无线传感网络节点定位的三边扩展法

针对无线传感网络中难以解决的基于欧氏距离的多跳定位问题,通过引入刚性图与整体刚性图的概念,应用刚性框架理论和图论知识,将多跳定位的首要问题——唯一可解性问题转化成了整体刚性图的判定问题,同时给出了判定的充分必要条件,有效降低了刚性框架理论的分析复杂度.再采用三边扩展法逐步构建整体刚性图,不断扩大可定位节点的范围,实现确定网络中所有可定位节点位置的目的.     

Tandem queueing networks with neighbor blocking and back-offs

We introduce a novel class of tandem queueing networks which arise in modeling the congestion behavior of wireless multi-hop networks with distributed medium access control. These models provide valuable insight in how the network performance in terms of throughput depends on the back-off mechanism that governs the competition among neighboring nodes for access to the medium. The models fall at the interface between classical queueing networks and interacting particle systems, and give rise to high-dimensional stochastic processes that challenge existing methodologies. We present various open problems and conjectures, which are supported by partial results for special cases and limit regimes as well as simulation experiments.     

A method for maximizing the reliability coefficient of a communications network

The most common idea of network reliability in the literature is a numerical parameter calledoverall network reliability, which is the probability that the network will be in a successful state in which all nodes can mutually communicate. Most papers concentrate on the problem of calculating the overall network reliability which is known to be an NP hard problem. In the present paper, the question asked is how to find a method for determining a reliable subnetwork of a given network. Givenn terminals and one central computer, the problem is to construct a network that links each terminal to the central computer, subject to the following conditions: (1) each link must be economically feasible; (2) the minimum number of links should be used; and (3) the reliability coefficient should be maximized. We argue that the network satisfying condition (2) is a spanning arborescence of the network defined by condition (1). We define the idea of thereliability coefficient of a spanning arborescence of a network, which is the probability that a node at average distance from the root of the arborescence can communicate with the root. We show how this coefficient can be calculated exactly when there are no degree constraints on nodes of the spanning arborescence, or approximately when such degree constraints are present. Computational experience for networks consisting of up to 900 terminals is given.This report was prepared as part of the activities of the Management Science Research Group, Carnegie-Mellon University, under Contract No. N00014-82-K-0329 NR 047–048 with the U.S. Office of Naval Research. Reproduction in whole or in part is permitted for any purpose of the U.S. Government.     

On the characterization of Aloha in underwater wireless networks

Standard analyses of wireless random access protocols that are available in the literature assume negligible propagation delay between any two nodes. This assumption holds good in reasonably short-range terrestrial RF (radio frequency) wireless networks. On the contrary, in wireless communications involving acoustic wave propagation, as in underwater wireless networks, even short distance propagation has appreciably large propagation delay. This observation has led to several recent simulation and experimental studies on underwater Aloha and slotted-Aloha (S-Aloha) protocols and also a few new proposals on random access protocols for underwater wireless ad hoc networks (UWN). To study the efficiency of more advanced multiaccess communication protocols for UWN, it is important to benchmark their performances with respect to the two basic random access protocols, Aloha and S-Aloha. This paper provides an analytic framework to capture the performance of Aloha and S-Aloha protocols in an underwater environment with high and random internodal signal propagation delay. The performance of underwater Aloha and S-Aloha are contrasted with those in short-range terrestrial RF wireless networks. The analysis shows that random internodal propagation delay has no effect on the underwater Aloha performance. It also sheds light on the throughput degradation of underwater S-Aloha with a slotting concept that achieves RF S-Aloha equivalent one-slot vulnerability. Additionally, a modified slotting concept is introduced where the slot size is judiciously reduced such that even by allowing some collisions the overall system throughput can be increased. Our calculations show that, with the modified slotting approach up to 17% throughput performance gain can be achieved over the naive (RF S-Aloha equivalent) slotting approach in UWN. Our analytic results are supported by discrete event simulations.     

Modeling and Optimization of Interference Limited Wireless Communications

Multiple access interference (MAI) limits the system capacity of wireless communications systems applying code division multiple access (CDMA). Provided that channel knowledge is available in the transmitter, the transmitted signal can be preprocessed by multiuser transmission (MUT) methods. As optimization criterion, the bit error probability/rate (BER) is chosen. On the transmit signal, a limited power constraint is imposed, which is a quadratic function of the transmit signal. The nonlinear optimization problem is modeled in this paper. Unfortunately, the problem is non‐convex. However, with iterative nonlinear optimization methods like SQP, local minima can be found with a performance outperforming other MUT methods. The main remaining challenge are low‐complexity optimization algorithms to allow for a real‐time implementation in highdata rate wireless communications. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

A robust optimization approach for multicast network coding under uncertain link costs

Network coding is a technique that can be used to improve the performance of communication networks by performing mathematical operations at intermediate nodes. An important problem in coding theory is that of finding an optimal coding subgraph for delivering network data from a source node throughout intermediate nodes to a set of destination nodes with the minimum transmission cost. However, in many real applications, it can be difficult to determine exact values or specific probability distributions of link costs. Establishing minimum-cost multicast connections based on erroneous link costs might exhibit poor performance when implemented. This paper considers the problem of minimum-cost multicast using network coding under uncertain link costs. We propose a robust optimization approach to obtain solutions that protect the system against the worst-case value of the uncertainty in a prespecified set. The simulation results show that a robust solution provides significant improvement in worst-case performance while incurring a small loss in optimality for specific instances of the uncertainty.     

A Markov Renewal Based Model for Wireless Networks

We propose a queueing network model which can be used for the integration of the mobility and teletraffic aspects that are characteristic of wireless networks. In the general case, the model is an open network of infinite server queues where customers arrive according to a non-homogeneous Poisson process. The movement of a customer in the network is described by a Markov renewal process. Moreover, customers have attributes, such as a teletraffic state, that are driven by continuous time Markov chains and, therefore, change as they move through the network. We investigate the transient and limit number of customers in disjoint sets of nodes and attributes. These turn out to be independent Poisson random variables. We also calculate the covariances of the number of customers in two sets of nodes and attributes at different time epochs. Moreover, we conclude that the arrival process per attribute to a node is the sum of independent Poisson cluster processes and derive its univariate probability generating function. In addition, the arrival process to an outside node of the network is a non-homogeneous Poisson process. We illustrate the applications of the queueing network model and the results derived in a particular wireless network.     

A problem identification taxonomy for classification and automated formulation of multiple objective linear programming models

This paper considers a network supply problem in which flows between any pair of nodes are possible. It is assumed that users place a value on connection to other users in the network, and (possibly) on access to an external source. Cost on each link is an arbitrary concave function of link capacity. The objective is to study coalitional stability in this situation, when collections of flows can be served by competing suppliers. In contrast to other network games, this approach focuses on the cost of serving flows rather than the cost of attaching nodes to the network. The network is said to be stable if the derived cost function is supportable. Supportable cost functions, defined by Sharkey and Telser [9], are cost functions for which there exists a price vector which covers total cost, and simultaneously deters entry at any lower output by a rival firm with the same cost function. If the minimal cost network includes a link between every pair of nodes, then the cost function is shown to be supportable. In the special case in which link cost is independent of capacity, the cost function is also supportable. The paper also considers Steiner networks in which new nodes may be created in order to minimize total cost, or in which access may be obtained at more than one source location. When link costs are independent of capacity in such a network, it is argued that the cost function is approximately supportable in a well defined sense.     

Clustering intelligent transportation sensors using public transportation

Advanced transportation sensors use a wireless medium to communicate and use data fusion techniques to provide complete information. Large-scale use of intelligent transportation sensors can lead to data bottlenecks in an ad-hoc wireless sensor network, which needs to be reliable and should provide a framework to sensors that constantly join and leave the network. A possible solution is to use public transportation vehicles as data fusion nodes or cluster heads. This paper presents a mathematical programming approach to use public transportation vehicles as cluster heads. The mathematical programming solution seeks to maximize benefit achieved by covering both mobile and stationary sensors, while considering cost/penalty associated with changing cluster head locations. A simulation is developed to capture realistic considerations of a transportation network. This simulation is used to validate the solution provided by the mathematical model.     

Queueing analysis of the DRX power saving mechanism in fault-tolerant 3GPP LTE wireless networks

Energy efficiency and high reliability are major aspects of modern mobile wireless networks. Therefore, it is a critical step to use power management methods along with fault-tolerant techniques. In this paper, we mathematically investigate the Discontinuous Reception, a power saving mechanism in 3GPP LTE wireless networks, with checkpointing and rollback recovery using a variant of an M/G/1 queue with a modified service time and multiple vacations. Due to the lack of enough storage, the mobile device periodically stores its checkpoint data in a stable fixed server, and rolling back to the latest checkpoint when a transient fault or a wireless link error occurs. Various energy and performance metrics are obtained, while constrained optimization problems are formulated and solved. Extensive numerical results are provided, and give an insight into the operation of the model.     

基于等级划分的可信接入和修复模型研究

提出了一种基于等级划分的层次化可信接入框架和修复模型,详细说明了可信属性的划分规则和等级的评估方法以及修复模型的工作流程,着重阐明了基于该框架的实际应用和终端接入过程.仿真实验结果表明,框架在保证网络系统安全性和可信性的同时,能够增加终端接入网络的灵活性,并为各厂商可信网络设备的互联、互通和互操作提供支撑,而且修复模型部署简单,为不满足本地安全策略的终端提供方便可靠的修复服务.     

A Stochastic Game Analysis of the Binary Exponential Backoff Algorithm with Multi-Power Diversity and Transmission Cost

In this paper, we present a game analysis of the Binary Exponential Backoff (BEB), a popular bandwidth allocation mechanism used by a large number of distributed wireless technologies. A Markov chain analysis is used to obtain equilibrium retransmission probabilities and throughput. Numerical results show that when the arrival probability increases, the behavior of mobile stations MSs become more and more aggressive resulting in a global deterioration of the system throughput. We then consider a non-cooperative game framework to study the operation and evaluate the performance of the BEB algorithm when a group of MSs competing with each other to gain access to the wireless channel. We focus our attention to the case when an MS acts selfishly by attempting to gain access to the channel using a higher retransmission probability as a means to increase its own throughput. As a means to improve the system performance, we further explore the use of two transmission mechanisms and policies. First, we introduce the use of multiple power levels (MPLs) for the data transmission. The use of multiple power levels results on a capture effect allowing the receiver to properly decode the message even in the presence of a collision. Under the proposed scheme, named MPL-BEB, the effect of the aggressive behavior, higher transmission probabilities, is diminished since the power level is chosen randomly and independently by each and every station. Second, we introduce a disutility policy for power consumption. The resulting mechanism, named MPL-BEB with costs, is of prime interest in wireless networks composed of battery-powered nodes. Under this scheme aggressive behavior is discouraged since each retransmission translates into the depletion of the energy stored in the battery. Via price of anarchy, our results identify a behavior similar to the well-know prisoner’s dilemma. A non-efficiency of Nash equilibrium is observed for all schemes (BEB, MPL-BEB, MPL-BEB with costs) under heavy traffic with a notable outperformance of MPL-BEB with costs over both MPL-BEB and BEB.     

Exact approaches for lifetime maximization in connectivity constrained wireless multi-role sensor networks

In this paper, we consider the duty scheduling of sensor activities in wireless sensor networks to maximize the lifetime. We address full target coverage problems contemplating sensors used for sensing data and transmit it to the base station through multi-hop communication as well as sensors used only for communication purposes. Subsets of sensors (also called covers) are generated. Those covers are able to satisfy the coverage requirements as well as the connection to the base station. Thus, maximum lifetime can be obtained by identifying the optimal covers and allocate them an operation time. The problem is solved through a column generation approach decomposed in a master problem used to allocate the optimal time interval during which covers are used and in a pricing subproblem used to identify the covers leading to maximum lifetime. Additionally, Branch-and-Cut based on Benders’ decomposition and constraint programming approaches are used to solve the pricing subproblem. The approach is tested on randomly generated instances. The computational results demonstrate the efficiency of the proposed approach to solve the maximum network lifetime problem in wireless sensor networks with up to 500 sensors.     

基于失效边数概率分布的K-终端网络重要度计算方法

重要度是现代网络薄弱环节识别的常用工具,其能量化网络不同的边对网络可靠性的影响程度。以往的K-终端网络重要度计算方法需已知网络边的可靠性以及边发生失效相互独立的条件,不能满足现实网络对于网络重要度计算的需求。鉴于此,为了突破这些条件的限制,本文在给定失效边数目的概率分布的背景下,发展K-终端网络重要度的计算方法,并提供一个十二面体网络的算例,验证了该计算方法的有效性和正确性。     

马氏模型下移动自组网随选型路由协议特性分析

移动自组网络（简称MANET）因其移动性及无基础设施支持等特点已经成为无线通信网络中的热门问题．通过将一个MANET网络中每条链边的长度看作一个生灭过程,并且假设在泛洪过程中空间可以复用n次,建立了移动自组网络空间可复用的马氏模型,简记为n-SRBDM．在一个典型的随选型路由协议即动态源路由（DSR）协议的基础上,研究了网络的一些关键性能参数,给出了路由泛洪距离的概率分布和期望,限定泛洪步数时成功寻路的概率、发现τ-时有效路径及对称有效路径的概率,发现一条有效路径的平均时间等,对于路由维护过程,也引入并研究了一些网络性能参数,例如,路由恢复的平均频率,路由有效的平均时间．对于这些网络参数在空间可复用和空间不可复用两种情形下进行了比较．证明了空间可复用模型下的路由选择更为有效．     

Nodal distance distributions in cluster flight spacecraft network

The high-speed flight of cluster flight spacecraft modules increases the uncertainty of network topology. In order to better design the orbital of the cluster flight spacecraft and improve the performance of cluster flight spacecraft network (CFSN), this paper studies the nodal distance distributions (NDDs). First, based on twin-satellites mode, the mobility model of nodes is established. And then by adopting empirical statistical method and curve fitting method, the solution of the nodal distance density function in the CFSN is obtained. Second, the probability density function is applied to the model distance-dependent path loss, and the probability density of path loss under the model is analyzed. Finally, the distributions of maximum and minimum distance among multiple nodes and the threshold range of nodal connection distance are derived, and the probabilistic connectivity matrix of any time slot in the orbital hyper-period and spatial–temporal evolution graphs under different thresholds is obtained. The analytical results verify the feasibility of the model and the approximate solution of the NDDs in this paper. This method also provides a theoretical reference for the nodal connection in irregular wireless networks.     

An efficient approximation for minimum energy broadcast in multi-channel multi-hop wireless network with directional antennas

In this paper, We discuss the minimum energy broadcast problem (MEB) in multi-channel multi-hop wireless networks with directional antennas (MEB-MB). This problem is NP-hard since its special version, MEB in single-channel network with directional antennas (MEB-SB) is proved to be NP-hard. We design an efficient approximation for MEB-MB problem, analyze its approximation ratio, and evaluate its performance via numerical experiments.     

The Cross-Entropy Method for Network Reliability Estimation

Consider a network of unreliable links, modelling for example a communication network. Estimating the reliability of the network—expressed as the probability that certain nodes in the network are connected—is a computationally difficult task. In this paper we study how the Cross-Entropy method can be used to obtain more efficient network reliability estimation procedures. Three techniques of estimation are considered: Crude Monte Carlo and the more sophisticated Permutation Monte Carlo and Merge Process. We show that the Cross-Entropy method yields a speed-up over all three techniques.     

A Two Stage Stochastic Semidefinite Relaxation for wireless OFDMA Networks

In this paper, we propose a two stage stochastic binary quadratic program for OFDMA wireless networks. The aim is to minimize the total power consumption of the network subject to user bit rates, sub-carrier and modulation constraints. We derive from the quadratic model a linear (LP) and a semidefinite programming (SDP) relaxation. Numerical results show tight and near optimal bounds for the SDP relaxation.