On the Performance of Flooding-Based Resource Discovery

We consider flooding-based resource discovery in distributed systems. With flooding, a node searching for a resource contacts its neighbors in the network, which in turn contact their own neighbors and so on until a node possessing the requested resource is located. Flooding assumes no knowledge about the network topology or the resource distribution thus offering an attractive means for resource discovery in dynamically evolving networks such as peer-to-peer systems. We provide analytical results for the performance of a number of flooding-based approaches that differ in the set of neighbors contacted at each step. The performance metrics we are interested in are the probability of locating a resource and the average number of steps and messages for doing so. We study both uniformly random resource requests and requests in the presence of popular (hot) resources. Our analysis is also extended to take into account the fact that nodes may become unavailable either due to failures or voluntary departures from the system. Our analytical results are validated through simulation     

Sensitivity analysis of an optimal routing policy in an ad hoc wireless network

We examine the sensitivity of optimal routing policies in ad hoc wireless networks with respect to estimation errors in channel quality. We consider an ad hoc wireless network where the wireless links from each node to its neighbors are modeled by a probability distribution describing the local broadcast nature of wireless transmissions. These probability distributions are estimated in real-time. We investigate the impact of estimation errors on the performance of a set of proposed routing policies.     

Adding structure to unstructured peer-to-peer networks: the use of small-world graphs

The “small-world” graph structure is pervasive and is observed to arise “without-design” or “naturally” in many practical systems such as the World Wide Web. In contrast to natural systems, overlay networks provide an opportunity to design structure. We seek the advantages of designing overlay topologies with small-world properties to support file sharing in peer-to-peer networks. We focus on two metrics of performance: (a) search protocol performance, a local gain perceived directly by peer-to-peer network users and (b) network utilization, a global property that is of interest to network service providers. We propose a class of overlay topologies and show, by simulation, that a particular topology instance of this class where every node has many close neighbors and few random neighbors (i.e., a small-world graph) exhibits very good properties. In this overlay topology, the chances of locating files are high, and the nodes where these files are found are, on average, close to the query source. This improvement in search protocol performance is achieved while decreasing the traffic load on the links in the underlying network. We propose a simple greedy algorithm to construct such overlay topologies where each node operates independently and in a decentralized manner to select its neighbors.     

Neighbor discovery for wireless networks via compressed sensing

This paper studies the problem of neighbor discovery in wireless networks, namely, each node wishes to discover and identify the network interface addresses (NIAs) of those nodes within a single hop. A novel paradigm, called compressed neighbor discovery is proposed, which enables all nodes to simultaneously discover their respective neighborhoods with a single frame of transmission, which is typically of a few thousand symbol epochs. The key technique is to assign each node a unique on–off signature and let all nodes simultaneously transmit their signatures. Despite that the radios are half-duplex, each node observes a superposition of its neighbors’ signatures (partially) through its own off-slots. To identify its neighbors out of a large network address space, each node solves a compressed sensing (or sparse recovery) problem.Two practical schemes are studied. The first employs random on–off signatures, and each node discovers its neighbors using a noncoherent detection algorithm based on group testing. The second scheme uses on–off signatures based on a deterministic second-order Reed–Muller code, and applies a chirp decoding algorithm. The second scheme needs much lower signal-to-noise ratio (SNR) to achieve the same error performance. The complexity of the chirp decoding algorithm is sub-linear, so that it is in principle scalable to networks with billions of nodes with 48-bit IEEE 802.11 MAC addresses. The compressed neighbor discovery schemes are much more efficient than conventional random-access discovery, where nodes have to retransmit over many frames with random delays to be successfully discovered.     

Consumer credit risk: Individual probability estimates using machine learning

Consumer credit scoring is often considered a classification task where clients receive either a good or a bad credit status. Default probabilities provide more detailed information about the creditworthiness of consumers, and they are usually estimated by logistic regression. Here, we present a general framework for estimating individual consumer credit risks by use of machine learning methods. Since a probability is an expected value, all nonparametric regression approaches which are consistent for the mean are consistent for the probability estimation problem. Among others, random forests (RF), k-nearest neighbors (kNN), and bagged k-nearest neighbors (bNN) belong to this class of consistent nonparametric regression approaches. We apply the machine learning methods and an optimized logistic regression to a large dataset of complete payment histories of short-termed installment credits. We demonstrate probability estimation in Random Jungle, an RF package written in C++ with a generalized framework for fast tree growing, probability estimation, and classification. We also describe an algorithm for tuning the terminal node size for probability estimation. We demonstrate that regression RF outperforms the optimized logistic regression model, kNN, and bNN on the test data of the short-term installment credits.     

非对称异步移动传感网中低延时邻居发现算法

邻居发现即通过一定的手段快速而有效地去感知与节点能够直接通信的一跳范围内的邻居的问题,是移动传感网（MSN）的重要部分。非对称异步MSN中,已有的算法需要大量的时间和能量去完成相互发现。针对此问题,基于信标与活动时隙分离的邻居发现模型,提出一种适用于异步对称场景的BMCS-A算法,信标在工作周期的不同时隙进行广播以保证邻居发现的确定性。其次,扩展BMCS-A,提出一种持续性广播的BMCS-B算法,节点在第一个子周期内持续性广播信标,接收到该信标的节点将自适应地调整信标的发送时刻以加快邻居发现过程。最后,实现协作式BMCS-B算法,基于已发现邻居的睡眠苏醒调度信息,节点主动发送信标去发现潜在的邻居。仿真实验结果表明,与Searchlight、G-Nihao和Disco相比,协作式BMCS-B将最坏发现时延分别降低了84.62%、85.71%和81.82%。     

A self-stabilizing algorithm for cut problems in synchronous networks

Consider a synchronized distributed system where each node can only observe the state of its neighbors. Such a system is called self-stabilizing if it reaches a stable global state in a finite number of rounds. Allowing two different states for each node induces a cut in the graph. In each round, every node decides whether it is (locally) satisfied with the current cut. Afterwards all unsatisfied nodes change sides independently with a fixed probability $p$. Using different notions of satisfaction enables the computation of maximal and minimal cuts, respectively. We analyze the expected time until such cuts are reached on several graph classes and study the impact of the parameter $p$ and the initial cut.     

Radio-over-Fiber based architecture for seamless wireless indoor communication in the 60 GHz band

In order to satisfy the increasing demand of wireless broadband multimedia services, much attention has been paid to the 60 GHz band where as much as 5 GHz of spectrum has been reserved. However, in the indoor environment, the propagation of signals at this millimeter wave band is strongly hindered by walls, people and their movement, furniture, etc. As a result, a mobile user might experience frequent loss of connection as the user moves from one cell to another. In this paper, we propose a flexible and cost-effective Radio-over-Fiber (RoF) based network architecture to support indoor networking at millimeter wave bands. To create sufficient overlap areas between cells and thus to ensure a seamless communication environment for mobile users, the concept of Extended Cell is introduced. We demonstrate the effectiveness of the proposed architecture with a detailed simulation study of an indoor scenario. Furthermore, we analyze the impact of the architecture on the performance of two popular state-of-the-art protocols, namely IEEE 802.11 and IEEE 802.16, to find which Medium Access Control (MAC) protocol is suitable for RoF networks.     

Decentralized receding horizon control for large scale dynamically decoupled systems

We present a detailed study on the design of decentralized receding horizon control (RHC) schemes for decoupled systems. We formulate an optimal control problem for a set of dynamically decoupled systems where the cost function and constraints couple the dynamical behavior of the systems. The coupling is described through a graph where each system is a node, and cost and constraints of the optimization problem associated with each node are only function of its state and the states of its neighbors. The complexity of the problem is addressed by breaking a centralized RHC controller into distinct RHC controllers of smaller sizes. Each RHC controller is associated with a different node and computes the local control inputs based only on the states of the node and of its neighbors. We analyze the properties of the proposed scheme and introduce sufficient stability conditions based on prediction errors. Finally, we focus on linear systems and show how to recast the stability conditions into a set of matrix semi-definiteness tests.     

A Distributed and Efficient Flooding Scheme Using 1-Hop Information in Mobile Ad Hoc Networks

Flooding is one of the most fundamental operations in mobile ad hoc networks. Traditional implementation of flooding suffers from the problems of excessive redundancy of messages, resource contention, and signal collision. This causes high protocol overhead and interference with the existing traffic in the networks. Some efficient flooding algorithms were proposed to avoid these problems. However, these algorithms either perform poorly in reducing redundant transmissions or require each node to maintain 2-hop (or more) neighbors information. In the paper, we study the sufficient and necessary condition of 100 percent deliverability for flooding schemes that are based on only 1-hop neighbors information. We further propose an efficient flooding algorithm that achieves the local optimality in two senses: 1) the number of forwarding nodes in each step is minimal and 2) the time complexity for computing forwarding nodes is the lowest, which is O(nlogn), where n is the number of neighbors of a node. Extensive simulations have been conducted and simulation results have shown the excellent performance of our algorithm     

Mobility-sensitive topology control in mobile ad hoc networks

In most existing localized topology control protocols for mobile ad hoc networks (MANETs), each node selects a few logical neighbors based on location information and uses a small transmission range to cover those logical neighbors. Transmission range reduction conserves energy and bandwidth consumption, while still maintaining network connectivity. However, the majority of these approaches assume a static network without mobility. In a mobile environment network connectivity can be compromised by two types of "bad" location information: inconsistent information, which makes a node select too few logical neighbors, and outdated information, which makes a node use too small a transmission range. In this paper, we first show some issues in existing topology control. Then, we propose a mobility-sensitive topology control method that extends many existing mobility-insensitive protocols. Two mechanisms are introduced: consistent local views that avoid inconsistent information and delay and mobility management that tolerate outdated information. The effectiveness of the proposed approach is confirmed through an extensive simulation study.     

A compact dual band short ended metamaterial antenna with extended bandwidth

A compact dual‐band CPW–fed metamaterial inspired antenna using Composite Right/Left Handed (CRLH) resonant approach is presented in this article. The antenna is designed such that it can be operated in series resonant mode where resonance behavior is characterized by series LC parameters. Proposed antenna comprises two annular ring resonators connected with the signal patch intended to excite the higher order modes. This results extension of second band from 51.4% (f_c = 6.92 GHz) to 69.2% (f_c = 7.35 GHz). In addition to that proposed antenna shows compact nature with an electrical size of 0.14 λ₀ × 0.21 λ0 × 0.01 λ₀ at f₀ = 2.18 GHz. The antenna is operating over 2.14–2.23 GHz, 4.81–9.90 GHz with simulated peak gain of 0.66 and 4.44 dB, respectively. Simulated radiation efficiencies of proposed antenna are 69.8 and 94.1% throughout first and second band, respectively. To examine the resonance and radiation characteristics prototype is fabricated and measured. Observed experimental results are in good agreement with those simulated one. These characteristics makes this antenna is a good candidate for modern wireless communication systems such as Bluetooth, WLAN/Wi‐Fi band. © 2016 Wiley Periodicals, Inc. Int J RF and Microwave CAE 26:435–441, 2016.     

A Hopfield Neural Network for Image Change Detection

This paper outlines an optimization relaxation approach based on the analog Hopfield neural network (HNN) for solving the image change detection problem between two images. A difference image is obtained by subtracting pixel by pixel both images. The network topology is built so that each pixel in the difference image is a node in the network. Each node is characterized by its state, which determines if a pixel has changed. An energy function is derived, so that the network converges to stable states. The analog Hopfield's model allows each node to take on analog state values. Unlike most widely used approaches, where binary labels (changed/unchanged) are assigned to each pixel, the analog property provides the strength of the change. The main contribution of this paper is reflected in the customization of the analog Hopfield neural network to derive an automatic image change detection approach. When a pixel is being processed, some existing image change detection procedures consider only interpixel relations on its neighborhood. The main drawback of such approaches is the labeling of this pixel as changed or unchanged according to the information supplied by its neighbors, where its own information is ignored. The Hopfield model overcomes this drawback and for each pixel allows a tradeoff between the influence of its neighborhood and its own criterion. This is mapped under the energy function to be minimized. The performance of the proposed method is illustrated by comparative analysis against some existing image change detection methods.     

Constructing minimum extended weakly-connected dominating sets for clustering in ad hoc networks

Motivated by cooperative communication in ad hoc networks, Wu et al. proposed extended dominating set (EDS) where each node in an ad hoc network is covered by either a dominating neighbor or several 2-hop dominating neighbors, and defined two types of dominating sets: extended strongly connected dominating set (ECDS) and extended weakly connected dominating set (EWCDS), according to the success of a broadcast process. An EWCDS is an effective method for clustering. In this paper, we extend the dominative capabilities of nodes such that each forward node dominates not only itself and its regular neighbors fully, but also its quasi-neighbors partly. Based on this extension, three novel algorithms to find EWCDSs in ad hoc networks are proposed. The correctness and performance of our algorithms are confirmed through theoretical analysis and comprehensive simulations.     

基于区域的无线传感器网络密钥管理

要密钥分配是无线传感器网络中极具挑战性的安全问题之一．目前提出的解决方法是采用密钥预分配策略,给每个节点分配多个密钥,如Eschenauer和Gligor提出的随机密钥预分配方案（R—KPS）．随机密钥预分配方案没有利用节点的部署和位置信息,在许多应用场合中,部署和位置信息能被用于改善网络性能．在R—KPS中,每个节点有可能成为其它任何节点的邻居,所以节点必须从同一密钥池中选取密钥．如果能把网络划分为多个区域,则同一区域内和相邻区域间的节点更有可能成为邻居．文章提出一种利用已知区域信息的密钥预分配方案,相比随机密钥预分配方案,能提高网络的连通性,减小节点所需存储空间,并能增强网络抗攻击能力．最后利用上述区域信息提出一种不借助定位设备的节点定位算法,此算法实现简单,适用于定位精度要求不高的场合．     

A compact wide band textile MIMO antenna with very low mutual coupling for wearable applications

This communication presents a compact wide band wearable MIMO antenna with very low mutual coupling (VLMC). The proposed antenna is composed of Jeans material. Two “I” shaped stubs are connected in series and are employed on the ground plane between the two patches separated by 0.048 λ to increase isolation characteristics of the antenna‐port. The antenna covers frequency spectrum from 1.83 GHz to 8 GHz (about 125.5%) where the minimum port isolation of about 22 dB at 2.4 GHz and maximum of about 53 dB at 5.92 GHz are obtained. The envelope correlation coefficient (ECC) of the MIMO antenna is obtained to be less than 0.01 with a higher diversity gain (DG > 9.6) throughout the whole operating band. The proposed MIMO antenna is cost effective and works over a wide frequency band of WLAN (2.4‐2.484 GHz/5.15‐5.35 GHz/5.72‐5.825 GHz), WiMAX (3.2‐3.85 GHz) and C‐band downlink‐uplink (3.7‐4.2 GHz/5.925‐6.425 GHz) applications. Simulation results are in well agreement with the measurement results.     

TAP: Traffic-aware topology control in on-demand ad hoc networks

Energy efficiency is crucial to achieve satisfactory network lifetime in ad hoc networks. In order to reduce the energy consumption significantly, a node needs to turn off its transceiver. Many existing energy-saving algorithms are based on constructing a simplified routing backbone for global connectivity. In this paper some problems involved with node sleep in on-demand ad hoc networks are addressed firstly. Then we propose a distributed, cross-layer Traffic-Aware Participation (TAP) algorithm, where nodes make decisions on whether to sleep or not based on both the traffic pattern and local connectivity. Nodes get dynamic traffic characteristics as well as active neighbors within two hops via routing control and data packets periodically. We further present a lightweight algorithm to avoid network partition resulted from node sleeping. Simulation results show that, compared to current sleep-based topology control algorithms, TAP achieves better network service quality and lower delay while allowing comparable energy conservation.     

Cooperative device discovery for multi-interface self-organizing networks

For device-to-device communications, a device must locate neighbor devices on a certain channel within a short period to establish a communication link. When the channel information is not provided, a rendezvous technique can be adapted to resolve the issue of device discovery. Unlike existing approaches that have considered the rendezvous problem for a flat network and a single interface, the proposed approach considers a hierarchical network where nodes have different ranks and multiple interfaces. We extend the jump-and-stay rendezvous algorithm for multiple interfaces and divide the interfaces into two types: standby and scan interfaces. Scan interfaces follow the extended pattern of the jump-and-stay algorithm. Standby interfaces remain on a selected channel for a round of slots until rendezvous with other nodes. To determine the interface type of each node, we consider the rank of a node such that a higher-ranked node is assigned more standby interfaces. Based on this framework, we propose a cooperative rendezvous algorithm where a node rebroadcasts the channel information of a higher-ranked node together with its rendezvous message. Our simulation results confirm that the proposed rendezvous algorithm achieves superior performance compared to conventional methods.     

Activity maxima in random networks in the heavy tail case

We consider a model of information network described by an undirected random graph, where each node has a random information activity whose distribution possesses a heavy tail (with regular variation). We investigate the cases of networks described by classical and power-law random graphs. We derive sufficient conditions under which the maximum of aggregate activities (over a node and its nearest neighbors) asymptotically grows in the same way as the maximium of individual activities and the Fréchet limit law holds for them.     

认知增强型无线传感器节点设计

为了提高无线传感器节点及其网络的吞吐量和频谱利用率,从节点设计的角度,引入认知方法增强节点的频谱感知能力,设计了基于低功耗高速率处理器的多射频接口认知增强无线传感器节点.节点采用STR911系列的ARM9微处理器,具有4个射频接口,覆盖了ISM频段和ZigBee频段.实验结果表明,相比基于Atmega128处理器的节点,该节点具有更强的认知能力,吞吐量提高了68.41%,平均信道感知时延缩短了1.4782ms;相比于CSMA/CA方法,通信时延缩短了11.86%,链路层控制方案能够有效避免干扰对节点间通信的影响.