Showing papers on "Sensor node published in 2013"

Wireless Sensor Network -A Survey

Abstract: Wireless sensor networks are the networks consisting of large number of small and tiny sensor nodes. The nodes are supplied with limited power, memory and other resources and perform in-network processing. In this paper, various issues are discussed that actually put the limitations in the well working and the life time of the network. In Wireless sensor network, nodes should consume less power, memory and so data aggregation should be performed. Security is another aspect which should be present in the network. Quality of service, routing, medium access schemes all are considered in designing the protocols.

A Batteryless 19 $\mu$ W MICS/ISM-Band Energy Harvesting Body Sensor Node SoC for ExG Applications

Abstract: This paper presents an ultra-low power batteryless energy harvesting body sensor node (BSN) SoC fabricated in a commercial 130 nm CMOS technology capable of acquiring, processing, and transmitting electrocardiogram (ECG), electromyogram (EMG), and electroencephalogram (EEG) data. This SoC utilizes recent advances in energy harvesting, dynamic power management, low voltage boost circuits, bio-signal front-ends, subthreshold processing, and RF transmitter circuit topologies. The SoC is designed so the integration and interaction of circuit blocks accomplish an integrated, flexible, and reconfigurable wireless BSN SoC capable of autonomous power management and operation from harvested power, thus prolonging the node lifetime indefinitely. The chip performs ECG heart rate extraction and atrial fibrillation detection while only consuming 19 μW, running solely on harvested energy. This chip is the first wireless BSN powered solely from a thermoelectric harvester and/or RF power and has lower power, lower minimum supply voltage (30 mV), and more complete system integration than previously reported wireless BSN SoCs.

An energy aware fuzzy approach to unequal clustering in wireless sensor networks

Abstract: In order to gather information more efficiently in terms of energy consumption, wireless sensor networks (WSNs) are partitioned into clusters. In clustered WSNs, each sensor node sends its collected data to the head of the cluster that it belongs to. The cluster-heads are responsible for aggregating the collected data and forwarding it to the base station through other cluster-heads in the network. This leads to a situation known as the hot spots problem where cluster-heads that are closer to the base station tend to die earlier because of the heavy traffic they relay. In order to solve this problem, unequal clustering algorithms generate clusters of different sizes. In WSNs that are clustered with unequal clustering, the clusters close to the base station have smaller sizes than clusters far from the base station. In this paper, a fuzzy energy-aware unequal clustering algorithm (EAUCF), that addresses the hot spots problem, is introduced. EAUCF aims to decrease the intra-cluster work of the cluster-heads that are either close to the base station or have low remaining battery power. A fuzzy logic approach is adopted in order to handle uncertainties in cluster-head radius estimation. The proposed algorithm is compared with some popular clustering algorithms in the literature, namely Low Energy Adaptive Clustering Hierarchy, Cluster-Head Election Mechanism using Fuzzy Logic and Energy-Efficient Unequal Clustering. The experiment results show that EAUCF performs better than the other algorithms in terms of first node dies, half of the nodes alive and energy-efficiency metrics in all scenarios. Therefore, EAUCF is a stable and energy-efficient clustering algorithm to be utilized in any WSN application.

A Modular 1 mm $^{3}$ Die-Stacked Sensing Platform With Low Power I $^{2}$ C Inter-Die Communication and Multi-Modal Energy Harvesting

Abstract: A 1.0 mm3 general-purpose sensor node platform with heterogeneous multi-layer structure is proposed. The sensor platform benefits from modularity by allowing the addition/removal of IC layers. A new low power I2C interface is introduced for energy efficient inter-layer communication with compatibility to commercial I2C protocols. A self-adapting power management unit is proposed for efficient battery voltage down conversion for wide range of battery voltages and load current. The power management unit also adapts itself by monitoring energy harvesting conditions and harvesting sources and is capable of harvesting from solar, thermal and microbial fuel cells. An optical wakeup receiver is proposed for sensor node programming and synchronization with 228 pW standby power. The system also includes two processors, timer, temperature sensor, and low-power imager. Standby power of the system is 11 nW.

Practical Secure Communication for Integrating Wireless Sensor Networks Into the Internet of Things

Abstract: If a wireless sensor network (WSN) is integrated into the Internet as a part of the Internet of things (IoT), there will appear new security challenges, such as setup of a secure channel between a sensor node and an Internet host. In this paper, we propose a heterogeneous online and offline signcryption scheme to secure communication between a sensor node and an Internet host. We prove that this scheme is indistinguishable against adaptive chosen ciphertext attacks under the bilinear Diffie-Hellman inversion problem and existential unforgeability against adaptive chosen messages attacks under the q-strong Diffie-Hellman problem in the random oracle model. Our scheme has the following advantages. First, it achieves confidentiality, integrity, authentication, and non-repudiation in a logical single step. Second, it allows a sensor node in an identity-based cryptography to send a message to an Internet host in a public key infrastructure. Third, it splits the signcryption into two phases: i) offline phase; and ii) online phase. In the offline phase, most heavy computations are done without the knowledge of a message. In the online phase, only light computations are done when a message is available. Our scheme is very suitable to provide security solution for integrating WSN into the IoT.

Minimizing charging delay in wireless rechargeable sensor networks

Abstract: As a pioneering experimental platform of wireless rechargeable sensor networks, the Wireless Identification and Sensing Platform (WISP) is an open-source platform that integrates sensing and computation capabilities to the traditional RFID tags. Different from traditional tags, a RFID-based wireless rechargeable sensor node needs to charge its onboard energy storage above a threshold in order to power its sensing, computation and communication components. Consequently, such charging delay imposes a unique design challenge for deploying wireless rechargeable sensor networks. In this paper, we tackle this problem by planning the optimal movement strategy of the RFID reader, such that the time to charge all nodes in the network above their energy threshold is minimized. We first propose an optimal solution using the linear programming method. To further reduce the computational complexity, we then introduce a heuristic solution with a provable approximation ratio of (1 + θ)/(1 - e) by discretizing the charging power on a two-dimensional space. Through extensive evaluations, we demonstrate that our design outperforms the set-cover-based design by an average of 24.7% while the computational complexity is O((N/e)2).

Context-Adaptive Multimodal Wireless Sensor Network for Energy-Efficient Gas Monitoring

Abstract: We present a wireless sensor network (WSN) for monitoring indoor air quality, which is crucial for people's comfort, health, and safety because they spend a large percentage of time in indoor environments A major concern in such networks is energy efficiency because gas sensors are power-hungry, and the sensor node must operate unattended for several years on a battery power supply A system with aggressive energy management at the sensor level, node level, and network level is presented The node is designed with very low sleep current consumption (only 8 μA), and it contains a metal oxide semiconductor gas sensor and a pyroelectric infrared (PIR) sensor Furthermore, the network is multimodal; it exploits information from auxiliary sensors, such as PIR sensors about the presence of people and from the neighbor nodes about gas concentration to modify the behavior of the node and the measuring frequency of the gas concentration In this way, we reduce the nodes' activity and energy requirements, while simultaneously providing a reliable service To evaluate our approach and the benefits of the context-aware adaptive sampling, we simulate an application scenario which demonstrates a significant lifetime extension (several years) compared to the continuously-driven gas sensor In March 2012, we deployed the WSN with 36 nodes in a four-story building and by now the performance has confirmed models and expectations

A wireless sensing platform utilizing ambient RF energy

Abstract: An ambient RF energy harvesting sensor node with onboard sensing and communication functionality was developed and tested. The minimal RF input power required for sensor node operation was -18 dBm (15.8 μW). Using a 6 dBi receive antenna, the most sensitive RF harvester was shown to operate at a distance of 10.4 km from a 1 MW UHF television broadcast transmitter, and over 200 m from a cellular base transceiver station. A complete ambient RF-powered prototype was constructed which measured temperature and light level and wirelessly transmitted these measurements.

Compressive sensing based multi-user detection for machine-to-machine communication

Abstract: With the expected growth of machine-to-machine communication, new requirements for future communication systems have to be considered. More specifically, the sporadic nature of machine-to-machine communication, low data rates, small packets and a large number of nodes necessitate low overhead communication schemes that do not require extended control signaling for resource allocation and management. Assuming a star topology with a central aggregation node that processes all sensor information, one possibility to reduce control signaling is the estimation of sensor node activity. In this paper, we discuss the application of greedy algorithms from the field of compressive sensing in a channel coded code division multiple access context to facilitate a joint detection of sensor node activity and transmitted data. To this end, a short introduction to compressive sensing theory and algorithms will be given. The main focus, however, will be on implications of this new approach. Especially, we consider the activity detection, which strongly determines the performance of the overall system. We show that the performance on a system level is dominated by the missed detection rate in comparison with the false alarm rate. Furthermore, we will discuss the incorporation of activity-aware channel coding into this setup to extend the physical layer detection capabilities to code-aided joint detection of data and activity. Copyright © 2013 John Wiley & Sons, Ltd.

Localization Techniques in Wireless Sensor Networks

Abstract: The important function of a sensor network is to collect and forward data to destination. It is very important to know about the location of collected data. This kind of information can be obtained using localization technique in wireless sensor networks (WSNs). Localization is a way to determine the location of sensor nodes. Localization of sensor nodes is an interesting research area, and many works have been done so far. It is highly desirable to design low-cost, scalable, and efficient localization mechanisms for WSNs. In this paper, we discuss sensor node architecture and its applications, different localization techniques, and few possible future research directions.

On Energy Efficiency in Collaborative Target Tracking in Wireless Sensor Network: A Review

Abstract: Energy-efficiency in target tracking applications has been extensively studied in the literature of Wireless Sensor Networks (WSN). However, there is little work which has been done to survey and summarize this effort. In this paper, we address the lack of these studies by giving an up-to-date State-of-the-Art of the most important energy-efficient target tracking schemes. We propose a novel classification of schemes that are based on the interaction between the communication subsystem and the sensing subsystem on a single sensor node. We are interested in collaborative target tracking instead of single-node tracking. In fact, WSNs are often of a dense nature, and redundant data that can be received from multiple sensors help at improving tracking accuracy and reducing energy consumption by using limited sensing and communication ranges. We show that energy-efficiency in a collaborative WSN-based target tracking scheme can be achieved via two classes of methods: sensing-related methods and communication-related methods. We illustrate both of them with several examples. We show also that these two classes can be related to each other via a prediction algorithm to optimize communication and sensing operations. By self-organizing the WSN in trees and/or clusters, and selecting for activation the most appropriate nodes that handle the tracking task, the tracking algorithm can reduce the energy consumption at the communication and the sensing layers. Thereby, network parameters (sampling rate, wakeup period, cluster size, tree depth, etc.) are adapted to the dynamic of the target (position, velocity, direction, etc.). In addition to this general classification, we discuss also a special classification of some protocols that put specific assumptions on the target nature and/or use a "non-standard" hardware to do sensing. At the end, we conduct a theoretic comparison between all these schemes in terms of objectives and mechanisms. Finally, we give some recommendations that help at designing a WSN-based energy efficient target tracking scheme.

Harnessing Interference for Analog Function Computation in Wireless Sensor Networks

Abstract: It is known that if the objective of a wireless sensor network is not to reconstruct individual sensor readings at a fusion center but rather to compute a linear function of them, then the interference property of the wireless channel can be beneficially harnessed by letting nodes transmit simultaneously. Recently, an analog computation scheme was proposed to show that it is possible to take the advantage of the interference property even if nonlinear functions are to be computed. The scheme involves some pre-processing on the sensor readings and post-processing on the superimposed signals observed by the fusion center. Correspondingly, this paper provides a thorough base for a theory of analog-computing functions over wireless channels by specifying what is the maximum achievable. This means it is determined for networks of arbitrary topology which functions are generally analog-computable over the channel and how many wireless resources are needed. It turns out that the considerations are closely related to the famous 13th Hilbert problem and that analog-computations can be universally performed in the sense that the pre-processing at sensor nodes is independent of the function to be computed. Universality reduces the complexity of transmitters and the signaling overhead, and it is shown that this property is preserved if nodes leave or join the network. Analog-computability is therefore of high practical relevance as it allows for an efficient computation of functions in sensor networks.

Mobile data gathering with Wireless Energy Replenishment in rechargeable sensor networks

Abstract: The emerging wireless energy transfer technology enables charging sensor batteries in a wireless sensor network (WSN) and maintaining perpetual operation of the network. Recent breakthrough in this area has opened up a new dimension to the design of sensor network protocols. In the meanwhile, mobile data gathering has been considered as an efficient alternative to data relaying in WSNs. However, time variation of recharging rates in wireless rechargeable sensor networks imposes a great challenge in obtaining an optimal data gathering strategy. In this paper, we propose a framework of joint Wireless Energy Replenishment and anchor-point based Mobile Data Gathering (WerMDG) in WSNs by considering various sources of energy consumption and time-varying nature of energy replenishment. To that end, we first determine the anchor point selection and the sequence to visit the anchor points. We then formulate the WerMDG problem into a network utility maximization problem which is constrained by flow conversation, energy balance, link and battery capacity and the bounded sojourn time of the mobile collector. Furthermore, we present a distributed algorithm composed of cross-layer data control, scheduling and routing subalgorithms for each sensor node, and sojourn time allocation subalgorithm for the mobile collector at different anchor points. Finally, we give extensive numerical results to verify the convergence of the proposed algorithm and the impact of utility weight on network performance.

Energy-Aware Sensor Node Design With Its Application in Wireless Sensor Networks

Abstract: Energy consumption remains as a major obstacle for full deployment and exploitation of wireless sensor network (WSN) technology nowadays. This paper presents the design and implementation of an energy-aware sensor node, which can help in constructing energy-efficient WSNs. An energy-efficient strategy, which aims at minimizing energy consumption from both the sensor node level and the network level in a WSN, is proposed. To minimize the communication energy consumption of the sensor node, the distance between the transmitter and the receiver is estimated before available transmission, and then, the lowest transmission power needed to transmit the measurement data is calculated and determined. The sensor nodes are also set to sleep mode between two consecutive measurements for energy saving in normal operating conditions. Furthermore, energy saving can be achieved by estimating the energy consumption within the whole network under different network configurations and then by choosing the most energy-efficient one.

Distributed Sensor Fusion for Scalar Field Mapping Using Mobile Sensor Networks

Abstract: In this paper, autonomous mobile sensor networks are deployed to measure a scalar field and build its map. We develop a novel method for multiple mobile sensor nodes to build this map using noisy sensor measurements. Our method consists of two parts. First, we develop a distributed sensor fusion algorithm by integrating two different distributed consensus filters to achieve cooperative sensing among sensor nodes. This fusion algorithm has two phases. In the first phase, the weighted average consensus filter is developed, which allows each sensor node to find an estimate of the value of the scalar field at each time step. In the second phase, the average consensus filter is used to allow each sensor node to find a confidence of the estimate at each time step. The final estimate of the value of the scalar field is iteratively updated during the movement of the mobile sensors via weighted average. Second, we develop the distributed flocking-control algorithm to drive the mobile sensors to form a network and track the virtual leader moving along the field when only a small subset of the mobile sensors know the information of the leader. Experimental results are provided to demonstrate our proposed algorithms.

SoNIC: classifying interference in 802.15.4 sensor networks

Abstract: Sensor networks that operate in the unlicensed 2.4~GHz frequency band suffer cross-technology radio interference from a variety of devices, e.g., Bluetooth headsets, laptops using WiFi, or microwave ovens. Such interference has been shown to significantly degrade network performance. We present SoNIC, a system that enables resource-limited sensor nodes to detect the type of interference they are exposed to and select an appropriate mitigation strategy. The key insight underlying SoNIC is that different interferers disrupt individual 802.15.4 packets in characteristic ways that can be detected by sensor nodes. In contrast to existing approaches to interference detection, SoNIC does not rely on active spectrum sampling or additional hardware, making it lightweight and energy-efficient.In an office environment with multiple interferers, a sensor node running SoNIC correctly detects the predominant interferer 87% of the time. To show how sensor networks can benefit from SoNIC, we add it to a mobile sink application to improve the application's packet reception ratio under interference.

Path Planning Algorithm for Mobile Anchor-Based Localization in Wireless Sensor Networks

Abstract: Localization is an essential issue in wireless sensor networks because many applications require the sensor nodes to know their locations with a high degree of precision. Various localization methods based on mobile anchor nodes have been proposed for assisting the sensor nodes to determine their locations. However, none of these methods attempt to optimize the trajectory of the mobile anchor node. Accordingly, this paper presents a path planning scheme, which ensures that the trajectory of the mobile anchor node minimizes the localization error and guarantees that all of the sensor nodes can determine their locations. The obstacle-resistant trajectory is also proposed to handle the obstacles in the sensing field. The performance of the proposed scheme is evaluated through a series of simulations with the ns-2 network simulator. The results show that the proposed path planning algorithm yields both a lower localization error and a higher percentage of localized sensor nodes than existing path planning schemes.

Mobi-Sync: Efficient Time Synchronization for Mobile Underwater Sensor Networks

Abstract: Time synchronization is an important requirement for many services provided by distributed networks. A lot of time synchronization protocols have been proposed for terrestrial Wireless Sensor Networks (WSNs). However, none of them can be directly applied to Underwater Sensor Networks (UWSNs). A synchronization algorithm for UWSNs must consider additional factors such as long propagation delays from the use of acoustic communication and sensor node mobility. These unique challenges make the accuracy of synchronization procedures for UWSNs even more critical. Time synchronization solutions specifically designed for UWSNs are needed to satisfy these new requirements. This paper proposes Mobi-Sync, a novel time synchronization scheme for mobile underwater sensor networks. Mobi-Sync distinguishes itself from previous approaches for terrestrial WSN by considering spatial correlation among the mobility patterns of neighboring UWSNs nodes. This enables Mobi-Sync to accurately estimate the long dynamic propagation delays. Simulation results show that Mobi-Sync outperforms existing schemes in both accuracy and energy efficiency.

Comparative study of trust and reputation systems for wireless sensor networks

Abstract: Wireless sensor networks (WSNs) are emerging as useful technology for information extraction from the surrounding environment by using numerous small-sized sensor nodes that are mostly deployed in sensitive, unattended, and (sometimes) hostile territories. Traditional cryptographic approaches are widely used to provide security in WSN. However, because of unattended and insecure deployment, a sensor node may be physically captured by an adversary who may acquire the underlying secret keys, or a subset thereof, to access the critical data and/or other nodes present in the network. Moreover, a node may not properly operate because of insufficient resources or problems in the network link. In recent years, the basic ideas of trust and reputation have been applied to WSNs to monitor the changing behaviors of nodes in a network. Several trust and reputation monitoring (TRM) systems have been proposed, to integrate the concepts of trust in networks as an additional security measure, and various surveys are conducted on the aforementioned system. However, the existing surveys lack a comprehensive discussion on trust application specific to the WSNs. This survey attempts to provide a thorough understanding of trust and reputation as well as their applications in the context of WSNs. The survey discusses the components required to build a TRM and the trust computation phases explained with a study of various security attacks. The study investigates the recent advances in TRMs and includes a concise comparison of various TRMs. Finally, a discussion on open issues and challenges in the implementation of trust-based systems is also presented. Copyright © 2012 John Wiley & Sons, Ltd.

Underwater Sensor Nodes and Networks

Abstract: Sensor technology has matured enough to be used in any type of environment. The appearance of new physical sensors has increased the range of environmental parameters for gathering data. Because of the huge amount of unexploited resources in the ocean environment, there is a need of new research in the field of sensors and sensor networks. This special issue is focused on collecting recent advances on underwater sensors and underwater sensor networks in order to measure, monitor, surveillance of and control of underwater environments. On the one hand, from the sensor node perspective, we will see works related with the deployment of physical sensors, development of sensor nodes and transceivers for sensor nodes, sensor measurement analysis and several issues such as layer 1 and 2 protocols for underwater communication and sensor localization and positioning systems. On the other hand, from the sensor network perspective, we will see several architectures and protocols for underwater environments and analysis concerning sensor network measurements. Both sides will provide us a complete view of last scientific advances in this research field.

Wireless Sensor Networks: Principles, Design and Applications

Abstract: Wireless Sensor Networks presents the latest practical solutions to the design issues presented in wireless-sensor-network-based systems. Novel features of the text, distributed throughout, include workable solutions, demonstration systems and case studies of the design and application of wireless sensor networks (WSNs) based on the first-hand research and development experience of the author, and the chapters on real applications: building fire safety protection; smart home automation; and logistics resource management. Case studies and applications illustrate the practical perspectives of: sensor node design; embedded software design; routing algorithms; sink node positioning; co-existence with other wireless systems; data fusion; security; indoor location tracking; integrating with radio-frequency identification; and Internet of thingsWireless Sensor Networks brings together multiple strands of research in the design of WSNs, mainly from software engineering, electronic engineering, and wireless communication perspectives, into an over-arching examination of the subject, benefiting students, field engineers, system developers and IT professionals. The contents have been well used as the teaching material of a course taught at postgraduate level in several universities making it suitable as an advanced text book and a reference book for final-year undergraduate and postgraduate students.

Energy Efficient Image Transmission in Wireless Multimedia Sensor Networks

Abstract: The key obstacle to communicating images over wireless sensor networks has been the lack of suitable processing architecture and communication strategies to deal with the large volume of data. High packet error rates and the need for retransmission make it inefficient in terms of energy and bandwidth. This paper presents novel architecture and protocol for energy efficient image processing and communication over wireless sensor networks. Practical results show the effectiveness of these approaches to make image communication over wireless sensor networks feasible, reliable and efficient.

Distributed Sampling Rate Control for Rechargeable Sensor Nodes with Limited Battery Capacity

Abstract: Energy harvesting is a promising technology for extending the lifetime of battery-powered sensor networks. Due to time variations of harvested energy, one of the main challenging issues is to maximize the uninterrupted sampling rates of all sensor nodes, which represents the network performance. Most of existing works do not consider the limited capacity of rechargeable battery. In this paper, we are concerned with how to adaptively decide the sampling rate for each rechargeable sensor node with a limited battery capacity to maximize the overall network performance. To solve this problem, we firstly propose an adaptive Energy Allocation sCHeme (EACH) for each sensor node to manage its energy use in an efficient way. Then we develop a Distributed Sampling Rate Control (DSRC) algorithm to obtain the optimal sampling rate. Furthermore, an Improved adaptive Energy Allocation sCHeme (IEACH) is proposed to reduce the impact due to imprecise estimation of harvested energy. Extensive simulations using real experimental data obtained from Baseline Measurement System (BMS) of Solar Radiation Research Laboratory are conducted to demonstrate the efficiency of the proposed algorithms.

Mobile Relay Configuration in Data-Intensive Wireless Sensor Networks

Abstract: Wireless Sensor Networks (WSNs) are increasingly used in data-intensive applications such as microclimate monitoring, precision agriculture, and audio/video surveillance. A key challenge faced by data-intensive WSNs is to transmit all the data generated within an application's lifetime to the base station despite the fact that sensor nodes have limited power supplies. We propose using low-cost disposable mobile relays to reduce the energy consumption of data-intensive WSNs. Our approach differs from previous work in two main aspects. First, it does not require complex motion planning of mobile nodes, so it can be implemented on a number of low-cost mobile sensor platforms. Second, we integrate the energy consumption due to both mobility and wireless transmissions into a holistic optimization framework. Our framework consists of three main algorithms. The first algorithm computes an optimal routing tree assuming no nodes can move. The second algorithm improves the topology of the routing tree by greedily adding new nodes exploiting mobility of the newly added nodes. The third algorithm improves the routing tree by relocating its nodes without changing its topology. This iterative algorithm converges on the optimal position for each node given the constraint that the routing tree topology does not change. We present efficient distributed implementations for each algorithm that require only limited, localized synchronization. Because we do not necessarily compute an optimal topology, our final routing tree is not necessarily optimal. However, our simulation results show that our algorithms significantly outperform the best existing solutions.

Compressed sensing techniques for detecting damage in structures

Abstract: One of the principal challenges facing the structural health monitoring community is taking large, heterogeneous sets of data collected from sensors, and extracting information that allows the estimation of the damage condition of a structure Another important challenge is to collect relevant data from a structure in a manner that is cost-effective, and respects the size, weight, cost, energy consumption and bandwidth limitations placed on the system In this work, we established the suitability of compressed sensing to address both challenges A digital version of a compressed sensor is implemented on-board a microcontroller similar to those used in embedded SHM sensor nodes The sensor node is tested in a surrogate SHM application using acceleration measurements Currently, the prototype compressed sensor is capable of collecting compressed coefficients from measurements and sending them to an off-board processor for signal reconstruction using l1 norm minimization A compressed version of the matched

A Delay-Aware Network Structure for Wireless Sensor Networks With In-Network Data Fusion

Abstract: A wireless sensor network (WSN) comprises a large number of wireless sensor nodes. Wireless sensor nodes are battery-powered devices with limited processing and transmission power. Therefore, energy consumption is a critical issue in system designs of WSNs. In-network data fusion and clustering have been shown to be effective techniques in reducing energy consumption in WSNs. However, clustering can introduce bottlenecks to a network, which causes extra delays in a data aggregation process. The problem will be more severe when in-network data fusion does not yield any size reduction in outgoing data. Such problems can be greatly alleviated by modifying the network structure. In this paper, a delay-aware network structure for WSNs with in-network data fusion is proposed. The proposed structure organizes sensor nodes into clusters of different sizes so that each cluster can communicate with the fusion center in an interleaved manner. An optimization process is proposed to optimize intra-cluster communication distance. Simulation results show that, when compared with other existing aggregation structures, the proposed network structure can reduce delays in data aggregation processes and keep the total energy consumption at low levels provided that data are only partially fusible.