Deploying wireless sensor networks–based smart grid for smart meters monitoring and control

Transmission and distribution systems for electricity have undergone a technological revolution in terms of operation and management using computer networks, automation, remote sensing, and information and communication technologies to improve the performance of digital electronic meters. This work describes the integration of a wireless sensor networks (WSNs)–based communication system with an electrical energy‐measurement structure, to verify the feasibility of large‐scale installation of intelligent electronic meters in low‐voltage consumer units. The study is based on simulations, using Castalia, considering 2 scenarios, the first in a flat network and the second in a hierarchical network of WSNs to analyze the feasibility of sending messages from intelligent electronic meters to the concessionaires through a ZigBee network.In addition, the time requirements of the IEC 61850 standard for sending and receiving manufacturing message specifications and generic object‐oriented substation event type messages are verified. This work demonstrated the technical feasibility of using WSNs for different node densities by region and evaluated the location of the sink node, and adequate infrastructures for WSNs were found. This extends time checks for both vertical (usually for supervision) and horizontal (used for protection) messages. The proposed model has great potential to use a WSN infrastructure and to evaluate if this infrastructure allows data transmission of the protocols used in smart grids, mainly verifying the requirements of transmission times required by each application.     

Middleware for integration of legacy electrical equipment into smart grid infrastructure using wireless sensor networks

To improve the efficiency of electricity distribution, smart grids allow communication between their devices. Pieces of legacy equipment operating in the distribution network do not communicate using any commercial protocol, such as DNP3, IEC 61850, or Modbus. Thus, herein, a middleware is proposed to allow the integration of the legacy electrical equipment into a smart grid using wireless sensor networks (WSNs). Each piece of legacy electrical equipment is connected to a sensor node, and the WSN sink node runs a middleware to enable the integration of this device with a smart grid, according to the commercial communication protocols. The middleware model is proposed to guide users in the development of a WSN‐based system for integrating electrical equipment into a smart grid. The middleware was validated in a real environment, which is related to the concept of power metering. Experiments were performed using the software supervisory control and data acquisition and distributed test manager to validate the communication between the electrical equipment and the computer of the power substation control centre.     

HDF: Hybrid Debugging Framework for Distributed Network Environments

Debugging in distributed environments, such as wireless sensor networks (WSNs), which consist of sensor nodes with limited resources, is an iterative and occasionally laborious process for programmers. In sensor networks, it is not easy to find unintended bugs that arise during development and deployment, and that are due to a lack of visibility into the nodes and a dearth of effective debugging tools. Most sensor network debugging tools are not provided with effective facilities such as real‐time tracing, remote debugging, or a GUI environment. In this paper, we present a hybrid debugging framework (HDF) that works on WSNs. This framework supports query‐based monitoring and real‐time tracing on sensor nodes. The monitoring supports commands to manage/control the deployed nodes, and provides new debug commands. To do so, we devised a debugging device called a Docking Debug‐Box (D2‐Box), and two program agents. In addition, we provide a scalable node monitor to enable all deployed nodes for viewing. To transmit and collect their data or information reliably, all nodes are connected using a scalable node monitor applied through the Internet. Therefore, the suggested framework in theory does not increase the network traffic for debugging on WSNs, and the traffic complexity is nearly O(1).     

On the design of secure user authenticated key management scheme for multigateway‐based wireless sensor networks using ECC

In wireless sensor networks (WSNs), there are many critical applications (for example, healthcare, vehicle tracking, and battlefield), where the online streaming data generated from different sensor nodes need to be analyzed with respect to quick control decisions. However, as the data generated by these sensor nodes usually flow through open channel, so there are higher chances of various types of attacks either on the nodes or on to the data captured by these nodes. In this paper, we aim to design a new elliptic curve cryptography–based user authenticated key agreement protocol in a hierarchical WSN so that a legal user can only access the streaming data from generated from different sensor nodes. The proposed scheme is based upon 3‐factor authentication, as it applies smart card, password, and personal biometrics of a user (for ticket generation). The proposed scheme maintains low computation cost for resource‐constrained sensor nodes, as it uses efficient 1‐way cryptographic hash function and bitwise exclusive‐OR operations for secure key establishment between different sensor nodes. The security analysis using the broadly accepted Burrows‐Abadi‐Needham logic, formal security verification using the popular simulation tool (automated validation of Internet security protocols and applications), and informal security show that the proposed scheme is resilient against several well‐known attacks needed for a user authentication scheme in WSNs. The comparison of security and functionality requirements, communication and computation costs of the proposed scheme, and other related existing user authentication schemes shows the superior performance of the proposed scheme.     

Secure coverage-preserving node scheduling scheme using energy prediction for wireless sensor networks

With the fast development of the micro-electro-mechanical systems(MEMS),wireless sensor networks(WSNs)have been extensively studied.Most of the studies focus on saving energy consumption because of restricted energy supply in WSNs.Cluster-based node scheduling scheme is commonly considered as one of the most energy-efficient approaches.However,it is not always so efficient especially when there exist hot spot and network attacks in WSNs.In this article,a secure coverage-preserved node scheduling scheme for WSNs based on energy prediction is proposed in an uneven deployment environment.The scheme is comprised of an uneven clustering algorithm based on arithmetic progression,a cover set partition algorithm based on trust and a node scheduling algorithm based on energy prediction.Simulation results show that network lifetime of the scheme is 350 rounds longer than that of other scheduling algorithms.Furthermore,the scheme can keep a high network coverage ratio during the network lifetime and achieve the designed objective which makes energy dissipation of most nodes in WSNs balanced.     

A frequency‐aware data‐centric mechanism for wireless sensor networks

Wireless sensor networks (WSNs) are characterized by their low bandwidth, limited energy, and largely distributed deployment. To reduce the flooding overhead raised by transmitting query and data information, several data‐centric storage (DCS) mechanisms are proposed. However, the locations of these data‐centric nodes significantly impact the power consumption and efficiency for information queries and storage capabilities, especially in a multi‐sink environment. This paper proposes a novel dissemination approach, which is namely the dynamic data‐centric routing and storage mechanism (DDCRS), to dynamically determine locations of data‐centric nodes according to sink nodes' location and data collecting rate and automatically construct shared paths from data‐centric nodes to multiple sinks. To save the power consumption, the data‐centric node is changed when new sink nodes participate when the WSNs or some queries change their frequencies. The simulation results reveal that the proposed protocol outperforms existing protocols in terms of power conservation and power balancing. Copyright © 2009 John Wiley & Sons, Ltd.     

DR-NAP: Data reduction strategy using neural adaptation phenomenon in wireless sensor networks

Internet of Things (IoT) has got significant popularity among the researchers' community as they have been applied in numerous application domains. Most of the IoT applications are implemented with the help of wireless sensor networks (WSNs). These WSNs use different sensor nodes with a limited battery power supply. Hence, the energy of the sensor node is considered as one of the primary constraints of WSN. Besides, data communication in WSN dissipates more energy than processing the data. In most WSNs applications, the sensed data generated from the same location sensor nodes are identical or time-series/periodical data. This redundant data transmission leads to more energy consumption. To reduce the energy consumption, a data reduction strategy using neural adaptation phenomenon (DR-NAP) has been proposed to decrease the communication energy in routing data to the BS in WSN. The neural adaptation phenomenon has been utilized for designing a simple data reduction scheme to decrease the amount of data transmitted. In this way, the sensor node energy is saved and the lifetime of the network is enhanced. The proposed approach has been implanted in the existing gravitational search algorithm (GSA)-based clustered routing for WSN. The sensed data are transmitted to CH and BS using DR-NAP. Real sensor data from the Intel Berkeley Research lab have been used for conducting the experiments. The experiment results show 47.82% and 51.96% of improvement in network lifetime when compared with GSA-based clustered routing and clustering scheme using Canada Geese Migration Principle (CS-CGMP) for routing, respectively.     

Coverage and connectivity aware critical target monitoring for wireless sensor networks: Novel NSGA‐II–based approach

As sensor nodes have limited sensing and transmission capability, their efficient deployment takes an important role in proper monitoring of the critical targets in various applications of wireless sensor networks (WSNs). The key issues that need to be taken care during deployment are the lesser number of deployed sensors, coverage of the targets, and connectivity between the sensor nodes. In this paper, we have proposed NSGA‐II with modified dominance to solve the node deployment problem with the aforementioned three conflicting objectives. The conventional domination method is modified for better performance of the NSGA‐II. An intelligent representation of chromosome is provided. Three conflicting objectives are derived to evaluate the chromosomes. Extensive simulation on the proposed algorithm and the statistical test, and analysis of variance (ANOVA) followed by post hoc analysis are performed.     

基于物联网的智能家居服务网关的设计

为了实现智能家居系统中的远程及近程控制,从物联网的概念出发,设计实现了一个嵌入式的WEB网关服务器,将基于Zigbee协议的无线传感器网络与基于TCP/IP协议的Internet相联。该设计采用STM32F107VC为主控制器,通过串口实现与WSN协调器的通信,外接一个网卡芯片实现与Internet的连接。在软件设计上重点实现智能家居通信控制系统,并引入嵌入式操作系统uCOS-II对系统资源进行管理,移植LwIP协议栈实现TCP/IP的基本功能。     

基于能量监测的传感器信任评估方法研究

目前解决无线传感网节点安全的方式多种多样,无线传感器也将随着物联网的发展而呈现多样化.根据物联网传感层的特点和其特有的安全问题,本文提出了一种基于能量监测的信任评估方法来解决无线传感网节点的信任问题.该方法首先针对无线传感器能耗情况,创建了传感器能量监测机制;然后,根据监测能量机制中的监测信息,通过互相关系数方法分析计算,得出传感器所处的几种信任度;最后,对传感器进行信任评估,并给出评估结果.仿真对比结果表明,本文提出的方法具有较高的准确性.     

Efficient flow‐control algorithm cooperating with energy allocation scheme for solar‐powered WSNs

Recently, solar energy emerged as a feasible supplement to battery power for wireless sensor networks (WSNs) which are expected to operate for long periods. Since solar energy can be harvested periodically and permanently, solar‐powered WSNs can use the energy more efficiently for various network‐wide performances than traditional battery‐based WSNs of which aim is mostly to minimize the energy consumption for extending the network lifetime. However, using solar power in WSNs requires a different energy management from battery‐based WSNs since solar power is a highly varying energy supply. Therefore, firstly we describe a time‐slot‐based energy allocation scheme to use the solar energy optimally, based on expectation model for harvested solar energy. Then, we propose a flow‐control algorithm to maximize the amount of data collected by the network, which cooperates with our energy allocation scheme. Our algorithms run on each node in a distributed manner using only local information of its neighbors, which is a suitable approach for scalable WSNs. We implement indoor and outdoor testbeds of solar‐powered WSN and demonstrate the efficiency of our approaches on them. Copyright © 2010 John Wiley & Sons, Ltd.     

基于CoAP的无线传感器网络与互联网的互联研究

无线传感器网络与其他网络的互联是无线传感器网络研究热点方向之一,基于IPv6的全IP化互联方式是当前最受关注的焦点。本文介绍了在IP化无线传感器网络上实现REST风格服务的受限应用层协议CoAP,比较了CoAP与HTTP的不同和性能差异,最后提出和总结了基于CoAP的无线传感器网络与互联网的两种互联方式。     

DynaChannAl: dynamic channel allocation with minimal end‐to‐end delay for two‐tier wireless sensor networks

With recent advances in wireless networking and in low‐power sensor technology, wireless sensor networks (WSNs) have taken significant roles in various applications. Whereas some WSNs only require minimal bandwidth, newer applications operate with a noticeably larger amount of data. One way to deal with these applications is to maximize the available capacity by utilizing multiple wireless channels. We propose DynaChannAl, a distributed dynamic wireless channel allocation algorithm that effectively distributes nodes to multiple wireless channels in WSNs. Specifically, DynaChannAl targets applications where mobile nodes connect to preexisting wireless backbones and takes the expected end‐to‐end queuing delay as its core metric. We used the link quality indicator values provided by 802.15.4 radios to whitelist high‐quality links and evaluate these links with the aggregated queuing latency, making it useful for applications that require minimal end‐to‐end delay (i.e., health care). DynaChannAl is a lightweight and adoptable scheme that can be incorporated easily with predeveloped systems. As the first study to consider end‐to‐end latency as the core metric for channel allocation in WSNs, we evaluate DynaChannAl on a 45 node test bed and show that DynaChannAl successfully distributes source nodes to different channels and enables them to select channels and links that minimizes the end‐to‐end latency. Copyright © 2012 John Wiley & Sons, Ltd.     

Tree‐based channel assignment schemes for multi‐channel wireless sensor networks

Many sensor node platforms used for establishing wireless sensor networks (WSNs) can support multiple radio channels for wireless communication. Therefore, rather than using a single radio channel for whole network, multiple channels can be utilized in a sensor network simultaneously to decrease overall network interference, which may help increase the aggregate network throughput and decrease packet collisions and delays. This method, however, requires appropriate schemes to be used for assigning channels to nodes for multi‐channel communication in the network. Because data generated by sensor nodes are usually delivered to the sink node using routing trees, a tree‐based channel assignment scheme is a natural approach for assigning channels in a WSN. We present two fast tree‐based channel assignment schemes (called bottom up channel assignment and neighbor count‐based channel assignment) for multi‐channel WSNs. We also propose a new interference metric that is used by our algorithms in making decisions. We validated and evaluated our proposed schemes via extensive simulation experiments. Our simulation results show that our algorithms can decrease interference in a network, thereby increasing performance, and that our algorithms are good alternatives for static channel assignment in WSNs. Copyright © 2015 John Wiley & Sons, Ltd.     

A cluster‐based fault‐tolerant routing protocol for wireless sensor networks

Energy conservation and fault tolerance are two critical issues in the deployment of wireless sensor networks (WSNs). Many cluster‐based fault‐tolerant routing protocols have been proposed for energy conservation and network lifetime maximization in WSNs. However, these protocols suffer from high frequency of re‐clustering as well as extra energy consumption to tolerate failures and consider only some very normal parameters to form clusters without any verification of the energy sufficiency for data routing. Therefore, this paper proposes a cluster‐based fault‐tolerant routing protocol referred as CFTR. This protocol allows higher energy nodes to become Cluster Heads (CHs) and operate multiple rounds to diminish the frequency of re‐clustering. Additionally, for the sake to get better energy efficiency and balancing, we introduce a cost function that considers during cluster formation energy cost from sensor node to CH, energy cost from CH to sink, and another significant parameter, namely, number of cluster members in previous round. Further, the proposed CFTR takes care of nodes, which have no CH in their communication range. Also, it introduces a routing algorithm in which the decision of next hop CH selection is based on a cost function conceived to select routes with sufficient energy for data transfer and distribute uniformly the overall data‐relaying load among the CHs. As well, a low‐overhead algorithm to tolerate the sudden failure of CHs is proposed. We perform extensive simulations on CFTR and compare their results with those of two recent existing protocols to demonstrate its superiority in terms of different metrics.     

e‐LiteSense: Self‐adaptive energy‐aware data sensing in WSN environments

Currently deployed in a wide variety of applicational scenarios, wireless sensor networks (WSNs) are typically a resource‐constrained infrastructure. Consequently, characteristics such as WSN adaptability, low‐overhead, and low‐energy consumption are particularly relevant in dynamic and autonomous sensing environments where the measuring requirements change and human intervention is not viable. To tackle this issue, this article proposes e‐LiteSense as an adaptive, energy‐aware sensing solution for WSNs, capable of auto‐regulate how data are sensed, adjusting it to each applicational scenario. The proposed adaptive scheme is able to maintain the sensing accuracy of the physical phenomena, while reducing the overall process overhead. In this way, the adaptive algorithm relies on low‐complexity rules to establish the sensing frequency weighting the recent drifts of the physical parameter and the levels of remaining energy in the sensor. Using datasets from WSN operational scenarios, we prove e‐LiteSense effectiveness in self‐regulating data sensing accurately through a low‐overhead process where the WSN energy levels are preserved. This constitutes a step‐forward for implementing self‐adaptive energy‐aware data sensing in dynamic WSN environments.     

A lightweight,self‐adaptive lock gate designation scheme for data collection in long‐thin wireless sensor networks

Constrained by the physical environments, the long‐thin topology has recently been promoted for many practical deployments of wireless sensor networks (WSNs). In general, a long‐thin topology is composed of a number of long branches of sensor nodes, where along a branch each sensor node has only one potential parent node toward the sink node. Although data aggregation may alleviate excessive packet contention, the maximum payload size of a packet and the dynamically changing traffic loads may severely affect the amount of sensor readings that may be collected along a long branch of sensor nodes. In addition, many practical applications of long‐thin WSNs demand the exact sensor readings at each location along the deployment areas for monitoring and analysis purposes, so sensor readings may not be aggregated when they are collected. This paper proposes a lightweight, self‐adaptive scheme that designates multiple collection nodes, termed lock gates, along a long‐thin network to collect sensor readings sent from their respective upstream sensor nodes. The self‐adaptive lock gate designation scheme balances between the responsiveness and the congestion of data collection while mitigating the funneling effect. The scheme also dynamically adapts the designation of lock gates to accommodate the time‐varying sensor reading generation rates of different sensor nodes. A testbed of 100 Jennic sensor nodes is developed to demonstrate the effectiveness of the proposed lock gate designation scheme. Copyright © 2011 John Wiley & Sons, Ltd.     

PFARS: Enhancing throughput and lifetime of heterogeneous WSNs through power‐aware fusion,aggregation, and routing scheme

Heterogeneous wireless sensor networks (WSNs) consist of resource‐starving nodes that face a challenging task of handling various issues such as data redundancy, data fusion, congestion control, and energy efficiency. In these networks, data fusion algorithms process the raw data generated by a sensor node in an energy‐efficient manner to reduce redundancy, improve accuracy, and enhance the network lifetime. In literature, these issues are addressed individually, and most of the proposed solutions are either application‐specific or too complex that make their implementation unrealistic, specifically, in a resource‐constrained environment. In this paper, we propose a novel node‐level data fusion algorithm for heterogeneous WSNs to detect noisy data and replace them with highly refined data. To minimize the amount of transmitted data, a hybrid data aggregation algorithm is proposed that performs in‐network processing while preserving the reliability of gathered data. This combination of data fusion and data aggregation algorithms effectively handle the aforementioned issues by ensuring an efficient utilization of the available resources. Apart from fusion and aggregation, a biased traffic distribution algorithm is introduced that considerably increases the overall lifetime of heterogeneous WSNs. The proposed algorithm performs the tedious task of traffic distribution according to the network's statistics, ie, the residual energy of neighboring nodes and their importance from a network's connectivity perspective. All our proposed algorithms were tested on a real‐time dataset obtained through our deployed heterogeneous WSN in an orange orchard and also on publicly available benchmark datasets. Experimental results verify that our proposed algorithms outperform the existing approaches in terms of various performance metrics such as throughput, lifetime, data accuracy, computational time, and delay.     

Congestion control in wireless sensor and 6LoWPAN networks: toward the Internet of Things

The Internet of Things (IoT) is the next big challenge for the research community where the IPv6 over low power wireless personal area network (6LoWPAN) protocol stack is a key part of the IoT. Recently, the IETF ROLL and 6LoWPAN working groups have developed new IP based protocols for 6LoWPAN networks to alleviate the challenges of connecting low memory, limited processing capability, and constrained power supply sensor nodes to the Internet. In 6LoWPAN networks, heavy network traffic causes congestion which significantly degrades network performance and impacts on quality of service aspects such as throughput, latency, energy consumption, reliability, and packet delivery. In this paper, we overview the protocol stack of 6LoWPAN networks and summarize a set of its protocols and standards. Also, we review and compare a number of popular congestion control mechanisms in wireless sensor networks (WSNs) and classify them into traffic control, resource control, and hybrid algorithms based on the congestion control strategy used. We present a comparative review of all existing congestion control approaches in 6LoWPAN networks. This paper highlights and discusses the differences between congestion control mechanisms for WSNs and 6LoWPAN networks as well as explaining the suitability and validity of WSN congestion control schemes for 6LoWPAN networks. Finally, this paper gives some potential directions for designing a novel congestion control protocol, which supports the IoT application requirements, in future work.