Sensors

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1238 KiB

Open AccessArticle

Distributed Data Service for Data Management in Internet of Things Middleware

by Ruben Cruz Huacarpuma, Rafael Timoteo De Sousa Junior, Maristela Terto De Holanda, Robson De Oliveira Albuquerque, Luis Javier García Villalba and Tai-Hoon Kim

Sensors 2017, 17(5), 977; https://doi.org/10.3390/s17050977 - 27 Apr 2017

Cited by 41 | Viewed by 8637

Abstract

The development of the Internet of Things (IoT) is closely related to a considerable increase in the number and variety of devices connected to the Internet. Sensors have become a regular component of our environment, as well as smart phones and other devices [...] Read more.

The development of the Internet of Things (IoT) is closely related to a considerable increase in the number and variety of devices connected to the Internet. Sensors have become a regular component of our environment, as well as smart phones and other devices that continuously collect data about our lives even without our intervention. With such connected devices, a broad range of applications has been developed and deployed, including those dealing with massive volumes of data. In this paper, we introduce a Distributed Data Service (DDS) to collect and process data for IoT environments. One central goal of this DDS is to enable multiple and distinct IoT middleware systems to share common data services from a loosely-coupled provider. In this context, we propose a new specification of functionalities for a DDS and the conception of the corresponding techniques for collecting, filtering and storing data conveniently and efficiently in this environment. Another contribution is a data aggregation component that is proposed to support efficient real-time data querying. To validate its data collecting and querying functionalities and performance, the proposed DDS is evaluated in two case studies regarding a simulated smart home system, the first case devoted to evaluating data collection and aggregation when the DDS is interacting with the UIoT middleware, and the second aimed at comparing the DDS data collection with this same functionality implemented within the Kaa middleware. Full article

(This article belongs to the Special Issue Topology Control in Emerging Sensor Networks)

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2680 KiB

Open AccessArticle

Measuring Complexity and Predictability of Time Series with Flexible Multiscale Entropy for Sensor Networks

by Renjie Zhou, Chen Yang, Jian Wan, Wei Zhang, Bo Guan and Naixue Xiong

Sensors 2017, 17(4), 787; https://doi.org/10.3390/s17040787 - 6 Apr 2017

Cited by 14 | Viewed by 4646

Abstract

Measurement of time series complexity and predictability is sometimes the cornerstone for proposing solutions to topology and congestion control problems in sensor networks. As a method of measuring time series complexity and predictability, multiscale entropy (MSE) has been widely applied in many fields. [...] Read more.

Measurement of time series complexity and predictability is sometimes the cornerstone for proposing solutions to topology and congestion control problems in sensor networks. As a method of measuring time series complexity and predictability, multiscale entropy (MSE) has been widely applied in many fields. However, sample entropy, which is the fundamental component of MSE, measures the similarity of two subsequences of a time series with either zero or one, but without in-between values, which causes sudden changes of entropy values even if the time series embraces small changes. This problem becomes especially severe when the length of time series is getting short. For solving such the problem, we propose flexible multiscale entropy (FMSE), which introduces a novel similarity function measuring the similarity of two subsequences with full-range values from zero to one, and thus increases the reliability and stability of measuring time series complexity. The proposed method is evaluated on both synthetic and real time series, including white noise, 1/f noise and real vibration signals. The evaluation results demonstrate that FMSE has a significant improvement in reliability and stability of measuring complexity of time series, especially when the length of time series is short, compared to MSE and composite multiscale entropy (CMSE). The proposed method FMSE is capable of improving the performance of time series analysis based topology and traffic congestion control techniques. Full article

(This article belongs to the Special Issue Topology Control in Emerging Sensor Networks)

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3499 KiB

Open AccessArticle

A Quantitative Risk Assessment Model Involving Frequency and Threat Degree under Line-of-Business Services for Infrastructure of Emerging Sensor Networks

by Xu Jing, Hanwen Hu, Huijun Yang, Man Ho Au, Shuqin Li, Naixue Xiong, Muhammad Imran and Athanasios V. Vasilakos

Sensors 2017, 17(3), 642; https://doi.org/10.3390/s17030642 - 21 Mar 2017

Cited by 10 | Viewed by 4907

Abstract

The prospect of Line-of-Business Services (LoBSs) for infrastructure of Emerging Sensor Networks (ESNs) is exciting. Access control remains a top challenge in this scenario as the service provider’s server contains a lot of valuable resources. LoBSs’ users are very diverse as they may [...] Read more.

The prospect of Line-of-Business Services (LoBSs) for infrastructure of Emerging Sensor Networks (ESNs) is exciting. Access control remains a top challenge in this scenario as the service provider’s server contains a lot of valuable resources. LoBSs’ users are very diverse as they may come from a wide range of locations with vastly different characteristics. Cost of joining could be low and in many cases, intruders are eligible users conducting malicious actions. As a result, user access should be adjusted dynamically. Assessing LoBSs’ risk dynamically based on both frequency and threat degree of malicious operations is therefore necessary. In this paper, we proposed a Quantitative Risk Assessment Model (QRAM) involving frequency and threat degree based on value at risk. To quantify the threat degree as an elementary intrusion effort, we amend the influence coefficient of risk indexes in the network security situation assessment model. To quantify threat frequency as intrusion trace effort, we make use of multiple behavior information fusion. Under the influence of intrusion trace, we adapt the historical simulation method of value at risk to dynamically access LoBSs’ risk. Simulation based on existing data is used to select appropriate parameters for QRAM. Our simulation results show that the duration influence on elementary intrusion effort is reasonable when the normalized parameter is 1000. Likewise, the time window of intrusion trace and the weight between objective risk and subjective risk can be set to 10 s and 0.5, respectively. While our focus is to develop QRAM for assessing the risk of LoBSs for infrastructure of ESNs dynamically involving frequency and threat degree, we believe it is also appropriate for other scenarios in cloud computing. Full article

(This article belongs to the Special Issue Topology Control in Emerging Sensor Networks)

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Open AccessArticle

A Novel Topology Link-Controlling Approach for Active Defense of Nodes in Networks

by Jun Li, HanPing Hu, Qiao Ke and Naixue Xiong

Sensors 2017, 17(3), 553; https://doi.org/10.3390/s17030553 - 9 Mar 2017

Cited by 8 | Viewed by 5221

Abstract

With the rapid development of virtual machine technology and cloud computing, distributed denial of service (DDoS) attacks, or some peak traffic, poses a great threat to the security of the network. In this paper, a novel topology link control technique and mitigation attacks [...] Read more.

With the rapid development of virtual machine technology and cloud computing, distributed denial of service (DDoS) attacks, or some peak traffic, poses a great threat to the security of the network. In this paper, a novel topology link control technique and mitigation attacks in real-time environments is proposed. Firstly, a non-invasive method of deploying virtual sensors in the nodes is built, which uses the resource manager of each monitored node as a sensor. Secondly, a general topology-controlling approach of resisting the tolerant invasion is proposed. In the proposed approach, a prediction model is constructed by using copula functions for predicting the peak of a resource through another resource. The result of prediction determines whether or not to initiate the active defense. Finally, a minority game with incomplete strategy is employed to suppress attack flows and improve the permeability of the normal flows. The simulation results show that the proposed approach is very effective in protecting nodes. Full article

(This article belongs to the Special Issue Topology Control in Emerging Sensor Networks)

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1021 KiB

Open AccessArticle

A Topology Control Strategy with Reliability Assurance for Satellite Cluster Networks in Earth Observation

by Qing Chen, Jinxiu Zhang and Ze Hu

Sensors 2017, 17(3), 445; https://doi.org/10.3390/s17030445 - 23 Feb 2017

Cited by 9 | Viewed by 4502

Abstract

This article investigates the dynamic topology control problemof satellite cluster networks (SCNs) in Earth observation (EO) missions by applying a novel metric of stability for inter-satellite links (ISLs). The properties of the periodicity and predictability of satellites’ relative position are involved in the [...] Read more.

This article investigates the dynamic topology control problemof satellite cluster networks (SCNs) in Earth observation (EO) missions by applying a novel metric of stability for inter-satellite links (ISLs). The properties of the periodicity and predictability of satellites’ relative position are involved in the link cost metric which is to give a selection criterion for choosing the most reliable data routing paths. Also, a cooperative work model with reliability is proposed for the situation of emergency EO missions. Based on the link cost metric and the proposed reliability model, a reliability assurance topology control algorithm and its corresponding dynamic topology control (RAT) strategy are established to maximize the stability of data transmission in the SCNs. The SCNs scenario is tested through some numeric simulations of the topology stability of average topology lifetime and average packet loss rate. Simulation results show that the proposed reliable strategy applied in SCNs significantly improves the data transmission performance and prolongs the average topology lifetime. Full article

(This article belongs to the Special Issue Topology Control in Emerging Sensor Networks)

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Open AccessArticle

A Web of Things-Based Emerging Sensor Network Architecture for Smart Control Systems

by Murad Khan, Bhagya Nathali Silva and Kijun Han

Sensors 2017, 17(2), 332; https://doi.org/10.3390/s17020332 - 9 Feb 2017

Cited by 42 | Viewed by 6848

Abstract

The Web of Things (WoT) plays an important role in the representation of the objects connected to the Internet of Things in a more transparent and effective way. Thus, it enables seamless and ubiquitous web communication between users and the smart things. Considering [...] Read more.

The Web of Things (WoT) plays an important role in the representation of the objects connected to the Internet of Things in a more transparent and effective way. Thus, it enables seamless and ubiquitous web communication between users and the smart things. Considering the importance of WoT, we propose a WoT-based emerging sensor network (WoT-ESN), which collects data from sensors, routes sensor data to the web, and integrate smart things into the web employing a representational state transfer (REST) architecture. A smart home scenario is introduced to evaluate the proposed WoT-ESN architecture. The smart home scenario is tested through computer simulation of the energy consumption of various household appliances, device discovery, and response time performance. The simulation results show that the proposed scheme significantly optimizes the energy consumption of the household appliances and the response time of the appliances. Full article

(This article belongs to the Special Issue Topology Control in Emerging Sensor Networks)

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Open AccessArticle

Effective Alternating Direction Optimization Methods for Sparsity-Constrained Blind Image Deblurring

by Naixue Xiong, Ryan Wen Liu, Maohan Liang, Di Wu, Zhao Liu and Huisi Wu

Sensors 2017, 17(1), 174; https://doi.org/10.3390/s17010174 - 18 Jan 2017

Cited by 37 | Viewed by 7022

Abstract

Single-image blind deblurring for imaging sensors in the Internet of Things (IoT) is a challenging ill-conditioned inverse problem, which requires regularization techniques to stabilize the image restoration process. The purpose is to recover the underlying blur kernel and latent sharp image from only [...] Read more.

Single-image blind deblurring for imaging sensors in the Internet of Things (IoT) is a challenging ill-conditioned inverse problem, which requires regularization techniques to stabilize the image restoration process. The purpose is to recover the underlying blur kernel and latent sharp image from only one blurred image. Under many degraded imaging conditions, the blur kernel could be considered not only spatially sparse, but also piecewise smooth with the support of a continuous curve. By taking advantage of the hybrid sparse properties of the blur kernel, a hybrid regularization method is proposed in this paper to robustly and accurately estimate the blur kernel. The effectiveness of the proposed blur kernel estimation method is enhanced by incorporating both the

L_{1}

-norm of kernel intensity and the squared

L_{2}

-norm of the intensity derivative. Once the accurate estimation of the blur kernel is obtained, the original blind deblurring can be simplified to the direct deconvolution of blurred images. To guarantee robust non-blind deconvolution, a variational image restoration model is presented based on the

L_{1}

-norm data-fidelity term and the total generalized variation (TGV) regularizer of second-order. All non-smooth optimization problems related to blur kernel estimation and non-blind deconvolution are effectively handled by using the alternating direction method of multipliers (ADMM)-based numerical methods. Comprehensive experiments on both synthetic and realistic datasets have been implemented to compare the proposed method with several state-of-the-art methods. The experimental comparisons have illustrated the satisfactory imaging performance of the proposed method in terms of quantitative and qualitative evaluations. Full article

(This article belongs to the Special Issue Topology Control in Emerging Sensor Networks)

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614 KiB

Open AccessArticle

Cluster-Based Maximum Consensus Time Synchronization for Industrial Wireless Sensor Networks

by Zhaowei Wang, Peng Zeng, Mingtuo Zhou, Dong Li and Jintao Wang

Sensors 2017, 17(1), 141; https://doi.org/10.3390/s17010141 - 13 Jan 2017

Cited by 38 | Viewed by 6279

Abstract

Time synchronization is one of the key technologies in Industrial Wireless Sensor Networks (IWSNs), and clustering is widely used in WSNs for data fusion and information collection to reduce redundant data and communication overhead. Considering IWSNs’ demand for low energy consumption, fast convergence, [...] Read more.

Time synchronization is one of the key technologies in Industrial Wireless Sensor Networks (IWSNs), and clustering is widely used in WSNs for data fusion and information collection to reduce redundant data and communication overhead. Considering IWSNs’ demand for low energy consumption, fast convergence, and robustness, this paper presents a novel Cluster-based Maximum consensus Time Synchronization (CMTS) method. It consists of two parts: intra-cluster time synchronization and inter-cluster time synchronization. Based on the theory of distributed consensus, the proposed method utilizes the maximum consensus approach to realize the intra-cluster time synchronization, and adjacent clusters exchange the time messages via overlapping nodes to synchronize with each other. A Revised-CMTS is further proposed to counteract the impact of bounded communication delays between two connected nodes, because the traditional stochastic models of the communication delays would distort in a dynamic environment. The simulation results show that our method reduces the communication overhead and improves the convergence rate in comparison to existing works, as well as adapting to the uncertain bounded communication delays. Full article

(This article belongs to the Special Issue Topology Control in Emerging Sensor Networks)

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Open AccessArticle

A Social Potential Fields Approach for Self-Deployment and Self-Healing in Hierarchical Mobile Wireless Sensor Networks

by Eva González-Parada, Jose Cano-García, Francisco Aguilera, Francisco Sandoval and Cristina Urdiales

Sensors 2017, 17(1), 120; https://doi.org/10.3390/s17010120 - 9 Jan 2017

Cited by 7 | Viewed by 4971

Abstract

Autonomous mobile nodes in mobile wireless sensor networks (MWSN) allow self-deployment and self-healing. In both cases, the goals are: (i) to achieve adequate coverage; and (ii) to extend network life. In dynamic environments, nodes may use reactive algorithms so that each node locally [...] Read more.

Autonomous mobile nodes in mobile wireless sensor networks (MWSN) allow self-deployment and self-healing. In both cases, the goals are: (i) to achieve adequate coverage; and (ii) to extend network life. In dynamic environments, nodes may use reactive algorithms so that each node locally decides when and where to move. This paper presents a behavior-based deployment and self-healing algorithm based on the social potential fields algorithm. In the proposed algorithm, nodes are attached to low cost robots to autonomously navigate in the coverage area. The proposed algorithm has been tested in environments with and without obstacles. Our study also analyzes the differences between non-hierarchical and hierarchical routing configurations in terms of network life and coverage. Full article

(This article belongs to the Special Issue Topology Control in Emerging Sensor Networks)

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Open AccessArticle

Node Deployment with k-Connectivity in Sensor Networks for Crop Information Full Coverage Monitoring

by Naisen Liu, Weixing Cao, Yan Zhu, Jingchao Zhang, Fangrong Pang and Jun Ni

Sensors 2016, 16(12), 2096; https://doi.org/10.3390/s16122096 - 9 Dec 2016

Cited by 11 | Viewed by 6423

Abstract

Wireless sensor networks (WSNs) are suitable for the continuous monitoring of crop information in large-scale farmland. The information obtained is great for regulation of crop growth and achieving high yields in precision agriculture (PA). In order to realize full coverage and k-connectivity [...] Read more.

Wireless sensor networks (WSNs) are suitable for the continuous monitoring of crop information in large-scale farmland. The information obtained is great for regulation of crop growth and achieving high yields in precision agriculture (PA). In order to realize full coverage and k-connectivity WSN deployment for monitoring crop growth information of farmland on a large scale and to ensure the accuracy of the monitored data, a new WSN deployment method using a genetic algorithm (GA) is here proposed. The fitness function of GA was constructed based on the following WSN deployment criteria: (1) nodes must be located in the corresponding plots; (2) WSN must have k-connectivity; (3) WSN must have no communication silos; (4) the minimum distance between node and plot boundary must be greater than a specific value to prevent each node from being affected by the farmland edge effect. The deployment experiments were performed on natural farmland and on irregular farmland divided based on spatial differences of soil nutrients. Results showed that both WSNs gave full coverage, there were no communication silos, and the minimum connectivity of nodes was equal to k. The deployment was tested for different values of k and transmission distance (d) to the node. The results showed that, when d was set to 200 m, as k increased from 2 to 4 the minimum connectivity of nodes increases and is equal to k. When k was set to 2, the average connectivity of all nodes increased in a linear manner with the increase of d from 140 m to 250 m, and the minimum connectivity does not change. Full article

(This article belongs to the Special Issue Topology Control in Emerging Sensor Networks)

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4181 KiB

Open AccessArticle

Adjustable Trajectory Design Based on Node Density for Mobile Sink in WSNs

by Guisong Yang, Shuai Liu, Xingyu He, Naixue Xiong and Chunxue Wu

Sensors 2016, 16(12), 2091; https://doi.org/10.3390/s16122091 - 9 Dec 2016

Cited by 13 | Viewed by 4604

Abstract

The design of movement trajectories for mobile sink plays an important role in data gathering for Wireless Sensor Networks (WSNs), as it affects the network coverage, and packet delivery ratio, as well as the network lifetime. In some scenarios, the whole network can [...] Read more.

The design of movement trajectories for mobile sink plays an important role in data gathering for Wireless Sensor Networks (WSNs), as it affects the network coverage, and packet delivery ratio, as well as the network lifetime. In some scenarios, the whole network can be divided into subareas where the nodes are randomly deployed. The node densities of these subareas are quite different, which may result in a decreased packet delivery ratio and network lifetime if the movement trajectory of the mobile sink cannot adapt to these differences. To address these problems, we propose an adjustable trajectory design method based on node density for mobile sink in WSNs. The movement trajectory of the mobile sink in each subarea follows the Hilbert space-filling curve. Firstly, the trajectory is constructed based on network size. Secondly, the adjustable trajectory is established based on node density in specific subareas. Finally, the trajectories in each subarea are combined to acquire the whole network’s movement trajectory for the mobile sink. In addition, an adaptable power control scheme is designed to adjust nodes’ transmitting range dynamically according to the movement trajectory of the mobile sink in each subarea. The simulation results demonstrate that the proposed trajectories can adapt to network changes flexibly, thus outperform both in packet delivery ratio and in energy consumption the trajectories designed only based on the network size and the whole network node density. Full article

(This article belongs to the Special Issue Topology Control in Emerging Sensor Networks)

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Open AccessArticle

Lightweight Sensor Authentication Scheme for Energy Efficiency in Ubiquitous Computing Environments

by Jaeseung Lee, Yunsick Sung and Jong Hyuk Park

Sensors 2016, 16(12), 2044; https://doi.org/10.3390/s16122044 - 1 Dec 2016

Cited by 19 | Viewed by 6124

Abstract

The Internet of Things (IoT) is the intelligent technologies and services that mutually communicate information between humans and devices or between Internet-based devices. In IoT environments, various device information is collected from the user for intelligent technologies and services that control the devices. [...] Read more.

The Internet of Things (IoT) is the intelligent technologies and services that mutually communicate information between humans and devices or between Internet-based devices. In IoT environments, various device information is collected from the user for intelligent technologies and services that control the devices. Recently, wireless sensor networks based on IoT environments are being used in sectors as diverse as medicine, the military, and commerce. Specifically, sensor techniques that collect relevant area data via mini-sensors after distributing smart dust in inaccessible areas like forests or military zones have been embraced as the future of information technology. IoT environments that utilize smart dust are composed of the sensor nodes that detect data using wireless sensors and transmit the detected data to middle nodes. Currently, since the sensors used in these environments are composed of mini-hardware, they have limited memory, processing power, and energy, and a variety of research that aims to make the best use of these limited resources is progressing. This paper proposes a method to utilize these resources while considering energy efficiency, and suggests lightweight mutual verification and key exchange methods based on a hash function that has no restrictions on operation quantity, velocity, and storage space. This study verifies the security and energy efficiency of this method through security analysis and function evaluation, comparing with existing approaches. The proposed method has great value in its applicability as a lightweight security technology for IoT environments. Full article

(This article belongs to the Special Issue Topology Control in Emerging Sensor Networks)

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917 KiB

Open AccessArticle

Market Model for Resource Allocation in Emerging Sensor Networks with Reinforcement Learning

by Yue Zhang, Bin Song, Ying Zhang, Xiaojiang Du and Mohsen Guizani

Sensors 2016, 16(12), 2021; https://doi.org/10.3390/s16122021 - 29 Nov 2016

Cited by 3 | Viewed by 5530

Abstract

Emerging sensor networks (ESNs) are an inevitable trend with the development of the Internet of Things (IoT), and intend to connect almost every intelligent device. Therefore, it is critical to study resource allocation in such an environment, due to the concern of efficiency, [...] Read more.

Emerging sensor networks (ESNs) are an inevitable trend with the development of the Internet of Things (IoT), and intend to connect almost every intelligent device. Therefore, it is critical to study resource allocation in such an environment, due to the concern of efficiency, especially when resources are limited. By viewing ESNs as multi-agent environments, we model them with an agent-based modelling (ABM) method and deal with resource allocation problems with market models, after describing users’ patterns. Reinforcement learning methods are introduced to estimate users’ patterns and verify the outcomes in our market models. Experimental results show the efficiency of our methods, which are also capable of guiding topology management. Full article

(This article belongs to the Special Issue Topology Control in Emerging Sensor Networks)

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Open AccessArticle

An Improved Mobility-Based Control Protocol for Tolerating Clone Failures in Wireless Sensor Networks

by Yuping Zhou, Naixue Xiong, Mingxin Tan, Rufeng Huang and Jon Kleonbet

Sensors 2016, 16(11), 1955; https://doi.org/10.3390/s16111955 - 23 Nov 2016

Cited by 3 | Viewed by 4578

Abstract

Nowadays, with the ubiquitous presence of the Internet of Things industry, the application of emerging sensor networks has become a focus of public attention. Unattended sensor nodes can be comprised and cloned to destroy the network topology. This paper proposes a novel distributed [...] Read more.

Nowadays, with the ubiquitous presence of the Internet of Things industry, the application of emerging sensor networks has become a focus of public attention. Unattended sensor nodes can be comprised and cloned to destroy the network topology. This paper proposes a novel distributed protocol and management technique for the detection of mobile replicas to tolerate node failures. In our scheme, sensors’ location claims are forwarded to obtain samples only when the corresponding witnesses meet. Meanwhile, sequential tests of statistical hypotheses are applied to further detect the cloned node by witnesses. The combination of randomized detection based on encountering and sequential tests drastically reduces the routing overhead and false positive/negative rate for detection. Theoretical analysis and simulation results show the detection efficiency and reasonable overhead of the proposed method. Full article

(This article belongs to the Special Issue Topology Control in Emerging Sensor Networks)

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Open AccessArticle

A Methodological Approach for Assessing Amplified Reflection Distributed Denial of Service on the Internet of Things

by João José Costa Gondim, Robson De Oliveira Albuquerque, Anderson Clayton Alves Nascimento, Luis Javier García Villalba and Tai-Hoon Kim

Sensors 2016, 16(11), 1855; https://doi.org/10.3390/s16111855 - 4 Nov 2016

Cited by 19 | Viewed by 8431

Abstract

Concerns about security on Internet of Things (IoT) cover data privacy and integrity, access control, and availability. IoT abuse in distributed denial of service attacks is a major issue, as typical IoT devices’ limited computing, communications, and power resources are prioritized in implementing [...] Read more.

Concerns about security on Internet of Things (IoT) cover data privacy and integrity, access control, and availability. IoT abuse in distributed denial of service attacks is a major issue, as typical IoT devices’ limited computing, communications, and power resources are prioritized in implementing functionality rather than security features. Incidents involving attacks have been reported, but without clear characterization and evaluation of threats and impacts. The main purpose of this work is to methodically assess the possible impacts of a specific class–amplified reflection distributed denial of service attacks (AR-DDoS)–against IoT. The novel approach used to empirically examine the threat represented by running the attack over a controlled environment, with IoT devices, considered the perspective of an attacker. The methodology used in tests includes that perspective, and actively prospects vulnerabilities in computer systems. This methodology defines standardized procedures for tool-independent vulnerability assessment based on strategy, and the decision flows during execution of penetration tests (pentests). After validation in different scenarios, the methodology was applied in amplified reflection distributed denial of service (AR-DDoS) attack threat assessment. Results show that, according to attack intensity, AR-DDoS saturates reflector infrastructure. Therefore, concerns about AR-DDoS are founded, but expected impact on abused IoT infrastructure and devices will be possibly as hard as on final victims. Full article

(This article belongs to the Special Issue Topology Control in Emerging Sensor Networks)

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Open AccessArticle

An Effective Massive Sensor Network Data Access Scheme Based on Topology Control for the Internet of Things

by Meng Yi, Qingkui Chen and Neal N. Xiong

Sensors 2016, 16(11), 1846; https://doi.org/10.3390/s16111846 - 3 Nov 2016

Cited by 7 | Viewed by 5587

Abstract

This paper considers the distributed access and control problem of massive wireless sensor networks’ data access center for the Internet of Things, which is an extension of wireless sensor networks and an element of its topology structure. In the context of the arrival [...] Read more.

This paper considers the distributed access and control problem of massive wireless sensor networks’ data access center for the Internet of Things, which is an extension of wireless sensor networks and an element of its topology structure. In the context of the arrival of massive service access requests at a virtual data center, this paper designs a massive sensing data access and control mechanism to improve the access efficiency of service requests and makes full use of the available resources at the data access center for the Internet of things. Firstly, this paper proposes a synergistically distributed buffer access model, which separates the information of resource and location. Secondly, the paper divides the service access requests into multiple virtual groups based on their characteristics and locations using an optimized self-organizing feature map neural network. Furthermore, this paper designs an optimal scheduling algorithm of group migration based on the combination scheme between the artificial bee colony algorithm and chaos searching theory. Finally, the experimental results demonstrate that this mechanism outperforms the existing schemes in terms of enhancing the accessibility of service requests effectively, reducing network delay, and has higher load balancing capacity and higher resource utility rate. Full article

(This article belongs to the Special Issue Topology Control in Emerging Sensor Networks)

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Open AccessArticle

Estimation of Anonymous Email Network Characteristics through Statistical Disclosure Attacks

by Javier Portela, Luis Javier García Villalba, Alejandra Guadalupe Silva Trujillo, Ana Lucila Sandoval Orozco and Tai-Hoon Kim

Sensors 2016, 16(11), 1832; https://doi.org/10.3390/s16111832 - 1 Nov 2016

Cited by 6 | Viewed by 5285

Abstract

Social network analysis aims to obtain relational data from social systems to identify leaders, roles, and communities in order to model profiles or predict a specific behavior in users’ network. Preserving anonymity in social networks is a subject of major concern. Anonymity can [...] Read more.

Social network analysis aims to obtain relational data from social systems to identify leaders, roles, and communities in order to model profiles or predict a specific behavior in users’ network. Preserving anonymity in social networks is a subject of major concern. Anonymity can be compromised by disclosing senders’ or receivers’ identity, message content, or sender-receiver relationships. Under strongly incomplete information, a statistical disclosure attack is used to estimate the network and node characteristics such as centrality and clustering measures, degree distribution, and small-world-ness. A database of email networks in 29 university faculties is used to study the method. A research on the small-world-ness and Power law characteristics of these email networks is also developed, helping to understand the behavior of small email networks. Full article

(This article belongs to the Special Issue Topology Control in Emerging Sensor Networks)

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Open AccessArticle

A Novel Energy Efficient Topology Control Scheme Based on a Coverage-Preserving and Sleep Scheduling Model for Sensor Networks

by Binbin Shi, Wei Wei, Yihuai Wang and Wanneng Shu

Sensors 2016, 16(10), 1702; https://doi.org/10.3390/s16101702 - 14 Oct 2016

Cited by 10 | Viewed by 4748

Abstract

In high-density sensor networks, scheduling some sensor nodes to be in the sleep mode while other sensor nodes remain active for monitoring or forwarding packets is an effective control scheme to conserve energy. In this paper, a Coverage-Preserving Control Scheduling Scheme (CPCSS) based [...] Read more.

In high-density sensor networks, scheduling some sensor nodes to be in the sleep mode while other sensor nodes remain active for monitoring or forwarding packets is an effective control scheme to conserve energy. In this paper, a Coverage-Preserving Control Scheduling Scheme (CPCSS) based on a cloud model and redundancy degree in sensor networks is proposed. Firstly, the normal cloud model is adopted for calculating the similarity degree between the sensor nodes in terms of their historical data, and then all nodes in each grid of the target area can be classified into several categories. Secondly, the redundancy degree of a node is calculated according to its sensing area being covered by the neighboring sensors. Finally, a centralized approximation algorithm based on the partition of the target area is designed to obtain the approximate minimum set of nodes, which can retain the sufficient coverage of the target region and ensure the connectivity of the network at the same time. The simulation results show that the proposed CPCSS can balance the energy consumption and optimize the coverage performance of the sensor network. Full article

(This article belongs to the Special Issue Topology Control in Emerging Sensor Networks)

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Open AccessArticle

A Hybrid Spectral Clustering and Deep Neural Network Ensemble Algorithm for Intrusion Detection in Sensor Networks

by Tao Ma, Fen Wang, Jianjun Cheng, Yang Yu and Xiaoyun Chen

Sensors 2016, 16(10), 1701; https://doi.org/10.3390/s16101701 - 13 Oct 2016

Cited by 188 | Viewed by 11652

Abstract

The development of intrusion detection systems (IDS) that are adapted to allow routers and network defence systems to detect malicious network traffic disguised as network protocols or normal access is a critical challenge. This paper proposes a novel approach called SCDNN, which combines [...] Read more.

The development of intrusion detection systems (IDS) that are adapted to allow routers and network defence systems to detect malicious network traffic disguised as network protocols or normal access is a critical challenge. This paper proposes a novel approach called SCDNN, which combines spectral clustering (SC) and deep neural network (DNN) algorithms. First, the dataset is divided into k subsets based on sample similarity using cluster centres, as in SC. Next, the distance between data points in a testing set and the training set is measured based on similarity features and is fed into the deep neural network algorithm for intrusion detection. Six KDD-Cup99 and NSL-KDD datasets and a sensor network dataset were employed to test the performance of the model. These experimental results indicate that the SCDNN classifier not only performs better than backpropagation neural network (BPNN), support vector machine (SVM), random forest (RF) and Bayes tree models in detection accuracy and the types of abnormal attacks found. It also provides an effective tool of study and analysis of intrusion detection in large networks. Full article

(This article belongs to the Special Issue Topology Control in Emerging Sensor Networks)

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4162 KiB

Open AccessArticle

A Cluster-Based Dual-Adaptive Topology Control Approach in Wireless Sensor Networks

by Jinsong Gui, Kai Zhou and Naixue Xiong

Sensors 2016, 16(10), 1576; https://doi.org/10.3390/s16101576 - 25 Sep 2016

Cited by 14 | Viewed by 4915

Abstract

Multi-Input Multi-Output (MIMO) can improve wireless network performance. Sensors are usually single-antenna devices due to the high hardware complexity and cost, so several sensors are used to form virtual MIMO array, which is a desirable approach to efficiently take advantage of MIMO gains. [...] Read more.

Multi-Input Multi-Output (MIMO) can improve wireless network performance. Sensors are usually single-antenna devices due to the high hardware complexity and cost, so several sensors are used to form virtual MIMO array, which is a desirable approach to efficiently take advantage of MIMO gains. Also, in large Wireless Sensor Networks (WSNs), clustering can improve the network scalability, which is an effective topology control approach. The existing virtual MIMO-based clustering schemes do not either fully explore the benefits of MIMO or adaptively determine the clustering ranges. Also, clustering mechanism needs to be further improved to enhance the cluster structure life. In this paper, we propose an improved clustering scheme for virtual MIMO-based topology construction (ICV-MIMO), which can determine adaptively not only the inter-cluster transmission modes but also the clustering ranges. Through the rational division of cluster head function and the optimization of cluster head selection criteria and information exchange process, the ICV-MIMO scheme effectively reduces the network energy consumption and improves the lifetime of the cluster structure when compared with the existing typical virtual MIMO-based scheme. Moreover, the message overhead and time complexity are still in the same order of magnitude. Full article

(This article belongs to the Special Issue Topology Control in Emerging Sensor Networks)

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Open AccessArticle

A Novel Petri Nets-Based Modeling Method for the Interaction between the Sensor and the Geographic Environment in Emerging Sensor Networks

by Feng Zhang, Yuetong Xu and Jarong Chou

Sensors 2016, 16(10), 1571; https://doi.org/10.3390/s16101571 - 25 Sep 2016

Cited by 10 | Viewed by 6682

Abstract

The service of sensor device in Emerging Sensor Networks (ESNs) is the extension of traditional Web services. Through the sensor network, the service of sensor device can communicate directly with the entity in the geographic environment, and even impact the geographic entity directly. [...] Read more.

The service of sensor device in Emerging Sensor Networks (ESNs) is the extension of traditional Web services. Through the sensor network, the service of sensor device can communicate directly with the entity in the geographic environment, and even impact the geographic entity directly. The interaction between the sensor device in ESNs and geographic environment is very complex, and the interaction modeling is a challenging problem. This paper proposed a novel Petri Nets-based modeling method for the interaction between the sensor device and the geographic environment. The feature of the sensor device service in ESNs is more easily affected by the geographic environment than the traditional Web service. Therefore, the response time, the fault-tolerant ability and the resource consumption become important factors in the performance of the whole sensor application system. Thus, this paper classified IoT services as Sensing services and Controlling services according to the interaction between IoT service and geographic entity, and classified GIS services as data services and processing services. Then, this paper designed and analyzed service algebra and Colored Petri Nets model to modeling the geo-feature, IoT service, GIS service and the interaction process between the sensor and the geographic enviroment. At last, the modeling process is discussed by examples. Full article

(This article belongs to the Special Issue Topology Control in Emerging Sensor Networks)

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2892 KiB

Open AccessArticle

CoDA: Collaborative Data Aggregation in Emerging Sensor Networks Using Bio-Level Voronoi Diagrams

by Chengpei Tang and Nian Yang

Sensors 2016, 16(8), 1235; https://doi.org/10.3390/s16081235 - 5 Aug 2016

Cited by 3 | Viewed by 5605

Abstract

To implement minimum power consumption of the link, cluster heads adopt the multi-hop manner for inter-cluster communication so as to forward the aggregation data to the relay nodes. This paper proposes a collaborative data aggregation in emerging sensor networks using a bio-level Voronoi [...] Read more.

To implement minimum power consumption of the link, cluster heads adopt the multi-hop manner for inter-cluster communication so as to forward the aggregation data to the relay nodes. This paper proposes a collaborative data aggregation in emerging sensor networks using a bio-level Voronoi diagram, which is an energy-efficient data aggregation protocol that integrates topology control, Multiple Access Control (MAC) and routing. The sensor nodes situated in the lower level of the diagram are responsible for listening and gathering data, and should be organized by optimal clustering node. In the inter-cluster communication stage, a particle swarm optimization algorithm is addressed to seek optimal transmission path which could simultaneously achieve the minimization of the maximum next hop distance between two nodes in the routing path and the minimization of the maximum hop count, so the minimization of whole network energy consumption is realized. The results of theoretical analysis and simulation results show that energy efficiency and synchronization accuracy of the proposed algorithm can be much better than with traditional routing protocols, and the energy consumption of nodes in the whole network can be more balanced. Full article

(This article belongs to the Special Issue Topology Control in Emerging Sensor Networks)

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Open AccessArticle

Maximum Data Collection Rate Routing Protocol Based on Topology Control for Rechargeable Wireless Sensor Networks

by Haifeng Lin, Di Bai, Demin Gao and Yunfei Liu

Sensors 2016, 16(8), 1201; https://doi.org/10.3390/s16081201 - 30 Jul 2016

Cited by 29 | Viewed by 5917

Abstract

In Rechargeable Wireless Sensor Networks (R-WSNs), in order to achieve the maximum data collection rate it is critical that sensors operate in very low duty cycles because of the sporadic availability of energy. A sensor has to stay in a dormant state in [...] Read more.

In Rechargeable Wireless Sensor Networks (R-WSNs), in order to achieve the maximum data collection rate it is critical that sensors operate in very low duty cycles because of the sporadic availability of energy. A sensor has to stay in a dormant state in most of the time in order to recharge the battery and use the energy prudently. In addition, a sensor cannot always conserve energy if a network is able to harvest excessive energy from the environment due to its limited storage capacity. Therefore, energy exploitation and energy saving have to be traded off depending on distinct application scenarios. Since higher data collection rate or maximum data collection rate is the ultimate objective for sensor deployment, surplus energy of a node can be utilized for strengthening packet delivery efficiency and improving the data generating rate in R-WSNs. In this work, we propose an algorithm based on data aggregation to compute an upper data generation rate by maximizing it as an optimization problem for a network, which is formulated as a linear programming problem. Subsequently, a dual problem by introducing Lagrange multipliers is constructed, and subgradient algorithms are used to solve it in a distributed manner. At the same time, a topology controlling scheme is adopted for improving the network’s performance. Through extensive simulation and experiments, we demonstrate that our algorithm is efficient at maximizing the data collection rate in rechargeable wireless sensor networks. Full article

(This article belongs to the Special Issue Topology Control in Emerging Sensor Networks)

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