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distributed sensor networks - a review of recent research

JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS 2001年第6期338卷 655-668页

作者： Qi, HR Iyengar, SS Chakrabarty, K Univ Tennessee Dept Elect & Comp Engn Knoxville TN 37996 USA Louisiana State Univ Dept Comp Sci Baton Rouge LA 70803 USA Duke Univ Dept Elect & Comp Engn Durham NC 27708 USA

Advances in sensor technology and computer networks have enabled distributed sensor networks (DSNs) to evolve from small clusters of large sensors to large swarms of microsensors, from fixed sensor nodes to mobile nodes, from wired communications to wireless communications, from static network topology to dynamically changing topology. However, these technological advances have also brought new challenges to processing large amount of data in a bandwidth-limited, power-constraint, unstable and dynamic environment. This paper reviews recent developments in DSNs from four aspects: network structure, data processing paradigm, sensor fusion algorithm with emphasis on fault-tolerant algorithm design, and optimal sensor deployment strategy. (C) 2001 The Franklin Institute. Published by Elsevier Science Ltd. All rights reserved.

关键词： distributed sensor networks data processing paradigm sensor fusion fault tolerant algorithm

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distributed sensor networks based on mobile agents paradigm

Distributed sensor networks based on mobile agents paradigm

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37th Southeastern Symposium on System Theory (SSST05)

作者： Ketel, M Dogan, NS Homaifar, A N Carolina Agr & Tech State Univ Dept Comp Sci Greensboro NC 27411 USA

ISBN: (纸本)0780388089

distributed sensor networks (DSNs) are being developed for a wide range of applications. A sensor networks consist of a large number of nodes performing distributed sensing/event detection. sensor nodes are energy-constrained, efficient routing is essential for increasing the lifetime of a sensor network A DSN requires interoperability, low latency, and low power consumption in order to operate for long periods of time. Due to power constraints, DSN should be able to operate at low data rates and still delivering acceptable quality of service. In a DSN the energy required for communications tasks is usually much greater than the energy required for computational tasks. To reduce the data communication between nodes and to maximize the network lifetime, we propose to use the mobile-agent paradigm. In mobile-agent based DSN, instead of moving data front an individual sensor node to a processing center as in the client-server based computing, mobile agents are dispatched from the processing center to the sensor nodes and process data locally. By moving code to the data, a mobile agent can reduce latency, bandwidth and vulnerability to network disconnection.

关键词： distributed sensor networks mobile-agents performance

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Secure and practical key establishment for distributed sensor networks

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SECURITY AND COMMUNICATION networks 2009年第6期2卷 595-610页

作者： Kotzanikolaou, Panayiotis Magkos, Emmanouil Vergados, Dimitrios Stefanidakis, Michalis Univ Piraeus Dept Informat Piraeus 18534 Greece Ionian Univ Dept Informat Corfu 49100 Greece

Key establishment in sensor networks is a challenging task, due to the physical constraints of sensor devices and their exposure to several threats. Existing protocols based on symmetric cryptography are very efficient but they are weak against several node impersonation and insider attacks. On the other hand, asymmetric protocols are resilient to such attacks but unfortunately, they are not feasible for sensor networks, even in their most efficient versions (e.g. the elliptic curve (EC) Diffie-Hellman family of key agreement protocols). In this paper, we present two pairwise key establishment protocols for sensor nodes in unattended distributed sensor networks (DSNs). The first protocol is hybrid and it combines asymmetric (elliptic curve (EC)) cryptography with symmetric key techniques. The second protocol is fully asymmetric. Furthermore, through simulations, we measure the efficiency of the proposed protocols in comparison with existing hybrid protocols. Our results show that under conditions, it is feasible for highly sensitive applications of static sensor networks to employ partial or fully asymmetric key establishment techniques and thus extend their security properties. Copyright (C) 2009 John Wiley & Sons, Ltd.

关键词： distributed sensor networks multiphase node deployment pairwise key establishment protocol elliptic curve cryptography implicit certificate

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Data-Driven Monitoring for distributed sensor networks: An End-to-End Strategy Based on Collaborative Learning

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IEEE sensorS JOURNAL 2022年第22期22卷 21795-21805页

作者： Chen, Fuyang He, Sudao Li, Yiwei Chen, Hongtian Nanjing Univ Aeronaut & Astronaut Coll Automat Engn Nanjing 211106 Peoples R China Univ Alberta Dept Chem & Mat Engn Edmonton AB T6G 1H9 Canada

This article proposes an end-to-end event monitoring method for a distributed sensor network with non-concentrated label noises based on a collaborative soft-label network (CSLN). The proposed CSLN framework is composed of a fundamental learner (FL) and a collaborative label modification. FL is designed based on a bidirectional gated recurrent unit (BiGRU) with attention to tackle the indistinct boundary problem by modeling multiscale dependencies. BiGRU can learn latent representations through capturing local dependencies in a bidirectional time flow. The attention mechanism is capable of modeling long-range dependencies through assigning learnable weights to the latent representations. Then, the collaborative label modification is established to reduce label noises by combining a truncated loss function and a dual-space smoothing technique. The truncated loss function can prevent FL from overfitting to noisy labels by isolating them in optimization. The dual-space smoothing technique can generate soft labels based on the local similarities. Furthermore, the proposed CSLN method is optimized by a bi-loop recursive strategy to reduce label noises gradually through alternatively training FL and generating soft labels. The feasibility and effectiveness of the proposed method are validated through real-field experiments of perimeter security applications based on distributed optical fiber sensors (DOFSs).

关键词： Monitoring Noise measurement sensors Smoothing methods Collaboration Training Security Bidirectional gated recurrent unit (BiGRU) with attention collaborative label modification distributed sensor networks event monitoring non-concentrated label noises

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Robust Sequential Detection in distributed sensor networks

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2018年第21期66卷 5648-5662页

作者： Leonard, Mark R. Zoubir, Abdelhak M. Tech Univ Darmstadt Inst Telecommun Signal Proc Grp D-64283 Darmstadt Germany

We consider the problem of sequential binary hypothesis testing with a distributed sensor network in a non-Gaussian noise environment. To this end, we present a general formulation of the Consensus + Innovations Sequential Probability Ratio Test (CISPRT). Furthermore, we introduce two different concepts for robustifying the CISPRT and propose four different algorithms, namely the Least-Favorable-Density-CISPRT, the Median-CISPRT, the M-CISPRT, and the Myriad-CISPRT. Subsequently, we analyze their suitability for different binary hypothesis tests before verifying and evaluating their performance in a shift-in-mean and a shift-in-variance scenario for different network connectivities and amounts of noise contamination.

关键词： Sequential hypothesis testing sequential detection robustness distributed sensor networks distributed detection

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High performance sensor integration in distributed sensor networks using mobile agents

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INTERNATIONAL JOURNAL OF HIGH PERFORMANCE COMPUTING APPLICATIONS 2002年第3期16卷 325-335页

作者： Qi, HR Wang, XL Iyengar, SS Chakrabarty, K Louisiana State Univ Dept Comp Sci Baton Rouge LA 70803 USA Univ Tennessee Dept Elect & Comp Engn Knoxville TN 37996 USA Duke Univ Dept Elect & Comp Engn Durham NC 27708 USA

The recent change of emphasis from high performance parallel computing to high performance parallel/distributed computing has called for new techniques in distributed problem solving. Mobile agent, as a new computing paradigm, breaks the barrier of traditional client/server model and provides a more efficient solution to distributed computing. In the mobile-agent-based paradigm, data stay at the local site, while the execution code is moved to the data sites. In this paper, we describe the deployment of mobile agent in distributed sensor networks (DSNs). Mobile agent is used to integrate pre-processed data located at local sensor nodes. We take target classification as an example to illustrate how mobile-agent-based DSN (MADSN) supports high performance distributed integration.

关键词： distributed sensor networks mobile agent high performance distributed computing sensor integration

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Cellular automata for distributed sensor networks

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INTERNATIONAL JOURNAL OF HIGH PERFORMANCE COMPUTING APPLICATIONS 2008年第2期22卷 167-176页

作者： Allegretti, Dylan G. Kenyon, Garrett T. Priedhorsky, William C. Los Alamos Natl Lab P Div Los Alamos NM 87545 USA Los Alamos Natl Lab Threat Reduct Directorate Los Alamos NM 87545 USA

distributed sensor networks (DSNs) may be useful for detecting and tracking moving objects. Although such systems have important surveillance and homeland security applications, several technical problems exist. The cheap, low-powered sensors necessary for deployment over large areas may function poorly in low signal-to-noise environments. Although combining information from multiple sensors improves detection capabilities, long-range communication with a central computer may exhaust local power resources. We consider cellular automata rules that address these problems. By communicating locally, sensors can accurately track a moving object in a noisy environment. By communicating anonymously, they can use low-powered radio transmitters and receivers and avoid complex digital communication protocols. Our computer simulations show that DSNs can use cellular automata to greatly enhance the detection capabilities of individual sensors and reduce the amount of long-range communication by an order of magnitude.

关键词： distributed sensor networks tracking low signal-to-noise local communication continuous automata

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Joint Sparsity Pattern Recovery With 1-b Compressive Sensing in distributed sensor networks

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IEEE TRANSACTIONS ON SIGNAL AND INFORMATION PROCESSING OVER networks 2019年第1期5卷 15-30页

作者： Kafle, Swatantra Gupta, Vipul Kailkhura, Bhavya Wimalajeewa, Thakshila Varshney, Pramod K. Syracuse Univ Dept EECS Syracuse NY 13244 USA Univ Calif Berkeley Dept EECS Berkeley CA 94720 USA Lawrence Livermore Natl Lab Livermore CA 94550 USA

In this paper, we study the problem of joint sparse support recovery with 1-b quantized compressive measurements in a distributed sensor network. Multiple nodes in the network are assumed to observe sparse signals having the same but unknown sparse support. Each node quantizes its measurement vector element-wise to 1-b. First, we consider that all the quantized measurements are available at a central fusion center. We derive performance bounds for sparsity pattern recovery using 1-bit quantized measurements from multiple sensors when the maximum likelihood decoder is employed. We further develop two computationally tractable algorithms for joint sparse support recovery in the centralized setting. One algorithm minimizes a cost function defined as the sum of the likelihood function and the l(1,infinity) quasi-norm, while the other algorithm extends the binary iterative hard thresholding algorithm to the multiple measurement vector case. Second, we consider a decentralized setting where each node transmits 1-b measurements to its one-hop neighbors. The basic idea behind the algorithms developed in the decentralized setting is to embed collaboration among nodes and fusion strategies. We show that even with noisy 1-b compressed measurements, joint support recovery can he carried out accurately in both centralized and decentralized settings. We further show that the performance of the proposed 1-bit compressive sensing-based algorithms is very close to that of their real-valued counterparts except when the signal-to-noise ratio is very small.

关键词： Compressive sensing distributed sensor networks quantization common sparsity pattern recovery binary iterative hard thresholding

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Fine-grained data access control for distributed sensor networks

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WIRELESS networks 2011年第5期17卷 1235-1249页

作者： Hur, Junbeom Univ Illinois Dept Comp Sci Urbana IL 61801 USA

distributed sensor networks are becoming a robust solution that allows users to directly access data generated by individual sensors. In many practical scenarios, fine-grained access control is a pivotal security requirement to enhance usability and protect sensitive sensor information from unauthorized access. Recently, there have been proposed many schemes to adapt public key cryptosystems into sensor systems consisting of high-end sensor nodes in order to enforce security policy efficiently. However, the drawback of these approaches is that the complexity of computation increases linear to the expressiveness of the access policy. Key-policy attribute-based encryption is a promising cryptographic solution to enforce fine-grained access policies on the sensor data. However, the problem of applying it to distributed sensor networks introduces several challenges with regard to the attribute and user revocation. In this paper, we propose an access control scheme using KP-ABE with efficient attribute and user revocation capability for distributed sensor networks that are composed of high-end sensor devices. They can be achieved by the proxy encryption mechanism which takes advantage of attribute-based encryption and selective group key distribution. The analysis results indicate that the proposed scheme achieves efficient user access control while requiring the same computation overhead at each sensor as the previous schemes.

关键词： distributed sensor networks Attribute-based encryption Revocation Access control

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On computing mobile agent routes for data fusion in distributed sensor networks

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IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING 2004年第6期16卷 740-753页

作者： Wu, QS Rao, NSV Barhen, J Iyengar, SS Vaishnavi, VK Qi, HR Chakrabarty, K Oak Ridge Natl Lab Ctr Engn Sci Adv Res Div Math & Comp Sci Oak Ridge TN 37831 USA Louisiana State Univ Dept Comp Sci Baton Rouge LA 70803 USA Georgia State Univ Dept Comp Informat Syst Atlanta GA 30302 USA Univ Tennessee Dept Elect & Comp Engn Knoxville TN 37996 USA Duke Univ Dept Elect & Comp Engn Durham NC 27708 USA

The problem of computing a route for a mobile agent that incrementally fuses the data as it visits the nodes in a distributed sensor network is considered. The order of nodes visited along the route has a significant impact on the quality and cost of fused data, which, in turn, impacts the main objective of the sensor network, such as target classification or tracking. We present a simplified analytical model for a distributed sensor network and formulate the route computation problem in terms of maximizing an objective function, which is directly proportional to the received signal strength and inversely proportional to the path loss and energy consumption. We show this problem to be NP-complete and propose a genetic algorithm to compute an approximate solution by suitably employing a two-level encoding scheme and genetic operators tailored to the objective function. We present simulation results for networks with different node sizes and sensor distributions, which demonstrate the superior performance of our algorithm over two existing heuristics, namely, local closest first and global closest first methods.

关键词： genetic algorithms mobile agents distributed sensor networks

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