed error control (JSDEC) and devise a low-complexity solution algorithm based on dynamic programming. Extensive experiments have been carried out on the basis of H.264/AVC codec to demonstrate the effectiveness of the proposed algorithm over the existing joint source and channel coding (JSCC) algorithm in terms of PSNR perceived at the decoder under time-varying multihop wireless links.     

Energy efficient multicast routing in ad hoc wireless networks

In this paper, we discuss the energy efficient multicast problem in ad hoc wireless networks. Each node in the network is assumed to have a fixed level of transmission power. The problem of our concern is: given an ad hoc wireless network and a multicast request, how to find a multicast tree such that the total energy cost of the multicast tree is minimized. We first prove this problem is NP-hard and it is unlikely to have an approximation algorithm with a constant performance ratio of the number of nodes in the network. We then propose an algorithm based on the directed Steiner tree method that has a theoretically guaranteed approximation performance ratio. We also propose two efficient heuristics, node-join-tree (NJT) and tree-join-tree (TJT) algorithms. The NJT algorithm can be easily implemented in a distributed fashion. Extensive simulations have been conducted to compare with other methods and the results have shown significant improvement on energy efficiency of the proposed algorithms.     

Fundamental limits on end-to-end throughput of network coding in multi-rate and multicast wireless networks

This paper investigates the interaction between network coding and link-layer transmission rate diversity in multi-hop wireless networks. By appropriately mixing data packets at intermediate nodes, network coding allows a single multicast flow to achieve higher throughput to a set of receivers. Broadcast applications can also exploit link-layer rate diversity, whereby individual nodes can transmit at faster rates at the expense of corresponding smaller coverage area. We first demonstrate how combining rate-diversity with network coding can provide a larger capacity for data dissemination of a single multicast flow, and how consideration of rate diversity is critical for maximizing system throughput. Next we address the following question: given a specific topology of wireless nodes, what is the maximum rate that can be supported by the resultant network exploiting both network coding and multi-rate? We present a linear programming model to compute the maximal throughput that a multicast application can achieve with network coding in a rate-diverse wireless network. We also present analytical results where we observe noticeably better throughput than traditional routing. This suggests there is opportunity for achieving higher throughput by combining network coding and multi-rate diversity.     

Utility-based scheduling in wireless multi-hop networks over non-deterministic fading channels

In this paper, an innovative scheduling scheme is proposed for interference-limited wireless multi-hop networks with non-deterministic fading channels. The scheduling problem is considered as a network utility maximization (NUM) problem subject to link rate constraints. By jointly taking into account of the link scheduling and the statistical variations of signal and interference power, the convex sets for the NUM are derived. Two types of non-deterministic fading channels (i.e., Rayleigh fading channel and Ricean fading channel) are characterized into our NUM models as examples. To solve the convex optimization problem, the subgradient projection method based on dual decomposition is employed. Then, a heuristic algorithm is designed for the TDM mode wireless multi-hop networks by minimizing the discrepancy between the expected network cost and the optimal one in each timeslot. At last, the source–destination session rate and network utility are evaluated in a dedicated wireless multi-hop network scenario. The numerical results demonstrate that the session rates convergence and the network utility is improved by our proposed scheme.     

A new territory of multi-user variable remote control for interactive TV

Unlike passive analog TV, interactive TV (iTV) is the next step toward interactivity that offers users a friendly interactive experience. As there are fewer studies focused on multi-user interaction in a local environment, we concentrate on multi-user interaction with families, especially within a home information system. Therefore, we propose a control service framework “MVC-iTV,” based on distributed computing and Machine-to-Machine (M2M) communications, in which external displays (TVs or projectors) and handheld devices can be used for controlling iTV services by several members of the family at the same time, without any relocation. Further, the new remote control framework can free users from the restrictions of using one remote controller. The experiment results indicate that the MVC-iTV framework is applicable to the iTV service and that users can operate the service in any visible environment via wireless networking technologies. Besides, requirements of the hardware compatibility of the TV appliance and remote controller will be reduced in the MVC-iTV framework.     

Wireless MediaNets: application-driven next-generation wireless IP networks

Thanks to the explosive creation of multimedia contents, the pervasive adoption of multimedia coding standards and the ubiquitous access of multimedia services, multimedia networking is everywhere in our daily lives. Unfortunately, the existing best effort IP network infrastructure, originally designed with little real-time QoS requirement, has started to suffer from performance degradation on emerging multimedia networking applications. This inadequacy problem is further deepened by the prevalence of last/first-mile wireless networking, such as Wi-Fi, mobile WiMAX, and many wireless sensors and ad-hoc networks. This can be evidenced by more and more fragmentation of application-driven IP-based networks, such as for power grid distribution, networked security surveillance, intelligent transportation communication, and many other sensor networks. To overcome the QoS challenges, the next generation wireless IP networks have to be architected in a top-down manner, i.e., application-driven layered protocol design. More specifically, based on the application media data, compression schemes are applied, the subsequent Network, MAC- and PHY-layered protocols need to be accordingly or jointly enhanced to reach the optimal performance. This is the fundamental concept behind the design of Wireless MediaNets. In this survey paper, I will address the QoS challenges specifically encountered in video over heterogeneous wireless broadband networks and address several application-driven Wireless MediaNet solutions based on effective cross-layer integration of APP and MAC/PHY layers. More specifically, the congestion control for achieving airtime fairness of video streaming to maximize the link adaptation performance of Wi-Fi, the minimum latency event-driven data exchange for distributed wireless ad-hoc sensor networks, and the opportunistic multicast of scalable video live streaming over mobile WiMAX.     

面向MIMO多跳无线网络的多用户视频传输优化方法

MIMO(multi-input multi-output)作为一种有效提高无线信道可靠性和带宽的新兴技术,已在无线网络中得到广泛应用.但是,如何利用MIMO在多跳无线网络中为多用户提供高质量视频服务,尚未得到广泛关注.多跳无线链路之间的共信道干扰是需要解决的关键问题.提出一种面向多跳无线网络的多用户视频传输方法,利用链路选择、MIMO的空间复用和空间分集等特点,减少链路间的共信道干扰,最大化多用户的平均视频传输质量.通过对链路选择和天线分组进行建模,将上述传输策略抽象成一个最优化问题,该问题是一个NP-hard问题.为了降低求解复杂度,引入遗传算法来求解链路选择问题.该算法采用基因遗传“优胜劣汰”的特性,在保证性能的同时,大幅度降低了求解复杂度.另外,由于遗传算法中每条“染色体”的“优劣”与天线分组策略有关,因此结合可伸缩视频的失真模型,将天线分组问题转化为一个标准的0/1背包问题,并在搜索时采用深度优先和分支限界技术,进一步降低算法复杂度.实验结果表明,所提出的链路选择算法和天线分组算法均能显著提高用户接收视频的质量.     

A cross-layer optimization framework for joint channel assignment and multicast routing in multi-channel multi-radio wireless mesh networks

Existing literature on multicast routing protocols in wireless mesh networks (WMNs) from the view point of the links involved in routing are divided into two categories: schemes are aimed at multicast construction with minimal interference which is known as NP hard problem. In contrast, other methods develop network-coding-based solutions with the main objective of throughput maximization, which can effectively reduce the complexity of finding the optimal routing solution from exponential to polynomial time. The proposed framework in this paper is placed in the second category. In multi-channel multi-radio WMNs (MCMR WMNs), each node is equipped with multiple radios, each tuned on a different channel. In this paper, for the first time, we propose a cross-layer convex optimization framework for joint channel assignment and multicast throughput maximization in MCMR WMNs. The proposed method is composed of two phases: in the first phase, using cellular learning automata, channels are assigned to the links established between the radios of the nodes in a distributed fashion such that the minimal interference coefficient for each link is provided. Then, the resultant channel assignment scheme is utilized in the second phase for throughput maximization within an iterative optimization framework based on Lagrange relaxation and primal problem decomposition. We have conducted many experiments to contrast the performance of our solution against many representative approaches.     

基于遗传算法的多用户检测技术分析

CDMA移动通信系统中的最优多用户检测问题是一个NP完备组合优化问题,遗传算法是求解这类问题的有效方法。通过分析CDMA系统多用户检测模型,对几种基于不同遗传算法的多用户检测方法的检测性能进行了实验仿真。仿真结果表明：基于多种群并行进化的分布式遗传算法更适合于多用户检测技术,具有较低的误码率和较强的抗远近效应能力。