An efficient fault-tolerant distributed channel allocation algorithm for cellular networks

A channel allocation algorithm in a cellular network consists of two parts: a channel acquisition algorithm and a channel selection algorithm. Some of the previous works in this field focused on centralized approaches to allocating channels. But, centralized approaches are neither scalable nor reliable. Recently, distributed dynamic channel allocation algorithms have been proposed, and they have gained a lot of attention due to their high reliability and scalability. But, in most of the algorithms, the cell that wants to borrow a channel has to wait for replies from all its interference neighbors and, hence, is not fault-tolerant. In this paper, we propose a new algorithm that is fault-tolerant and makes full use of the available channels. It can tolerate the failure of mobile nodes as well as static nodes without any significant degradation in service.     

Distributed dynamic fault-tolerant channel allocation for cellularnetworks

Efficient allocation of communication channels is critical for the performance of cellular systems. The centralized channel allocation algorithms proposed in literature are neither robust nor scalable. Several of these algorithms are unable to dynamically adjust to spatial and temporal fluctuations in channel demand (load). We present a distributed dynamic channel allocation (DCA) algorithm in which heavily loaded regions acquire a large number of communication channels, while their lightly loaded neighbors get assigned fewer channels. As the spatial distribution of channel demand changes with time, the spatial distribution of allocated channels adjusts accordingly. The algorithm described in this paper requires minimal involvement of the mobile nodes, thus conserving their limited energy supply. The algorithm is proved to be deadlock free, starvation free, and fair. It prevents cochannel interference and can tolerate the failure of mobile as well as static nodes without any significant degradation in service. Simulation experiments demonstrate that the performance of the proposed distributed dynamic algorithm is comparable to, and for some metrics, better than that of efficient centralized dynamic algorithms where the central switch has complete and latest information about channel availability. The major advantages of the proposed algorithm over its dynamic centralized counterparts are its scalability, flexibility, and low computation and communication overheads     

Fair Algorithms for Maximal Link Activation in Multihop Radio Networks

We present a distributed algorithm for obtaining a fair time slot allocation for link activation in a multihop radio network. We introduce the concept of maximal fairness in which the termination of a fair allocation algorithm is related to maximal reuse of the channel under a given fairness metric. The fairness metric can be freely interpreted as the expected link traffic load demands, link priorities, etc. Since respective demands for time slot allocation will not necessarily be equal, we define fairness in terms of the closeness of allocation to respective link demands while preserving the collision free property. The algorithm can be used in conjunction with existing link activation algorithms to provide a fairer and fuller utilization of the channel.     

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.     

Joint Optimization for Congestion Avoidance in Cognitive Radio WMNs under SINR Model

Due to limited spectrum resources and differences in link loads, network congestion is one of the key issues in cognitive radio wireless mesh networks. In this letter, a congestion avoidance model with power control, channel allocation, and routing under the signal‐to‐interference‐and‐noise ratio is presented. As a contribution, a nested optimization scheme combined with a genetic algorithm and linear programming solver is proposed. Extensive simulation results are presented to demonstrate the effectiveness of our algorithm.     

Distributed congestion control strategy using network utility maximization theory in VANET

Cooperative vehicle safety system (CVSS) rely on periodical beacons to track neighboring vehicles.High traffic density often causes channel congestion,seriously damaging the performance of CVSS.Existing congestion control strategies aim to ensure the performance in network layer,without considering the service requirements of vehicles in different driving contexts.To solve the problem,a distributed congestion control strategy using network utility maximization (NUM) theory was proposed.First of all,the NUM model for channel resource allocation was introduced.A utility function reflecting vehicle’s safety requirements was proposed in the model.Then under the condition of fixed transmit powers,a optimization problem of channel resource allocation was proposed.Lastly,to solve the optimization problem,a distributed congestion control algorithm named utility-based rate congestion control (UBRCC) algorithm was designed,the algorithm worked out the optimal beaconing rate by updating vehicle’s congestion price,realizing the resource allocation according to vehicle’s safety requirements.Simulation results validate that UBRCC algorithm can efficiently control channel congestion,reduce transmission delay,ensure reliable data transmission and satisfies the requirements of safety applications.     

信道公平分配的局部拥塞控制算法

提出基于信道公平分配的局部拥塞控制算法FCA(fair channel allocation),在缓解局部拥塞的同时增强信道分配的公平性。为减少获取邻居节点实时缓存信息的通信开销和提高以单一节点缓存是否溢出为检测模型的准确性,FCA采用以节点实时缓存长度预测为基础的邻居节点缓存总长度和分组平均传输延迟作为检测指标的拥塞检测模型。为避免使用独立拥塞通告消息增加信道负载,FCA采用在ACK控制帧中增加一个节点地址位携带拥塞信息。在去拥塞阶段,FCA采用基于实时缓存长度和队列优先权值的信道分配机制保证公平传输和防止部分节点因缓存增速过快导致溢出分组丢失。实验结果表明,FCA在碰撞次数、分组传递率、吞吐量和公平性等方面相比802.11、CODA和PCCP具有显著优势。     

Mixed Power Control with Directed Assignment (MPCDA), a Method for Interference Reduction in Channelized Wireless Systems

Power control, often coupled with dynamic channel assignment, has been viewed as a promising answer to the challenge of reducing interference and increasing capacity. Indiscriminate use of power control, however, may exacerbate the near-far-end problem on the down link, and give rise to other complications when users are mobile. We propose a power control policy that can alleviate the near-far-end interference caused by the use of either the same channel or neighbor channels inside the same cell, while at the same time aiding in the reduction of interference from different cells through user matching. We present a heuristic algorithm for user matching, which is distributed and simple to implement. The method can be combined with an array of either fixed or dynamic channel assignment algorithms and applies to both circuit-based and packet-based traffic. It is ideal for fixed or slow circuit-based traffic and for packet-based traffic.A duality relationship is derived for the proposed power control policy between the signal-to-interference ratio of two interfering users experienced in the two communication directions. This relationship enables one to validate channel assignment decisions on both communication directions by analyzing only the decisions for one.     

Multiple link failure recovery in survivable optical networks

Survivability is of critical importance in high-speed optical communication networks. A typical approach to the design of survivable networks is through a protection scheme that pre-determines and reserves backup bandwidth considering single/double link failure scenarios. In this article, a greedy algorithm is presented to reserve backup bandwidth considering multiple (F > 2) link (SRLG) failure scenarios. A bandwidth-saving joint selection scheme of working and protection paths is presented for protection against random multiple-link failures under dynamic traffic. Simulation shows that the algorithm can achieve maximum sharing of backup bandwidth for protection against random multiple-link failure with significant amount of bandwidth saving.     

Distributed Kalman Filter with Fast Consensus for Wireless Sensor Networks

With the revolution of wireless sensor networks and the advances on microchip technologies the potential of distributed interconnected systems have exploded. Yet, even with great sensing capability and great communication throughput in the wireless links, we encounter fundamental problems: Communication Congestion and Scalability. The scalability issue and communication congestion are closely related in the application of distributed estimation algorithms. The more sensors we add to our system the more communication we will require. In general, in order to share the information gathered by all the sensors, we also get a higher likelihood of running into critical network congestion. Moreover, the scalability problem is not only related to communication issues but also to computation problems, as with higher dimensional measurement vectors it also comes a higher computational demand for the estimation algorithms. Distributed Kalman Filter (DKF) is one of the most fundamental distributed estimation algorithms. Most of the proposed DKF in the literature rely on consensus filters algorithm. The convergence rate of such distributed consensus algorithms typically depends on the network topology and the weights given to the edges between neighboring sensors. This paper proposes a DKF with fast consensus. The idea is to apply a polynomial filter on the network matrix in order to increase the convergence by minimizing its second largest eigenvalue of the polynomial. Fast convergence can contribute to significant energy saving. Moreover we redesigned the DKF to reduce its computational complexity and to reduce the communication traffic between the sensor nodes. Thus, the experimental results show that the TelosB mote can run DKF with up to seven neighbors for real application.     

Adaptive reliable and congestion control routing protocol for MANET

In mobile ad hoc networks (MANETs), the packet loss can be caused either by link failure or by node failure. Moreover, the techniques for selecting the bypass route and avoiding congestion in the bypass route are rarely handled. To overcome these, in this paper, we propose an adaptive reliable and congestion control routing protocol to resolve congestion and route errors using bypass route selection in MANETs. The multiple paths are constructed. Among which, the shortest paths are found for efficient data transmission. The congestion is detected on the basis of utilization and capacity of link and paths. When a source node detects congestion on a link along the path, it distributes traffic over alternative paths by considering the path availability threshold and using a traffic splitting function. If a node cannot resolve the congestion, it signals its neighbors using the congestion indication bit. By using simulation, we show that that the proposed protocol is reliable and achieves more throughput with reduced packet drops and overhead.     

End-to-End Optimal Algorithms for Integrated QoS, Traffic Engineering, and Failure Recovery

This paper addresses the problem of optimal quality of service (QoS), traffic engineering (TE) and failure recovery (FR) in computer networks by introducing novel algorithms that only use source inferrable information. More precisely, optimal data rate adaptation and load balancing laws are provided which are applicable to networks where multiple paths are available and multiple classes of service (CoS) are to be provided. Different types of multiple paths are supported, including point-to-point multiple paths, point-to-multipoint multiple paths, and multicast trees. In particular, it is shown that the algorithms presented only need a minimal amount of information for optimal control, i.e., whether a path is congested or not. Hence, the control laws provided in this paper allow source inferred congestion detection without the need for explicit congestion feedback from the network. The proposed approach is applicable to utility functions of a very general form and endows the network with the important property of robustness with respect to node/link failures; i.e., upon the occurrence of such a failure, the presented control laws reroute traffic away from the inoperative node/link and converge to the optimal allocation for the ldquoreducedrdquo network. The proposed control laws set the foundation for the development of highly scalable feature-rich traffic control protocols at the IP, transport, or higher layers with provable global stability and convergence properties.     

Performance Comparison of Two Channel Allocation Strategies in Cellular Networks

Channel allocation plays an important role in increasing the throughput and assuring fairness to users not only in traditional cellular networks but also in cognitive radio networks and mesh networks. In this paper, we study the effect of pre-allocating channels to cells with respect to a distributed and fault-tolerant channel allocation algorithm. Results from our extensive performance evaluation indicate that distributed channel allocation algorithms that pre-allocate all channels to cells can have lower call failure rate, call blocking rate, and handoff drop rate compared to algorithms that partially pre-allocate channels or does not pre-allocate channels.     

An Efficient Cross-Layer Optimization Algorithm for Data Transmission in Wireless Sensor Networks

In this paper, we propose a cross layer congestion optimization scheme for allocating the resources of wireless sensor networks to achieve maximization of network performance. The congestion control, routing selection, link capacity allocation, and power consumption are all taken account to yield an optimal scheme based on the Lagrangian optimization. The Lagrangian multiplier is adopted to adjust power consumption, congestion rate, routing selection and link capacity allocation, so that the network performance can be satisfied between the trade-off of efficiency and fairness of resource allocation. The proposed algorithm can significantly achieve the maximization of network performance in relieving the network congestion with less power consumption. Excellent simulation results are obtained to demonstrate our innovative idea, and show the efficiency of our proposed algorithm.     

基于补偿式CSI的分布式跨层联合资源分配算法

为消除过时信道状态信息(CSI)对分布式无线多跳网络环境下跨层资源分配效率的影响,提高跨层联合资源分配的准确性,基于信道相关性提出了一种补偿式跨层联合资源分配算法。利用瞬时和过时信道状态信息之间的条件概率密度函数,基于瑞利衰落信道模型求得信噪比(SINR) 模型下条件容量的闭式解。为补偿部分网络性能的损失,提出了一种考虑过时信道状态信息的联合拥塞控制、信道分配和功率控制的算法,在此过程中网络被建模成一个NUM 问题,可变的链路数据率和功率等资源限制作为约束条件。运用拉格朗日对偶分解技术,NUM问题被分布式求解。实验对比分析表明：在确保较低复杂度的前提下,该算法有效改善了分布式多跳网络资源分配的合理性,使其网络总体效用得到提升,降低了能耗。     

基于强化学习的定向无线通信网络抗干扰资源调度算法

为了在无线网络中进行高效的链路资源调度、减小网络干扰、提高网络容量,提出了一种利用回溯天线并考虑干扰环境的链路资源分布式智能调度算法.首先,结合通信的路径损耗模型设计卷积核,对节点密度矩阵进行卷积来衡量干扰链路强度,从而避免对所有干扰链路进行信道估计产生巨大的计算代价;然后,结合强化学习的思想设计了与通信环境交互的链路调度学习模型,每个链路利用神经网络进行独立的训练,将训练所得的决策结果反馈到环境中进行状态更新,模型在不断更新的环境中迭代来学习最优的调度策略.该方法能分布式的运行,可有效衡量无线网络中的链路干扰强度,结合衡量结果进行高效的链路资源分布式调度,从而最大化网络容量.仿真结果验证了该调度算法无论是在算法迭代收敛还是网络容量性能上都能很好地逼近全局的调度算法,达到全局算法最优结果的92%~100%.     

基于OFDM-PON动态带宽分配算法研究

正交频分复用是一种多载波调制技术,用于解决各种无线和有线通信系统中因信道色散引起的符号间干扰问题。近年来的研究表明,OFDM在无源光网络方面有广泛地应用前景。文中以OFDM-PON为对象,对其传输性能、动态带宽分配算法进行了研究。提出了基于传统CP算法的改进算法,使OFDM-PON系统的上行带宽分配性能得到改善。经过建模仿真证明,系统上行业务时延和链路利用率都得到了提高。     

一种基于最大化Rayleigh熵的稳健干扰对齐算法

干扰对齐在消除干扰方面具有独到的优势,但需要完美的信道状态信息(CSI),这在实际中很难实现。该文分析了传统稳健干扰对齐方案的优缺点,在此基础上,提出一种最大化Rayleigh熵的稳健干扰对齐算法,并对收敛性,自由度和频谱效率等进行了分析。不同于MAX-SINR算法,该文通过最大化信号的Rayleigh熵,求得干扰抑制矩阵。在正向通信中,考虑到数据流之间的相关性取干扰抑制矩阵为原始干扰抑制矩阵的酉矩阵形式,并采用注水功率分配实现用户数据流间的最佳功率分配;基于信道的互惠性,在反向通信时,做类似的处理。通过迭代计算,逐渐将干扰压缩。最后,在完美CSI和误差CSI时,仿真表明该算法显著地提高了系统的性能。     

Performance of optimum transmitter power control in cellular radiosystems

Most cellular radio systems provide for the use of transmitter power control to reduce cochannel interference for a given channel allocation. Efficient interference management aims at achieving acceptable carrier-to-interference ratios in all active communication links in the system. Such schemes for the control of cochannel interference are investigated. The effect of adjacent channel interference is neglected. As a performance measure, the interference (outage) probability is used, i.e., the probability that a randomly chosen link is subject to excessive interference. In order to derive upper performance bounds for transmitter power control schemes, algorithms that are optimum in the sense that the interference probability is minimized are suggested. Numerical results indicate that these upper bounds exceed the performance of conventional systems by an order of magnitude regarding interference suppression and by a factor of 3 to 4 regarding the system capacity. The structure of the optimum algorithm shows that efficient power control and dynamic channel assignment algorithms are closely related     

A topology preserving cluster‐based channel assignment for wireless mesh networks

Wireless Mesh Networks (WMN) with multiple radios and multiple channels are expected to resolve the capacity limitation problem of simpler wireless networks. However, optimal WMN channel assignment (CA) is NP complete, and it requires an optimal mapping of available channels to interfaces mounted over mesh routers. Acceptable solutions to CA must minimize network interference and maximize available network throughput. In this paper, we propose a CA solution called as cluster‐based channel assignment (CBCA). CBCA aims at minimizing co‐channel interference yet retaining topology through non‐default CA. Topology preservation is important because it avoids network partitions and is compatible with single‐interface routers in the network. A ‘non‐default’ CA solution is desired because it uses interfaces over different channels and reduces medium contention among neighbors. To the best of our knowledge, CBCA is a unique cluster‐based CA algorithm that addresses topology preservation using a non‐default channel approach. The main advantage of CBCA is it runs in a distributed manner by allowing cluster heads to perform CA independently. CBCA runs in three stages, where first the WMN nodes are partitioned into clusters. The second stage performs binding of interfaces to neighbors and third stage performs CA. The proposed algorithm improves over previous work because it retains network topology and minimizes network interference, which in turn improves available network throughput. Further, when compared with two other CBCA algorithms, CBCA provides better performance in terms of improved network interference, throughput, delay, and packet delivery ratios when tested upon network topologies with various network densities and traffic loads. Copyright © 2014 John Wiley & Sons, Ltd.