一种环境感知的无线Mesh网络自适应QoS路径选择算法

本文针对如何改善无线多跳Mesh网络的服务质量,满足无线多媒体业务对数据传输的带宽、时延、抖动的要求等问题,研究了一种基于无线信道状态和链路质量统计的MAC层最大重传次数的自适应调整算法。该算法通过对无线Mesh网络的无线信道环境的动态感知,利用分层判断法区分无线分组丢失的主要原因是无线差错还是网络拥塞导致,实时调整MAC层的最佳重传次数,降低无线网络中的分组冲突概率。基于链路状态信息的统计和最大重传策略,提出了一种启发式的基于环境感知的QoS路由优化机制HEAOR。该算法通过动态感知底层链路状态信息,利用灰色关联分析法自适应选择最优路径,在不增加系统复杂度的基础上,减少链路误判概率,提高传输效率。NS2仿真结果表明,HEAOR算法能有效减少重路由次数,降低链路失效概率,提高网络的平均吞吐率。本文提出的方法不仅能够优化MAC层的重传,而且通过发现跨层设计的优化参数实现对路径的优化选择。      

Lifetime optimization for reliable broadcast and multicast in wireless ad hoc networks

In this paper, we consider the reliable broadcast and multicast lifetime maximization problems in energy‐constrained wireless ad hoc networks, such as wireless sensor networks for environment monitoring and wireless ad hoc networks consisting of laptops or PDAs with limited battery capacities. In packet loss‐free networks, the optimal solution of lifetime maximization problem can be easily obtained by tree‐based algorithms. In unreliable networks, we formulate them as min–max tree problems and prove them NP‐complete by a reduction from a well‐known minimum degree spanning tree problem. A link quality‐aware heuristic algorithm called Maximum Lifetime Reliable Broadcast Tree (MLRBT) is proposed to build a broadcast tree that maximizes the network lifetime. The reliable multicast lifetime maximization problem can be solved as well by pruning the broadcast tree produced by the MLRBT algorithm. The time complexity analysis of both algorithms is also provided. Simulation results show that the proposed algorithms can significantly increase the network lifetime compared with the traditional algorithms under various distributions of error probability on lossy wireless links. Copyright © 2012 John Wiley & Sons, Ltd.     

A packet-reordering solution to wireless losses in transmission control protocol

The wireless medium may cause substantial packet losses, rendering Transmission Control Protocol (TCP) inefficient. We propose a cross-layer solution by combining link-layer retransmission techniques and a solution for TCP packet reordering. It is costly to conduct link-layer retransmission with the constraint of orderly packet delivery. We require the link layer to provide reliable packet delivery, but without orderly delivery guarantee, thus transforming the problem of high packet error rates to the problem of packet reordering. The latter is dealt with by enhancing TCP with a solution for packet reordering. We justify our design by analyzing both general scenarios and the case of IEEE 802.11n. Our simulation results demonstrate that the proposed method is effective in improving TCP connection goodput in wireless networks.     

Cross-layer optimization for SVC video delivery over the IEEE 802.11e wireless networks

The Scalable Video Coding (SVC) standard extends the H.264/AVC with scalability support and is effective to adapt bitrate to the time-varying wireless channel bandwidth. In this paper, we propose a cross-layer optimization scheme, which includes packet prioritization and QoS mapping, for the delivery of SVC over the IEEE 802.11e wireless networks. The proposed structure enables interaction among different network layers, providing differentiated services for video packets. Our cross-layer optimization performs with the following information: (i) SVC packet prioritization at the application layer, (ii) service differentiation at the MAC layer, and (iii) interface queue (IFQ) occupation status at the link layer. We formulate the QoS mapping problem as a joint optimization of access category (AC) assignment and IFQ control. A novel and efficient solution is proposed to reduce the computational complexity of the joint optimization problem. Simulation results show that the proposed approach achieves notable improvement when compared to conventional methods.     

Security enhancement with joint transmit antenna selection and transmit beamforming under energy harvesting constraints

This paper considers a multiuser multiple‐input single‐output (MISO) broadcasting system with simultaneous wireless information and power transfer (SWIPT), which consists of one information receiver (IR) and several energy harvesting receivers (ERs) which are capable of eavesdropping the legitimate signals. For reducing cost and hardware complexity, transmit antenna selection (TAS) is applied in the transmitter. We aim to maximize the achievable secrecy rate under the individual energy harvesting constraint at the ERs and the transmit power constraint at the transmitter by jointly optimizing TAS, transmit beamforming, and artificial noise (AN). The joint optimization problem is a non‐convex mixed integer programming problem. We apply variable replacements to decouple the variable couplings and relax and approach the binary constraint by the difference of two convex constraints. Afterwards, penalty method and constrained concave convex procedure (CCCP) are applied to transform the relaxed problem into a sequence of semi‐definiteness programming (SDP) problems. Simulation results shows that our proposed joint optimization scheme is superior over existing non‐joint optimization schemes. This paper studies the joint transmit antenna selection (TAS), transmit beamforming, and artificial noise (AN) optimization in a multiple‐input multiple‐output (MISO) wiretap system with simultaneous wireless information and power transfer (SWIPT). The joint optimization problem is nonconvex and we propose a penalty method based scheme to solve it. The simulation results show that our joint optimization scheme is superior to other non‐joint optimization schemes.     

Throughput and resource optimization for adaptive coding‐based random access networks with correlated sources

Modern wireless communication networks frequently have lower application throughput due to higher number of collisions and subsequent retransmission of data packets. Moreover, these networks are characterized by restricted computational capacity due to limited node‐battery power. These challenges can be assessed for deploying fast, reliable network design with resource‐restrained operation by means of concurrent optimization of multiple performance parameters across different layers of the conventional protocol stack. This optimization can be efficiently accomplished via cross‐layer design with the aid of network coding technique and optimal allocation of limited resources to wireless links. In this paper, we evaluate and analyze intersession coding across several source–destination pairs in random access ad hoc networks with inherent power scarcity and variable capacity links. The proposed work addresses the problem of joint optimal coding, rate control, power control, contention, and flow control schemes for multi‐hop heterogeneous networks with correlated sources. For this, we employ cross‐layer design for multiple unicast sessions in the system with network coding and bandwidth constraints. This model is elucidated for global optimal solution using CVX software through disciplined convex programming technique to find the improved throughput and power allocation. Simulation results show that the proposed model effectively incorporates throughput and link power management while satisfying flow conservation, bit error rate, data compression, power outage, and capacity constraints of the challenged wireless networks. Finally, we compare our model with three previous algorithms to demonstrate its efficacy and superiority in terms of various performance metrics such as transmission success probability, throughput, power efficiency, and delay.     

An adaptive opportunistic retransmission control scheme environment-aware-based for wireless multimedia Mesh networks

In this paper, we propose an aware-based adaptive opportunistic retransmission control scheme for wireless multimedia Mesh networks. The proposed scheme provides maximum retransmission count optimization based on environment-aware to improve packet relay probability. The scheme discriminates the types of packet loss in wireless link by means of environment information and selects the retransmission count by taking the IEEE 802.11 wireless channel characteristics into consideration. Furthermore, the maximum retransmission count of MAC is adjusted adaptively. Extensive simulations demonstrate that the proposed scheme significantly reduces packet collision probability and packet loss rate, and thus improves network throughput.     

Cross-Layer Optimization for Video Summary Transmission over Wireless Networks

Video summarization has gained increased popularity in the emerging multimedia communication applications, however, very limited work has been conducted to address the transmission problem of video summary frames. In this paper, we propose a cross-layer optimization framework for delivering video summaries over wireless networks. Within a rate-distortion theoretical framework, the source coding, allowable retransmission, and adaptive modulation and coding have been jointly optimized, which reflects the joint selection of parameters at physical, data link and application layers. The goal is to achieve the best video quality and content coverage of the received summary frames and to meet the delay constraint. The problem is solved using Lagirangian relaxation and dynamic programming. Experimental results indicate the effectiveness and efficiency of the proposed optimization framework, especially when the delay budget imposed by the upper layer applications is small, where more than 10% distortion gain can be achieved.     

Performance modeling and optimization of multiple‐objective cross‐layer design in multi‐flow ad‐hoc networks

In ad‐hoc wireless networks, to achieve good performance, multiple parameters need to be optimized jointly. However, existing literature lacks a design framework that investigates the synchronic impact of several parameters on overall system performance. Among several design parameters, energy conservation, end‐to‐end delay minimization, and improved throughput are considered most important for efficient operation of these networks. In this paper, we propose a novel scheme for multiple‐objective cross‐layer optimization capable of optimizing all these performance objectives simultaneously for reliable, energy‐efficient, and timely transmission of continuous media information across the network. The three global criteria considered for optimization are incorporated in a single programming problem via linear scalarization. Besides, we employ standard convex optimization method and Lagrangian technique to solve the proposed problem to seek optimality. Extensive simulation results are generated accounting for several topologies with multiple concurrent flows in the network. These results are used to validate the analytical results and demonstrate the efficiency of the proposed optimization model. Efficiency of the model is verified by finding the set of Pareto‐optimal solutions plotted in three‐dimensional objective space. These solution points constituting the Pareto front are used as the best possible balance points among maximum throughput, maximum residual energy, and least network delay. Finally, to emphasize the effectiveness and supremacy of our proposed multiple‐objective cross‐layer design scheme, we compare it with the conventional multiple‐objective genetic algorithm. Simulation results demonstrate that our method provides significant performance gain over the genetic algorithm approach in terms of the above specified three objectives.     

Joint source-channel coding and power adaptation for energy efficient wireless video communications

We consider efficiently transmitting video over a hybrid wireless/wire-line network by optimally allocating resources across multiple protocol layers. Specifically, we present a framework of joint source-channel coding and power adaptation, where error resilient source coding, channel coding, and transmission power adaptation are jointly designed to optimize video quality given constraints on the total transmission energy and delay for each video frame. In particular, we consider the combination of two types of channel coding—inter-packet coding (at the transport layer) to provide protection against packet dropping in the wire-line network and intra-packet coding (at the link layer) to provide protection against bit errors in the wireless link. In both cases, we allow the coding rate to be adaptive to provide unequal error protection at both the packet and frame level. In addition to both types of channel coding, we also compensate for channel errors by adapting the transmission power used to send each packet. An efficient algorithm based on Lagrangian relaxation and the method of alternating variables is proposed to solve the resulting optimization problem. Simulation results are shown to illustrate the advantages of joint optimization across multiple layers.     

Network Coding in Multicast Routing for Wireless Link Breakage Problem

Link breakage is one of the critical problems that limit the performance of multicast routing in wireless networks. To ease the problem, we apply network coding to the routing operation. In our proposal, data packets are encoded by a random coding scheme. By performing a re-encoding process, the coding scheme is able to keep conveying the data in the network even though link breakage occurs (without the need of waiting for retransmission). To route encoded packets in the network, a disjoint-path tree is used, which is the routing structure constructed by combining a number of multicast trees without the overlapping links among them. Simulation results show that our proposal can effectively ease the impact of link breakage, achieving better packet delivery ratio and higher multicast capacity under different scenarios.     

Cross‐layer bandwidth and power allocation for a two‐hop link in wireless mesh network

In this paper, a cross‐layer analytical framework is proposed to analyze the throughput and packet delay of a two‐hop wireless link in wireless mesh network (WMN). It considers the adaptive modulation and coding (AMC) process in physical layer and the traffic queuing process in upper layers, taking into account the traffic distribution changes at the output node of each link due to the AMC process therein. Firstly, we model the wireless fading channel and the corresponding AMC process as a finite state Markov chain (FSMC) serving system. Then, a method is proposed to calculate the steady‐state output traffic of each node. Based on this, we derive a modified queuing FSMC model for the relay to gateway link, which consists of a relayed non‐Poisson traffic and an originated Poisson traffic, thus to evaluate the throughput at the mesh gateway. This analytical framework is verified by numerical simulations, and is easy to extend to multi‐hop links. Furthermore, based on the above proposed cross‐layer framework, we consider the problem of optimal power and bandwidth allocation for QoS‐guaranteed services in a two‐hop wireless link, where the total power and bandwidth resources are both sum‐constrained. Secondly, the practical optimal power allocation algorithm and optimal bandwidth allocation algorithm are presented separately. Then, the problem of joint power and bandwidth allocation is analyzed and an iterative algorithm is proposed to solve the problem in a simple way. Finally, numerical simulations are given to evaluate their performances. Copyright © 2008 John Wiley & Sons, Ltd.     

Adaptive cross-layer MAC design for improved energy-efficiency in multi-channel wireless sensor networks

We present a novel cross-layer design for improving energy efficiency in a wireless sensor network that utilizes a multi-channel non-persistent CSMA MAC protocol with adaptive MQAM modulation at the physical layer. Cross-layer interactions are achieved through joint, traffic-dependent adaptation of the backoff probability at the MAC layer and the modulation order at the physical layer. The joint optimization of the backoff probability and the modulation order is conducted subject to a constraint on the packet retransmission delay. Such an optimization is shown to produce a significant improvement in the per-bit energy requirement for successful packet delivery. Our analytical findings are verified through numerical results and computer simulations.     

An energy‐efficient,scalable and collision‐free MAC layer protocol for wireless sensor networks

Wide range of applications such as disaster management, military and security have fueled the interest in sensor networks during the past few years. Sensors are typically capable of wireless communication and are significantly constrained in the amount of available resources such as energy, storage and computation. Such constraints make the design and operation of sensor networks considerably different from contemporary wireless networks, and necessitate the development of resource conscious protocols and management techniques. In this paper, we present an energy‐efficient, scalable and collision‐free MAC layer protocol for sensor networks. The approach promotes time‐based arbitration of medium access to limit signal interference among the transmission of sensors. Transmission and reception time slots are prescheduled to allow sensors to turn their radio circuitry off when not engaged. In addition, energy consumption due to active to sleep mode transitions is minimized through the assignment of contiguous transmission/reception slots to each sensor. Scalability of the approach is supported through grouping of sensors into clusters. We describe an optimization algorithm for energy conscious scheduling of time slots that prevents intra‐cluster collisions and eliminates packet drop due to buffer size limitations. In addition, we also propose an arbitration scheme that prevents collisions among the transmission of sensors in different clusters. The impact of our approach on the network performance is qualified through simulation.. Copyright © 2004 John Wiley & Sons, Ltd.     

Packet Size Optimization for Improving the Energy Efficiency in Body Sensor Networks

Energy consumption is a key issue in body sensor networks (BSNs) since energy‐constrained sensors monitor the vital signs of human beings in healthcare applications. In this paper, packet size optimization for BSNs has been analyzed to improve the efficiency of energy consumption. Existing studies on packet size optimization in wireless sensor networks cannot be applied to BSNs because the different operational characteristics of nodes and the channel effects of in‐body and on‐body propagation cannot be captured. In this paper, automatic repeat request (ARQ), forward error correction (FEC) block codes, and FEC convolutional codes have been analyzed regarding their energy efficiency. The hop‐length extension technique has been applied to improve this metric with FEC block codes. The theoretical analysis and the numerical evaluations reveal that exploiting FEC schemes improves the energy efficiency, increases the optimal payload packet size, and extends the hop length for all scenarios for in‐body and on‐body propagation.     

Cross‐Layer Resource Allocation in Multi‐interface Multi‐channel Wireless Multi‐hop Networks

In this paper, an analytical framework is proposed for the optimization of network performance through joint congestion control, channel allocation, rate allocation, power control, scheduling, and routing with the consideration of fairness in multi‐channel wireless multi‐hop networks. More specifically, the framework models the network by a generalized network utility maximization (NUM) problem under an elastic link data rate and power constraints. Using the dual decomposition technique, the NUM problem is decomposed into four subproblems — flow control; next‐hop routing; rate allocation and scheduling; power control; and channel allocation — and finally solved by a low‐complexity distributed method. Simulation results show that the proposed distributed algorithm significantly improves the network throughput and energy efficiency compared with previous algorithms.     

Time‐aware and energy‐efficient opportunistic routing with residual energy collection in wireless sensor networks

In 1‐dimensional queue wireless sensor networks, how to balance end‐to‐end latency and energy consumption is a challenging problem. However, traditional best path routing and existing opportunistic routing protocols do not address them well because relay hop counts are usually much more, and the link appears more unreliable compared with general mesh topology. In this work, we formulate these 2 problems as a multiobjective optimization problem. Specifically, we first classify network packets into types of time tolerant and time critical and introduce a residual energy collection mechanism of neighboring nodes for forwarder set selection. We then propose a time‐aware and energy‐efficient opportunistic routing protocol (TE‐OR) to optimize energy consumption and to reduce latency for time‐critical packets. We evaluate TE‐OR by different parameters and compare it with existing protocols. The performance results show that TE‐OR achieves a trade‐off between energy consumption and time delay and balances energy consumption among nodes while guaranteeing the latency of time‐critical packets is minimized.     

Resource allocation for real-time traffic in unreliable wireless cellular networks

Providing reliable transmission for real-time traffic in wireless cellular networks is a great challenge due to the unreliable wireless links. This paper concentrates on the resource allocation problem aiming to improve the real-time throughput. First, the resource allocation problem is formulated as a Markov Decision Process and thus the optimal resource allocation policy could be obtained by adopting the value iteration algorithm. Considering the high time complexity of the optimal algorithm, we further propose an approximate algorithm which decomposes the resource allocation problem into two subproblems, namely link scheduling problem and packet scheduling problem. By this method, the unreliable wireless links are only constrained in the link scheduling problem, and we can focus on the real-time requirement of traffic in packet scheduling problem. For the link scheduling problem, we propose the maxRel algorithm to maximize the long-term network reliability, and we theoretically prove that the maxRel algorithm is optimal in scenarios with dynamic link reliabilities. The Least Laxity First algorithm is adopted for the packet scheduling problem. Extensive simulation results show that the proposed approximate resource allocation algorithm makes remarkable improvement in terms of time complexity, packet loss rate and delay.     

Power efficient scheduling over fading channel for cross‐layer optimization

We consider the minimization of long‐term average power consumption for packet transmission between a mobile station and the base station over Nakagami‐m fading channel. Power consumption is minimized by intelligent transmission scheduling design, with the average queuing delay and joint packet loss across MAC and physical layers being confined below certain levels. The problem is formulated as an infinite horizon constrained Markov decision problem and solved by linear programming (LP) method. The primary intention of this paper is to provide a visible paradigm on using LP method to optimize the performance of mobile wireless communication systems. We elaborate the detailed mathematical solution with consistent simulation experiments and emphasize the effectiveness of adaptive transmission scheduling for cross‐layer QoS provisioning. Copyright © 2010 John Wiley & Sons, Ltd.     

A fairness adaptive TDMA scheduling algorithm for wireless sensor networks with unreliable links

Wireless sensor networks consist of a large number of wireless sensor nodes that organize themselves into multihop radio networks. With different link quality, different distance to the sink, nodes in a network are not treated equally, especially in a network with high traffic. In this paper, we propose a fairness adaptive time division multiple access scheduling algorithm (FATS) considering the fairness of network resource allocation. This algorithm, combining several heuristic algorithms, can assign network resources to the nodes to lead to maximizing the minimum end‐to‐end packet delivery success ratio. Because the wireless link is usually time‐varying, this algorithm can also assign the time slots to the nodes adaptively and energy‐efficiently according to the variation of link quality. We define several criteria for the slot assignment and adjustment. The change in slot assignment can be finished quickly during normal packet transmission, which causes little affect to the network. Meanwhile, considering the required data rate, FATS can achieve the maximum transmission capacity of the network with specified static or dynamic reliability. The simulation results show that the FATS can significantly reduce the difference of the end‐to‐end packet delivery ratio, track the variation of link quality quickly, and achieve the fairness of resource allocation.Copyright © 2012 John Wiley & Sons, Ltd.