In wireless sensor network applications, an event is observed by a group of spatially distributed sensors which collaborate to make decisions. Pervasive computing 1 data compression techniques in wireless sensor networks youchiun wang abstract wireless sensor networks wsns open a new research. An adaptive lossless data compression scheme for wireless. Data compression techniques in wireless sensor networks. Many wsn applications aim at longterm environmental monitoring. Lifetime maximization in wireless sensor networks based on. On the implementation of compressive sensing on wireless. Thus, any data compression scheme proposed for wsns must be lightweight. The experimental validation reveals that the proposed algorithm outperforms several existing wsn data compression methods in terms of compression efficiency and signal reconstruction. Data compression seeks to reduce the number of bits used to store or transmit information.
A data compression method is proposed to limit the amount of data transmitted within the network. As radio communications is the main source of energy consumption, reducing transmission overhead would be extended the sensor node lifetime. Data compression is used to reduce the amount of information or data transmitted by source nodes. The plain data collection is a method where each sensor node sends its measurement to a base node at which data. Research article robust data compression for irregular. Robust data compression model for linear signal data in the wireless sensor networks sukhcharn sandhu gurukul vidyapeeth mr. Among those proposed techniques, the data compression scheme is one that can be used to reduce transmitted data over wireless channels. Compression at cluster heads, gateways, or even within a sensor node with multiple sensing units, is one key ingredient in prolonging network lifetime. Ratedistortion balanced data compression for wireless. In this paper, we propose preprocessing techniques for highefficiency data compression in wireless multimedia sensor networks. Data compression techniques for wireless sensor network.
Wireless sensor networks wsns open a new research field for pervasive computing and contextaware monitoring of the physical environments. Compression is useful because it helps us to reduce the resources use, such as data. This paper considers the data gathering problem in a largescale wireless sensor network. Gailly, the data compression book, mis press, 1996. Data compression in sensor networks umd department of. Recent compressive sensing solutions proposed in wireless sensor networks have proven advantages in minimizing the number of measurements, but they are still not competitive with the existing data compression techniques 3. Topology maintenance is one of the most important issues researched to reduce. The second part deals with efficient data gathering and lossy compression techniques in wireless sensor networks.
It includes the encoding information at data generating nodes and decoding it at sink node. Since the communication unit on a wireless sensor node is the major power consumer, data compression is one of possible techniques that can help reduce the. Ratedistortion balanced data compression for wireless sensor networks abstract. Pervasive computing 1 data compression techniques in wireless sensor networks youchiun wang abstractwireless sensor networks wsns open a. Compression techniques for wireless sensor networks. Data compression and dimensionality reduction in wireless sensor networks wsns refer to the problem of encoding the data collected from sensor nodes using fewer bits. Wireless sensor networks possess significant limitations in storage, bandwidth, and power. Continuousmonitoring cm of natural phenomenon is one of the major streams of applications in wireless sensor networks wsns, where aggregation and clustering techniques are beneficial as correlation dominates in both spatial and temporal aspects of sensed phenomenon. A data compression application for wireless sensor. With recent growing interest in this field, several new techniques. In these largescale sensing networks, data compression is required for encoding the data collected. Alish preethi1, anjali ramakrishnan2 1department of electronics and communication, sathyabama university, india 2department of electronics and communication, sathyabama university, india abstract. Pdf the advancement in the wireless technologies and digital integrated circuits led to the development of wireless sensor networks wsn. Practical data compression in wireless sensor networks.
Robust data compression model for linear signal data in. The sensor nodes in wireless sensor network sense the physical environment and the sensed information is transferred to the destination. It also helps to cut communication cost and computation cost. Finally, the third part addresses csdriven designs for spectrum sensing and multiuser detection for cognitive and wireless communications. Although existing data compression techniques for wireless sensor networks have been surveyed in the literature such as kimura and latifi 2005, the survey was not uptodate and contained algorithms that were not practical in wsns. Optimization techniques for wireless sensor networks. On the implementation of compressive sensing on wireless sensor network dongyu cao, kai yu, shuguo zhuo, yuhen hu, fellow, ieee, and zhi wang, member, ieee abstractcompressive sensing cs is applied to enable real time data transmission in a wireless sensor network by signif. We study the problem of data gathering in wireless sensor networks and compare several approaches belonging to different research fields. A comparison of these data compression techniques is also given in this chapter.
We designed an algorithm that reduces the amount of data traffic. Compression techniques for wireless sensor networks springerlink. Lastly, data packets are created for transmission over the wireless sensor network. Data compression for inf erence t asks in wireless sensor networks by mo chen chair. Additionally, realtime sensor networks cannot tolerate high latency. Moreover, an energy analysis shows that compressing the data can reduce the. Data compression is a useful method to reduce the communication energy consumption in wireless sensor networks wsns. Technique for wireless sensor networks compression techniques are predominately used to increase the energy efficiency and the life time of sensors. We study the various optimization techniques of wireless sensor networks in various aspects and focus on meeting the requirements for efficiently utilizing network resources with qos mechanisms. It is expected that the numberof sensor nodes deployed could be on the order of hundreds or thousands.
Lifetime maximization in wireless sensor networks based on using data compression safa khudair leabi dept. Compressed sensing with applications in wireless networks. As a result, it may not be feasible to run sophisticated data compression algorithms on them. Wang, data compression techniques in wireless sensor networks, pervasive comput. In this paper, we propose and evaluate rida, a novel information. Compressive data gathering for largescale wireless sensor.
Wireless sensor networks data compression energy efficiency bit rate. While some good compression algorithms exist specific to sensor networks, there remains a need for methods that do not introduce additional latency. This has spurred a need for designing techniques tailored specifically toward object tracking sensor network environments to allow optimized tradeoff between the energy. This technique leads to a reduction in the required. The common encoders are huffman encoder, arithmetic encoder and simple runlength encoder. Data compression technique for wireless sensor networks. Data compression methods for wireless sensor networks. Pervasive computing 1 data compression techniques in.
Pdf data compression techniques in wireless sensor networks. Coalition formation based compressive sensing in wireless. Ieee 8th international conference on intelligent sensors, sensor networks and information processing, 20, pp. In this chapter, we discuss the data compression techniques in wsns, which can be classified. Conversely, in event driven reporting edr, the efficient transmission of sensitive data related to some predefined alarm. A survey on data compression techniques in wireless sensor network a. Realtime data compression in wireless sensor networks. In wireless sensor network applications, an event is observed by a group of spatially. The data collection in wireless sensor networks is carried out by three methods is the plain data collection, network data aggregation and network compression. In this paper, a survey is done on various data compression techniques in wireless sensor network. For instance, data compression might reduce the amount of energy used for radio transmission, but.
However, wireless sensor networks possess significant limitations in communication, processing, storage, bandwidth, and power. In dictionarybased compression, the compressor maintains a dictionary of encountered data and substitutes a reference to a dictionary location if the new data is already in the dictionary. A survey of data compression techniques in sensor network. Abstract a basic tenet of wireless sensor networks is that processing of data is less expensive in terms of power than transmitting data. Since there is limited bandwidth in wireless sensor networks, it is important to reduce data bits communicated among sensor nodes to. The objective of the proposed work is to minimize the total number of bits required to be transmitted from the sensor node to reduce the energy consumed by the sensor node. There are many data compression algorithm which are applicable for wireless sensor networks 6.
Most existing neural network compression methods focus on improving the compression and reconstruction accuracy i. Library of congress cataloginginpublication data akyildiz, ian fuat. A survey on data compression techniques in wireless sensor. Request pdf data compression techniques in wireless sensor networks wireless sensor networks wsns open a new research field for pervasive computing and contextaware monitoring of the. In this research, we used a combination of huffman encoding and variable length encoding. Fowler in order for wireless sensor networks to exploit signal, signal data must be collected at a multitude of sensors and must be shared among the sensors. Request pdf data compression techniques in wireless sensor networks wireless sensor networks wsns open a new research field for pervasive. In this paper, we present an adaptive lossless data compression aldc algorithm for wireless sensor networks. Mouftah, a data mining approach to energy efficiency in wireless sensor networks, ieee 24thinternational symposium on personal, indoor and mobile radio communications. Youchiun wang, data compression techniques in wireless sensor networks, pervasive computing. Highlighted methods are extended for sensor networks. The proposed techniques consider the characteristics of sensed multimedia data to perform the first stage preprocessing by deleting the low priority bits that do not affect the image quality. This paper introduces a methodology for comparing data compression algorithms in sensor networks based on the. Second, the communication in wireless sensor networks is typically done in a broadcast manner when a node transmits a message, all nodes within the radio range can receive the message.
The experimental validation reveals that our approach outperforms several existing wireless sensor network s data compression methods in terms of compression e ciency and signal reconstruction. Since transmission cost is the dominant energy consumption. Compressing moving object trajectory in wireless sensor. Department of computer engineering, king fahd university of petroleum and minerals, dhahran, saudi arabia. Energy conservation is a critical issue in wireless sensor networks since sensor nodes are powered by battery. We then present a new data compression scheme, called espiht, that. A simple algorithm for data compression in wireless sensor. Different data collection techniques are formulated, among which the compressive sensing technique plays a vital role.
Survey on compressive data collection techniques for. A simple algorithm for data compression in wireless sensor networks. Data gathering techniques for wireless sensor networks. Sequential coded data compression techniques for wireless. Aziz, an energy efficient image compression scheme for wireless sensor networks, in. When we return to the literature 2, we can distinguish between several data compression techniques used in particular around wireless sensor networks.
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