Secure and Efficient Hierarchical Data Aggregation in Wireless Sensor Networks

Wireless sensor networks (WSNs) are novel large-scale wireless networks that consist of distributed, self organizing, low-power, low-cost, tiny sensor devices to cooperatively collect information through infrastructure less wireless networks. These networks are envisioned to play a crucial role in variety of applications like critical military surveillance applications, forest fire monitoring, commercial applications such as building security monitoring, traffic surveillance, habitat monitoring and smart homes and many more scenarios. Node capture attack is one of the most dreadful security attack exist in wireless sensor networks. An adversary steals cryptographic key or other confidential information like node’s id etc from a captured node to compromise entire network. So, Security of wireless sensor network is an important issue for maintaining confidentiality and integrity of wireless links. Now-a-days, researchers are paying attention towards developing security schemes against Node capture attack. Our survey provides deep insights of existing techniques that enhance the attacking efficiency of the node capture attack in wireless sensor network. It also analyzes various detection and key predistribution schemes for inventing a new scheme to improve resilience against node capture attack.

Modern data loggers record and store large amounts of data from many different types of sensors. This enables their use in various applications to capture different measurands. However wireless access to the recorded data opens countless possibilities for novel and innovative applications, for example in the health monitoring of humans or livestock. In many of these applications a central device connects simultaneously to several data loggers. This paper discusses the experiences made during the design, implementation and test of an energy efficient wireless interface to a data logger. The implemented system serves as an application example for Bluetooth Smart. It allows a user to monitor ongoing measurements of several data loggers through a smartphone. Additionally the recorded data of several loggers can be simultaneously uploaded to a central gateway. The available Bluetooth Smart chips and software stacks place limitations on usable bandwidth as well as on the number of simultaneous connections. Although most modern smartphones include hardware for Bluetooth Smart, implementations differ widely across platforms, thus creating additional effort for the app programmer. This paper presents measurement results and introduces the implemented approaches to optimize these parameters.

In this paper propose an several concepts for optimal algorithm of aggregation of data in wireless sensor network. Given analysis of problems for information aggregation in wireless sensor network. Proposed optimise of structure the node and given basic concepts for reducing energy consumption. Also proposed network partitioning into piconet with next clustering. In final proposed are two modifications for ant algorithms to optimize data collection in wireless sensor network.

In the networking research community, Wireless Sensor Networks (WSN) has achieved considerable significance in the past years and it can be used in extensive variety of domains. In recent years, the tremendous growth of WSN does not meet all the necessities of environmental monitoring. Wireless Multimedia Sensor Network (WMSN) is required to fulfill the requirements of environment monitoring. In this paper, WMSN is used to monitor the agriculture soil environment. In order to ensure optimal use of the sensor nodes in WMSN and accurate access to the collected data,the routing protocols with both energy efficiency and quality of service ( QoS) properties are necessary for the transmission of photo, video and scalar data.This paper proposes a priority aware energy efficient QoS based data transmission for agriculture soil environment and also detects the pest. It utilizes the available bandwidth and data rate in the best way and in order to be more energy efficient during data transmission.For performance analysis, the proposed system is simulated using Java and the results of the experiments suggest that the proposed algorithm is more efficient compared to other methods in terms of delay and energy consumption.

Data aggregation processes aim to reduce the amount of exchanged data in wireless sensor networks and consequently minimize the packet overhead and optimize energy efficiency. Securing the data aggregation process is a real challenge since the aggregation nodes must access the relayed data to apply the aggregation functions. The data aggregation security problem has been widely addressed in classical homogeneous wireless sensor networks, however, most of the proposed security protocols cannot guarantee a high level of security since the sensor node resources are limited. Heterogeneous wireless sensor networks have recently emerged as a new wireless sensor network category which expands the sensor nodes’ resources and capabilities. These new kinds of WSNs have opened new research opportunities where security represents a most attractive area. Indeed, robust and high security level algorithms can be used to secure the data aggregation at the heterogeneous aggregation nodes which is impossible in classical homogeneous WSNs. Contrary to the homogeneous sensor networks, the data aggregation security problem is still not sufficiently covered and the proposed data aggregation security protocols are numberless. To address this recent research area, this paper describes the data aggregation security problem in heterogeneous wireless sensor networks and surveys a few proposed security protocols. A classification and evaluation of the existing protocols is also introduced based on the adopted data aggregation security approach.

For the purpose of saving the resources of wireless sensor networks, it is necessary to fuse the existing data in wireless sensor networks. When using the current method to fuse data in wireless sensor networks, the fusing time is too long to remove the noise signal in wireless sensor networks effectively. In the process of fusing, data packet loss is easy to occur. There are some problems such as low fusion efficiency, poor denoising performance and high packet loss rate. A multi-path data hierarchical fusion method based on routing algorithm is proposed in this paper. The redundant node decision method based on mesh partitioning is combined with the grid algorithm and EECRS protocol to establish a routing protocol based on redundant node elimination, and the redundant data existing in the redundant nodes of the wireless sensor network is removed. Based on the statistical data of the data, the probability density function is deduced and analyzed, and the noise filtering matrix is constructed to optimize the measurement matrix and remove the noise existing in the wireless sensor network. The multi-path scheduling technology is used to synthesize the pheromone table and the data forwarding flow table, and the ant is used to actively monitor the link QOS real-time information in the path finding process to update the pheromone table and the flow table, and calculate the link idle rate according to the update result. According to the calculation result, the data transmission path is selected, and the multi-path data layer fusion is completed. The experimental results show that the proposed method has high fusion efficiency, good denoising performance and low packet loss rate.

Data aggregation is a promising approach for reducing energy consumption and relaying of redundant data in wireless sensor networks for monitoring applications. However data aggregation implies, on the one hand, an increase in network processing at certain nodes, referred to as aggregators, possibly leading to a higher delivery delay to the sink. On the other hand, the advantages of using aggregation are numerous, especially under the perspective of energy consumption reduction and network lifetime increase. In this paper we provide a closed form expression for the end-to-end delay and network lifetime distributions in a wireless sensor network employing aggregation. These derivations can be used to provide some insights on the expected performance in terms of the metrics above mentioned, when data aggregation is used. For example, if a certain constraint on the maximum tolerable delivery delay is given, ¿*, this can be useful to characterize what is the probability to satisfy this constraint.

Classification of sensory data is a major research problem in wireless sensor networks and it can be widely used in reducing the data transmission in wireless sensor networks effectively and also in process monitoring. In order to examine the huge size of data set in stream model generated by sensor network, it will be analyzed different sensor's output signal, topology of sensors network, number of sensor parameters and number of acquisition data. In our wind energy monitoring, sensor node monitors six attributes: speed, direction, temperature, pressure, humidity, and battery voltage. Every attribute value is set as four measures: average, instantaneous, minimum, and maximum. This paper presents several data mining techniques applied on the wireless sensor network's data considered: Naïve Bayes, k-nearest neighbor, decision trees, IF-THEN rules, and neural networks. Before classification, the data was clustered in order to be labeled. A similarity based algorithm, k-means, was selected in the clustering process for its simplicity and efficiency. A conclusion that decision trees are a suitable method to classify the large amount of data considered is made finally according to the mining result and its reasonable explanation.

In wireless sensor network, the storage amount of information is high, and the transmission and scheduling of control information is reasonable. The node communication model, network structure model, and energy consumption model are constructed. On this basis, the high-density data in wireless sensor network are scheduled to optimize the time for nodes to perform tasks. The nodes in the network are fully scheduled to control the generation time of packets in the network and the generation time of packets in the network. Experimental results show that in different iterations, the proposed method has lower node delay and node energy consumption, with values less than 0.2 and 2, respectively, and the maximum data fusion quality can reach 98, with high fusion benefits, so as to improve the transmission and scheduling efficiency and quality of high-density data in wireless sensor network.

In this study, a system for monitoring the structural health of bridge deck and predicting various possible damages to this section was designed based on measuring the temperature and humidity with the use of wireless sensor networks then it was implemented and investigated. This paper also presents the experimental development of an automatic wireless sensor monitoring system for concrete structures. The objective is to provide a solution to measure both temperature and humidity inside a concrete structure. The research has been focused in the early age and curing phase period. Four solutions have been addressed. The first one involves the use of a negative temperature coefficient thermistor and an IRIS mote allowing for the creation of an IEEE 802.15.4 network. The second one considers the use of the SHT15 sensor, together with the PIC18F4680 microcontroller or the Arduino platform. The third solution involves the use of the SHT21S sensor and the eZ430-RF2500 wireless development tool platform for the MSP430 microcontroller. Finally, the fourth solution considers both the SHT15 and SHT21S sensors completely shielded allowing for the creation of a long-term solution. The potential of applying the proposed inexpensive wireless sensor network approach is completely investigated and verified.

Tree-based routing structures are widely used to gather data in wireless sensor networks. Along with tree structures, in-network aggregation is adopted to reduce transmissions, to save energy and to prolong the network lifetime. Most existing works that focus on the lifetime optimization for data aggregation do not take the link quality into consideration. In this paper, we study the problem of Maximizing Reliability of Lifetime Constrained data aggregation trees (MRLC) in WSNs. Considering the NP-completeness of the MRLC problem, we propose an algorithm, namely Iterative Relaxation Algorithm (IRA), to iteratively relax the optimization program and to find the aggregation tree subject to the lifetime bound with a sub-optimal cost. To adapt to the distributed nature of the WSNs in practice, we further propose a Prufer code based distributed updating protocol. Through extensive simulations, we demonstrate that IRA outperforms the best known related work in term of reliability.

Many routing protocols have been designed and evaluated for Wireless Sensor Networks using simulation tools. Only a few of these proposed works have been tested in real world scenarios. This paper presents a Wireless Sensor Network (WSN) data aggregation & routing protocol that is particularly suited to largely deployed sensor networks. The proposed mechanism combines a gradient based routing scheme with the hierarchical scheme of the LEACH protocol. By combining these two protocols and taking the important factor of node energy into consideration when selecting the cluster heads, a robust strategy for data aggregation and routing is developed. Simulation results show that the proposed protocol improves the wireless sensor network performance in two ways. First, the data aggregation feature reduces 75% data load on the network and second, energy aware clustering and cost aware multi-hop communication increases the lifetime of network as compared to LEACH and EEPSC routing protocols

With the limited resources, it is difficult for wireless sensor network to achieve a long time, continuous, high-speed acquisition of multimedia information and a real-time, reliable transmission of high-volume sampling data. This article proposed the novel data acquisition strategy based on compressed sensing theory, which can perfectly achieve the long time, real-time, reliable transmission of high-volume multimedia data in wireless sensor network. Reasonable experiments were designed to verify the effectiveness of the algorithms, and the experiment results show that: the proposed multimedia signal acquisition strategy is reasonable, practicable, and more suitable for the wireless multimedia sensor networks.

In practical applications, because of some reasons, such as node failure or link failure, data loss is a normal occurrence in wireless sensor networks. For many applications on which data has a great impact, it is important to recover the lost data. Because of the sensory data has spatial correlation and temporal correlation, it is difficult to recover the lost data. Consider this, in this paper, we propose a novel algorithm based on the Markov Random Field to reduce the data error ratio during the data recovery process. In our proposed algorithm, we use the curved face recovery to utilize the spatial correlation in the sensory data, then we explore the temporal correlation between data in wireless sensor networks so that it can improve the accuracy of data recovered. A large amount of experiments show that, compared to other relevant works, the data recovery algorithm we proposed can reduce the error rate of the fitting data, especially data lost seriously in the wireless sensor network.

In this paper, we study two problems of providing reliable data transmission and developing aggregation techniques for correlated data in wireless sensor networks. A system with forward error correction (FEC) can provide an objective reliability while using less transmission power than a system without FEC. Because of the additional parity bits and encoding/decoding energy consumptions, we study the effect of FEC on energy efficiency. We propose to use LDPC codes for FEC. We show that wireless sensor networks using LDPC codes are almost 45% more energy efficient than those that use BCH codes, which were shown to be 15% more energy efficient than the best performing convolutional codes. Then we study the problem of providing aggregation for two and three correlated nodes in wireless sensor networks. We propose to use LDPC codes in wireless sensor networks for source and channel coding to obtain a two-fold energy savings. For two correlated nodes, we study both distributed source coding and joint source-channel coding. While distributed source coding using LDPC codes was studied before, joint source-channel coding using LDPC codes is introduced for the first time. The difference between our work in distributed source coding using LDPC codes and the previous work lies in the LDPC code design procedure. The simulation results show that our proposed design criteria improves the performance of the source coding. The convergence of the non-uniform LDPC code of our design technique is almost 60% closer to the Slepian-Wolf limit. For three correlated nodes, we study distributed source coding using LDPC codes. We simplified the problem of design procedure to randomly punctured LDPC codes. This is a new approach for designing LDPC codes and the simulation results for code of length 1000 shows that the convergence of the LDPC code is achieved at compression rate 0.3174 which is only 0.08 away from the Slepian-Wolf limit.