International Journal of Sensor Networks (24 papers in press)

Regular Issues

• Recent Advances in Wireless Sensor Networks with Environmental Energy Harvesting
  by Lei Shu, Wanjiun Liao, Jaime Lloret, Lei Wang 
  Keywords: .
  
  
• Information and Communication Technologies for the improvement of the Irrigation Scheduling  
  by Mohamed Ali Fourati, Walid Chebbi, Mounir Ben Ayed, Anas Kamoun 
  Abstract: Nowadays, agricultural water management is becoming a disturbing issue where scarce resources are increasingly affected by global warming and economic current changes. Indeed, actual irrigation systems are not perfectly adjusted to real contexts or they do not support farmers to carry out all their activities and needs. In order to redress existent deficiencies, information and communication technologies (ICT) are well proposed to minimize losses and improve decisions against unforeseen water shortages. We present in this work a precision irrigation application based on wireless and decision support technologies. Our application provides real-time remote control of decisions and optimizes allocation of exactly required water quantities (beginning and stopping, interruption and recovery times). The objective of such an application is to facilitate the manipulation of the irrigation process and offer flexible opportunities for better watering scheduling and reserves distribution. Therefore, efficient yield will be raised and better profits in time and money will be achieved. We had developed and deployed the system in a real case study where results are evaluated and well judged as regards the objectives.
  Keywords: Precision irrigation; information and communication technologies; wireless sensors network; decision support system; optimization; remote control.
  
  
• Data Retrieval for Deadline-based Multi-request in MIMO Wireless Networks  
  by Ping He, Weidong Li, Shufu Cao 
  Abstract: Data retrieval problem is an important issue that generates an access pattern for downloading a request with multiple data items among the parallel channels such that the efficiency of wireless networks is improved. Although many related papers have discussed data retrieval problem that clients require to retrieve one request under the condition of clients equipped with one and multiple antennae, but there are few study on this problem that clients equipped with multiple antennae require to retrieve multiple requests, in particular that each request has time constraint. The problem has great value in the aspects of theory and applications in MIMO wireless networks, such as data sharing and e-business. So, this paper proposes an algorithm that schedules the suitable antennae to find a retrieval sequence (to access data items) about these requests for keeping the balance of access latency among the antennae. For retrieving each request, we develop an efficient scheme that adopts maximum match to generate an access pattern for downloading all requested data items so that the access latency of each request and deadline miss ratio are minimized. Through experiments, the proposed algorithms keep good performance.
  Keywords: Mobile computing; Data broadcast; Indexing; Data scheduling; Datarnretrieval; Data grouping.
  
  
• SIMAS: Smart IoT Model for Acute Stroke Avoidance  
  by Samaleswari Prasad Nayak, Surajit Das, Satyananda Champati Rai, Sateesh Kumar Pradhan 
  Abstract: The rate of growth in chronic heart diseases increases the necessity of health care nursing and its constant monitoring. But different constraints have bound us to always avail a physical medical health care for every single person. Technical advancement in medical sciences and Internet of Things provides an opportunity to monitor patients health conditions from anywhere at any time and by anyone efficiently. As a primary diagnostic assessment, correct heart rate and body temperature are the common parameters to be measured. We have developed an IoT based healthcare model SIMAS, which is capable of monitoring the patient heart rate and body temperature locally as well as remotely with almost negligible error rate and includes surrounding factors affecting a patients health condition. Specially by considering the conditions of patients and sports persons who are either in a state of unconsciousness or are unaware of their current health status while in the an intense physical activity the integrated designed healthcare model will work in such a way that the persons required information can be retrieved efficiently and effectively by the authorized users to avoid from critical situations as well as major mishaps.
  Keywords: Heart rate; Humidity; IoT; NodeMCU; Real-Time; Remote patient monitoring.
  
  
• Energy Analysis and Optimization in Amplify-and-Forward Wireless Relay Networks  
  by Hai Zhu, Mengmeng Xu, Hengzhou Xu 
  Abstract: In this paper, three kinds of transmission strategies are dealt with: 1) direct transmission without relay; 2) relay transmission without a direct link; and 3) relay transmission with a direct link. We first develop an analytical framework for the total energy consumption per transferred payload bit in amplify-and-forward wireless relay networks. In this framework, analytical expressions of the total energy consumption per transferred payload bit are derived for the three transmission strategies, which are functions of the following network parameters: packet length, transmission energy, coding rate, modulation,rntransmission distance, relay location. Then, the three transmission strategies are optimized to minimize the total energy consumption with respect to the packet length and the transmission energy. By simulation, we compare the three transmission strategies in terms of the total energy consumption per transferred payload bit under different network scenarios. Our results provide several insights into the choice of transmission strategy if some network parameters are given.
  Keywords: Wireless Relay Network; Direct Transmission; Relay Transmission; Energy Analysis and Optimization; Amplify-and-Forward.
  
  
• Low Complexity Versatile Video Coding for Traffic Surveillance System  
  by Zhaoqing Pan, He Qin, Xiaokai Yi, Yuhui Zheng, Asifullah Khan 
  Abstract: Due to the diversity of data flows in traffic and mobile data environments, there have been some challenges to both transmission speed and bandwidth. In response to the upcoming challenges of video data compression, the Joint Video Exploration Team (JVET) explored and developed the next-generation video coding standard-Versatile Video Coding (VVC). Compared with HEVC, VVC achieves an improvement of 40\\% compression efficiency, but the coding complexity is very high, and it needs further optimization. In this paper, we propose an efficient Motion Estimation (ME) algorithm for improving the encoding complexity of VVC. First, we propose a content oriented adaptive search range setting algorithm, where the search range size of the children Coding Units (CUs) can be adaptively set by using the best motion vector information of their parent CU. In addition, based on the high spatial correlation and similar characteristics, we design a fast reference frame direction decision method to further reduce the ME encoding complexity. The simulation results show that the encoding complexity saving performance of the proposed algorithm is quite well, i.e. the total encoding time is saved by an average of 34.27%, and the ME encoding time is saved by an average of 40.79%. At the same time, there will be a certain decline in video quality performance which can be ignored.
  Keywords: Search Range; Reference Frame; Motion Estimation; Low Complexity; Versatile Video Coding; Traffic Surveillance System.
  
  
• Performance Analysis of Wireless Sensor Networks and Priority Queueing Systems  
  by Jaime Chen, Eduardo Cañete, Manuel Diaz, Bartolomé Rubio, Jose M. Troya 
  Abstract: Wireless sensor and actor networks (WSANs) have been acknowledged as one of the most promising technologies of the 21st century. For example, recently, the use of WSAN technology has been proposed for Critical Infrastructure Protection (CIP). These new applications make more demanding requirements of WSANs and therefore it is necessary to develop algorithms that can manage the communications and route the information from each sensor node to the sink nodes while providing QoS requirements, principally priority and reliability. Many different routing protocols, programming abstractions and middlewares have been proposed in order to provide the QoS, however, WSANs are still far from becoming a mainstream technology. In order to assess the current state of WSANs in terms of performance and QoS support, this article empirically studies the performance of a network with different workloads in terms of reliability, delay and queue occupation with common network topologies. The performance of common queue-based priority mechanisms is also tested. The results reveal the intrinsic lack of reliability and low throughput that this technology currently exhibits, the importance of matching network level capabilities to data link layer capabilities and different behavior of a PQS in terms of reliability and delay depending on the congestion of the network.
  Keywords: Wireless Sensor and Actor Networks; Performance evaluation; Priority queueing system; MAC layer; Network layer.
  
  
• Joint Topology Control and Routing Design for Reconfigurable Ring-Tree Networks  
  by Chih-Min Yu, Chun-Chyuan Chen 
  Abstract: This article presents a joint topology control and routing design of Reconfigurable Ring-Tree (RRT) topology for Bluetooth non-uniform networks. The non-uniform network consists of one dense and many other sparse regions. In the dense area, the RRT builds a ring-shaped topology as a backbone subnet in a distributive manner, which is expanded by a tree-shaped topology to other, more sparse areas. For various sizes of networks, the size of the ring subnet is controlled by the trade-off between the network performance and the construction cost. Because corresponding nodes in the ring subnet do not procure the global computation situations, obtaining the optimal ring size is an NP-complete problem. In seeking to finalize the optimum ring size, an empirical max-search strategy is provided to attain the preferred cost-performance ratio. The max-search strategy is a methodical decision policy, carried out by three working elements: the topology construction, the packet routing and the maximum decision elements. The topology construction element engenders the ring-tree topology, the packet routing element processes the routing performance with a uniform traffic model, and the maximum decision element utilizes a decision-making criterion to discover the optimum ring size. Experimental values demonstrate that the optimum ring size can be resolved by the max-search scheme for various sizes of networks, and the RRT delivers a better throughput performance than that of the conventional BlueHRT and Bluetree networks.
  Keywords: Bluetooth; Sensor networks; Topology configuration; Routing scheme.
  
  
• Target Detection and Tracking Based on Information Geometry for Sensor Networks  
  by Hao Xu, Huafei Sun, Yongqiang Cheng 
  Abstract: Information geometry is becoming an important research field due to the various applications in statistical inferences, signal processing, neural networks and so on. In this paper, the application of information geometry is explored in anrnattempt to gain a better understanding of sensor system issues for target resolution and tracking in ground-to-air sensor networks. In particular, the Fisher information distance between two targets is used to measure the target resolvability in the region covered by the sensor system and is approximately calculated when it is close enough. And then, the accumulative information is proposed to analyze the resolution of the target on the same detection cellrnwith respect to one measurement model. Furthermore, the single step tracking method is presented based on Fisher information with single bearings-only sensor. The preliminary analysis results presented in this paper provide evidence that information geom- etry is able to offer consistent but more comprehensive means to understand and solve sensor network problems which are difficult to deal with via conventional analysis methods.
  Keywords: Information geometry; information resolution; target detection; accumulative information; target tracking.
  
  
• Design of Human Behavior Recognition Algorithm based on Wearable IMU Sensor  
  by Wei Zhuang, Yi Chen, Jian Su, Baowei Wang, Chunming Gao 
  Abstract: In recent years, with the rapid development of Inertial Measurement Unit (IMU) technology, wireless body area network and pattern recognition theory, human motion recognition based on wearable technology has gradually gained the attention of researchers. In this paper, the human behavior recognition method based on wearable sensor motion information fusion is studied. On the existing wearable system platform, the time domain analysis and frequency domain analysis of human motion information are used to distinguish the daily behavior of the human body, and based on the human motion data acquisition experiment, time domain features, frequency domain features and attitude angles of the human motion data are used as identification features. On the basis of it, multi-classification behavior recognition algorithm based on support vector machine is proposed and human motion pattern recognition is carried out. The experimental results show that the system can accurately identify the daily behavior of the human body.
  Keywords: IMU; Wearable technology; Attitude angle estimation; Posture recognition; Support vector machine.
  
  
• Local Outlier Detection Based on Information Entropy Weighting  
  by Lina Wang 
  Abstract: As a key research area in data mining technologies, outlier detection can expose data inconsistent with the majority in the dataset and therefore is applicable in extensive areas. The addition of entropy weighting to the spatial local outlier measure (SLOM) and local distance-based outlier factor (LDOF) algorithms in outlier data mining, i.e. the adoption of entropy in the calculation of weighted distance is taken into consideration, leads to enhanced accuracy of outlier detection and produces more expense of time. The algorithm of entropy-weighted LDOF is more optimized than that of entropy-weighted SLOM in terms of detection accuracy. The superiority of the entropy-weighted algorithm is verified through experimental results.
  Keywords: Local outlier; detection; information entropy weighting; SLOM; LDOF.
  
  
• Driving behavior recognition based on orientation and position deviations  
  by Wei Sun, Xiaorui Zhang, Xu Zhang, Xiaozheng He, Guoce Zhang 
  Abstract: This paper proposes a driving behavior recognition method, which applies vehicle orientation and position deviations to warn the driver against possible dangers. We integrate a gradient reinforcement method based on the linear discriminate analysis (LDA) to reinforce lane edges. An improved Canny operator based on adaptive threshold segmentation is exploited to extract the lane edges reliably. Based on an improved Hough transform algorithm, the reinforced lane edges help the detection of polar angle and polar radius of lanes that are used to calculate the vanishing point position. After that, the proposed method predicts current-frame lane parameters based on the previous-frame parameters through using the Kalman filter. Combining deviation angle and deviation distance, the proposed method categorizes vehicle lane-keeping behavior into three states: normal, left deviation, and right deviation. Experimental results of a variety of traveling scenes show that the proposed method outperforms other existing methods in precision.
  Keywords: lane detection; vanishing point; Hough transform; Kalman filter; slope angle; offset distance; fatigue driving.
  
  
• Multi-scale Residual Network for Energy Disaggregation  
  by Wan'an Liu, Liguo Weng, Min Xia, Yiqing Xu, Ke Wang, Zhuhan Qiao 
  Abstract: Energy disaggregation technology is a key technology to realize real-time non-intrusive load monitoring. Current energy disaggregation methods use the same scale to extract features from the sequence, which makes part of the local features lost, resulting in lower recognition accuracy of electrical appliances with low using frequency. Aiming at the low accuracy of non-intrusive energy disaggregation with low-frequency sampling, a non-intrusive sequential energy disaggregation method based on multi-scale residual network is proposed. Multi-scale residual network extracts multi-scale feature information through multi-scale convolution, and uses residual learning to deepen the network structure to further improve the performance of the algorithm. Through multi-scale convolution, more scale features are captured, and improve the recognition accuracy of electrical appliances with low using frequency. Sequence-to-Sequence energy disaggregation method can improve the disaggregation efficiency and ensure the efficiency of the algorithm. The experimental comparison results show that the model can get a better disaggregation effect, and can effectively identify the start-stop state of electrical appliances.
  Keywords: Energy disaggregation; Deep learning; Residual learning; Multi-scale convolution; Non-intrusive load monitoring.
  
  
• Distributed Spectrum-Sharing in Cognitive Ad Hoc Networks using Evolutionary Game Theory  
  by Yifei Wei, Bo Gu, Yali Wang, Mei Song, Xiaojun Wang 
  Abstract: As smart portable devices are becoming increasingly popular and autonomous, decentralized ad hoc networks have been widely applied. Meanwhile, to address the critical problem of spectrum congestion and inefficiency, cognitive radio (CR) are introduced. Cognitive radio ad hoc networks (CRAHNs) consist of a group of cognitive radios nodes connected in an ad hoc manner. Due to its decentralized architecture, unstable network topology, highly fluctuated available spectrum and various transmitting requirements, CRAHNs impose unique difficulties for spectrum sharing among CR users. A challenging and open question is how CR users could share vacant spectrum reasonably in CRAHNs without centralized control. Hence, we formulate the vacant spectrum sharing among CR users in CRAHNs with Evolutionary Game Theory (EGT). In the proposed game, we define the payoff of each CR user as a function consist of the achieved transmit rate and the produced interference to primary users. And we use replicator dynamics to model the strategy adaptation process. Simulation results suggest that the evolutionary equilibrium can be obtained through strategy adaptation and convergence is sensitive to the information latency. The fairness can be guaranteed in the EGT-based spectrum sharing.
  Keywords: Spectrum-Sharing; Cognitive Networks; Evolutionary Game Theory.
  
  
• Accurate Bus Occupancy Estimation for WLAN Probing Utilizing Probabilistic Models  
  by Lars Mikkelsen, Hans Peter Schwefel, Tatiana Madsen 
  Abstract: This paper obtains an improved estimator of number of people on the bus, based on probabilistic models. The improved estimator is based on a baseline estimator for number of WLAN enabled devices present on the bus. The estimated number of devices is subject to both false positives and false negatives. The false positives are caused by detecting devices on the roadside outside the bus and not being able to distinguish them from inside bus devices. The amount of false negatives depends on probe emission frequency, message losses due to collisions, MAC address randomization, WLAN channel selection and the time a person stays on a bus. The model proposed in the paper includes the influences of these factors assuming FP and FN being binomially distributed. Distribution parameters for false positives and false negatives are found from measurements.
  Keywords: WLAN probes; bus occupancy; device count; stochastic models; public transport; devices per person; maximum likelihood estimator; MAC randomization; probe frequency; probe signal strength.
  
  
• Optimizing Rendezvous-based Data collection for Target Tracking in WSNs with Mobile Elements  
  by Jian Zhang, Tianbao Wang, Jian Tang 
  Abstract: Wireless sensor networks (WSNs) applications have referred to many fieldsrninvolving target tracking systems, however, energy efficiency issues in applications always suffer bottleneck and hence continuously receive significant attention for recent decades. In the literature, naturally, a mobility collector is utilized as an energy-efficient solution to prolong the network lifetime, meanwhile, data collection strategies are investigated due to the factors including the amount of contributed data and the range of transmittedrndistances. For contributed data, the quantization technology plays an important role in the sense of energy efficiency. Considering the uncertainty of sensing data for nodes, we proposed a distributed algorithm for selecting an contributed group from intra-cluster members to gather data with rigorously mathematical analysis. We formulate our design for target tracking as a selection optimization problem, maximizing the utilization of the quality of contributed data by using information matrix. As a result, we proposed an optimization algorithm named rendezvous-based data collection(RDC) which not only integrates positive factors mentioned above to track a target but also maintains WSNsrnfunctions more prior than traditional clustering. Furthermore, two stages of WSNs are analyzed for data collection, i.e., sensing data and transmitting data as far as intra-cluster and inter-cluster. Simulations verify that the proposed schemes achieve network energy saving as well as energy balance in the framework of target tracking.
  Keywords: Wireless sensor networks; Mobile collectors; Rendezvous nodes; Data collection; Fisher information matrix; Target tracking.
  
  
• DVF-fog: Distributed Virtual Firewall in Fog Computing based on Risk analysis  
  by Ferdaous Kammoun-Abid, Amel Meddeb-makhlouf, Faouzi Zarai, Mohsen Guizani 
  Abstract: To eliminate network saturation during dada exchanges, Fog Computing is deployed as the technology that benefits from both Cloud computing and Internet of Things (IoT) paradigms. This new phenomena is called edge computing. In this study, we focus on network access control issues that are considered as grave challenges in a distributed environment such as fog/cloud computing. Therefore, we present an architecture for distributed fog with a divided topology into Zones and implement distributed firewall and distributed Controller. This way, we can combine user-based access control and distributed network-based access control based on risk analysis and estimation. The performance of our work is evaluated via simulations using Nessi
  Keywords: Fog computing; Access control; Distributed firewall; Risk analysis; Cooperative controller.
  
  
• Online calibration of ultra-short baseline installation error in dynamic environment  
  by Liang Zhang, Tao Zhang, Jinwu Tong, Shaoen Wu 
  Abstract: Due to its advantages of small size and easy installation, the ultra-short base-line system is widely used in the navigation of ships and underwater vehicles. The installation error between the sensor and inertial measurement unit are the main sources of positioning inaccuracy. In high-precision navigation, the installation error is not negligible. A method based on Kalman filter is used to estimate the installation error of USBL in real time. The detailed derivation of Kalman filter for the calibration is presented in the paper. In order to show the validity of extending the installation error to the state of the filter, observability analysis is carried out. Simulation results show that the method proposed in this paper can calibrate the installation error between the ultra-short baseline and inertial measurement unit in real time and online. The positioning accuracy is improved five times by compensating the installation error. Therefore, the error calibration method proposed in this paper is effective and can greatly improve the positioning accuracy of USBL.
  Keywords: Error Calibration; Kalman filter; Ultra-short baseline; Observability analysis.
  
  
• Partition-aware centrality measures for connectivity restoration in mobile sensor networks  
  by Izzet Fatih Senturk 
  Abstract: Mobile sensor networks (MSNs) often operate unattended in environments where human intervention is limited. To sustain network operations, network connectivity must be maintained at all times. However, the network can be partitioned due to random node failures. To tolerate such failures in a reactive manner, network topology can be restructured through node mobility. Minimising the mobility cost requires addressing two different challenges. First, identifying nodes to be relocated. Second, determining target locations for movement. We address the first problem by presenting three different partition-aware centrality measures based on closeness centrality, geometric centrality, and harmonic centrality. To determine the movement target, we consider the former locations of the upstream nodes so that simultaneous node failures can be tolerated with limited data collection scope. The approaches that we present in this paper not only ensure recovery but also minimise the recovery cost so that the network lifetime is extended.
  Keywords: mobile sensor networks; topology management; closeness centrality; geometric centrality; harmonic centrality; connectivity restoration; fault tolerance; mobility.
  DOI: 10.1504/IJSNET.2019.10020666
   
  
• Enhancing reliability by adoptive graph traversals for backbone-assisted communication in wireless sensor networks  
  by Itu Snigdh, Nisha Gupta 
  Abstract: Some applications in wireless sensor networks (WSNs) require dedicated backbones for effective and faster delivery of data under the stringent network conditions. An inherent flaw of such networks is that with the failure of a relay node, the entire structure is affected and needs restructuring in the worst-case failures. In this paper, we try to enhance the capabilities of such types of networks in terms of reliability by providing spare routes for robust data delivery. Our approach is twofold. First, we estimate the reliability of the network through Markov model to show the improvement and effect on the reliability owing to employing ad hoc spare routes in the existing backbone structures. Second, we also propose and implement an adoptive relay selection (ARS) algorithm to confirm the improvement in the percentage of data delivery at the sink. Our analysis shows the improvement on the packet delivery ratio and the reliability under different failure conditions.
  Keywords: WSN; wireless sensor network; communication reliability; Markov model; packet delivery ratio; breadth first search; minimum spanning trees.
  DOI: 10.1504/IJSNET.2019.10020694
   
  
• An energy-saving wireless sensor network based model for monitoring of ammonia concentration  
  by Chong Chen, Xingqiao Liu, Chengyun Zhu, Caihong Huo 
  Abstract: The ammonia concentration in the piggery plays a key role in the growth of fattening pigs. An intelligent environmental monitoring system is proposed based on a wireless sensor network. Specifically, a model has been developed to predict environmental parameters in the server. To optimise its prediction accuracy, this model was designed based on least squares support vector regression (LSSVR) with chaotic mutation to improve the estimation of distribution algorithm (CMEDA) for searching of the optimised parameters, which are γ and σ. Three optimisation methods were involved and compared with it. The experimental results indicated that it exhibits advantages in the prediction accuracy over the other three algorithms. Furthermore, the prediction accuracy of the server was 95%, resulting in reduction of internet of things (IoT) card flow and battery power of LoRa module per day by 50%. The proposed monitoring system is an effective strategy for piggery environmental control.
  Keywords: energy-saving; prediction model; LSSVR; least squares support vector regression; chaotic mutation; EDA; estimation of distribution algorithm; WSN; wireless sensor network.
  DOI: 10.1504/IJSNET.2019.10020671
   
  
• Computational model for the recognition of lower limb movement using wearable gyroscope sensor  
  by Tahir Hussain, Hafiz Farhan Maqbool, Nadeem Iqbal, Mukhtaj Khan, Salman, Abbas A. Dehghani-Sanij 
  Abstract: Human activity recognition (HAR) using inertial sensors has enabled many applications in different fields, especially healthcare and biomedical engineering. In this regard, an activity recognition system is proposed using the signals of a single gyroscope sensor placed at the shank. Principal component analysis method was utilised to exclude the redundant features from the feature set. Furthermore, different classifiers such as probabilistic neural network, k-nearest neighbour (KNN) and support vector machine (SVM) were used for recognition of walking activities. K-fold cross validation and four performance parameters namely accuracy, sensitivity, specificity, and Matthew's correlation coefficient were used to inspect the performance of the recognition model. The proposed model yielded encouraging recognition accuracy of 98.7% compared to the existing activity recognition systems. It is realised that the proposed system will potentially be utilised in the control of lower limb prosthesis and be useful tool for the gait analysis applications.
  Keywords: principal component analysis; HAR; human activity recognition; gyroscope; SVM; support vector machine; classification.
  DOI: 10.1504/IJSNET.2019.10020697
   
  
• Controlling interferences in smart building IoT networks using machine learning  
  by Per Lynggaard 
  Abstract: The coexistence of many internet of things (IoT) networks in smart buildings poses a major challenge because they interfere mutually. In most settings this results in a greedy approach where each IoT node optimises its own performance parameters like increasing transmit-power, etc. However, this means that interference levels are increased, battery powers are wasted, and spectrum resources are exhausted in high dense settings. To control interference levels, share spectrum resources, and lower the overall powerconsumptions this paper proposes a centralised control scheme which is based on a nonlinear cost function. This cost function is optimised by using machine learning in the form of a binary particle swarm optimisation (BPSO) algorithm. It has been found that this approach shares the spectrum in a fair way, it saves power and lowers the interference levels, and it dynamically adapts to network changes.
  Keywords: smart buildings; IoT networks; interferences; fading; machine learning; BPSO; transmit-power regulation; centralised control scheme.
  DOI: 10.1504/IJSNET.2019.10020703
   
  
• Dynamic load tuning for energy-hole avoidance in corona model for a wireless sensor network  
  by Krishna Pal Sharma, Teek Parval Sharma 
  Abstract: In wireless sensor networks (WSNs), nodes near to sink communicate more than the nodes at farther away from the sink. This load imbalance causes an energy hole around sink and affects overall network lifetime. Therefore, a corona model based approach is proposed to enhance network's lifetime by balancing energy depletion rate across network and avoiding energy hole around sink. The approach balances energy depletion in inter-corona as well as in intra-corona. In inter-corona, the balance in energy depletion rate is achieved by assigning decreasing communication ranges from outermost to innermost coronas whereas in intra-corona, the balance is achieved by dynamically tuning relay load over nodes during data transmission. The relay load tuning considers current relay load and remaining energy of nodes. The proposed scheme works well for uniformly and non-uniformly deployed networks. To validate the results, the approach is compared with baseline approaches through ns-2 based simulation.
  Keywords: communication range; energy holes; network lifetime; non-uniform deployment; WSNs; wireless sensor networks.
  DOI: 10.1504/IJSNET.2019.10020705