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Wireless Sensor Networks (WSNs) contain coverage holes caused by both random node sensor deployment and malfunctioning nodes. Because fixing the battery is challenging, collaborative discovery and assessment of coverage shortfalls, as well as getting rid of these holes, has been recognized as critical in WSNs. While placing nodes for sensors in a large-scale WSN is challenging. This research provides a cost-effective coverage hole detection approach based on collaborative distributed point placement. Create a polygon first by employing an angle estimate approach and neighbor data. Following that, a based on points hole identification technique is used to assess if a coverage issue appears in a large-scale WSN's supplied ROI. Furthermore, the region of the coverage hole is estimated using computational geometry-based polygonal triangulation methods. The accuracy of the method is tested here using statistical data. The results show that it outperforms earlier coverage hole-detecting algorithms. In particular, the method improves coverage rate by 75% when compared to conventional methodologies. It also lowers energy usage by 90%, adding to increased network lifetime. The quantitative favourable results demonstrate the effectiveness of the collaborative distributed point placement technique in detecting and successfully resolving coverage gaps in WSNs. In regards to coverage rate, energy consumption, and network longevity, the system being proposed beats previous coverage hole-detecting techniques. [ABSTRACT FROM AUTHOR]

Sensor nodes, typically small and low-power devices, are components of wireless sensor networks (WSNs). Each node monitors its surroundings for relevant environmental changes and sends all detected events to the data collector for analysis. If the sensor nodes are not placed correctly, there may be areas that are not within the detection zone of any sensor node. Coverage holes in WSNs are usually caused by random deployment and node failure. Energy holes and dead nodes are the main problems caused by detection and recovery of coverage holes in WSNs. The size of coverage holes increases the time complexity and power of recent protocols. However, there is a high computational complexity associated with distributed methods proposed in recent years to solve the coverage hole detection problem. In this paper, we propose optimal cluster-based node position estimation and coverage hole detection in WSNs using a hybrid deep learning approach. First, a modified Lyapunov optimization (MLO) algorithm to compute the node position is presented, which ensures edge nodes in the network. Next, we design optimal clustering technique by using improved sand cat swarm optimization (ISCSO) algorithm to formulate efficient balanced clusters which computes coverage hole area in the network. Afterward, we develop a hybrid deep reinforcement learning (Hyb-DRL) technique for hole shape detection and hole size judgment within clusters, among clusters and along edges. The results show that the proposed approach achieves significant improvements compared to existing benchmark approaches. Specifically, the average energy consumption of CG-DCHD approach is 43.835%, 32.674% and 26.164% lower for node density, hole density and simulation rounds, respectively. The hole detection time is 18.4%, 16.802% and 15.462% lower, while the coverage is 16.885%, 14.977% and 12.219% higher for node density, hole density and simulation rounds, respectively. Additionally, the network lifetime of CG-DCHD approach is 15.58%, 17.702% and 20.492% higher, while the control packet overhead is 0.83%, 1.907% and 1.466% lower for node density, hole density and simulation rounds, respectively. [ABSTRACT FROM AUTHOR]

Intelligent reflecting surfaces (IRSs) have been attracting attention as a solution to coverage hole problems in millimeter-wave communication areas. They are considered to be one of the key technologies of next-generation mobile communication systems. Since polarized multiple-input-multiple-output (MIMO) is utilized in millimeter-wave communication systems to deliver high-speed data transmission, an IRS is also required to be applied for polarized MIMO and reflect signals in a wide angle range. To realize an IRS for the polarized MIMO, the IRS is required to reflect the signal of each polarization in the same direction with high isolation. In addition, the IRS is required to control the reflection phase over a wide range. In recent research, many proposals related to the development of IRSs have been proposed. However, since the configuration of a conventional IRS with diodes controls the reflection characteristics by controlling the electric length or shape of the reflecting element, it becomes asymmetrical in the direction of each polarization and it is difficult to apply polarized MIMO. To solve this problem, in this paper, we propose a new design of a dual-polarized liquid-crystal-based IRS for 28 GHz mobile communication systems. Since the proposed IRS controls the reflecting phase by controlling the electric thickness of the substrate, the IRS can control the reflecting phase without changing the shape of the reflecting element. By optimizing the design of the reflecting element, the IRS can achieve a wide reflection phase control of 260 degrees for both vertical and horizontal polarizations. The IRS can also control the reflection direction of each polarization in the range of ±60 degrees with a high isolation of more than 20 dB. The main contributions of this paper are 1) a proposal for the design of a liquid crystal IRS for polarized MIMO; 2) a proposal of a design method for the liquid-crystal IRS using unit cell analysis; 3) verification of the proposed IRS through electromagnetic field analysis; 4) development of the proposed liquid-crystal IRS; 5) experimental verification of the proposed IRS in an anechoic chamber, and 6) derivation of the MIMO channel capacity of the proposed dual-polarized IRS.

A coverage hole is a problem that cannot be completely avoided in three-dimensional hybrid wireless sensor networks. It can lead to hindrances in monitoring tasks and adversely affect network performance. To address the problem of coverage holes caused by the uneven initial deployment of the network and node damage during operation, we propose a distributed hole detection and multi-objective optimization emperor penguin repair algorithm (DHD-MEPO). In the detection phase, the monitoring region is zoned as units according to the quantity of nodes and the sensing range, and static nodes use the sum-of-weights method to campaign for group nodes on their terms, determining the location of holes by calculating the coverage of each cell. In the repair phase, the set of repair nodes is determined by calculating the mobile node coverage redundancy. Based on the characteristics of complex environments, the regions of high hole levels are prioritized. Moreover, the residual energy homogeneity of nodes is considered for the design of multi-objective functions. A lens-imaging mapping learning strategy is introduced to perturb the location of repair nodes for the optimization of the emperor penguin algorithm. Experimental results illustrate that the DHD-MEPO, compared with the C-CICHH, 3D-VPCA, RA, EMSCOLER, and IERP algorithms, can balance the uniformity of the residual energy of each node while satisfying the network coverage requirements and network connectivity, which effectively improves the network coverage performance. [ABSTRACT FROM AUTHOR]

The Sensor Nodes (SN) play an important role in various hazardous applications environments such as military surveillance, forests, battlefield, etc. The Wireless Sensor Network (WSN) comprised multiple numbers of sensor nodes which are used to perform sensing the physical conditions and subsequently transmitting data to the Base Station (BS). The nodes have limited batteries. The random distribution of nodes in the hazardous areas causes overlapping of nodes and coverage hole issues in the network. The Coverage Optimization and Resolve Hole Healing (CHOP) Protocol is proposed to optimize the network's overlapping and resolve the coverage hole problem. The working phases of the proposed protocol are network initialization, formation of the cluster, Selection of Cluster Head, and sleep and wake-up phase. The issues are optimized, and maximum coverage is achieved for a specific sensing range. Using statistics and probability theory, a link is established between the radius of the node and the coverage area. The protocol used the sleep and wake phase to select optimal nodes active to achieve maximum coverage. The proposed protocol outperformed and showed improvements in the network's performance and lifetime compared to LEACH, TEEN, SEP, and DEEC protocols.

The uneven distribution caused by the random deployment of sensor nodes often leads to coverage holes or redundant coverage in the sensing region of wireless sensor network, which severely affects the network performance. Therefore, it is necessary to redeploy the sensor nodes to repair the network topology. This paper summarizes and analyzes the major research directions and achievements related to the nodes redeployment in recent years. Firstly, it reviews the three basic sensing models. Secondly, it gives a comprehensive overview about the nodes redeployment from three perspectives: research questions, optimization objectives for strategy design, and classification methods. Thirdly, it classifies and analyzes the redeployment strategies of typical sensor nodes and Sink nodes. Finally, it discusses the nodes redeployment strategy under reinforcement learning framework and the relocation of wireless sensor network under security monitoring requirements, and points out the application prospect, development trend and future optimization direction of redeployment strategy. [ABSTRACT FROM AUTHOR]

For the problems of traditional overburden hole detection methods, such as overtime, low accuracy and high running cost, etc. A multi factor reliable coverage hole detection method based on LEACH algorithm is proposed. Based on the analysis of the QoS architecture of wireless sensor networks and the research of representative network layer symmetry protocols, a symmetric network model is constructed according to the selection of gateway performance parameters, gateway selection criterion function and symmetry criterion, and a symmetric criterion design and optimization strategy is given. It uses this strategy to improve LEACH algorithm in three aspects. Two reliability optimization factors are added to the similarity calculation of coverage hole detection, which are node intrusion optimization factor and multipath transmission optimization factor respectively. Multipath transmission optimization factor is used in data transmission. In hostile environments, in order to avoid a large number of malicious nodes interfering with real data, the data containing noise should be filtered and processed. Then, the similarity is calculated by multi-path transmission optimization factor, and the coverage holes of wireless sensor networks are detected by weighted average. The experimental results show that the proposed method takes less time to detect the covering holes, which has higher detection accuracy and lower operation cost. [ABSTRACT FROM AUTHOR]

The improvement of coverage is a critical issue in the coverage hole patching of sensors. Traditionally, VOPR and VORCP algorithms improve the coverage of the detection area by improving the original VOR algorithm, but coverage hole patching algorithms only target homogeneous networks. In the real world, however, the nodes in the wireless sensor network (WSN) are often heterogeneous, i.e., the sensors have different sensing radii. The VORPH algorithm uses the VOR in a hybrid heterogeneous network and improves the original algorithm. The patched nodes are better utilized, and the detection range is enlarged. However, the utilization rate of the patched nodes is not optimized, making it impossible to patch the coverage holes to the maximum degree. In the environment of hybrid heterogeneous WSN, we propose a coverage hole patching algorithm with a priority mechanism. The algorithm determines the patching priority based on the size of the coverage holes, thereby improving network coverage, reducing node redundancy, and balancing resource allocation. The proposed algorithm was compared under the same environment by simulation and analysis. The results show that our algorithm is superior to the traditional coverage hole patching algorithms in coverage rate, and can reduce node redundancy. [ABSTRACT FROM AUTHOR]

Wireless Underground Sensor Networks (WUSN) are gaining popularity due to their usage in vast prospective domains. Despite wide potential applications, many research issues in WUSNs need to be dealt with. Coverage Holes in WUSNs are one of the major issues that need attention. Nature-inspired optimization algorithms play a crucial role in modern computing, and for more than three decades, the field has made tremendous progress. Traditional algorithms are being replaced with these and have proved their competitiveness in various domains. In this paper, we have proposed an intelligent optimization algorithm based on the TSA (Tree Seed Algorithm) for patching the holes in the network and deciding on effective patching positions such that it reduces the maximum number of holes in the network. The proposed algorithm makes use of random, best, and spiral tree generation for getting the best optimal locations of sensor nodes to be deployed for healing the target region. First, an energy-efficient deterministic algorithm is applied for hole identification in the network. Then, an optimization-based nature-inspired algorithm is applied to heal the holes. The proposed algorithms and others are simulated through MATLAB and results are computed for the randomly deployed network. The proposed hole healing algorithm MTSA (modified TSA) has been compared with PSO (Particle Swarm Optimization) and TSA algorithms. Simulation results prove the effectiveness and robustness of the proposed algorithm. The proposed hole healing algorithm is suitable for small to large-size networks and reduces the larger number of holes than PSO and the original TSA algorithm.

Wireless underground sensor networks (WUSNs) are being used in agricultural applications, in border patrol, and in the monitoring of remote areas. Coverage holes in WUSNs are an issue which needs to be dealt with. Coverage holes may occur due to random deployment of nodes as well as the failure of nodes with time. In this paper, a mathematical approach for hole detection using Delaunay geometry is proposed which divides the network region into Delaunay triangles and applies the laws of triangles to identify coverage holes. WUSNs comprise static nodes, and replacing underground nodes is a complex task. A simplistic algorithm for detecting coverage holes in static WSNs/WUSNs is proposed. The algorithm was simulated in the region of interest for the initially randomly deployed network and after energy depletion of the nodes with time. The performance of the algorithm was evaluated by varying the number of nodes and the sensing radius of the nodes. Our scheme is advantageous over other schemes in the following aspects: (1) it builds a mathematical model and polynomial-time algorithm for detecting holes, and (2) the scheme does not work on centralized computation and therefore provides better scalability, (3) is energy-efficient, and (4) provides a cost-effective solution to detect holes with great accuracy and a low detection time. The algorithm takes less than 0.1 milliseconds to detect holes in a 100 m × 100 m-size network with 100 sensor nodes having a sensing radius of 8 m. The detection time shows only a linear change with an increase in the number of nodes in the network, which makes the algorithm applicable for every network size from small to large. [ABSTRACT FROM AUTHOR]

Wireless Sensor Network (WSN) operations are confined to the available node energy due to which limited application support is available. Energy constraints result in coverage holes in the network, degrading the node-to-node transmissions. Therefore energy conservation and transmission rates are to be evenly balanced without compromising the network efficiency and service parameters. In this article, a Connectivity-Aware Neighbor Orchestration Scheme (CANOS) is introduced for optimizing the fore-mentioned balancing cause. The proposed scheme identifies transmission applicable network slices for neighbor orchestration. In this orchestration process, operational neighbor availability and destination connecting probability are analyzed. Based on the analysis, the network slice with transmission-ability is framed and communication is pursued. A decisive training method recommends the slice forming and de-forming instances for surpassing the region-wise coverage holes. In this training process, neighbor availability and connecting probabilities with energy constraints are considered. Therefore, the outcome is an endurable route to the destination, with a high coverage factor, high network lifetime, and energy utilization. [ABSTRACT FROM AUTHOR]

In wireless sensor networks (WSNs), coverage is a significant indicator of the quality of service. However, full coverage is not feasible to achieve due to coverage holes (CH) in the targeted area. CH occurs for many reasons, such as energy depletion, occlusions and random deployment of nodes. Most of the existing CH restoration methods have huge limitations like high energy consumption (EC), low coverage ratio (CR) and less network lifetime. To address these issues, an Enhanced Mobile Sink-based Coverage Optimization and Link-stability Estimation based Routing (EMSCOLER) protocol is proposed in this paper. The proposed EMSCOLER provides a solution to the coverage restoration issue optimally and avoids network transmission faults. This work consists of two phases such as coverage restoration and Link Stability Estimation based Routing (LSER). Initially, the grid is constructed in the coverage area and randomly deploys the nodes over the grid based coverage area. Grid-based Red Deer Simulated Annealing (GRDSA) model detects the CH in the sensing field and moves the redundant nodes to the hole area to solve the restoration problem. LSER algorithm estimates the link quality and chooses the relay nodes for the transmission of data in order to maximize the whole network lifetime and provide an energy efficient routing. MATLAB tool is used for implementing the proposed protocol. The results of the proposed EMSCOLER are analysed using CR, EC, average residual energy (ARE), moving EC and network lifetime by comparing with the state of the art techniques. The proposed EMSCOLER approach achieved 98.53% CR, 5.842 J EC, 5.94 J moving EC, 0.1980 J ARE and 99.61% network lifetime. From the experimental analysis, the proposed method achieved better results than other techniques. Therefore, the proposed approach can effectively solve the coverage restoration problem and perform energy efficient routing. [ABSTRACT FROM AUTHOR]

Recently, Distributed Energy Resources (DERs) have been utilized with increasing frequency in Industrial Internet of Things (IIoT) to deal with energy and environmental challenges. IIoT with wireless communication technology, which is easy to be intercepted, often facing various attack. For the safety of the network, more complex algorithms need to be run on IIoT, but the action need more energy. In addition, in some application scenarios, the location where the packets were generated indicates that an event occurred. An attacker can find the sensor node through a backtracking attack, which is equivalent to reaching the place where the event occurred. In order to hide the location information of the event, it is necessary to protect source location privacy (SLP), which will also increase the energy consumption of IIoT. If only the traditional battery is used to power the nodes in IIoT, the lifetime of the system will be limited. When IIoT is deployed outdoors, it is often difficult to replace the battery. The existence of lakes make IIoT have coverage holes during deployment. In order to implement SLP and make the system work for a long time in the environment with deployment holes, we use DERs. Herein, we propose an SLP protection scheme based on phantom nodes, rings, and fake paths (PRFs) for IIoT. To increase the safety time of the network, the PRFs dynamically selects the phantom nodes. To adapt to a complex deployment environment, the ring can be flexibly deployed according to the terrain. The PRFs uses fake paths to confuse attackers. We integrate DERs technology into PRFs, such as using solar power modules, looking forward to extending the lifetime of the system. The experimental results proved that the PRFs could efficiently reduce backtracking attacks while maintaining a balance between security and network energy consumption of IIoT.

Wireless underground sensor networks (WUSNs) are being used in agricultural applications, in border patrol, and in the monitoring of remote areas. Coverage holes in WUSNs are an issue which needs to be dealt with. Coverage holes may occur due to random deployment of nodes as well as the failure of nodes with time. In this paper, a mathematical approach for hole detection using Delaunay geometry is proposed which divides the network region into Delaunay triangles and applies the laws of triangles to identify coverage holes. WUSNs comprise static nodes, and replacing underground nodes is a complex task. A simplistic algorithm for detecting coverage holes in static WSNs/WUSNs is proposed. The algorithm was simulated in the region of interest for the initially randomly deployed network and after energy depletion of the nodes with time. The performance of the algorithm was evaluated by varying the number of nodes and the sensing radius of the nodes. Our scheme is advantageous over other schemes in the following aspects: (1) it builds a mathematical model and polynomial-time algorithm for detecting holes, and (2) the scheme does not work on centralized computation and therefore provides better scalability, (3) is energy-efficient, and (4) provides a cost-effective solution to detect holes with great accuracy and a low detection time. The algorithm takes less than 0.1 milliseconds to detect holes in a 100 m × 100 m-size network with 100 sensor nodes having a sensing radius of 8 m. The detection time shows only a linear change with an increase in the number of nodes in the network, which makes the algorithm applicable for every network size from small to large.

Over the course of operation, a wireless sensor network can experience failures that are detrimental to the underlying application’s objectives. In this paper, we address the problem of restoring coverage ratio of a damaged area (hole) using only the neighboring nodes. Most existing solutions fail to simultaneously prevent new holes formation, collisions, oscillations, cascaded movements, and overlapped areas. To do this, we propose an intersection points-based strategy to properly locate and characterize any type of coverage hole. Then, we allow nodes, whether or not redundant, to coordinate their movements and ranges in order to effectively eliminate the detected hole. We suggest for that purpose, a tabu search based optimization scheme along with a location-allocation model through a mixed integer linear program. Simulation results show that our protocol significantly increases the network’s resilience.

In the last years, due to the limited resources of consumer products, energy-saving is known as one of the design challenges of Wireless Sensor Networks (WSNs). Clustering is a practical technique to enhance the performance of the network including energy efficiency, network scalability, and network easier management. In cluster-based networks, the size of clusters has a key role in the network power consumption. Non-optimized clustering results in increasing the power consumption of the whole network. The small size clusters leads to appear coverage hole in the network, as well as this property is the opposite of being the scalability of the network. In addition, in non-optimized clusters, reducing the energy consumption of the nodes as the key objective of clustering, cannot be pursued, thus the clustering will result contrary. Consequently, the energy consumption reduction after clustering can be guaranteed by considering the power consumption of nodes before clustering in cluster size optimization. Hence, in this paper, an Energy-efficient and Coverage-guaranteed Unequal-sized Clustering (ECUC) scheme is proposed which considers both energy and coverage issues simultaneously in optimizing the cluster size. Based on the simulation results, the proposed scheme remarkably enhances the network lifetime by reducing the total dissipated energy while guarantying the coverage issue.

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Reliable and secure data transmission in the application environment assisted by the wireless sensor network is one of the major challenges. Problem like blind forwarding and data inaccessibility affect the efficiency of overall infrastructure performance. This paper proposes routing protocol for forwarding and error recovery during packet loss. The same is achieved by energy and hops distance-based formulation of the routing mechanism. The reachability of the intermediate node to the source node is the major factor that helps in improving the lifetime of the network. On the other hand, intelligent hop selection increases the reliability over continuous data transmission. The number of hop count is factor of hop weight and available energy of the node. The comparison over the previous state of the art using QualNet-7.4 network simulator shows the effectiveness of proposed work in terms of overall energy conservation of network and reliable data delivery. The simulation results also show the elimination of blind forwarding and data inaccessibility. [ABSTRACT FROM AUTHOR]

In wireless sensor networks (WSNs), the appearance of coverage holes over a large target field is mostly possible. Those holes reduce network performance and may affect the network efficiency. Several approaches were proposed to heal coverage holes in WSNs, but they still suffer from some weaknesses. In this paper we suggest a distributed algorithm, named hybrid hole healing algorithm (3HA), to find the minimum effective patching positions to deploy additional nodes to cover the holes. A hole manager node of each hole is responsible for operating the 3HA algorithm which requires two phases. The first phase finds all candidate patching positions using a Voronoi diagram. It takes all Voronoi vertices within the hole as the initial patching positions list. The second phase reduces as much as possible this list based on integer linear programming and on a probabilistic sensor model. The 3HA algorithm repeats the above phases in rounds, until all Voronoi vertices are covered. Simulation results show that our solution offers a high coverage ratio for various forms and sizes of holes and reduces the number of additional sensors when compared to some algorithms like the Perimeter-based, the Delaunay triangulation-based, the Voronoi-based, and the Trees-based coverage hole healing methods. [ABSTRACT FROM AUTHOR]

Wireless sensor networks have been widely considered as one of the most important 21th century technologies and are used in so many applications such as environmental monitoring, security and surveillance. Wireless sensor networks are used when it is not possible or convenient to supply signaling or power supply wires to a wireless sensor node. The wireless sensor node must be battery powered.Coverage and network lifetime are major problems in WSNs so in order to address this difficulty we propose a combinational method consists of fuzzy-logic and genetic algorithms. The proposed scheme detects the coverage holes in the network and selects the most appropriate hole's neighbor to move towards the blank area and compensate the coverage loss with fuzzy-logic contribution and above node new coordinate is determined by genetic algorithm. As fuzzy-logic will be so effective if more than one factor influence on decision making and also genetic algorithms perform well in dynamic problems so our proposed solution results in fast, optimized and reliable output

Due to limited power supplies, the sensor nodes exhaust their energy eventually. Accordingly, data transmission mechanisms between nodes and their destinations need to be designed based on energy efficiency. Most of the existing cluster-based schemes adopt direct data transmission manner for intra-cluster communication, which leads to the unbalanced energy consumption of member nodes (MNs) and results in coverage holes in the network. Several mobile sink (MS)-based schemes focus exclusively on optimizing the sojourn locations of the MS to balance the energy consumption among sensor nodes. However, in most of them, the MS stays at only one location within a cluster which leads to the unbalanced energy consumption of MNs. Furthermore, the time limitation for balancing the energy consumption of nodes has not been considered in the previous schemes, which results in reduced network performance. In this paper, the Energy-Efficient Intra-cluster Routing (EIR) algorithm is proposed to balance the energy consumption of MNs during a limited time, which leads to enhancing the coverage time of the network. In the proposed scheme, upon arriving the MS to a cluster, the optimal sojourn locations are determined with respect to allocated sojourn time to the cluster in such a way that moving the MS along these locations leads to balancing energy consumption among MNs. Based on the simulation results, the EIR algorithm remarkably increases the network performance in terms of different performance evaluation metrics. [ABSTRACT FROM AUTHOR]

Maximizing network coverage is among the key factors in designing efficient sensor-deployment algorithms for wireless sensor networks (WSNs). In this study, we consider a WSN in which mobile sensor nodes (SNs) are randomly deployed over a two-dimensional region with the existence of coverage holes due to the absence of any SNs. To improve the network coverage, we thus propose a novel distributed deployment algorithm - coverage hole-healing algorithm (CHHA) - to maximize the area coverage by healing the coverage holes such that the total SN moving distance is minimized. Once the network is formed after an initial random placement of the SNs, CHHA is applied to detect coverage holes, including hole-boundary SNs, based on computational geometry, i.e., Delaunay triangulation. The distributed deployment feature of CHHA applies a concept to virtual forces that is used to decide the movement of mobile SNs to heal the coverage holes. The simulation results show that our proposed algorithm is capable of exact detection of coverage holes in addition to area-coverage improvement by healing the holes. The results also demonstrate the effectiveness of CHHA compared with other competitive approaches, namely, VFA, VEDGE, and HEAL, in terms of total moving distance. [ABSTRACT FROM AUTHOR]

Abstract Due to limited resources of the sensor nodes energy efficiency is an important performance metric to evaluate the wireless sensor networks (WSN). In cluster-based WSNs, the cluster heads (CH) located around base station (BS) consume more energy and exhaust their energy supplies faster than other ones which leads to energy hole problem and premature network death. Furthermore, single-hop transmission manner is usually applied for intra-cluster communication, therefore the member nodes (MN) located farther away from CHs die sooner than other MNs, which leads to coverage holes and reduce the network performance. In this paper, we propose mobile sink (MS) based inter- and intra-cluster routing algorithms. The first algorithm aims to solve the unbalanced energy consumption of CHs, which results in enhanced network lifetime. Likewise, the goal of the second algorithm is to balance the energy consumption of MNs, which results in improved coverage time of the network. In the proposed mechanism, MSs move along clusters and stay in each cluster for a limited sojourn time calculated via first algorithm. Then, the optimal sojourn positions of MSs in the clusters are determined via second algorithm. Simulation results reveal that the proposed algorithms enhance the network performance in terms of different performance evaluation metrics. [ABSTRACT FROM AUTHOR]

Aiming at the coverage hole problem in hybrid wireless sensor networks (WSNs),we propose a coverage hole recovery algorithm based on polar coordinates. Firstly, we determine the boundary points of coverage holes by calculating the intersections of statistic nodes' sensing circle, and connect the boundary points to construct coverage hole polygons. Secondly, the location of virtual recovering nodes in every polygon is calculated according to the polar coordinate method. Finally, we build the distance data table between virtual recovering nodes and moving nodes to complete the hole recovery work, that is moving the moving nodes in the table to the locations of virtual nodes that match them. Simulation results show that compared with other similar algorithms, the proposed algorithm can determine and recover the coverage holes in WSNs effectively, and meanwhile it needs less moving nodes and has a shorter average moving distance. In addition, it prolongs the network's life cycle while improving the quality of coverage. [ABSTRACT FROM AUTHOR]

Mobile sink (MS) has been used in wireless sensor networks (WSN) to increase the network lifetime by changing the location over time. The major quality of service given by WSN is coverage energy consumption (EC) and network lifetime. There are many methods implemented for enhance the coverage hole restoration and reduce the EC. We propose a novel MSCOLER (MS based Coverage Optimization and Link-stability Estimation Routing) protocol for Optimal Coverage restoration and Link stability Estimation. An optimization algorithm is used to optimize the coverage hole and move the redundant node besides the hole. During the routing process, link quality based routing is used to discover the relay nodes with the estimation of link stability to enhance the entire network lifetime and practically make the perfect transmission distance for energy saving. Experimental results demonstrate that proposed protocol can solve the coverage restoration problem, decrease the EC and reduce the network lifetime. The performance is evaluated regarding Average of residual energy (ARE), Receiving packets ratio (RPR), Moving energy consumption (MEC), Network lifetime (NL), Percentage of coverage (%C) and Average Energy Consumption (AEC). [ABSTRACT FROM AUTHOR]

A repairing strategy for the coverage of the sensor network based on multi-mobile nodes and path planning is designed.Such mechanism can ultimately repair common nodes in a timely fashion via energy consumption analysis of the nodes by using genetic algorithm to calculate the reasonable moving path of the mobile nodes,which can avoid cov-erage holes caused by the death of sensor nodes at its best.The global convergence the designed algorithm is proved by stochastic process.Simulation experiments have proven the effectiveness of the designed mechanism and the relevant solution algorithm.

Aiming at the phenomenon that coverage holes caused by energy depletion coexisted with remaining energy of dormant redundant nodes in hybrid wireless sensor networks(WSN),a coverage compensation algorithm based on vector algebra to repair coverage hole with redundant nodes was presented.This algorithm included both the respective dis-placement amount calculation method of all the redundant nodes which may be involved in compensation and policies of the choice of the best redundant nodes that were selected by hole boundary node on the basis of balancing the remaining energy of nodes.The result shows that this algorithm makes full of energy resources in the premise of complete coverage to repair coverage hole,and has a better performance in both movement distance and movement cost compared with ex-isting COA algorithm.

Wireless Sensors Networks (WSNs) are currently receiving much research interest due to their wide-ranging use is a number of different fields. In the current study, a system based on a WSN is proposed that can monitor indoor air pollution in several public spaces, such as subway stations, offices, schools, and hospitals. The proposed system uses integrated sensors in mobile phones, moving from a stationary nodes model to a mobile nodes model. The main objective of building this system is to provide full coverage of the target area. To achieve this goal, the system is simulated by MATLAB and the following algorithms are applied: Particle Swarm Optimization (PSO) to maximize the coverage in the region of interest (RoI), Voronoi Diagram (VD) to detect holes in the coverage, and finally the Point in Polygon (PiP) algorithm to heal the holes in the coverage. The application of the algorithms mentioned above has been very effective as PSO has increased the coverage rate of the monitoring area to 100%. The VD allowed us to define the exact location of coverage holes whilew the Point in Polygon algorithm allowed us to heal the holes and find the remaining sensors in order to improve network coverage. This enabled us to achieve full coverage of the monitoring area.

Wireless sensor networks deployment and operation are most likely to take place under hazardous conditions. One extreme scenario is the deployment of a wireless sensor network in a mountainous and forested region in which a fire has ignited, for the purpose of localizing and/or tracking, in real time, its spread. Some methods developed in this paper are expected to provide superior performances under these conditions. Existing fires in the deployment region will also affect the nodes' coverage because the nodes that will fall in the middle of the fire will likely cease to operate. In our work, we develop a coverage hole bypassing algorithm for storing and maintaining holes-information in the network based on which a boundary node can provide the communication path which is more efficient to try to bypass a hole. Simulation results are presented to illustrate the proposed method and evaluate its run-time and message count per node. We show that these routing can be used in many applications. [ABSTRACT FROM AUTHOR]

The coverage and connectivity are the two imperative performance metrics for the growth of wireless sensor networks (WSNs) with sprouting technologies. In order to maintain these metrics, the issue of finding and healing of coverage hole is closely related to these two facts and plays a vital role in the performance improvement of the network. Many works in the past explored for 2D-WSNs, but now the time has come to investigate this matter for 3D-WSNs to reach the new heights of research and technology. In this paper, different scenarios with respect to the deployment of sensor nodes or network topology with the presence of different shaped coverage holes are discussed. Not only this, to heal these perceived holes introduction of sensor nodes having sensing radius different from initial deployed sensors has been suggested which in turn outlines the development of heterogeneous sensor networks, a keen issue with respect to technology development. This deployment of sensors to constitute heterogeneous sensor networks also influences the overall network cost in terms of cost reduction with an optimum coverage level. A mathematical analysis to give a relationship between the radii of former and later deployed sensor nodes is presented in the form of theorem. At the end, the results and discussion in order to achieve a specified level of coverage with respect to different packing patterns based on the mathematical analysis are provided. Also, some future directions to guide the researchers are discussed in this paper. [ABSTRACT FROM AUTHOR]

To solve the problem of coverage holes in target areas,a principle for hole recovery was proposed.Based on the principle,a novel algorithm named SOI was proposed for hole recovery using mobile nodes,which does not require location information,figures out the optimal inner nodes in the edge of coverage holes,and then moves them to new po-sitions.Through this mechanism,the area of coverage holes could be reduced.Analysis and simulation results show that,SOI has a better performance in dense deployed wireless sensor networks compared with existing VHR algorithm.

Coverage holes directly reduce network performance and become a key problem of static wireless sensor net-works.A hole-patching method was presented to get the resilient coverage,in which mobile nodes were guided by the boundary nodes of the coverage hole and patched uncovered area in the hole triangle by triangle.Based on geometry theories and mathematic deduction,the moving destination of the mobile nodes was proved to be optimal,and the cover-age of the patched holes was higher than 90%.Simulation results show the coverage,stability and redundancy of the proposed method,and then the availability was compared with some related methods reported recently.

Summary: Nowadays, the wireless sensor network (WSN) with IoT is intended to monitor real‐world physical or environmental phenomena in a number of applications, including foreign areas such as health and habitat monitoring. The WSN‐IoT network generates huge volume of data, which has to be processed and accessed by the remote users. Due to this large volume of data generation and resource constraint ability make achieving optimal cluster based routing in WSN‐IoT. The location of the sensor nodes significantly affects the accuracy of the information collected, which determines the quality of service provided by the application system. WSN can have multiple conflicts, which can create different coverage holes. These holes will break the existing overlap or connection and affect the required operation of the networks. Therefore, it is essential to find and repair the coverage holes to ensure the full functioning of the WSN as a motivation of this study. In this paper, we suggest a novel Coverage Hole aware Optimal Cluster based Routing (CHOCR) scheme for WSN‐IoT. First, we propose Modified Lichtenberg optimization (MLO) algorithm for balanced clustering which improve the performance of coverage hole. Second, we develop a linear equilibrium optimization based decision making (LEO‐DM) technique to subtract trust value of each IoT node using multiple restraints in cluster and consider the highest trusted node is act as cluster head (CH). After that, a hybrid deep recurrent neural network (HD‐RNN) is developed for intermediate node selection to frame the routing between two nodes. Finally, we simulate our proposed CHOCR scheme on the NS3.26 simulator. According to energy consumption, network longevity, number of nodes that are still alive and packet delivery ratio, packet loss ratio and throughput, end‐to‐end latency and delay of our proposed CHOCR routing system, we compare it to other current routing schemes. [ABSTRACT FROM AUTHOR]