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Showing papers on "Sensor node published in 2011"


Journal ArticleDOI
TL;DR: Various aspects of energy harvesting sensor systems- architecture, energy sources and storage technologies and examples of harvesting-based nodes and applications are surveyed and the implications of recharge opportunities on sensor node operation and design of sensor network solutions are discussed.
Abstract: Sensor networks with battery-powered nodes can seldom simultaneously meet the design goals of lifetime, cost, sensing reliability and sensing and transmission coverage. Energy-harvesting, converting ambient energy to electrical energy, has emerged as an alternative to power sensor nodes. By exploiting recharge opportunities and tuning performance parameters based on current and expected energy levels, energy harvesting sensor nodes have the potential to address the conflicting design goals of lifetime and performance. This paper surveys various aspects of energy harvesting sensor systems- architecture, energy sources and storage technologies and examples of harvesting-based nodes and applications. The study also discusses the implications of recharge opportunities on sensor node operation and design of sensor network solutions.

1,870 citations


Proceedings ArticleDOI
10 Apr 2011
TL;DR: This paper investigates the operation of a sensor network under this new enabling energy transfer technology and proves that the optimal traveling path for the WCV is the shortest Hamiltonian cycle and provides a number of important properties.
Abstract: Traditional wireless sensor networks are constrained by limited battery energy. Thus, finite network lifetime is widely regarded as a fundamental performance bottleneck. Recent breakthrough in the area of wireless energy transfer offers the potential of removing such performance bottleneck, i.e., allowing a sensor network remain operational forever. In this paper, we investigate the operation of a sensor network under this new enabling energy transfer technology. We consider the scenario of a mobile charging vehicle periodically traveling inside the sensor network and charging each sensor node's battery wirelessly. We introduce the concept of renewable energy cycle and offer both necessary and sufficient conditions. We study an optimization problem, with the objective of maximizing the ratio of the wireless charging vehicle (WCV)'s vacation time over the cycle time. For this problem, we prove that the optimal traveling path for the WCV is the shortest Hamiltonian cycle and provide a number of important properties. Subsequently, we develop a near-optimal solution and prove its performance guarantee.

382 citations


01 Jan 2011
TL;DR: A rigorous proof of convergence to global synchronization is provided in the absence of process and measurement noise and of communication delay, and its effectiveness is shown through a number of experiments performed on a real wireless sensor network.
Abstract: This paper describes a new consensus-based protocol, referred to as Average TimeSync (ATS), for synchronizing the clocks of a wireless sensor network. This algorithm is based on a cascade of two consensus algorithms, whose main task is to average local information. The proposed algorithm has the advantage of being totally distributed, asynchronous, robust to packet drop and sensor node failure, and it is adaptive to time-varying clock drifts and changes of the communication topology. In particular, a rigorous proof of convergence to global synchronization is provided in the absence of process and measurement noise and of communication delay. Moreover, its effectiveness is shown through a number of experiments performed on a real wireless sensor network.

345 citations


Proceedings ArticleDOI
10 Apr 2011
TL;DR: Predictive-Wakeup MAC is presented, a new energy-efficient MAC protocol based on asynchronous duty cycling that minimizes sensor node energy consumption by enabling senders to predict receiver wakeup times and introduces an on-demand prediction error correction mechanism that effectively addresses timing challenges such as unpredictable hardware and operating system delays and clock drift.
Abstract: This paper presents PW-MAC (Predictive-Wakeup MAC), a new energy-efficient MAC protocol based on asynchronous duty cycling. In PW-MAC, nodes each wake up to receive at randomized, asynchronous times. PW-MAC minimizes sensor node energy consumption by enabling senders to predict receiver wakeup times; to enable accurate predictions, PW-MAC introduces an on-demand prediction error correction mechanism that effectively addresses timing challenges such as unpredictable hardware and operating system delays and clock drift. PW-MAC also introduces an efficient prediction-based retransmission mechanism to achieve high energy efficiency even when wireless collisions occur and packets must be retransmitted. We evaluate PW-MAC on a testbed of MICAz motes and compare it to X-MAC, WiseMAC, and RI-MAC, three previous energy-efficient MAC protocols, under multiple concurrent multihop traffic flows and under hidden-terminal scenarios and scenarios in which nodes have wakeup schedule conflicts. In all experiments, PW-MAC significantly outperformed these other protocols. For example, evaluated on scenarios with 15 concurrent transceivers in the network, the average sender duty cycle for X-MAC, WiseMAC, and RI-MAC were all over 66%, while PW-MAC's average sender duty cycle was only 11%; the delivery latency for PW-MAC in these scenarios was less than 5% that for WiseMAC and X-MAC. In all experiments, PW-MAC maintained a delivery ratio of 100%.

306 citations


Journal ArticleDOI
TL;DR: In this paper, a consensus-based protocol, referred to as Average TimeSync (ATS), is proposed for synchronizing the clocks of a wireless sensor network based on a cascade of two consensus algorithms, whose main task is to average local information.

262 citations


Book ChapterDOI
17 Apr 2011
TL;DR: Indriya as mentioned in this paper is a large-scale low-cost wireless sensor network testbed deployed at the National University of Singapore (NU) which uses TelosB devices and it is built on an active-USB infrastructure.
Abstract: This paper presents Indriya, a large-scale, low-cost wireless sensor network testbed deployed at the National University of Singapore. Indriya uses TelosB devices and it is built on an active-USB infrastructure. The infrastructure acts as a remote programming back-channel and it also supplies electric power to sensor devices. Indriya is designed to reduce the costs of both deployment and maintenance of a large-scale testbed. Indriya has been in use by over 100 users with its maintenance incurring less than US$500 for almost 2 years of its usage.

232 citations


Journal ArticleDOI
Gang Wang1, Kehu Yang1
TL;DR: A new approach to the localization problem in wireless sensor networks using received-signal-strength (RSS) measurements, which is approximately approached by the maximum likelihood (ML) parameter estimation, which the authors refer to as the weighted least squares (WLS) approach.
Abstract: In this letter, we propose a new approach to the localization problem in wireless sensor networks using received-signal-strength (RSS) measurements. The problem is reformulated under the equivalent exponential transformation of the conventional path loss measurement model and the unscented transformation (UT), and is approximately approached by the maximum likelihood (ML) parameter estimation, which we refer to as the weighted least squares (WLS) approach. This formulation is used for sensor node localization in both noncooperative and cooperative scenarios. Simulation results confirm the effectiveness of the approach for both outdoor and indoor environments.

224 citations


Journal ArticleDOI
TL;DR: A novel prediction-based data collection protocol is proposed, in which a double-queue mechanism is designed to synchronize the prediction data series of the sensor node and the sink node, and therefore, the cumulative error of continuous predictions is reduced.

198 citations


Journal ArticleDOI
TL;DR: The energy correlations between node components are revealed, and the node energy model based on the event-trigger mechanism is established, which can be used to analyze the WSNs energy consumption, to evaluate communication protocols, to deploy nodes and then to construct WSN applications.
Abstract: Energy consumption is the core issue in wireless sensor networks (WSN). To generate a node energy model that can accurately reveal the energy consumption of sensor nodes is an extremely important part of protocol development, system design and performance evaluation in WSNs. In this paper, by studying component energy consumption in different node states and within state transitions, the authors present the energy models of the node core components, including processors, RF modules and sensors. Furthermore, this paper reveals the energy correlations between node components, and then establishes the node energy model based on the event-trigger mechanism. Finally, the authors simulate the energy models of node components and then evaluate the energy consumption of network protocols based on this node energy model. The proposed model can be used to analyze the WSNs energy consumption, to evaluate communication protocols, to deploy nodes and then to construct WSN applications.

189 citations


Journal ArticleDOI
01 May 2011
TL;DR: This paper studies the performance of different medium access control (MAC) schemes based on CSMA and polling techniques for WSNs which are solely powered by ambient energy harvesting using energy harvesters, and designs a probabilistic polling protocol that takes into account the unpredictability of the energy harvesting process to achieve good performance.
Abstract: Energy consumption is a perennial issue in the design of wireless sensor networks (WSNs) which typically rely on portable sources like batteries for power. Recent advances in ambient energy harvesting technology have made it a potential and promising alternative source of energy for powering WSNs. By using energy harvesters with supercapacitors, WSNs are able to operate perpetually until hardware failure and in places where batteries are hard or impossible to replace. In this paper, we study the performance of different medium access control (MAC) schemes based on CSMA and polling techniques for WSNs which are solely powered by ambient energy harvesting using energy harvesters. We base the study on (i) network throughput (S), which is the rate of sensor data received by the sink, (ii) fairness index (F), which determines whether the bandwidth is allocated to each sensor node equally and (iii) inter-arrival time (@c) which measures the average time difference between two packets from a source node. For CSMA, we compare both the slotted and unslotted variants. For polling, we first consider identity polling. Then we design a probabilistic polling protocol that takes into account the unpredictability of the energy harvesting process to achieve good performance. Finally, we present an optimal polling MAC protocol to determine the theoretical maximum performance. We validate the analytical models using extensive simulations incorporating experimental results from the characterization of different types of energy harvesters. The performance results show that probabilistic polling achieves high throughput and fairness as well as low inter-arrival times.

178 citations


Journal ArticleDOI
05 Apr 2011
TL;DR: The proposed mobility-based clustering (MBC) protocol outperforms both the CBR protocol and the LEACH-mobile protocol in terms of average energy consumption and average control overhead, and can better adapt to a highly mobile environment.
Abstract: In this study, the authors propose a mobility-based clustering (MBC) protocol for wireless sensor networks with mobile nodes. In the proposed clustering protocol, a sensor node elects itself as a cluster-head based on its residual energy and mobility. A non-cluster-head node aims at its link stability with a cluster head during clustering according to the estimated connection time. Each non-cluster-head node is allocated a timeslot for data transmission in ascending order in a time division multiple address (TDMA) schedule based on the estimated connection time. In the steady-state phase, a sensor node transmits its sensed data in its timeslot and broadcasts a joint request message to join in a new cluster and avoid more packet loss when it has lost or is going to lose its connection with its cluster head. Simulation results show that the MBC protocol can reduce the packet loss by 25% compared with the cluster-based routing (CBR) protocol and 50% compared with the low-energy adaptive clustering hierarchy-mobile (LEACH-mobile) protocol. Moreover, it outperforms both the CBR protocol and the LEACH-mobile protocol in terms of average energy consumption and average control overhead, and can better adapt to a highly mobile environment.

Journal ArticleDOI
TL;DR: A sensor deployment scheme based on glowworm swarm optimization (GSO) to enhance the coverage after an initial random deployment of the sensors to provide high coverage with limited movement of the sensor nodes.
Abstract: A wireless sensor network is composed of a large number of sensor nodes that are densely deployed in a sensing environment. The effectiveness of the wireless sensor networks depends to a large extent on the coverage provided by the sensor deployment scheme. In this paper, we present a sensor deployment scheme based on glowworm swarm optimization (GSO) to enhance the coverage after an initial random deployment of the sensors. Each sensor node is considered as individual glowworms emitting a luminant substance called luciferin and the intensity of the luciferin is dependent on the distance between the sensor node and its neighboring sensors. A sensor node is attracted towards its neighbors having lower intensity of luciferin and decides to move towards one of them. In this way, the coverage of the sensing field is maximized as the sensor nodes tend to move towards the region having lower sensor density. Simulation results show that our GSO-based sensor deployment approach can provide high coverage with limited movement of the sensor nodes.

Book ChapterDOI
18 Jul 2011
TL;DR: Attraction Forces of Uncovered Points (AFUP), a distributed iterative algorithm and exploits the repel forces exerted by the uncovered points around the sensor nodes, improves the coverage by 18%-25% after the initial deployment.
Abstract: In directional sensor networks (DSNs), motility capability of a directional sensor node has a considerable impact on the coverage enhancement after the initial deployment. Since random deployment may result in overlapped field of views (FoVs) and occluded regions, directional sensor nodes with rotatable mechanisms may reorganize their working directions to improve the coverage. Our proposed algorithm, Attraction Forces of Uncovered Points (AFUP), aims at both minimizing the overlapped areas and facing the working directions towards the area of interest. AFUP is a distributed iterative algorithm and exploits the repel forces exerted by the uncovered points around the sensor nodes. The proposed algorithm improves the coverage by 18%-25% after the initial deployment. Moreover, AFUP outperforms three well-known area coverage enhancement methods [15] [19] [16] in terms of coverage improvement and overlap minimization. Our simulation results show that AFUP converges in five iterations in most of the scenarios.

Journal ArticleDOI
24 Mar 2011-Sensors
TL;DR: Insight is provided into routing protocols designed specifically for large-scale WSNs based on the hierarchical structure and a comparison of each routing protocol is conducted to demonstrate the differences between the protocols.
Abstract: With the advances in micro-electronics, wireless sensor devices have been made much smaller and more integrated, and large-scale wireless sensor networks (WSNs) based the cooperation among the significant amount of nodes have become a hot topic. “Large-scale” means mainly large area or high density of a network. Accordingly the routing protocols must scale well to the network scope extension and node density increases. A sensor node is normally energy-limited and cannot be recharged, and thus its energy consumption has a quite significant effect on the scalability of the protocol. To the best of our knowledge, currently the mainstream methods to solve the energy problem in large-scale WSNs are the hierarchical routing protocols. In a hierarchical routing protocol, all the nodes are divided into several groups with different assignment levels. The nodes within the high level are responsible for data aggregation and management work, and the low level nodes for sensing their surroundings and collecting information. The hierarchical routing protocols are proved to be more energy-efficient than flat ones in which all the nodes play the same role, especially in terms of the data aggregation and the flooding of the control packets. With focus on the hierarchical structure, in this paper we provide an insight into routing protocols designed specifically for large-scale WSNs. According to the different objectives, the protocols are generally classified based on different criteria such as control overhead reduction, energy consumption mitigation and energy balance. In order to gain a comprehensive understanding of each protocol, we highlight their innovative ideas, describe the underlying principles in detail and analyze their advantages and disadvantages. Moreover a comparison of each routing protocol is conducted to demonstrate the differences between the protocols in terms of message complexity, memory requirements, localization, data aggregation, clustering manner and other metrics. Finally some open issues in routing protocol design in large-scale wireless sensor networks and conclusions are proposed.

Journal ArticleDOI
TL;DR: A vehicle detector which includes a magnetic and an optical sensor and is intended as sensor node for use with a WSN, combined with power-efficient event-based software is presented.
Abstract: Vehicle detectors provide essential information about parking occupancy and traffic flow. To cover large areas that lack a suitable electrical infrastructure, wired sensors networks are impractical because of their high deployment and maintenance costs. Wireless sensor networks (WSNs) with autonomous sensor nodes can be more economical. Vehicle detectors intended for a WSN should be small, sturdy, low power, cost-effective, and easy to install and maintain. Currently available vehicle detectors based on inductive loops, ultrasound, infrared, or magnetic sensors do not fulfill the requirements above, which has led to the search for alternative solutions. This paper presents a vehicle detector which includes a magnetic and an optical sensor and is intended as sensor node for use with a WSN. Magnetic sensors based on magnetoresistors are very sensitive and can detect the magnetic anomaly in the Earth's magnetic field that results from the presence of a car, but their continuous operation would drain more than 1.5 mA at 3 V, hence limiting the autonomy of a battery-supplied sensor node. Passive, low-power optical sensors can detect the shadow cast by car that covers them, but are prone to false detections. The use of optical triggering to wake-up a magnetic sensor, combined with power-efficient event-based software, yields a simple, compact, reliable, low-power sensor node for vehicle detection whose quiescent current drain is 5.5 μA. This approach of using a low-power sensor to trigger a second more specific sensor can be applied to other autonomous sensor nodes.

Proceedings ArticleDOI
21 Aug 2011
TL;DR: There are obstacles to sensor mining applications, due to the severe resource limitations faced by mobile devices, and the WISDM (WIireless Sensor Data Mining) smart phone-based sensor mining architecture is proposed.
Abstract: Smart phones comprise a large and rapidly growing market. These devices provide unprecedented opportunities for sensor mining since they include a large variety of sensors, including an: acceleration sensor (accelerometer), location sensor (GPS), direction sensor (compass), audio sensor (microphone), image sensor (camera), proximity sensor, light sensor, and temperature sensor. Combined with the ubiquity and portability of these devices, these sensors provide us with an unprecedented view into people's lives---and an excellent opportunity for data mining. But there are obstacles to sensor mining applications, due to the severe resource limitations (e.g., power, memory, bandwidth) faced by mobile devices. In this paper we discuss these limitations, their impact, and propose a solution based on our WISDM (WIireless Sensor Data Mining) smart phone-based sensor mining architecture.

Journal ArticleDOI
TL;DR: This paper presents the first theoretical framework for WCL performance analysis in terms of its localization error distribution parameterized by node density, node placement, shadowing variance, correlation distance and inaccuracy of sensor node positioning.
Abstract: Information about primary transmitter location is crucial in enabling several key capabilities in cognitive radio networks, including improved spatio-temporal sensing, intelligent location-aware routing, as well as aiding spectrum policy enforcement. Compared to other proposed non-interactive localization algorithms, the weighted centroid localization (WCL) scheme uses only the received signal strength information, which makes it simple to implement and robust to variations in the propagation environment. In this paper we present the first theoretical framework for WCL performance analysis in terms of its localization error distribution parameterized by node density, node placement, shadowing variance, correlation distance and inaccuracy of sensor node positioning. Using this analysis, we quantify the robustness of WCL to various physical conditions and provide design guidelines, such as node placement and spacing, for the practical deployment of WCL. We also propose a power-efficient method for implementing WCL through a distributed cluster-based algorithm, that achieves comparable accuracy with its centralized counterpart.

Proceedings Article
12 Apr 2011
TL;DR: This paper presents and evaluates a method for simultaneously tracking a target while localizing the sensor nodes of a passive device-free tracking system that uses received signal strength measurements taken on the links connecting many nodes in a wireless sensor network.
Abstract: This paper presents and evaluates a method for simultaneously tracking a target while localizing the sensor nodes of a passive device-free tracking system. The system uses received signal strength (RSS) measurements taken on the links connecting many nodes in a wireless sensor network, with nodes deployed such that the links overlap across the region. A target moving through the region attenuates links intersecting or nearby its path. At the same time, RSS measurements provide information about the relative locations of sensor nodes. We utilize the Sequential Monte Carlo (particle filtering) framework for tracking, and we use an online EM algorithm to simultaneously estimate static parameters (including the sensor locations, as well as model parameters including noise variance and attenuation strength of the target). Simultaneous tracking, online calibration and parameter estimation enable rapid deployment of a RSS-based device free localization system, e.g., in emergency response scenarios. Simulation results and experiments with a wireless sensor network testbed illustrate that the proposed tracking method performs well in a variety of settings.

Proceedings ArticleDOI
20 Sep 2011
TL;DR: This paper will focus on security of Wireless Sensor Network, which is composed of large number of tiny sensor nodes, running separately, and in various cases, with none access to renewable energy resources.
Abstract: Wireless sensor networks (WSN) are generally set up for gathering records from insecure environment. Nearly all security protocols for WSN believe that the opponent can achieve entirely control over a sensor node by way of direct physical access. The appearance of sensor networks as one of the main technology in the future has posed various challenges to researchers. Wireless sensor networks are composed of large number of tiny sensor nodes, running separately, and in various cases, with none access to renewable energy resources. In addition, security being fundamental to the acceptance and employ of sensor networks for numerous applications, also different set of challenges in sensor networks are existed. In this paper we will focus on security of Wireless Sensor Network.

Journal ArticleDOI
TL;DR: A survey of wireless video sensor node platforms (WVSNPs) and a novel Flexi-WV SNP design is developed that includes dual-radio communication, a middleware for sensor operation and communication control, as well as a cohesive hardware and software design.
Abstract: The video capture, processing, and communication in wireless video sensor networks critically depend on the resources of the nodes forming the sensor networks. We provide a survey of wireless video sensor node platforms (WVSNPs). From a comprehensive literature review, we first select the node architectures that meet basic requirements for a WVSNP. We then introduce a classification of WVSNPs into general purpose architectures, heavily coupled architectures, and externally dependent architectures. We thoroughly survey and contrast the existing WVSNPs within this classification framework. Based on the insights from our survey we develop a novel Flexi-WVSNP design. The Flexi-WVSNP design includes dual-radio communication, a middleware for sensor operation and communication control, as well as a cohesive hardware and software design.

Journal ArticleDOI
TL;DR: This paper proposes an energy-efficient and high-accuracy (EEHA) scheme for secure data aggregation that is more efficient and accurate than the existing scheme and conducts extensive simulations to evaluate the performance.

Journal ArticleDOI
TL;DR: A ZigBee-based wireless sensor network node for the ultraviolet (UV) detection of flame and the performance of a prototype sensor node was verified when the luminous flame was imaged onto the sensor node with different angles and distances enabling effective fire safety applications.
Abstract: This paper describes a ZigBee-based wireless sensor network node for the ultraviolet (UV) detection of flame. The sensor node is composed of a ZnSSe UV photodetector, a current-sensitive front end including a high-gain current-to-voltage amplifier with 120 dB and a logarithm converter, and a transceiver operated at a 2.4-GHz industrial, scientific, and medical band. A passive photodetector is designed to have a cutoff at 360 nm and convert the UV emission of flame into picoamperes. Including mixed signal processing and ZigBee transmission, the speed of flame detection is as fast as 70 ms. The sensor node consumes only an average of 2.3 mW from a 3.3-V supply. The performance of a prototype sensor node was verified when the luminous flame was imaged onto the sensor node with different angles ranging from -30° to 30° and distances of 0.1, 0.2, and 0.3 m enabling effective fire safety applications.

Journal ArticleDOI
TL;DR: Simulation results show that by using the power-aware localized approach, the proposed L-PEDAPs can almost have the same performance of a centralized solution in terms of network lifetime, and close to 90 percent of an upper bound derived here.
Abstract: We propose localized, self organizing, robust, and energy-efficient data aggregation tree approaches for sensor networks, which we call Localized Power-Efficient Data Aggregation Protocols (L-PEDAPs). They are based on topologies, such as LMST and RNG, that can approximate minimum spanning tree and can be efficiently computed using only position or distance information of one-hop neighbors. The actual routing tree is constructed over these topologies. We also consider different parent selection strategies while constructing a routing tree. We compare each topology and parent selection strategy and conclude that the best among them is the shortest path strategy over LMST structure. Our solution also involves route maintenance procedures that will be executed when a sensor node fails or a new node is added to the network. The proposed solution is also adapted to consider the remaining power levels of nodes in order to increase the network lifetime. Our simulation results show that by using our power-aware localized approach, we can almost have the same performance of a centralized solution in terms of network lifetime, and close to 90 percent of an upper bound derived here.

Journal ArticleDOI
07 Jun 2011-Sensors
TL;DR: A wireless sensor network where each sensor node takes images from the field and internally uses image processing techniques to detect any unusual status in the leaves, which could be caused by a deficiency, pest, disease or other harmful agent.
Abstract: The first step to detect when a vineyard has any type of deficiency, pest or disease is to observe its stems, its grapes and/or its leaves. To place a sensor in each leaf of every vineyard is obviously not feasible in terms of cost and deployment. We should thus look for new methods to detect these symptoms precisely and economically. In this paper, we present a wireless sensor network where each sensor node takes images from the field and internally uses image processing techniques to detect any unusual status in the leaves. This symptom could be caused by a deficiency, pest, disease or other harmful agent. When it is detected, the sensor node sends a message to a sink node through the wireless sensor network in order to notify the problem to the farmer. The wireless sensor uses the IEEE 802.11 a/b/g/n standard, which allows connections from large distances in open air. This paper describes the wireless sensor network design, the wireless sensor deployment, how the node processes the images in order to monitor the vineyard, and the sensor network traffic obtained from a test bed performed in a flat vineyard in Spain. Although the system is not able to distinguish between deficiency, pest, disease or other harmful agents, a symptoms image database and a neuronal network could be added in order learn from the experience and provide an accurate problem diagnosis.

Journal ArticleDOI
TL;DR: The aim of this work is to give a detailed overview and classification of the most relevant preamble sampling MAC protocols, being motivated by the extremely large number of MAC protocols designed for WSNs in recent years.

Proceedings ArticleDOI
23 Mar 2011
TL;DR: A new energy efficient clustering protocol (FZ-LEACH) is proposed and analyzed that eliminates the above problem by forming Far-Zone and outperforms LEACH in terms of energy consumption and network lifetime.
Abstract: As the use of wireless sensor networks (WSNs) has grown enormously in the past few decades, the need of scalable & energy efficient routing and data aggregation protocol for large-scale deployments has also risen. LEACH is a hierarchical clustering protocol that provides an elegant solution for such protocols. One deficiency that affects the performance of the protocol is existence of very large and very small clusters in the network at the same time. This leads to the decrease in lifetime of WSNs. In this paper, we propose and analyze a new energy efficient clustering protocol (FZ-LEACH) that eliminates the above problem by forming Far-Zone. Far-Zone is a group of sensor nodes which are placed at locations where their energies are less than a threshold. The simulation results and analysis show that proposed FZ-LEACH algorithm outperforms LEACH in terms of energy consumption and network lifetime.

Journal ArticleDOI
TL;DR: An adaptive clustering protocol for wireless sensor networks is introduced, which is called Adaptive Decentralized Re-Clustering Protocol (ADRP) for Wireless Sensor Networks, where the cluster heads and next heads are elected based on residual energy of each node and the averageEnergy of each cluster.

Journal ArticleDOI
TL;DR: The development and the characterization of a wireless gas sensor network (WGSN) for the detection of combustible or explosive gases and how to determine the optimal temperature of the sensor's sensitive layer for methane detection, show the response time of the Sensor node to various gases, and evaluate the power consumption.
Abstract: a b s t r a c t This paper describes the development and the characterization of a wireless gas sensor network (WGSN) for the detection of combustible or explosive gases. The WGSN consists of a sensor node, a relay node, a network coordinator, and a wireless actuator. The sensor node attains early gas detection using an on board 2D semiconductor sensor. Because the sensor consumes a substantial amount of power, which negatively affects the node lifetime, we employ a pulse heating profile to achieve significant energy savings. The relay node receives and forwards traffic from sensor nodes towards the network coordinator and vice versa. When an emergency is detected, the network coordinator alarms an operator through the GSM/GPRS or Ethernet network, and may autonomously control the source of gas emission through the wireless actuator. Our experimental results demonstrate how to determine the optimal temperature of the sensor's sensitive layer for methane detection, show the response time of the sensor to various gases, and evaluate the power consumption of the sensor node. The demonstrated WGSN could be used for a wide range of gas monitoring applications.

Journal ArticleDOI
TL;DR: This paper investigates the ECB theory and ECB related mechanisms by surveying the current and state of the art research in this area and a classification of ECB mechanism is given.
Abstract: Wireless sensor networks comprise of a large number of low cost sensor nodes that have strictly restricted sensing, computation and communication capabilities. In addition to this, sensor nodes have limited battery life which is not rechargeable in many applications. Due to resource limitations for the sensor nodes, it is important to use energy efficiently for each sensor node. This will result in prolonged network lifetime and functionality. Energy consumption balancing (ECB) property ensures that the average energy dissipation per sensor is equal for all sensors in the network. ECB can be considered as energy efficiency property that optimally manages energy consumption of sensors to prolong network lifetime. This paper investigates the ECB theory and ECB related mechanisms. A classification of ECB mechanism is given by surveying the current and state of the art research in this area. In addition, comparison and main constraints of the mechanisms are presented. Copyright © 2011 John Wiley & Sons, Ltd. * Correspondence

Proceedings ArticleDOI
10 Oct 2011
TL;DR: I-LEACH (Improved LEACH) is purposed with two important changes, first residual energy is used to select the CH (Cluster Head) instead of probability as used in the LEACH, so that it can be used for the sensor nodes with different initial energy.
Abstract: Wireless sensor networks comprise of minor battery driven devices with restricted energy resources. Once installed, the minor sensor nodes are usually unapproachable to the operator, and thus auxiliary of the energy source is not practicable. Hence, energy proficiency is a vital design issue that needs to be boosted in order to increase the life span of the network. Numerous network layer protocols have been anticipated to increase the operative life span of a network with a restricted energy supply. Here I-LEACH (Improved LEACH) is purposed with two important changes, first residual energy is used to select the CH (Cluster Head) instead of probability as used in the LEACH, so that it can be used for the sensor nodes with different initial energy and other is coordinates are used to form clusters so that their must remain a CH close to every sensor node as there is no certainty in LEACH about the location of CHs. Simulation results display that I-LEACH implement the above discussed improvements effectively and efficiently and improves the network lifespan over LEACH. I-LEACH outperform LEACH with 171 more rounds which estimated around 15% more energy efficient with 1J/Node energy over a network area of a 100m×100 m.