On Maximizing Reliability of Lifetime Constrained Data Aggregation Tree in Wireless Sensor Networks

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.

One ultimate goal of wireless sensor networks is to collect the sensed data from a set of sensors and transmit them to some sink node via a data gathering tree. In this work, we are interested in data aggregation, where the sink node wants to know the value for a certain function of all sensed data, such as minimum, maximum, average, and summation. Given a data aggregation tree, sensors receive messages from children periodically, merge them with its own packet, and send the new packet to its parent. The problem of finding an aggregation tree with the maximum lifetime has been proved to be NP-hard and can be generalized to finding a spanning tree with the minimum maximum vertex load, where the load of a vertex is a nondecreasing function of its degree in the tree. Although there is a rich body of research in those problems, they either fail to meet a theoretical bound or need high running time. In this paper, we develop a novel algorithm with provable performance bounds for the generalized problem. We show that the running time of our algorithm is in the order of O(mnα(m, n)), where m is the number of edges, n is the number of sensors, and α is the inverse Ackerman function. Though our work is motivated by applications in sensor networks, the proposed algorithm is general enough to handle a wide range of degree-oriented spanning tree problems, including bounded degree spanning tree problem and minimum degree spanning tree problem. When applied to these problems, it incurs a lower computational cost in comparison to existing methods. Simulation results validate our theoretical analysis.

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 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.

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.

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.

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.

Data aggregation has been widely applied as efficient techniques in order to reduce the data redundancy and the communication load in Wireless Sensor Networks (WSNs). However, for dynamic scenarios, structured protocols may incur high overhead in the construction and the maintenance of the static structure. Without the explicit downstream and upstream relationship of nodes, it is also difficult to obtain high aggregation efficiency by using structure-free protocols. In order to address these aspects, we propose a semi-structured protocol based on the multi-objective tree. The routing scheme can explore the optimal structure by using the Ant Colony Optimization (ACO). Moreover, by using the prediction model for the arriving packets based on the sliding window, the adaptive timing policy can reduce the transmission delay and enhance the aggregation probability. Therefore, the packet transmission converges from both spatial and temporal points of view for the data aggregation procedure. Finally, simulation results validate the feasibility and the high efficiency of the novel protocol when compared with other existing approaches.

Information delivered through sensor networks is used in industries to increase quality of life (QoL). Lossless data in wireless sensor networks (WSNs) is a communications challenge that stands in the way of accurate data delivery. Although end-to-end data retransmission has evolved as a reliable mode of data transportation for the Internet, it is not applicable to WSNs due to the lack of reliable wireless links and resource constraints in sensor nodes. In this paper, we propose an efficient and reliable overhearing-based data transfer protocol for WSNs by introducing selective “direct acknowledgement (ACKdir)” or “implicit acknowledgement (ACKimp)” in cross-layer design. This protocol assesses the path (or link) quality and delegates the ACK message if it has good communication on paths. In addition, the protocol uses implicit ACK in order to be energy efficient, reducing traffic. Simulation results show that energy efficiency is improved by 30% compared with other approaches.

A wireless sensor network (WSN) is a wireless network consisting of spatially distributed autonomous devices that use sensor nodes to monitor physical or environmental conditions. These distributed autonomous devices, or nodes, combine with routers and a gateway to create a typical WSN system. The distributed sensor nodes communicate wirelessly to a central gateway, which provides a connection to the wired world where you can collect, process, analyze, and present your measurement data. Due to the broadcast nature of the transmission media they use, sensor networks are vulnerable to various security attacks, such as eavesdropping, jamming and node capture attacks. In this paper, we provide a solution for node capture attack. Node capture attacks result from the combination of active, passive and physical attacks by an intelligent adversary. In order to initialize or set up a node capture attack, the adversary will collect information about the WSN by eavesdropping on message exchanges, either local to a single adversarial device or throughout the network with the aid of a number of adversarial devices deployed throughout the network. Hence in order to securely aggregate data in a wireless sensor network, we must not only provide protection against eavesdroppers, but we should also prevent intermediate sensors from having access to the data.

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.

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

This paper considers the problem of jointly constructing and scheduling forwarding trees in a wireless sensor network, each for a group of sensor nodes, to collect measurements at a single sink node. The goal is to construct such trees which gather measurements in the most energy efficient manner and minimal gathering latency. We assume transmissions (carrying measurements) on wireless links interfere with one another, and thus appropriate link scheduling is required to overcome interference. We refer to this problem as Forwarding Tree Construction and Scheduling (FTCS). Each tree may be constructed independently and then its links are scheduled. However, when all trees are combined together, the shortest and energy efficient schedule may not be guaranteed. Further, a large number of possible forwarding trees for each group of sensors may be considered. Both problems of enumerating forwarding trees and scheduling links for those trees are hard combinatorial problems. This is compounded by the fact that the two problems must be solved jointly, to guarantee the selection of best forwarding trees which, when their links are scheduled, guarantee a shortest energy efficient schedule. After highlighting the complexity of the FTCS problem, we present a novel primal-dual decomposition method using column generation. We also highlight several challenges we faced when solving the decomposed problem and present efficient techniques for mitigating those challenges. One major advantage of our work is that it can serve as a benchmark for evaluating the performance of any low complexity method for solving the FTCS problem for larger network instances where no known exact solutions can be found.

Echo-Aided Bat Algorithm is proved a good evolutionary computing to solve continuous problems in previous investigate. In this study, EABA is applied to solve the discrete problem that construct a network topology with spanning tree in wireless sensor networks (WSNs). In this application, the presentation of bat and design of fitness function perhaps affect the evolutionary results. For the demonstration of simulated results, EABA still presents a satisfied performance in some scenarios designed in this study. In addition, the constructed network topology of spanning tree based on global optimum solution found by EABA is used to estimate the network lifetime. Overall, this framework including network topology constructed by EABD and network lifetime estimated by transmission simulation is created in this study to aid the plan for duration of WSN deployment.

Wireless Sensor Networks (WSNs) are being used globally in many areas. As the purpose of the WSN is raising at the similar rate the safety intimidation are also rising. Nodes in a WSN are vulnerable to different attacks mainly due to their unguarded communication and nature of exploitation. Therefore, the most important in such networks is to providing security. A vigorous security solution for the networks must also make possible node confirmation. But occasionally it would be an energy utilizing process. So, we require an energy efficient and safe mechanism to protected the entire network. Thus this paper, Energy Aware efficient Cryptographic Approach (EACA) for securing data in WSN is proposed. In this scheme, the dynamic mode and sleep mode of sensor to save the energy consumption in WSN. The sender side and receiver side algorithm provide the data security. Our simulation results demonstrate that improved the residual energy and throughput in WSN.