OLSR performance measurement in a military mobile ad hoc network

Wireless ad hoc networks are autonomous, self-configurating and adaptive. Thus, such networks are excellent candidates for military tactical networks, where their ability to be operational rapidly and without any centralized entity is essential. As radio coverage is usually limited, multihop routing is often needed; this is achieved by an ad hoc routing protocol supporting nodes mobility. In this paper, we present performance measurements of the Optimized Link State Routing (OLSR) routing protocol, having the status of IETF RFC. The measurements are performed at CELAR site on a platform representative of military scenarios in urban areas. This platform consists of ten routers, eight PDAs and laptops using a IEEE 802.11b radio interface and implementing OLSR v7. Some nodes are mobile within vehicles. The emphasis of the measurements is on the performance of the network (route repair, network convergence speed, user traffic performance) in presence of this mobility.     

Survivable Load Sharing Protocols: A Simulation Study

The development of robust, survivable wireless access networks requires that the performance of network architectures and protocols be studied under normal as well as faulty conditions where consideration is given to faults occurring within the network as well as within the physical environment. User location, mobility, and usage patterns and the quality of the received radio signal are impacted by terrain, man-made structures, population distribution, and the existing transportation system. The work presented herein has two thrusts. One, we propose the use of overlapping coverage areas and dynamic load balancing as a means to increase network survivability by providing mobiles with multiple access points to the fixed infrastructure. Two, we describe our simulation approach to survivability analysis which combines empirical spatial information, network models, and fault models for more realistic analysis of real service areas. We use our simulation approach to compare the survivability of our load balancing protocols to a reference scheme within two diverse geographic regions. We view survivability as a cost-performance tradeoff using handover activity as a cost metric and blocking probabilities as performance metrics. Our results illustrate this tradeoff for the protocols studied and demonstrate the extent to which the physical environment and faults therein affect the conclusions that are drawn.     

Revisiting vehicular network connectivity with radio propagation model

In vehicular networks, radio waves propagate in an external environment and are therefore subject to many obstacles such as buildings, trees or hills. Modeling the transmission range by a perfect circle around each transmitter is absolutely wrong especially in urban environments. In our previous work, we defined a terrain characteristics-based propagation model for vehicular network. This model determines the received signal power according to the type and the density of obstacles encountered by the radio waves. In this paper we calibrate the model parameters to meet the physical layer specifications of the standard dedicated to inter-vehicular communication, 802.11p. We validate the new values by several simulation tests. Based on this model, we present a study of the radio connectivity for a vehicular network in city environment and evaluate the impact of obstacles on information dissemination in such a network. The tests are performed by considering a simulation environment that represents a real city map. We define several metrics characterizing the radio connectivity and the information dissemination and examine the effect of vehicles density and obstacles on those metrics.     

A quadratic optimization method for connectivity and coverage control in backbone-based wireless networks

The use of directional wireless communications to form flexible mesh backbone networks, which provide broadband connectivity to capacity-limited wireless networks or hosts, promises to circumvent the scalability limitations of traditional homogeneous wireless networks. The main challenge in the design of directional wireless backbone (DWB) networks is to assure backbone network requirements such as coverage and connectivity in a dynamic wireless environment. This paper considers the use of mobility control, as the dynamic reposition of backbone nodes, to provide assured coverage-connectivity in dynamic environments. This paper presents a novel approach to the joint coverage-connectivity optimization problem by formulating it as a quadratic minimization problem. Quadratic cost functions for network coverage and backbone connectivity are defined in terms of the square distance between neighbor nodes, which are related to the actual energy usage of the network system. Our formulation allows the design of self-organized network systems which autonomously achieve energy minimizing configurations driven by local forces exerted on network nodes. The net force on a backbone node is defined as the negative energy gradient at the location of the backbone node. A completely distributed algorithm is presented that allows backbone nodes to adjust their positions based on information about neighbors’ position only. We present initial simulation results that show the effectiveness of our force-based mobility control algorithm to provide network configurations that optimize both network coverage and backbone connectivity in different scenarios. Our algorithm is shown to be adaptive, scalable and self-organized.     

Modeling a Mobile Cellular Network Using a Discrete-Event Simulator

In this paper we introduce a discrete-event-based simulation technology suitable to model cellular mobile radio systems with respect to their dynamic behavior. The latter results in the need for simulation tools which support mutable system configurations. The problems encountered when modeling mutable system configurations using conventional discrete-event simulators are discussed. In order to show a possible solution to this problem we introduce configuration events and configuration objects into the theory of discrete-event simulations. We demonstrate how configuration objects can be implemented in a discrete-event simulator using a dynamic map-function, hereby extending a definition of higher order functions. We apply the configuration objects in a Multiple Layer Model for modeling an entire mobile cellular radio network in a discrete-event simulator as an application for the extended theory. In this model we use the configuration objects to change the network's configuration during runtime. We show that this solution—combined with an object-oriented software design and, possibly, a visual programming language—is a powerful tool for the simulation of the dynamic aspects of mobile cellular radio networks. The software technology presented will be applied by the German cellular network operator Mannesmann Mobilfunk to model dynamic features applicable to the radio resource management of mobile radio networks and to access their performance by simulation.     

Learning Adaptive Temporal Radio Maps for Signal-Strength-Based Location Estimation

In wireless networks, a client's locations can be estimated using the signals received from various signal transmitters. Static fingerprint-based techniques are commonly used for location estimation, in which a radio map is built by calibrating signal-strength values in the offline phase. These values, compiled into deterministic or probabilistic models, are used for online localization. However, the radio map can be outdated when the signal-strength values change with time due to environmental dynamics, and repeated data calibration is infeasible or expensive. In this paper, we present a novel algorithm, known as LEMT (Location Estimation using Model Trees), to reconstruct a radio map using real-time signal- strength readings received at the reference points. This algorithm can take into account real-time signal-strength values at each time point and make use of the dependency between the estimated locations and reference points. We show that this technique can effectively accommodate the variations of signal strength over different time periods without the need to rebuild the radio maps repeatedly. We demonstrate the effectiveness of our proposed technique on realistic data sets collected from an 802.11b wireless network and a RFID-based network.     

Impact of Interference on the Wireless Ad-Hoc Networks Capacity and Topology

It is wide spread belief that wireless mobile ad-hoc networks will be a further evolutionary step towards ubiquitous communication and computing. Due to the mobility of the network nodes, the strongly varying radio propagation conditions and the varying data traffic load these networks constitute a very dynamic environment. One essential step in evaluating the true benefit of this new technology consists of estimates and constraints concerning the scalability and performance of such networks. Using a simple model we discuss analytically the effect of interference on the link quality and connectivity of large networks. It turns out that the outage probability rapidly increases with increasing traffic load. Furthermore, we investigate the connectivity of the network under varying traffic load and find a percolation phase transition at a particular value of the traffic load. We discuss the dependence of these effects on parameters characterizing the receiver and the radio propagation conditions.     

Multi-Service Coverage Analysis for CDMA Planning

In CDMA network planning,it's important to understand the characteristics of multi-services.A novelmethod for analyzing the coverage of mixed voice and packet data traffics is presented in this paper.Based upon GIS andMonte-Carlo simulation method,this method can provide more precise but less time-consuming analysis result than before.A practical analysis case using real geographic information and network parameters is applied to verify its performanceand find some useful solutions.Simulation results show that this coverage analysis method can provide helpful solution forthe radio networks planning.     

Backbone Topology Synthesis for Multiradio Mesh Networks

Wireless local area network (WLAN) systems are widely implemented today to provide hot-spot coverage. Operated typically in an infrastructure mode, each WLAN is managed by an access point (AP). Wireless mesh networks (WMNs) are employed for the purpose of extending the wireless coverage scope by interconnecting the underlying AP nodes. The capability and performance behavior of the WMN can further be upgraded by using multiple communications channels and by having more capable nodes use multiple radio modules. In this paper, we present a fully distributed multiradio backbone synthesis algorithm, which serves to construct a mesh backbone network of APs. We assume more capable nodes, such as APs, to be equipped with two radio modules, while less capable nodes employ a single radio module. Multihop communications among distant client stations take place in accordance with a routing algorithm that uses the mesh backbone to establish inter-WLAN routes. The presented backbone construction algorithm and the associated on-demand backbone-based routing mechanism are shown to improve the system's delay-throughput performance, as well as its asynchronous and distributed behavior in a stable fashion     

Modelling and planning fixed wireless networks

Abstract  

This paper describes a mathematical model for the automated design of fixed wireless access networks (FWA) through the automatic selection and configuration of base station sites. An optimisation algorithm is presented which generates the fixed wireless access network infrastructure design, and results are presented to illustrate the use of the model and its implementation. Economic measures based on the net present value (NPV) are defined to assess the financial viability of potential network designs. The NPV is used within the mathematical optimization framework to produce cost-effective deployments that maximize economic performance while maintaining technical constraints on the network. The model takes into account time-varying input parameters on CapEx, OpEx, revenues and subscriber requirements to model the dynamic nature of the market. Technical radio constraints taken into account include downlink area coverage, interference, capacity and availability. The model and optimisation framework are illustrated by considering the deployment and configuration of infrastructure for three scenarios representing urban, suburban and rural regions. Experiments illustrating the staged deployment of infrastructure over a number of time periods are also presented.     

Swarm intelligence routing approach in networked robots

Robot swarm combined with wireless communication has been a key driving force in recent few years and has currently expanded to wireless multihop networks, which include ad hoc radio networks, sensor networks, wireless mesh networks, etc. The aim of this paper is to propose an approach which introduces a polynomial time approximation path navigation algorithm and constructs dynamic state-dependent navigation policies. The proposed algorithm uses an inductive approach based on trial/error paradigm combined with swarm adaptive approaches to optimize simultaneously two criteria: cumulative cost path and end-to-end delay path. The approach samples, estimates, and builds the model of pertinent aspects of the environment. It uses a model that combines both a stochastic planned prenavigation for the exploration phase and a deterministic approach for the backward phase. To show the robustness and performances of the proposed approach, simulation scenario is built through the specification of the interested network topology and involved network traffic between robots. For this, this approach has been compared to traditional optimal path routing policy.     

移动网无线信号场强预测软件的研发

介绍了移动网无线信号场强预测软件研发的目的、目标、方法及其应用。研发的目的主要是开发出适用于900MHz移动通信网无线信号场强预测的算法及用于实际网络优化的应用软件。在研发的过程中，借鉴了神经网络的原理，形成了基于路测的自适应场强预测算法，并以GIS为手段，面向应用开发软件平台，总结出了无线信号场强预测的算法，研发出了用于无线网络优化的应用软件。     

Power control for data load balancing with coverage in dynamic femtocell networks

We consider the load balancing and coverage problem of femtocell networks in indoor environment. We propose a novel framework exploiting the Voronoi diagram with respect to the radio propagation distance. Our initial power assignment scheme achieves maximal indoor coverage with minimized maximum required transmit power, which results in reduced interference. Our approach can adopt any radio propagation model to achieve more accurate coverage for an indoor environment with various obstacles. Time varying data traffic may cause unbalanced data load of base stations producing traffic overload. Our dynamic power control algorithm redistributes the data load by automatically adjusting transmit power levels according to data traffic estimation while preserving coverage. Moreover, we present an algorithm to cope with the dynamic deletion and insertion of femto base stations. Simulations show that the proposed scheme achieves better coverage, reduced interference, and good load balance compared to previous algorithms.     

Disruption tolerant networking by Smart Caching

Future mobile radio networks will aim at achieving ‘broadband access for all’, anywhere. The performance of a radio network vitally depends on the characteristics of the transmission path between the user terminal and the access point and the degree of network coverage. In urban areas, full broadband radio coverage is difficult to provide, causing a high variation in the link quality and making broadband services hard to realize. In rural regions, massive deployment costs prevent a full broadband coverage. Most of the time users have to settle for UMTS‐like wide area networks. For mobile users accessing services, such as video streaming, which require continuous broadband connectivity, it virtually results in intermittent network connectivity. The frequent disruption of the broadband link and its replacement with no or only low‐performance connections is a problem that should be addressed. This article introduces a new technique called Smart Caching (SC), which is able to mitigate variations in the network performance so that non‐real‐time and non‐interactive services' quality is substantially improved. SC supports pre‐fetching from a server and buffering data at the edge of the core network, in the so‐called Smart Cache. It transmits data with extremely high speed to be buffered in the mobile terminal when it is in the service range of an access point. This allows for the provisioning of data‐intensive services even in the case of patchy wireless broadband network coverage and intermittent connectivity. The performance of the SC service is evaluated with two different sophisticated queuing models, both based on the Markov arrival process. The benefit of the new technique is discussed and dimensioning issues are outlined. Furthermore, a comparison with legacy network setups is given. Copyright © 2009 John Wiley & Sons, Ltd.     

LEO satellite communication networks—a routing approach

In the modern world of telecommunications, the concept of wireless global coverage is of the utmost importance. However, real global coverage can only be achieved by satellite systems. Until recently, the satellites were in geostationary orbit and their high altitude could not allow real‐time communication such as cellular networks. The development of LEO satellite networks seems to overcome this limit. However, LEO satellite systems have specific characteristics that need to be taken into account. In the same manner, the TCP/IP standard was developed for terrestrial network. The need is then to come up with a solution that would permit the use of TCP/IP on LEO satellite networks without losing too many packets. The idea is to develop a routing algorithm that maximizes the RTT delays compared to the TCP timer granularity. For that matter, we use an FSA‐based link assignment that simulates the satellite constellation as a fixed network for a predetermined time interval. In this configuration, the problem becomes a static routing problem where an algorithm can find the best solution. Copyright © 2003 John Wiley & Sons, Ltd.     

Radio and system design for a dense urban personal communicationnetwork

Future personal communication networks must be able to support handportable units in all environments. In particular, for dense urban applications where near ubiquitous radio coverage is essential, radio network design has to be sufficiently robust for good service quality to be maintained over a large range of outdoor and indoor conditions. This could be achieved through careful consideration of the many factors and tradeoffs which affect the performance of a radio network. In the paper these considerations are evaluated and their implications examined through a discussion of the planning process for a personal communication network based on the GSM standard     

基于EPON网的AES加密电路设计

EPON网是基于千兆以太网的无源光网络技术,是光纤接入网的重要解决方案之一,具有良好的市场发展空间。随着广电网络技术的发展,信息安全的重要性日益增加,加密技术也越来越受到关注。AES算法作为现在的主流加密手段,是密码学中的高级加密标准,对它进行学习和运用具有十分重要的现实意义。讨论EPON系统下行传输存在的安全问题,并简单介绍高级加密算法（AES）在EPON系统内的实现方式,其中主要涉及AES原理的分析以及AES算法的硬件实现和功能仿真。     

Reinforcement-Learning-Based Double Auction Design for Dynamic Spectrum Access in Cognitive Radio Networks

In cognitive radio networks, an important issue is to share the detected available spectrum among different secondary users to improve the network performance. Although some work has been done for dynamic spectrum access, the learning capability of cognitive radio networks is largely ignored in the previous work. In this paper, we propose a reinforcement-learning-based double auction algorithm aiming to improve the performance of dynamic spectrum access in cognitive radio networks. The dynamic spectrum access process is modeled as a double auction game. Based on the spectrum access history information, both primary users and secondary users can estimate the impact on their future rewards and then adapt their spectrum access or release strategies effectively to compete for channel opportunities. Simulation results show that the proposed reinforcement-learning-based double auction algorithm can significantly improve secondary users’ performance in terms of packet loss, bidding efficiency and transmission rate or opportunity access.     

Comparison and Extension of Existing 3D Propagation Models with Real-World Effects Based on Ray-Tracing

The next generation of cellular network deployment is heterogeneous and temporally changing in order to follow the coverage and capacity needs. Active Antenna Systems allows fast deployment changes by cell shaping and tilt adaptation which have to be controlled in self-organized manner. However, such kind of automated and flexible network operations require a Self Organizing Network (SON) algorithm that works based on network performance parameters being partly derived from the radio measurements. Thus, appropriate radio propagation models are not only needed for network planning tools but also for simulative lab tests of the developed SON algorithm controlling the flexible deployment changes enabled by Active Antenna Systems. In this paper, an extension of the existing 3D propagation model is proposed in order to incorporate the propagation condition variation effects, not considered so far, by changing antenna beam orientation like antenna tilting or when users are distributed in the third dimension (height) in multi-floor scenarios. Ray tracing based generated propagation maps that show the realistic propagation effect are used as 3D real world reference for investigation and model approval.     

Diffusing-CRN k-means: an improved k-means clustering algorithm applied in cognitive radio ad hoc networks

With increasing demand of new wireless applications and increasing number of wireless user’s, problem of spectrum scarcity arises. In this context, cognitive radio supports dynamic spectrum access to address spectrum scarcity problem. Cognitive radio defined the cognitive radio nodes by their ability to intelligently adapt the environment to achieve specific objectives through advanced techniques. The variance of channel availability for cognitive radio nodes degrades connectivity and robustness of this type of network; in this case the use of clustering is an effective approach to meet this challenge. Indeed, the geographical areas are homogeneous in terms of type of radio spectrum, radio resources are better allocated by grouping cognitive radio nodes per cluster. Clustering is interesting to effectively manage the spectrum or routing in cognitive radio ad hoc networks. In this paper, we aim to improve connectivity and cooperativeness of cognitive radio nodes based on the improvement of the k-means algorithm. Our proposed algorithm is applied in cognitive radio ad hoc networks. The obtained results in terms of exchange messages and execution time show the feasibility of our algorithm to form clusters in order to improve connectivity and cooperativeness of cognitive radio nodes in the context of cognitive radio ad hoc networks.