Density Of Sensor Nodes Research Articles

Multipath Routing in Wireless Sensor Networks: A Survey and Analysis

Due to restricted communication range and high density of sensor nodes in wireless sensor network, forwarding packets is an important field of research in sensor networks. Nowadays, multipath routing approach is widely used in wireless sensor networks to improve network performance through efficient utilization of the available network resources. The main aim of this survey is to present the concept of multipath routing, as well as the basic motivations for utilizing this technique. In addition, this paper presents a comprehensive taxonomy on the existing multipath routing protocols. This paper also highlights the objective behind the development of each protocol category. Finally, a detailed study has been made on the design and operation of the different protocols, with emphasis on their advantages and disadvantages.

Generic correlation model for wireless sensor network applications

In wireless sensor networks (WSNs) having a high density of sensor nodes, transmitted measurements are spatially correlated, often redundantly whenever an event of interest is detected. In this work, the authors propose a correlation model to enable energy-efficient methodologies that exploit the spatial correlation at the network and medium access control (MAC) layers. At the network layer, the authors first demonstrate how, through proper tuning of both the sensing range and correlation threshold, WSNs can be partitioned into disjoint correlated clusters without degrading the information reliability, thus enabling significant energy saving. On the other hand, as another contribution, the authors investigate the impacts of correlation between nodes on achieved distortion in the event estimation at the sink. The interactions among various parameters such as distortion constraints, spatial node density, node selection, sensing range and their impacts on the reconstruction performance are quantitatively studied. The authors demonstrate that the same level of distortion constraint can be achieved by selecting fewer nodes. The nodes can be still fewer if they are less spatially correlated. However, the MAC protocols which show distributive effect of this selection needs more study.

On energy-efficient trap coverage in wireless sensor networks

In wireless sensor networks (WSNs), trap coverage has recently been proposed to trade off between the availability of sensor nodes and sensing performance. It offers an efficient framework to tackle the challenge of limited resources in large-scale sensor networks. Currently, existing works only studied the theoretical foundation of how to decide the deployment density of sensors to ensure the desired degree of trap coverage. However, practical issues, such as how to efficiently schedule sensor node to guarantee trap coverage under an arbitrary deployment, are still left untouched. In this article, we formally formulate the Minimum Weight Trap Cover Problem and prove it is an NP-hard problem. To solve the problem, we introduce a bounded approximation algorithm, called Trap Cover Optimization (TCO) to schedule the activation of sensors while satisfying specified trap coverage requirement. We design Localized Trap Coverage Protocol as the localized implementation of TCO. The performance of Minimum Weight Trap Coverage we find is proved to be at most O (ρ) times of the optimal solution, where ρ is the density of sensor nodes in the region. To evaluate our design, we perform extensive simulations to demonstrate the effectiveness of our proposed algorithm and show that our algorithm achieves at least 14% better energy efficiency than the state-of-the-art solution.

A Survey on Clustering and Routing on LEACH for Wireless Sensor Network

In recent years, Wireless Sensor Networks (WSNs) have been promising approaches for a variety of application monitoring and capturing the required data from the environment. Due to the restricted communication range and high density of sensor nodes, routing in WSNs has been considered an important field of research over the past decade. The most popular protocol for clustering in WSNs is Low Energy Adaptive Clustering Hierarchy (LEACH) which is based on adaptive clustering technique. The factors affecting LEACH efficiency include Cluster Head (CH), topology structure and routing algorithm. This paper provides in the past years the taxonomy of various clustering and routing techniques based on LEACH in WSNs. The paper highlights the primary principle of each improved protocol and emphasize on their advantages and disadvantages compared to the LEACH.

무선 센서 네트워크의 수명연장을 위한 클러스터링 기법

In this paper, we propose two clustering schemes to prolong lifetime by improving unbalance of energy consumption among sensor nodes in wireless sensor networks. The first proposed scheme make up clusters according to density of sensor nodes in initial stage of wireless sensor networks for reducing energy consumption of wireless sensor networks. After the initial stage, a cluster header is selected by a relay scheme that determines a cluster header of next round among cluster members. by estimating of energy consumption of cluster members for improving unbalance of energy consumption among cluster members.

WSN in cyber physical systems: Enhanced energy management routing approach using software agents

Recently, the cyber physical system has emerged as a promising direction to enrich the interactions between physical and virtual worlds. Meanwhile, a lot of research is dedicated to wireless sensor networks as an integral part of cyber physical systems. A wireless sensor network (WSN) is a wireless network consisting of spatially distributed autonomous devices that use sensors to monitor physical or environmental conditions. These autonomous devices, or nodes, combine with routers and a gateway to create a typical WSN system. Shrinking size and increasing deployment density of wireless sensor nodes implies the smaller equipped battery size. This means emerging wireless sensor nodes must compete for efficient energy utilization to increase the WSN lifetime. The network lifetime is defined as the time duration until the first sensor node in a network fails due to battery depletion. One solution for enhancing the lifetime of WSN is to utilize mobile agents. In this paper, we propose an agent-based approach that performs data processing and data aggregation decisions locally i.e., at nodes rather than bringing data back to a central processor (sink). Our proposed approach increases the network lifetime by generating an optimal routing path for mobile agents to transverse the network. The proposed approach consists of two phases. In the first phase, Dijkstra’s algorithm is used to generate a complete graph to connect all source nodes in a WSN. In the second phase, a genetic algorithm is used to generate the best-approximated route for mobile agents in a radio harsh environment to route the sensory data to the base-station. To demonstrate the feasibility of our approach, a formal analysis and experimental results are presented.

DESIGN ISSUES AND CLASSIFICATION OF WSNS OPERATING SYSTEMS

Wireless Sensor Networks is an emerging area of research. Wireless Sensor networks (WSNs) face lot of problems that do not arise in other types of wireless networks and computing environments. Limited computational resources, power constraints, low reliability and higher density of sensor nodes (motes) are just some basic problems that have to be considered when designing or selecting a new operating system in order to evaluate the performance of wireless sensor nodes (motes). In this paper we focused on design issues, challenges and classification of operating systems for WSNs.

Connectivity Analysis for Wireless Sensor Networks with Antenna Array Integrated Central Node

In a wireless sensor network (WSN), after gathering information, tiny sensor nodes need to transmit data to a sink. It is important to guarantee that each node can communicate with a sink. Due to the multi-hop communication of WSNs, an essential condition for reliable transmission is completely connectivity of a network. Adaptive or smart antenna (SA) techniques in WSNs have been a topic of active research in recent years. These techniques have been shown to be effective with respect to decreasing energy consuming via specified regions which are formed by the SA beams. In this paper, we propose a probabilistic technique to determine the network connectivity probability of the SA integrated WSN. We employ the geometric shape model to evaluate the network connectivity probability of the WSN using the SA beam specifications. The sensor node density to satisfy the desired network connectivity is determined in terms of the beam-width of the antenna array and node transmission range. The analytical results agree with the simulation results by less than 4.7 % error in the average.

Detour Path Angular Information Based Range-Free Localization in Wireless Sensor Network

Range-free localization algorithm continues to be an important and challenging research topic in anisotropic Wireless Sensor Networks (WSNs). Designing range-free localization algorithms without considering obstacles or holes inside the network area does not reflect the real world conditions. In this paper, we have proposed Detour Path Angular Information (DPAI) based sensor localization algorithm to accurately estimate the distance between an anchor node and a sensor node. We utilized the Euclidean distance and transmission path distance among anchor nodes to calculate the angle of the transmission path between them one by one. Then the estimated hop distance is adjusted by the angle between the anchor pairs. Based on the angle of the detoured path (which is the key factor for accuracy), our algorithm determines whether the path is straight or detoured by anisotropic factors. Our proposed algorithm does not require any global knowledge of network topology to tolerate the network anisotropy nor require high sensor node density for satisfactory localization accuracy. Extensive simulations are performed and the results are observed to be in good agreement with the theoretical analysis. DPAI achieved average sensor localization accuracy better than 0.3r in isotropic network and 0.35r in anisotropic network when the sensor density is above 8.

The Effect of Wireless Sensor Nodes Deployment Density in Forest Fire Monitoring Quality Evaluation

The early detection and monitoring of forest fire are very important for fire suppression quickly and reducing the loss of human and property. At present, forest fire monitoring techniques based on wireless sensor networks have drawn more and more attention from both academic and forestry field. In order to reduce the cost of monitoring system, it is necessary to monitor a biggest area with sensor nodes of given number. In this paper, based on the forest fire circular and elliptical propagation model, the case where the sensors are located in a regular triangle grid is analyzed. Some results which relate the sensor node density to the forest fire monitoring quality are presented. The theoretical analysis and the results of Monte Carlo simulations in fire circular propagation situation show that, the expect value of the time to fire detection is proportional to the ration of node density to the fire propagation speed, and the expect value of burned area only depends on the node density, but it doesn’t depend on the distribution of the fire ignition and fire propagation model.

Optimum Sensor Density in Distortion-Tolerant Wireless Sensor Networks

The optimum sensor node density for one- and two-dimensional (1-D and 2-D) wireless sensor networks (WSNs) with spatial source correlation is studied in this paper. The WSN attempts to reconstruct a spatially correlated signal field by collecting the location-dependent measurements from the distributed sensor nodes. The WSN is designed to minimize the mean square error (MSE) distortion between the original and the reconstructed signals under the constraint of a fixed power per unit area. The impacts of node density and spatial data correlation on the network performance are investigated for both small networks with finite number of nodes, and large networks with infinite area, infinite number of nodes, but finite node density through asymptotic analysis. The interactions among the various network parameters and their impacts on the system performance are quantitatively identified with exact analytical expressions, many of which are in closed-forms. The results provide guidelines on the design of practical WSNs.

Anchor-Node-Based Distributed Localization with Error Correction in Wireless Sensor Networks

This paper proposes a scheme to enhance localization in terms of accuracy and transmission overhead in wireless sensor networks. This scheme starts from a basic anchor-node-based distributed localization (ADL) using grid scan with the information of anchor nodes within two-hop distance. Even though the localization accuracy of ADL is higher than that of previous schemes (e.g., DRLS), estimation error can be propagated when the ratio of anchor nodes is low. Thus, after each normal node estimates the initial position with ADL, it checks whether the position needs to be corrected because of the insufficient anchors within two-hop distance, that is, the node is in sparse anchor area. If correction needs, the initial position is repositioned using hop progress by the information of anchor nodes located several hops away so that error propagation is reduced (REP); the hop progress is an estimated hop distance using probability based on the density of sensor nodes. Results via in-depth simulation show that ADL has about 12% higher localization accuracy and about 10% lower message transmission cost than DRLS. In addition, the localization accuracy of ADL with REP is about 30% higher than that of DRLS, even though message transmission cost is increased.

Multipath Routing in Wireless Sensor Networks: Survey and Research Challenges

A wireless sensor network is a large collection of sensor nodes with limited power supply and constrained computational capability. Due to the restricted communication range and high density of sensor nodes, packet forwarding in sensor networks is usually performed through multi-hop data transmission. Therefore, routing in wireless sensor networks has been considered an important field of research over the past decade. Nowadays, multipath routing approach is widely used in wireless sensor networks to improve network performance through efficient utilization of available network resources. Accordingly, the main aim of this survey is to present the concept of the multipath routing approach and its fundamental challenges, as well as the basic motivations for utilizing this technique in wireless sensor networks. In addition, we present a comprehensive taxonomy on the existing multipath routing protocols, which are especially designed for wireless sensor networks. We highlight the primary motivation behind the development of each protocol category and explain the operation of different protocols in detail, with emphasis on their advantages and disadvantages. Furthermore, this paper compares and summarizes the state-of-the-art multipath routing techniques from the network application point of view. Finally, we identify open issues for further research in the development of multipath routing protocols for wireless sensor networks.

무선 센서 네트워크에서 에너지 효율을 고려한 모바일 sink의 적응적 경로설정 방법

In this paper, we propose a novel approach to optimize the movement of mobile sink node, called AMSP(Adaptive Mobile Sink Path) for mobile sensor network environments. Currently available studies usually suffer from unnecessary data transmission resulting from random way point approach. To address the problem, we propose a method which uses the Hilbert curve to create a path. The proposed method guarantees shorten transmission distance between the sink node and each sensor node by assigning orders of the curve according to sensor node density. Furthermore, The schedule of the sink node is informed to all of the sensing nodes so that the Duty Cycle helps the network be more energy efficient. In our experiments, the proposed method outperforms the existing works such as TTDD and CBPER by up to 80% in energy consumption.

센서 네트워크 바용 절감을 위한 에너지 공급장치 배치 기법

본 고에서는 각 센서에 필요한 에너지를 공급하는 장치를 포함한 센서 네트워크 시스템을 고려하고, 에너지 공급 장치의 설치 및 운용 비용을 최소화하는 방법을 제안한다. 센서와 에너지 공급원이 정방형으로 배치되는 구조하에서 센서 노드의 밀도, 에너지 공급장치당 센서 노드 커버 범위 등에 따라 에너지 공급 장치의 설치 및 운용비용을 함수화한다. 또한 주어진 센서 노드밀도 환경에서 총 비용을 최소화하는 에너지 공급장치당 센서 노드 커버 범위를 결정하여 에너지 공급장치가 포함한 센서 네트워크의 배치를 최적화한다. 모의 실험을 통해 기존 방법에 비해 제안된 방법이 약 19%의 센서 네트워크 비용을 절감하는 효과를 가짐을 보인다. This paper considers the cost minimization issue for sensor network systems where sensor energy is supplied by remote energy sources wirelessly. Assuming symmetric structures of sensor nodes and energy sources, cost minimization problem is formulated, where the cost of sensor networks is represented as a function of sensor node density and energy source coverage. The optimal solution for the problem is provided and simulation results show that the proposal scheme achieves around 19% cost reduction in comparision to a conventional scheme.

English

Aggregating data of several nodes in a wireless sensor networks allows us to accurately monitor a remote environment. However, low-cost battery-powered nodes are often used to implement such networks, resulting in tight energy and communication bandwidth constraints. We have found that sensor node distances and densities are key factors in clustering. The aim of this paper is to introduce a new protocol to reduce overall power consumption, extend network life time in wireless sensor networks. In this paper, Normal Technique and Distance and Density based Clustering Algorithm (DDCSA) technique is compared on various parameters. Simulation results show a better performance of DDCSA as compared to Normal Technique

센서 네트워크에서 최소 경계 다각형을 이용한 에너지 효율적인 군집 이벤트 탐지 기법

Many works on energy-efficient cluster event detection schemes have been done considering the energy restriction of sensor networks. The existing cluster event detection schemes transmit only the boundary information of detected cluster event nodes to the base station. However, If the range of the cluster event is widened and the distribution density of sensor nodes is high, the existing cluster event detection schemes need high transmission costs due to the increase of sensor nodes located in the event boundary. In this paper, we propose an energy-efficient cluster event detection scheme using the minimum boundary polygons (MBP) that can compress and summarize the information of event boundary nodes. The proposed scheme represents the boundary information of cluster events using the MBP creation technique in the large scale of sensor network environments. In order to show the superiority of the proposed scheme, we compare it with the existing scheme through the performance evaluation. Simulation results show that our scheme maintains about 92% accuracy and decreases about 80% in energy consumption to detect the cluster event over the existing schemes on average.

Distributed network control for mobile multi-modal wireless sensor networks

A sensor network operates on an infrastructure of sensing, computation, and communication, through which it perceives the evolution of events it observes. We propose a fusion-driven distributed dynamic network controller, called MDSTC, for a multi-modal sensor network that incorporates distributed computation for in-situ assessment, prognosis, and optimal reorganization of constrained resources to achieve high quality multi-modal data fusion. For arbitrarily deployed sensors, a certain level of data quality cannot be guaranteed in sparse regions. MDSTC reallocates resources to sparse regions; reallocation of network resources in this manner is motivated by the fact that an increased density of sensor nodes in a region of interest leads to better quality data and enriches the network resilience. Simulation results in NS-2 show the effectiveness of the proposed MDSTC. 1 1 This material is based upon work supported by the US Army Research Laboratory and the US Army Research Office under the eSensIF MURI Award No. W911NF-07-1-0376. Any opinions, findings, and conclusions or recommendations expressed in this publication are those of the authors and do not necessarily reflect the views of the sponsor.

A comparative study on simulation vs. real time deployment in wireless sensor networks

Increasing deployment density and shrinking size of wireless sensor nodes requires small equipped battery size. This means emerging wireless sensor nodes must compete for efficient energy utilization. Medium Access Control (MAC) protocols play a vital role in energy consumption of sensor node as it controls the radio activities. Customized or open source simulators play an important role to measure the performance effectiveness of MAC protocols based on the fact that they are flexible, reduce experimental overhead and cost. Nevertheless, these benefits come at the cost of results accuracy. In this paper, we investigate differences of the behaviour of our agent based S-MAC protocols in real deployment compared to the results produced using our custom based simulator, which ignores the lower layers effects such as packet collision and overhearing. We use network simulator 2 (ns2), an open source simulator, which provides a complete protocol stack. We further try to find and explain the rationale of the variance of results produced by real deployment and that of simulators.

Density‐adaptive network reprogramming protocol for wireless sensor networks

AbstractNetwork reprogramming is a process used to update program codes of sensor nodes that are already deployed. To deal with potentially unstable link conditions of wireless sensor networks, the epidemic approach based on 3‐way advertise‐request‐data handshaking is preferred for network reprogramming. Existing epidemic protocols, however, require a long completion period and high traffic overhead in high‐density networks, mainly due to the hidden terminal problem. In this paper, we address this problem by dynamically adjusting the frequency of advertisement messages in terms of the density of sensor nodes, which is the number of sensor nodes in a certain area. We compare the performance of the proposed scheme, called DANP (Density‐Adaptive Network Reprogramming Protocol), with a well‐known epidemic protocol, Deluge. Simulations indicate that, in the grid topologies, DANP outperforms Deluge by about 30% in terms of the completion time and about 50% in terms of the traffic overhead. Significant performance gain is observed in random topologies as well. The performance of DANP is further confirmed via measurements in an experimental test bed. Copyright © 2009 John Wiley & Sons, Ltd.