Uniform Deployment Research Articles

Full Coverage Deployment in Wireless Sensor Network

In wireless sensor network very less work has been done on deployment. As we know in random deployment we can’t achieve the maximum coverage in communication which result in short life time of the battery. So in this paper we discuss few benefit of the Uniform deployment in which we can achieve the full coverage with uniformity. In this paper we can achieve the maximum efficiency and increase lifetime time of the sensors which result in the long battery life which is the back bone of any Wireless Sensor Network for Remote Sensing like in Oceanographic, Glacier study and Metrological Department for weather study which are nearly inaccessible regions. Wireless sensor networks (WSNs) are composed of large number of sensor nodes that have capability of sensing, data processing and communication functionalities. The nodes are usually accoutered with power-strained batteries, which are often difficult, extravagant and even impossible to be restored once the nodes are deployed. Therefore energy aliveness becomes the key research challenge for sensor network protocols. The energy consumed by a node depends on its state. Each node could be in one of four states: transmit, receive, idle (when the node keeps listening to the medium even when no messages are being transmitted) and finally sleep state (where the radio module is switched off: no communication is possible). Recent research showed that accurate energy savings can be achieved by scheduling node’s activities in high-density WSNs. Specifically, some nodes are scheduled to sleep whereas the remaining ones provide continuous monitoring. The main issue here is how to minimize the number of active nodes in order to maximize the network lifetime. Sensing coverage is also a significant issue for sensor networks and is viewed as one of the critical measures of the supervision quality provided by a WSN. Sensor deployment is important in WSNs, as it not only determines the cost for creating the network but also affects how well a region is supervised by sensors. One frequently used method to decrease the undesirable energy consumption is to implement an energy-efficient configuration protocol where sensors operate under a well-defined activating schedule, that is, some unnecessary sensors switch to off mode or low-power listening mode. The coverage problem in WSNs is how one can be sure that the deployment of active sensors provides the necessary coverage level and how to determine the minimum number of active sensors required and their locations in the interested area to ensure desirable coverage. Regarding sensors activating or deployment control problem, some work have been investigated how some sensors can be arranged to go to sleeping modes to elongate the network lifetime while maintaining desirable coverage of sensing field. On the other hand how these active sensors can be selected to maintain the desirable coverage of sensing field. And provide a near-optimal grid-based sensor placement algorithm to achieve the complete coverage. In this method, the interested area is divided into grid points uniformly. If one grid point can be detected by at least one sensor, the grid point is covered. The coverage of the area is defined as the ratio of detected grid points to the total

GALSR: Geographical Based Adaptive Lifetime Secure Routing Protocol For Wireless Sensor Network

Wireless sensor networks (WSNs) are potentially increased in research field due to their wide range of application. The topology of advanced WSNs form Multi-Hop WSNs. The Main issues in this topology is location based security and lifetime preserving in energy resources. In this paper, we projected a Geographical based Adaptive Lifetime Security Routing (GALSR) Protocol and GALSR Algorithm to improve the lifetime and security of WSNs. This algorithm enhanced with Greedy for Shortest path finder and Direct Random Propagation for Random Walking. We then determine that the energy consumption is rigorously disproportional to the uniform energy deployment for the given network topology, which greatly reduces the lifetime of the sensor networks. To resolve this issue, we introduce non-uniform energy deployment to optimize the lifetime and message delivery ratio under same energy resources and security. This energy balancing is set by Energy balance control (EBC) and security parameter using Metric Energy Balancer (MEB).We validate our finding in both Quantitative and Qualitative measures. Our quantitative measures is shown out of NetSim Simulator similarly our implementation is an best prove for our qualitative measures, Our proposed model shows that we achieved with increased Lifetime, Adaptive Security and Monetary efficient protocol.

Optimal periphery deployment of wireless base stations in swine facilities for 1-coverage

Full 1-coverage is difficult to achieve from periphery deployment of wireless sensor networks (WSNs) for monitoring animal activity in swine facilities. Specifically in finishing and nursery buildings, difficulties for deploying Base Stations (BSs) within the WSN detection area exist. A feasible approach is to deploy BSs along the walls of the building or pen. This can be modeled as a periphery deployment along the sides of a rectangle area A for full 1-coverage within A with the sensing radius R of BSs greater than the half width of A. Evaluation indicators were described to estimate the performance of deployments. Optimal periphery deployments are proposed for achieving 1-coverage with fewest number of BSs, when R varies from the half width of A to the radio sensing maximum. Optimal deployments compared to uniform deployments in a simulated swine facility (80m×20m) with various sensing radius (R=12,20,21,25,30) in various value ranges of R were conducted and results show the optimal deployments are superior to uniform deployments for 1-coverage, efficiency of 1-coverage, and standard deviation coverage. A deployment and simulation software was developed to simulate, analyze, and evaluate WSN coverage in swine facilities. Optimal periphery deployments are advantageous to acquire data reliably and efficiently; thus, improving animal physiology and behaviors monitoring for future research in swine facilities.

Modeling the influence of Chevron alignment sign on young male driver performance: A driving simulator study

In China, the Chevron alignment sign on highways is a vertical rectangle with a white arrow and border on a blue background, which differs from its counterpart in other countries. Moreover, little research has been devoted to the effectiveness of China’s Chevron signs; there is still no practical method to quantitatively describe the impact of Chevron signs on driver performance in roadway curves. In this paper, a driving simulator experiment collected data on the driving performance of 30 young male drivers as they navigated on 29 different horizontal curves under different conditions (presence of Chevron signs, curve radius and curve direction). To address the heterogeneity issue in the data, three models were estimated and tested: a pooled data linear regression model, a fixed effects model, and a random effects model. According to the Hausman Test and Akaike Information Criterion (AIC), the random effects model offers the best fit. The current study explores the relationship between driver performance (i.e., vehicle speed and lane position) and horizontal curves with respect to the horizontal curvature, presence of Chevron signs, and curve direction. This study lays a foundation for developing procedures and guidelines that would allow more uniform and efficient deployment of Chevron signs on China’s highways.

Effect of Catchment-Scale Green Roof Deployment on Stormwater Generation and Reuse in a Tropical City

Low-impact development (LID) comprises a broad spectrum of stormwater management technologies for mitigating the impacts of urbanization on hydrological processes. Among these technologies, green roofs are one of the most adopted solutions, especially in densely populated metropolitan areas, where roofs take up a significant portion of the impervious surfaces and land areas are scarce. While the in situ hydrological performance of green roofs—i.e., reduction of runoff volume and peak discharge—is well addressed in literature, less is known about their impact on stormwater management and reuse activities at a catchment or city scale. This study developed an integrated urban water cycle model (IUWCM) to quantitatively assess the effect of uniform green roof deployment (i.e., 25, 50, and 100% conversion of traditional roofs) over the period 2009–2011 in the Marina Reservoir catchment, a 100-km2, highly urbanized area located in the heart of Singapore. The IUWCM consists of two components: (1) a physically based model for extensive green roofs integrated within a one-dimensional numerical hydrological-hydraulic catchment model linked with (2) an optimization-based model describing the operation of the downstream, stormwater-fed reservoir. The event-based hydrological performance of green roofs varied significantly throughout the simulation period with a median of about 5% and 12% for the catchment scale reduction of runoff volume and peak discharge (100% conversion of traditional roofs). The high variability and lower performance (with respect to temperate climates) are strongly related to the tropical weather and climatic conditions—e.g., antecedent dry weather period and maximum rainfall intensity. Average annual volume reductions were 0.6, 1.2, and 2.4% for the 25, 50, and 100% green roof scenarios, respectively. The reduction of the stormwater generated at the catchment level through green roof implementation had a positive impact on flood protection along Marina Reservoir shores and the energy costs encountered when operating the reservoir. Vice versa, the drinking water supply, which depends on the amount of available stormwater, decreased due to the evapotranspiration losses from green roofs. Better performance in terms of stormwater reuse could only be obtained by increasing the time of concentration of the catchment. This may be achieved through the combination of green roofs with other LID structures.

Coverage and Rate Analysis in Heterogeneous Cloud Radio Access Networks With Device-to-Device Communication

The implementation of heterogeneous cloud radio access network (H-CRAN) architecture is faced with practical challenges, such as the capacity and time-delay limitations of the fronthaul links. This paper considers the use of device-to-device (D2D) communication to offload the remote radio heads (RRHs) located in the coverage region of high-power nodes (HPNs). We propose an H-CRAN with non-uniformly deployed D2D communication, in which D2D links are only utilized outside a specified distance from any HPN. Based on the analytical framework provided in this paper, the coverage and the average ergodic rate of a typical user equipment (UE) are characterized. Through defining the exclusion area appropriately, the proposed non-uniform D2D deployment can achieve performance improvement compared with uniform D2D deployment. In addition, to account for the capacity constraint of fronthaul, we characterize the average traffic delivery latency experience by a typical UE when served by RRHs as a quality-of-service metric. Our results show that for a lower fronthaul capacity regime, the proposed non-uniform D2D deployment achieves lower average traffic delivery latency compared with both the uniform D2D deployment and the pure H-CRAN scenarios.

Lifetime optimisation for linear wireless sensor networks under retransmission

The lifetime of wireless sensor networks (WSN) is strongly affected by the energy consumption, which is partly attributed to retransmission. In this paper, the energy consumption of a linear WSN is analysed based on basic energy consumption models and a retransmission model. Optimisation models are proposed with the objective of maximising WSN lifetime under the coverage and success transmission rate constraints. In particular, for traditional uniform and non-uniform sensor deployment problems without considering the sleep/wakeup mechanism, the number of sensors and their distances are optimised. Moreover, for a linear WSN with a sleep/wakeup mechanism, a sensor deployment scheme is developed by optimally assigning sensors to fixed locations. The genetic algorithm and the generalised reduced gradient method are applied to solve these problems. Our case studies illustrate that the lifetime of WSN with and without retransmission are different, and it is important to consider retransmission in WSN lifetime optimisation.

Energy-efficient mobile cluster-head data collection model for wireless sensor networks

Wireless sensor networks have grown from homogeneous network architecture to heterogeneous networks for the improvement of network efficiency and lifetime. This paper exhibits a mobile cluster-head data collection (MCHDC) model for heterogeneous wireless networks. The MCHDC model illustrates the mobility pattern of mobile cluster-head nodes in a controlled environment with uniform and nonuniform deployment of mobile elements in the area of observation. It focuses on the threshold velocity for movement of mobile elements in the network area. In this paper the effects of data sending rate, network area, sensor node density, and cluster-head node density on energy efficiency of the network with the MCHDC model have been studied through simulations.

Lifetime optimisation for linear wireless sensor networks under retransmission

The lifetime of wireless sensor networks WSN is strongly affected by the energy consumption, which is partly attributed to retransmission. In this paper, the energy consumption of a linear WSN is analysed based on basic energy consumption models and a retransmission model. Optimisation models are proposed with the objective of maximising WSN lifetime under the coverage and success transmission rate constraints. In particular, for traditional uniform and non-uniform sensor deployment problems without considering the sleep/wakeup mechanism, the number of sensors and their distances are optimised. Moreover, for a linear WSN with a sleep/wakeup mechanism, a sensor deployment scheme is developed by optimally assigning sensors to fixed locations. The genetic algorithm and the generalised reduced gradient method are applied to solve these problems. Our case studies illustrate that the lifetime of WSN with and without retransmission are different, and it is important to consider retransmission in WSN lifetime optimisation.

HIGH: A Hexagon-based Intelligent Grouping Approach in Wireless Sensor Networks

In a random deployment or uniform deployment strategy, sensor nodes are scattered randomly or uniformly in the sensing field, respectively. Hence, the coverage ratio cannot be guarante ...

Localizing Wireless Sensors with Diverse Granularities in Wireless Sensor Networks

To obtain accurate location information of individual sensor nodes is of vital importance in wireless sensor networks (WSNs), especially for objective tracking applications. However, it is challenging to acquire fine-grained localization accuracy because of resource constraints of sensor nodes, unreliable wireless communication, and cost. Moreover, heterogeneous characteristics of both sensor nodes and applications make this problem even harder to solve. In this paper, we propose NLMR, a novel on-demand node localization technology based on multiresolution model. NLMR comprises three phases: (1) subregion classification, which categorizes regions into subregions with either uniform node deployment or nonuniform node deployment; (2) multiresolution model construction, which creates a multiresolution model that caters for diverse localization granularity; (3) node localization, which allows the control center to estimate the locations of sensor nodes in a centralized manner. Our analysis and simulation results demonstrate the performance of NLMR and verify that our scheme can provide diverse localization granularity with high probability.

Time Domain Similarity of Lightweight Parameters Based Soil Respiration Sensor Network Deployment

Deployment is a basic and key issue for all kinds of wireless sensor networks applications. Most of existing researches on deployment problem of wireless sensor network are on generic network level and not for specific application scenarios and also do not utilize any domain knowledge of practical applications. Focusing on the problem of limited number of sensing nodes in soil respiration sensor networks, using domain knowledge such as some lightweight parameters (temperature, humidity, etc.) influencing soil respiration and soil respiration having a day-periodic trend, we proposed a deployment method, TimSim, for soil respiration sensor network based on time domain similarity of lightweight parameters. Lightweight parameters data from positions in the region to be monitored are collected before the deployment of soil respiration sensing nodes, and then time domain similarities of lightweight data among different positions are analyzed, according to which these positions are divided into some groups. A representative position in each group is chosen to deploy a soil respiration sensing node. The experimental results show that TimSim method can place nodes to proper positions so as to monitor regional soil respiration carbon flux effectively with a smaller estimation error than uniform and random deployment methods.

Massive-MIMO Meets HetNet: Interference Coordination Through Spatial Blanking

In this paper, we study the downlink performance of a heterogeneous cellular network (HetNet) where both macro and small cells share the same spectrum and hence interfere with each other. We assume that the users are concentrated at certain areas in the cell, i.e., they form hotspots . While some of the hotspots are assumed to have a small cell in their vicinity, the others are directly served by the macrocell. Due to a relatively small area of each hotspot, the users lying in a particular hotspot appear to be almost co-located to the macrocells, which are typically deployed at some elevation. We assume a large number of antennas at the macrocell relative to the number of users simultaneously served. In this “massive MIMO” regime, the channel vectors become highly directional. We exploit this directionality in the channel vectors to obtain spatial blanking , i.e., concentrating transmission energy only in certain directions while creating transmission opportunities for the small cells lying in the other directions. In addition to this inherent interference suppression, we also develop three low-complexity interference coordination strategies: 1) turn off small cells based on the amount of cross-tier interference they receive or cause to the scheduled macrocell hotspots; 2) schedule hotspots such that treating interference as noise is approximately optimal for the resulting Gaussian interference channel; and 3) offload some of the macrocell hotspots to nearby small cells to improve throughput fairness across all hotspots. For all these schemes, we study the relative merits and demerits of uniform deployment of small cells vs. deploying more small cells towards the cell center or the cell edge.

Cost-Aware SEcure Routing (CASER) Protocol Design for Wireless Sensor Networks

Lifetime optimization and security are two conflicting design issues for multi-hop wireless sensor networks (WSNs) with non-replenishable energy resources. In this paper, we first propose a novel secure and efficient Cost-Aware SEcure Routing (CASER) protocol to address these two conflicting issues through two adjustable parameters: energy balance control (EBC) and probabilistic-based random walking. We then discover that the energy consumption is severely disproportional to the uniform energy deployment for the given network topology, which greatly reduces the lifetime of the sensor networks. To solve this problem, we propose an efficient non-uniform energy deployment strategy to optimize the lifetime and message delivery ratio under the same energy resource and security requirement. We also provide a quantitative security analysis on the proposed routing protocol. Our theoretical analysis and OPNET simulation results demonstrate that the proposed CASER protocol can provide an excellent tradeoff between routing efficiency and energy balance, and can significantly extend the lifetime of the sensor networks in all scenarios. For the non-uniform energy deployment, our analysis shows that we can increase the lifetime and the total number of messages that can be delivered by more than four times under the same assumption. We also demonstrate that the proposed CASER protocol can achieve a high message delivery ratio while preventing routing traceback attacks.

Energy Efficiency and QoS Enhancement for Wireless Sensor Networks with Applications to Long-Narrow Structures

There is a class of special environments, such as roads, mines tunnels, rivers, bridges, and pipelines, whose geographical shapes are long-narrow for several hundred meters. Wireless sensor networks (WSN) can be applied to monitor these environments. Long-narrow structure makes the WSN face plenty of challenges, such as unbalanced energy consumption and data aggregation. This paper proposes a nonuniform symmetric cluster model (NUSCM) using reasonable coverage routing controlling. The NUSCM consists of two base stations, sensor node clusters (SNCs) and transmission node clusters (TNCs), which can make the sensor networks be scalable to cover various long-narrow structures. Hierarchical nodes spacing and routing strategy of NUSCM are addressed. Furthermore, we simulate the proposed NUSCM, in comparison with the nonuniform deployment with two base stations (NUD-TBS) and uniform deployment with two base stations (UD-TBS). Research results indicate that the NUSCM and NUD-TBS have the same energy efficiency, which are better than that of UD-TBS. Moreover, NUSCM is superior to the UD-TBS and NUD-TBS in the link communication load and network survivability.

The dynamics of a rotating solar sail when it is deployed

A model of the release of a solar sail array, in which the sail, deployed from the packed state, is represented in the form of four released tethers, is considered. At the initial stage of the unfolding of the solar sail, taking into account the central symmetry of the constructional arrangement of the spools with the tethers, the release of one of the tethers is modelled on the assumption that all the remaining tethers are released in synchronism and the release control system ensures dynamic symmetry of the process. A differential equation of the small transverse oscillations in the plane of rotation of a point mass on a weightless tether during the deployment from the rotating central unit, is presented. An analytical solution of the linearized equation of the deployment of a point mass is obtained, expressed in terms of the Bessel functions for uniform deployment and in terms of the hypergeometric functions for a uniformly decelerated deployment. Numerical modelling, carried out for two cases, namely, when the tether is represented in the form of a set of point masses, connected successively by weightless inextensible threads, and in the form of a weightless inextensible thread with a heavy load at the free end, confirms the analytical results obtained.

Data gathering architecture for temporary worksites based on a uniform deployment of wireless sensors

Data management is an important issue in wireless sensor networks. However, the data gathering process may be unsuccessful in disconnected or random networks: some data gathered cannot be delivered to the sink, coverage holes may occur and result in missing data. To cope with this problem, we propose two distributed redeployment algorithms (distributed virtual forces algorithm (DVFA) and adaptive distributed virtual forces algorithm (ADVFA)), based on virtual forces, that provide a uniform deployment of sensor nodes. Both ensure full area coverage and network connectivity.We define a three-tier architecture where after the execution of a redeployment algorithm, sensor nodes are uniformly deployed to monitor a temporary worksite. We compute the optimal number of sensors needed to cover an area. Using this result, we parameterise DVFA and evaluate its performances. We then propose ADVFA to cope with DVFA drawbacks (e.g., node oscillations). ADVFA outperforms DVFA, considerably reducing the distance travelled by nodes and then maximising network lifetime by saving energy.

Deployment-based lifetime optimization model for homogeneous Wireless Sensor Network under retransmission.

Sensor-deployment-based lifetime optimization is one of the most effective methods used to prolong the lifetime of Wireless Sensor Network (WSN) by reducing the distance-sensitive energy consumption. In this paper, data retransmission, a major consumption factor that is usually neglected in the previous work, is considered. For a homogeneous WSN, monitoring a circular target area with a centered base station, a sensor deployment model based on regular hexagonal grids is analyzed. To maximize the WSN lifetime, optimization models for both uniform and non-uniform deployment schemes are proposed by constraining on coverage, connectivity and success transmission rate. Based on the data transmission analysis in a data gathering cycle, the WSN lifetime in the model can be obtained through quantifying the energy consumption at each sensor location. The results of case studies show that it is meaningful to consider data retransmission in the lifetime optimization. In particular, our investigations indicate that, with the same lifetime requirement, the number of sensors needed in a non-uniform topology is much less than that in a uniform one. Finally, compared with a random scheme, simulation results further verify the advantage of our deployment model.

Eigenvector centrality based cluster size control in randomly deployed wireless sensor networks

Cluster size control plays a significant role in balancing energy consumption and mitigating hot spot problem in wireless sensor networks. Cluster size control is necessary as clusters having higher member nodes consume significantly higher amount of energy while low member nodes in a cluster lead to under utilization of channel capacity. Further, cluster-heads located near to sink have to perform additional function of relaying data of other nodes. All these factors are responsible for hotspots or energy holes creation which in turn affect the network lifetime. In this paper, we propose a heuristic approach based upon Eigenvector centrality for cluster size control which we have named as Ev-CSC. While existing methods in literature consider distance of a cluster-head from sink, layered architecture, uniform deployment of nodes, prefixed sink location as a precondition, our proposed method does not have these constraints and is applicable to any kind of deployment, traffic pattern and node types. We have applied Ev-CSC on equal clustering methods and have also compared the same with state-of-the-art cluster size control methods. The experimental results demonstrate that our proposed method enhances the performance of respective equal clustering methods and performs better as compared to cluster size control methods.

Good on paper: the gap between programme theory and real-world context in Pakistan's Community Midwife programme.

ObjectiveTo understand why skilled birth attendance—an acknowledged strategy for reducing maternal deaths—has been effective in some settings but is failing in Pakistan and to demonstrate the value of a theory-driven approach to evaluating implementation of maternal healthcare interventions.DesignImplementation research was conducted using an institutional ethnographic approach.Setting and populationNational programme and local community levels in Pakistan.MethodsObservations, focus group discussions, and in-depth interviews were conducted with 38 Community Midwives (CMWs), 20 policymakers, 45 healthcare providers and 136 community members. A critical policy document review was conducted. National and local level data were brought together.Main outcomesAlignment of programme theory with real-world practice.ResultsData revealed gaps between programme theory, assumptions and reality on the ground. The design of the programme failed to take into account: (1) the incongruity between the role of a midwife and dominant class and gendered norms that devalue such a role; (2) market and consumer behaviour that prevented CMWs from establishing private practices; (3) the complexity of public–private sector cooperation. Uniform deployment policies failed to consider existing provider density and geography.ConclusionsGreater attention to programme theory and the ‘real-world’ setting during design of maternal health strategies is needed to achieve consistent results in different contexts.