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Special Issue "Smart Communication Protocols and Algorithms for Sensor Networks"

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensor Networks".

Deadline for manuscript submissions: 15 December 2017

Special Issue Editors

Guest Editor
Prof. Dr. Jaime Lloret Mauri

Integrated Management Coastal Research Institute, Polytechnic University of Valencia, Camino de Vera 46022, Valencia, Spain
Website | E-Mail
Fax: +34 96 2849313
Interests: wireless sensor networks; wireless local area networks; routing protocols; P2P networks; video streaming
Guest Editor
Dr. Guangjie Han

Department of Information and Communication System, Hohai University, Changzhou 213022, China
Website | E-Mail
Interests: wireless sensor networks; green computing; smart computing; mobile Internet; cloud computing

Special Issue Information

Dear Colleagues,

The use of smart communication systems is becoming one of the key issues to provide high performance communication systems for sensor networks, deployed in any type of environment, such as cities, rural areas, and underwater areas. Technical advances in such environments will benefit human quality-of-life, increase world sustainability, and decrease the production costs in agriculture and aquaculture.

Additionally, selected papers focused on sensor networks, submitted to WMNC 2017 (http://jlloret.webs.upv.es/wmnc2017/) and to JITEL 2017 (http://jlloret.webs.upv.es/jitel2017/),will also be invited to submit an extended version to the Special Issue.

Dr. Jaime Lloret Mauri
Dr. Guangjie Han
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

 

Keywords

  • Communication protocols for sensor networks

  • Communication algorithms for sensor networks

  • New architectures for smart sensor networks

  • Artificial intelligence applied to sensor nodes communication

  • Smart communication protocols and algorithms for sensors in smart cities

  • Intelligent communication systems to communicate sensors in precision agriculture

  • Smart underwater sensor networks to communicate sensors in aquaculture precision

Published Papers (11 papers)

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Research

Open AccessArticle A Game Theoretic Approach for Balancing Energy Consumption in Clustered Wireless Sensor Networks
Sensors 2017, 17(11), 2654; doi:10.3390/s17112654
Received: 8 October 2017 / Revised: 13 November 2017 / Accepted: 16 November 2017 / Published: 17 November 2017
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Abstract
Clustering is an effective topology control method in wireless sensor networks (WSNs), since it can enhance the network lifetime and scalability. To prolong the network lifetime in clustered WSNs, an efficient cluster head (CH) optimization policy is essential to distribute the energy among
[...] Read more.
Clustering is an effective topology control method in wireless sensor networks (WSNs), since it can enhance the network lifetime and scalability. To prolong the network lifetime in clustered WSNs, an efficient cluster head (CH) optimization policy is essential to distribute the energy among sensor nodes. Recently, game theory has been introduced to model clustering. Each sensor node is considered as a rational and selfish player which will play a clustering game with an equilibrium strategy. Then it decides whether to act as the CH according to this strategy for a tradeoff between providing required services and energy conservation. However, how to get the equilibrium strategy while maximizing the payoff of sensor nodes has rarely been addressed to date. In this paper, we present a game theoretic approach for balancing energy consumption in clustered WSNs. With our novel payoff function, realistic sensor behaviors can be captured well. The energy heterogeneity of nodes is considered by incorporating a penalty mechanism in the payoff function, so the nodes with more energy will compete for CHs more actively. We have obtained the Nash equilibrium (NE) strategy of the clustering game through convex optimization. Specifically, each sensor node can achieve its own maximal payoff when it makes the decision according to this strategy. Through plenty of simulations, our proposed game theoretic clustering is proved to have a good energy balancing performance and consequently the network lifetime is greatly enhanced. Full article
(This article belongs to the Special Issue Smart Communication Protocols and Algorithms for Sensor Networks)
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Open AccessArticle Efficient Graph-Based Resource Allocation Scheme Using Maximal Independent Set for Randomly- Deployed Small Star Networks
Sensors 2017, 17(11), 2553; doi:10.3390/s17112553
Received: 8 October 2017 / Revised: 30 October 2017 / Accepted: 2 November 2017 / Published: 6 November 2017
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Abstract
In future scenarios of heterogeneous and dense networks, randomly-deployed small star networks (SSNs) become a key paradigm, whose system performance is restricted to inter-SSN interference and requires an efficient resource allocation scheme for interference coordination. Traditional resource allocation schemes do not specifically focus
[...] Read more.
In future scenarios of heterogeneous and dense networks, randomly-deployed small star networks (SSNs) become a key paradigm, whose system performance is restricted to inter-SSN interference and requires an efficient resource allocation scheme for interference coordination. Traditional resource allocation schemes do not specifically focus on this paradigm and are usually too time consuming in dense networks. In this article, a very efficient graph-based scheme is proposed, which applies the maximal independent set (MIS) concept in graph theory to help divide SSNs into almost interference-free groups. We first construct an interference graph for the system based on a derived distance threshold indicating for any pair of SSNs whether there is intolerable inter-SSN interference or not. Then, SSNs are divided into MISs, and the same resource can be repetitively used by all the SSNs in each MIS. Empirical parameters and equations are set in the scheme to guarantee high performance. Finally, extensive scenarios both dense and nondense are randomly generated and simulated to demonstrate the performance of our scheme, indicating that it outperforms the classical max K-cut-based scheme in terms of system capacity, utility and especially time cost. Its achieved system capacity, utility and fairness can be close to the near-optimal strategy obtained by a time-consuming simulated annealing search. Full article
(This article belongs to the Special Issue Smart Communication Protocols and Algorithms for Sensor Networks)
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Open AccessArticle Multi-Source Cooperative Data Collection with a Mobile Sink for the Wireless Sensor Network
Sensors 2017, 17(11), 2493; doi:10.3390/s17112493
Received: 25 August 2017 / Revised: 22 October 2017 / Accepted: 25 October 2017 / Published: 30 October 2017
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Abstract
The multi-source cooperation integrating distributed low-density parity-check codes is investigated to jointly collect data from multiple sensor nodes to the mobile sink in the wireless sensor network. The one-round and two-round cooperative data collection schemes are proposed according to the moving trajectories of
[...] Read more.
The multi-source cooperation integrating distributed low-density parity-check codes is investigated to jointly collect data from multiple sensor nodes to the mobile sink in the wireless sensor network. The one-round and two-round cooperative data collection schemes are proposed according to the moving trajectories of the sink node. Specifically, two sparse cooperation models are firstly formed based on geographical locations of sensor source nodes, the impairment of inter-node wireless channels and moving trajectories of the mobile sink. Then, distributed low-density parity-check codes are devised to match the directed graphs and cooperation matrices related with the cooperation models. In the proposed schemes, each source node has quite low complexity attributed to the sparse cooperation and the distributed processing. Simulation results reveal that the proposed cooperative data collection schemes obtain significant bit error rate performance and the two-round cooperation exhibits better performance compared with the one-round scheme. The performance can be further improved when more source nodes participate in the sparse cooperation. For the two-round data collection schemes, the performance is evaluated for the wireless sensor networks with different moving trajectories and the variant data sizes. Full article
(This article belongs to the Special Issue Smart Communication Protocols and Algorithms for Sensor Networks)
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Open AccessArticle Bio-Inspired Distributed Transmission Power Control Considering QoS Fairness in Wireless Body Area Sensor Networks
Sensors 2017, 17(10), 2344; doi:10.3390/s17102344
Received: 24 August 2017 / Revised: 10 October 2017 / Accepted: 11 October 2017 / Published: 14 October 2017
PDF Full-text (4655 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Recently, the development of wireless body area sensor network (WBASN) has accelerated due to the rapid development of wireless technology. In the WBASN environment, many WBASNs coexist where communication ranges overlap with each other, resulting in the possibility of interference. Although nodes in
[...] Read more.
Recently, the development of wireless body area sensor network (WBASN) has accelerated due to the rapid development of wireless technology. In the WBASN environment, many WBASNs coexist where communication ranges overlap with each other, resulting in the possibility of interference. Although nodes in a WBASN typically operate at a low power level, to avoid adversely affecting the human body, high transmission rates may be required to support some applications. In addition to this, since many varieties of applications exist in the WBASN environment, each prospective user may have different quality of service (QoS) requirements. Hence, the following issues should be considered in the WBASN environment: (1) interference between adjacent WBASNs, which influences the performance of a specific system, and (2) the degree of satisfaction on the QoS of each user, i.e., the required QoS such as user throughput should be considered to ensure that all users in the network are provided with a fair QoS satisfaction. Thus, in this paper, we propose a transmission power adjustment algorithm that addresses interference problems and guarantees QoS fairness between users. First, we use a new utility function to measure the degree of the satisfaction on the QoS for each user. Then, the transmission power of each sensor node is calculated using the Cucker–Smale model, and the QoS satisfaction of each user is synchronized dispersively. The results of simulations show that the proposed algorithm performs better than existing algorithms, with respect to QoS fairness and energy efficiency. Full article
(This article belongs to the Special Issue Smart Communication Protocols and Algorithms for Sensor Networks)
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Open AccessArticle Video Synchronization With Bit-Rate Signals and Correntropy Function
Sensors 2017, 17(9), 2021; doi:10.3390/s17092021
Received: 4 August 2017 / Revised: 25 August 2017 / Accepted: 30 August 2017 / Published: 4 September 2017
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Abstract
We propose an approach for the synchronization of video streams using correntropy. Essentially, the time offset is calculated on the basis of the instantaneous transfer rates of the video streams that are extracted in the form of a univariate signal known as variable
[...] Read more.
We propose an approach for the synchronization of video streams using correntropy. Essentially, the time offset is calculated on the basis of the instantaneous transfer rates of the video streams that are extracted in the form of a univariate signal known as variable bit-rate (VBR). The state-of-the-art approach uses a window segmentation strategy that is based on consensual zero-mean normalized cross-correlation (ZNCC). This strategy has an elevated computational complexity, making its application to synchronizing online data streaming difficult. Hence, our proposal uses a different window strategy that, together with the correntropy function, allows the synchronization to be performed for online applications. This provides equivalent synchronization scores with a rapid offset determination as the streams come into the system. The efficiency of our approach has been verified through experiments that demonstrate its viability with values that are as precise as those obtained by ZNCC. The proposed approach scored 81 % in time reference classification against the equivalent 81 % of the state-of-the-art approach, requiring much less computational power. Full article
(This article belongs to the Special Issue Smart Communication Protocols and Algorithms for Sensor Networks)
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Open AccessArticle Dynamic Hierarchical Energy-Efficient Method Based on Combinatorial Optimization for Wireless Sensor Networks
Sensors 2017, 17(7), 1665; doi:10.3390/s17071665
Received: 31 May 2017 / Revised: 12 July 2017 / Accepted: 17 July 2017 / Published: 19 July 2017
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Abstract
Routing protocols based on topology control are significantly important for improving network longevity in wireless sensor networks (WSNs). Traditionally, some WSN routing protocols distribute uneven network traffic load to sensor nodes, which is not optimal for improving network longevity. Differently to conventional WSN
[...] Read more.
Routing protocols based on topology control are significantly important for improving network longevity in wireless sensor networks (WSNs). Traditionally, some WSN routing protocols distribute uneven network traffic load to sensor nodes, which is not optimal for improving network longevity. Differently to conventional WSN routing protocols, we propose a dynamic hierarchical protocol based on combinatorial optimization (DHCO) to balance energy consumption of sensor nodes and to improve WSN longevity. For each sensor node, the DHCO algorithm obtains the optimal route by establishing a feasible routing set instead of selecting the cluster head or the next hop node. The process of obtaining the optimal route can be formulated as a combinatorial optimization problem. Specifically, the DHCO algorithm is carried out by the following procedures. It employs a hierarchy-based connection mechanism to construct a hierarchical network structure in which each sensor node is assigned to a special hierarchical subset; it utilizes the combinatorial optimization theory to establish the feasible routing set for each sensor node, and takes advantage of the maximum–minimum criterion to obtain their optimal routes to the base station. Various results of simulation experiments show effectiveness and superiority of the DHCO algorithm in comparison with state-of-the-art WSN routing algorithms, including low-energy adaptive clustering hierarchy (LEACH), hybrid energy-efficient distributed clustering (HEED), genetic protocol-based self-organizing network clustering (GASONeC), and double cost function-based routing (DCFR) algorithms. Full article
(This article belongs to the Special Issue Smart Communication Protocols and Algorithms for Sensor Networks)
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Open AccessArticle Fuzzy-Logic Based Distributed Energy-Efficient Clustering Algorithm for Wireless Sensor Networks
Sensors 2017, 17(7), 1554; doi:10.3390/s17071554
Received: 4 April 2017 / Revised: 22 June 2017 / Accepted: 29 June 2017 / Published: 3 July 2017
Cited by 4 | PDF Full-text (2557 KB) | HTML Full-text | XML Full-text
Abstract
Due to the high-energy efficiency and scalability, the clustering routing algorithm has been widely used in wireless sensor networks (WSNs). In order to gather information more efficiently, each sensor node transmits data to its Cluster Head (CH) to which it belongs, by multi-hop
[...] Read more.
Due to the high-energy efficiency and scalability, the clustering routing algorithm has been widely used in wireless sensor networks (WSNs). In order to gather information more efficiently, each sensor node transmits data to its Cluster Head (CH) to which it belongs, by multi-hop communication. However, the multi-hop communication in the cluster brings the problem of excessive energy consumption of the relay nodes which are closer to the CH. These nodes’ energy will be consumed more quickly than the farther nodes, which brings the negative influence on load balance for the whole networks. Therefore, we propose an energy-efficient distributed clustering algorithm based on fuzzy approach with non-uniform distribution (EEDCF). During CHs’ election, we take nodes’ energies, nodes’ degree and neighbor nodes’ residual energies into consideration as the input parameters. In addition, we take advantage of Takagi, Sugeno and Kang (TSK) fuzzy model instead of traditional method as our inference system to guarantee the quantitative analysis more reasonable. In our scheme, each sensor node calculates the probability of being as CH with the help of fuzzy inference system in a distributed way. The experimental results indicate EEDCF algorithm is better than some current representative methods in aspects of data transmission, energy consumption and lifetime of networks. Full article
(This article belongs to the Special Issue Smart Communication Protocols and Algorithms for Sensor Networks)
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Open AccessArticle A Reliable Data Transmission Model for IEEE 802.15.4e Enabled Wireless Sensor Network under WiFi Interference
Sensors 2017, 17(6), 1320; doi:10.3390/s17061320
Received: 6 April 2017 / Revised: 23 May 2017 / Accepted: 5 June 2017 / Published: 7 June 2017
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Abstract
The IEEE 802.15.4e standard proposes Medium Access Control (MAC) to support collision-free wireless channel access mechanisms for industrial, commercial and healthcare applications. However, unnecessary wastage of energy and bandwidth consumption occur due to inefficient backoff management and collisions. In this paper, a new
[...] Read more.
The IEEE 802.15.4e standard proposes Medium Access Control (MAC) to support collision-free wireless channel access mechanisms for industrial, commercial and healthcare applications. However, unnecessary wastage of energy and bandwidth consumption occur due to inefficient backoff management and collisions. In this paper, a new channel access mechanism is designed for the buffer constraint sensor devices to reduce the packet drop rate, energy consumption and collisions. In order to avoid collision due to the hidden terminal problem, a new frame structure is designed for the data transmission. A new superframe structure is proposed to mitigate the problems due to WiFi and ZigBee interference. A modified superframe structure with a new retransmission opportunity for failure devices is proposed to reduce the collisions and retransmission delay with high reliability. Performance evaluation and validation of our scheme indicate that the packet drop rate, throughput, reliability, energy consumption and average delay of the nodes can be improved significantly. Full article
(This article belongs to the Special Issue Smart Communication Protocols and Algorithms for Sensor Networks)
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Open AccessArticle A Protocol Layer Trust-Based Intrusion Detection Scheme for Wireless Sensor Networks
Sensors 2017, 17(6), 1227; doi:10.3390/s17061227
Received: 29 March 2017 / Revised: 12 May 2017 / Accepted: 24 May 2017 / Published: 27 May 2017
Cited by 1 | PDF Full-text (5528 KB) | HTML Full-text | XML Full-text
Abstract
This article proposes a protocol layer trust-based intrusion detection scheme for wireless sensor networks. Unlike existing work, the trust value of a sensor node is evaluated according to the deviations of key parameters at each protocol layer considering the attacks initiated at different
[...] Read more.
This article proposes a protocol layer trust-based intrusion detection scheme for wireless sensor networks. Unlike existing work, the trust value of a sensor node is evaluated according to the deviations of key parameters at each protocol layer considering the attacks initiated at different protocol layers will inevitably have impacts on the parameters of the corresponding protocol layers. For simplicity, the paper mainly considers three aspects of trustworthiness, namely physical layer trust, media access control layer trust and network layer trust. The per-layer trust metrics are then combined to determine the overall trust metric of a sensor node. The performance of the proposed intrusion detection mechanism is then analyzed using the t-distribution to derive analytical results of false positive and false negative probabilities. Numerical analytical results, validated by simulation results, are presented in different attack scenarios. It is shown that the proposed protocol layer trust-based intrusion detection scheme outperforms a state-of-the-art scheme in terms of detection probability and false probability, demonstrating its usefulness for detecting cross-layer attacks. Full article
(This article belongs to the Special Issue Smart Communication Protocols and Algorithms for Sensor Networks)
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Open AccessArticle Power Allocation Based on Data Classification in Wireless Sensor Networks
Sensors 2017, 17(5), 1107; doi:10.3390/s17051107
Received: 29 March 2017 / Revised: 8 May 2017 / Accepted: 10 May 2017 / Published: 12 May 2017
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Abstract
Limited node energy in wireless sensor networks is a crucial factor which affects the monitoring of equipment operation and working conditions in coal mines. In addition, due to heterogeneous nodes and different data acquisition rates, the number of arriving packets in a queue
[...] Read more.
Limited node energy in wireless sensor networks is a crucial factor which affects the monitoring of equipment operation and working conditions in coal mines. In addition, due to heterogeneous nodes and different data acquisition rates, the number of arriving packets in a queue network can differ, which may lead to some queue lengths reaching the maximum value earlier compared with others. In order to tackle these two problems, an optimal power allocation strategy based on classified data is proposed in this paper. Arriving data is classified into dissimilar classes depending on the number of arriving packets. The problem is formulated as a Lyapunov drift optimization with the objective of minimizing the weight sum of average power consumption and average data class. As a result, a suboptimal distributed algorithm without any knowledge of system statistics is presented. The simulations, conducted in the perfect channel state information (CSI) case and the imperfect CSI case, reveal that the utility can be pushed arbitrarily close to optimal by increasing the parameter V, but with a corresponding growth in the average delay, and that other tunable parameters W and the classification method in the interior of utility function can trade power optimality for increased average data class. The above results show that data in a high class has priorities to be processed than data in a low class, and energy consumption can be minimized in this resource allocation strategy. Full article
(This article belongs to the Special Issue Smart Communication Protocols and Algorithms for Sensor Networks)
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Open AccessArticle DCE: A Distributed Energy-Efficient Clustering Protocol for Wireless Sensor Network Based on Double-Phase Cluster-Head Election
Sensors 2017, 17(5), 998; doi:10.3390/s17050998
Received: 30 March 2017 / Revised: 26 April 2017 / Accepted: 27 April 2017 / Published: 1 May 2017
Cited by 1 | PDF Full-text (5266 KB) | HTML Full-text | XML Full-text
Abstract
Clustering is an effective technique used to reduce energy consumption and extend the lifetime of wireless sensor network (WSN). The characteristic of energy heterogeneity of WSNs should be considered when designing clustering protocols. We propose and evaluate a novel distributed energy-efficient clustering protocol
[...] Read more.
Clustering is an effective technique used to reduce energy consumption and extend the lifetime of wireless sensor network (WSN). The characteristic of energy heterogeneity of WSNs should be considered when designing clustering protocols. We propose and evaluate a novel distributed energy-efficient clustering protocol called DCE for heterogeneous wireless sensor networks, based on a Double-phase Cluster-head Election scheme. In DCE, the procedure of cluster head election is divided into two phases. In the first phase, tentative cluster heads are elected with the probabilities which are decided by the relative levels of initial and residual energy. Then, in the second phase, the tentative cluster heads are replaced by their cluster members to form the final set of cluster heads if any member in their cluster has more residual energy. Employing two phases for cluster-head election ensures that the nodes with more energy have a higher chance to be cluster heads. Energy consumption is well-distributed in the proposed protocol, and the simulation results show that DCE achieves longer stability periods than other typical clustering protocols in heterogeneous scenarios. Full article
(This article belongs to the Special Issue Smart Communication Protocols and Algorithms for Sensor Networks)
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