Energy-Scalable Protocols for Battery-Operated MicroSensor Networks

In wireless sensor networks, the goal is to gather information from a large number of sensor nodes and communicate the information to the end-user, all under the constraint of limited energy resources. Network protocols minimize energy by using localized communication and control and by exploiting computation/communication tradeoffs. In addition, data fusion algorithms such as beamforming aggregate data from multiple sources to reduce data redundancy and enhance signal-to-noise ratios, thus further reducing the required communications. We have developed a sensor network system that uses a localized clustering protocol and beamforming data fusion to enable energy-efficient collaboration. We compare the performance of two beamforming algorithms, the Maximum Power and the Least Mean Squares (LMS) beamforming algorithms, using the StrongARM SA-1100 processor. Results show that the LMS algorithm requires less than one-fifth the energy required by the Maximum Power beamforming algorithm with only a 3 dB loss in performance, thus showing that the LMS algorithm is better suited for energy-constrained systems. We explore the energy-scalability of the LMS algorithm, and we propose an energy-quality scalable architecture that incorporates techniques such as variable filter length, variable voltage supply and variable adaptation time.     

A robust variable step-size LMS-type algorithm: analysis andsimulations

A number of time-varying step-size algorithms have been proposed to enhance the performance of the conventional LMS algorithm. Experimentation with these algorithms indicates that their performance is highly sensitive to the noise disturbance. This paper presents a robust variable step-size LMS-type algorithm providing fast convergence at early stages of adaptation while ensuring small final misadjustment. The performance of the algorithm is not affected by existing uncorrelated noise disturbances. An approximate analysis of convergence and steady-state performance for zero-mean stationary Gaussian inputs and for nonstationary optimal weight vector is provided. Simulation results comparing the proposed algorithm to current variable step-size algorithms clearly indicate its superior performance for cases of stationary environments. For nonstationary environments, our algorithm performs as well as other variable step-size algorithms in providing performance equivalent to that of the regular LMS algorithm     

面向6G物联网的分布式译码技术

随着5G商业化和标准化的逐步推进,对6G技术的研究也提上了日程。由于其在6G无线通信系统中的巨大应用前景,物联网(IoT)技术引起了人们广泛的兴趣。面向6G的物联网网络需要允许大量设备接入并支持海量数据传输,其鲁棒性和可扩展性至关重要。在物联网中,所述“事物”(用户)可以通过采用各种多功能无线传感器实时收集环境数据。通常来说,收集的数据将反馈到中央单元以进行进一步处理。但是这一机制依赖于中央单元的正常工作,鲁棒性较差。该文提出一种分布式译码算法,该算法通过让各用户之间互相协作,交换信息来实现在各个用户处完成译码。利用分布式译码算法,每个用户可以得到与中心化处理相似的译码性能,从而提高了网络的鲁棒性和可扩展性。同时,相比传统分布式译码算法,该算法不需要每个用户了解网络的拓扑结构,因此为面向6G的高动态物联网提供了技术支撑。     

An application of meta-heuristic and nature-inspired algorithms for designing reliable networks based on the Internet of things: A systematic literature review

The widespread use of Internet of Things (IoT) in various wireless sensor networks applications has increased their importance in recent years. IoT is a smart technology that connects anything anywhere at any time. These smart objects, which connect the physical world with the world of computing infrastructure, are expected to permeate all aspects of our daily lives and revolutionize a number of application domains such as healthcare, energy conservation, and transportation. As wireless networking expands, the disadvantage of wireless communication is clearly obvious. People's apprehension over the IoT's dependability has therefore skyrocketed. IoT networks' key requirements are dependability, channel security, fault tolerance, and reliability. Monitoring the IoT networks depends on the availability and correct functioning of all the network nodes. Recent research has proposed promising solutions to address these challenges. This article systematically examines recent articles that use meta-heuristic and nature-inspired algorithms to establish reliable IoT networks. Eighteen articles were analyzed in four groups. Results showed that reliable enhancement mechanisms in IoT networks increase fault node detection, network efficiency, and lifetime and attain energy optimization results in the IoT concept. Additionally, it was discovered in the literature that the current studies focus on how to effectively use edge network capabilities for IoT application executions and support, along with the related needs.     

一种新的变步长LMS算法

在对基本LMS算法分析的基础上,通过构造步长因子μ与误差信号e（n）之间的非线性函数,提出一种新的变步长最小均方误差（LMS）算法,并且分析了参数的取值对算法性能的影响。该算法通过调整步长参数,使权向量达到最优,有效改善了收敛速度与稳态误差的性能。理论分析和仿真结果表明,与基本LMS算法以及部分同类变步长LMS算法相比,该算法具有更快的收敛速度和更小的稳态误差,进一步验证了新算法优于这里所述其他算法。     

自适应算法在干扰抵消器应用中的比较研究

文中介绍了自适应滤波算法的原理和干扰抵消器工作原理，并将LMS算法、NLMS算法和变步长LMS算法分别应用在了干扰抵消器中进行了仿真。仿真的结果表明，三种自适应算法运用到了干扰抵消器中，都可以很好地滤除干扰，提取有用信号。其中运用了变步长LMS算法的干扰抵消器无论在收敛速度和滤波性能上，都要强于其他两种算法。     

A new class of gradient adaptive step-size LMS algorithms

The gradient adaptive step-size least-mean-square (LMS) algorithms [an important family of variable step-size LMS (VSLMS) algorithms] are revisited. We propose a simplification to a class of the studied algorithms and show that this leads to a new class of VSLMS algorithms with reduced complexity but with no observable loss in performance     

New Variable Step-Sizes Minimizing Mean-Square Deviation for the LMS-Type Algorithms

The least-mean-square-type (LMS-type) algorithms are known as simple and effective adaptation algorithms. However, the LMS-type algorithms have a trade-off between the convergence rate and steady-state performance. In this paper, we investigate a new variable step-size approach to achieve fast convergence rate and low steady-state misadjustment. By approximating the optimal step-size that minimizes the mean-square deviation, we derive variable step-sizes for both the time-domain normalized LMS (NLMS) algorithm and the transform-domain LMS (TDLMS) algorithm. The proposed variable step-sizes are simple quotient forms of the filtered versions of the quadratic error and very effective for the NLMS and TDLMS algorithms. The computer simulations are demonstrated in the framework of adaptive system modeling. Superior performance is obtained compared to the existing popular variable step-size approaches of the NLMS and TDLMS algorithms.     

SKWN: Smart and dynamic key management scheme for wireless sensor networks

In the era of the Internet of Things (IoT), we are witnessing to an unprecedented data production because of the massive deployment of wireless sensor networks (WSNs). Typically, a network of several hundred sensors is created to ensure the interactions between the cyber world and the physical world. Unfortunately, the intensive use of this kind of networks has raised several security issues. Indeed, many WSN‐based applications require secure communication in order to protect collected data. This security is generally ensured by encryption of communication between sensors, which requires the establishment of many cryptographic keys. Managing these keys, within a protocol, is an important task that guarantees the effectiveness of the security mechanism. The protocol should be intelligently adaptable not only to intrusion events but also to the security level needed by some applications. An efficient protocol optimizes also sensors energy and consequently increases the network life cycle. In this paper, we propose, a smart and dynamic key management scheme for hierarchical wireless sensor networks (SKWN). Our protocol offers three subschemes to deal with key establishment, key renewal, and new node integration. Regarding existing schemes, SKWN does not only provide reliable security mechanisms, but it also optimizes energy consumption and overheads related to the communication and memory usage. Furthermore, our approach relies on a machine learning approach to monitor the state of the network and decide the appropriate security level. We provide a formal approach and its implementation, together with simulations allowing to compare resources usage with respect to existing approaches.     

A New Method to Find a High Reliable Route in IoT by Using Reinforcement Learning and Fuzzy Logic

Recently, Internet is moving quickly toward the interaction of objects, computing devices, sensors, and which are usually indicated as the Internet of things (IoT). The main monitoring infrastructure of IoT systems main monitoring infrastructure of IoT systems is wireless sensor networks. A wireless sensor network is composed of a large number of sensor nodes. Each sensor node has sensing, computing, and wireless communication capability. The sensor nodes send the data to a sink or a base station by using wireless transmission techniques However, sensor network systems require suitable routing structure to optimizing the lifetime. For providing reasonable energy consumption and optimizing the lifetime of WSNs, novel, efficient and economical schemes should be developed. In this paper, for enhancing network lifetime, a novel energy-efficient mechanism is proposed based on fuzzy logic and reinforcement learning. The fuzzy logic system and reinforcement learning is based on the remained energies of the nodes on the routes, the available bandwidth and the distance to the sink. This study also compares the performance of the proposed method with the fuzzy logic method and IEEE 802.15.4 protocol. The simulations of the proposed method which were carried out by OPNET (Optimum Network performance) indicated that the proposed method performed better than other protocols such as fuzzy logic and IEEE802.15.4 in terms of power consumption and network lifetime.

     

基于室内无线传感器网络射频信号的老年人跌倒检测研究

利用无线信号的自然衰减,在不显著增加通信开销的基础上,提出了一种新的老年人跌倒行为的检测方法.给出阶段相关性这一概念并用以区分体域传感器网络节点与室内传感器网络节点信号在人运动与静止条件下的统计相关性.给出了最小通信决策集合的概念,通过对比最小通信决策集合的内容,提出了老年人位置估计方法和跌倒行为检测算法;利用仿真工具...     

On Prolonging the Lifetime for Wireless Video Sensor Networks

This paper investigates strategies for prolonging the system lifetime for wireless video sensor networks, by adopting a mobile sink and solar-powered video sensors. Issues of tracking moving objects in wireless video sensor networks are studied, and the effectiveness of adopting a mobile sink is evaluated. This paper applies a power-rate-distortion analysis framework, which provides a theoretical fundamental to quantify various properties of wireless video sensor networks. The performance of wireless video sensor networks is evaluated with a mobile sink versus a static sink, under different cluster sizes and number of sensors. Comparisons of network lifetime, tracking error, video distortion, are also covered in this paper. In addition, this paper also evaluates the performance of solar-powered video sensors under an unequal layered clustering topology.     

一种新的变步长自适应滤波算法及分析

现有的变步长自适应滤波算法可分为步长一致和步长非一致两种情况,本文着重对步长一致的情况进行分析讨论,给出了统一的表达式,并定性地提出了步长变化的准则.同时在分析了几种现有变步长自适应滤波算法的基础上,提出了一种新的变步长自适应滤波算法.理论分析和不同情况下的仿真实验结果都表明,新算法能够符合文中提出的变步长准则,在保持算法简单的同时能够满足收敛速度,跟踪能力和收敛精度的要求.     

基于小波变换的变步长LMS自适应滤波算法

变步长LMS自适应滤波算法通过构造合适的步长因子有效的解决了传统LMS算法收敛速度和稳态误差相矛盾的问题.变换域LMS自适应滤波算法通过正交变换降低了输入信号矩阵的相关性,提高了算法的收敛速度.将这两种算法相结合,提出了一种新的基于小波变换的变步长LMS自适应滤波算法.仿真结果表明,该算法无论是收敛速度还是稳态误差都有了很大的提高.     

一种新的变步长LMS自适应滤波算法

在对传统LMS算法、变步长SVSLMS算法及归一化LMS算法分析的基础上,提出了一种改进的归一化变步长LMS算法即N-SVSLMS（Normalized-SVSLMS）算法。该算法结合了参考文献中两种算法的思想,得到了改进的归一化LMS自适应算法。该算法在信道环境多变的情况下,收敛速度和稳定性能有了进一步的提高。理论分析及计算机仿真结果表明,N-SVSLMS算法明显优于传统LMS算法、变步长SVSLMS算法及归一化的LMS算法。     

Industrial wireless sensor and actuator networks in industry 4.0: Exploring requirements,protocols, and challenges—A MAC survey

The vision to connect everyday physical objects to the Internet promises to create the Internet of Things (IoT), which is expected to integrate the diverse technologies such as sensors, actuators, radio frequency identification, communication technologies, and Internet protocols. Thus, IoT promises to transfer traditional industry to advance digital industry known as the Industry 4.0. At the core of the Industry 4.0 are the wireless sensor networks (WSNs) and wireless sensor and actuator networks (WSANs) that led to the development of industrial wireless sensor networks (IWSNs) and industrial wireless sensor and actuator networks (IWSANs). These networks play a central role of connecting machines, parts, products, and humans and create a diverse set of new applications to support intelligent and autonomous decision making. The IWSAN is a promising technology for numerous industrial applications because of their several potential benefits such as simple deployment, low cost, less complexity, and mobility support. However, despite such benefits, they impose several unique challenges at different layers of the protocol stack when deploying them for various monitoring and control applications in the Industry 4.0. In this article, we explore IWSAN, its applications, requirements, challenges, and solutions in the context of industrial control applications. Our main focus is on the medium access control (MAC) layer that can be exploited to satisfy such requirements. Our discussion presents extensive background study of the MAC schemes and it reviews the MAC protocols of the existing wireless standards and technologies. A number of application‐specific MAC protocols developed to support industrial applications, which are not part of these standards, are also elaborated. We rationalize to what extent the existing standards and protocols help in solving such requirements as laid down by the Industry 4.0. In the end, we emphasize on existing challenges and present important future directions.     

Hybrid Wireless Sensors Deployment Scheme with Connectivity and Coverage Maintaining in Wireless Sensor Networks

With the rapid growth of the internet of things (IoT), an impressive number of IoT’s application based on wireless sensor networks (WSNs) has been deployed in various domain. Due to its wide ranged applications, WSNs that have the capability to monitor a given sensing field, became the most used platform of IoT. Therefore, coverage becomes one of the most important challenge of WSNs. The search for better positions to assign to the sensors in order to control each point of an area of interest and the collection of data from sensors are major concerns in WSNs. This work addresses these problems by providing a hybrid approach that ensures sensors deployment on a grid for targets coverage while taking into account connectivity. The proposed sequential hybrid approach is based on three algorithms. The first places the sensors so as to all targets are covered. The second removes redundancies from the placement algorithm to reduce the number of sensors deployed. The third one, based on the genetic algorithm, aims to generate a connected graph which provide a minimal path that links deployed sensors and sink. Simulations and a comparative study were carried out to prove the relevance of the proposed method.

     

一种新型无线传感器网络安全研究

物联网作为网络延伸的新拓展,广泛应用于社会各领域。无线传感器网络作为物联网的重要组成部分,基于无线传感器网络安全研究已成为目前物联网安全研究的重点。针对无线传感器网络计算能力较小、难以完成复杂计算的问题,设计了一种无线传感器网络安全架构方案。方案将无线传感器网络划分为若干个以中心节点作为信息传输端的节点网络,中心节点传递该节点网络搜集的信息到数据中心进行处理。采用可搜索加密技术,使得管理员可以直接获取所需信息对应的密文,而不用对整体密文解密后再搜集,提高了无线传感器网络的效率。     

A group-based security scheme for wireless sensor networks

In recent years, wireless sensor networks have been a very popular research topic, offering a treasure trove of systems, networking, hardware, security, and application-related problems. Distributed nature and their deployment in remote areas, these networks are vulnerable to numerous security threats that can adversely affect their proper functioning. The problem is more critical if its purpose is for some mission-critical applications such as in a tactical battlefield. This paper presents a security scheme for group-based distributed wireless sensor networks. Our first goal is to devise a group-based secure wireless sensor network. We exploit the multi-line version of matrix key distribution technique and Gaussian distribution to achieve this goal. Secondly, security mechanisms are proposed for such a group-based network architecture in which sensed data collected at numerous, inexpensive sensor nodes are filtered by local processing on its way through more capable and compromise-tolerant reporting nodes. We address the upstream requirement that reporting nodes authenticate data produced by sensors before aggregating and the downstream requirement that sensors authenticates commands disseminated from reporting nodes. Security analysis is presented to quantify the strength of the proposed scheme against security threats. Through simulations, we validate the analytical results.     

Cooperative Communications in Resource-Constrained Wireless Networks

Cooperative communications have been proposed to exploit the spatial diversity gains inherent in multiuser wireless systems without the need of multiple antennas at each node. This is achieved by having the users relay each others messages and thus forming multiple transmission paths to the destination. In resource constrained networks, such as wireless sensor networks, the advantages of cooperation can be further exploited by optimally allocating the energy and bandwidth resources among users based on the available channel state information (CSI) at each node. In the first part of this article, we provide a tutorial survey on various power allocation strategies for cooperative networks based on different cooperation strategies, optimizing criteria, and CSI assumptions. In the second part, we identify the similarities between cooperative networks and several sensor network applications that utilize collaboration among distributed sensors to achieve the system goal. These applications include decentralized detection/estimation and data gathering. The techniques developed in cooperative communications can be used to solve many sensor network problems