Wireless sensornetworks are widely used in a variety of commercial and military applications. As a fundamental requirement for providing security functionality in sensornetworks, key management plays an essential ro...
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ISBN:
(纸本)9780769540207
Wireless sensornetworks are widely used in a variety of commercial and military applications. As a fundamental requirement for providing security functionality in sensornetworks, key management plays an essential role in authentication and encryption. In this paper, we propose a Refined Key Link Tree (RKLT) scheme that incorporates dirty key path into the key link tree-based group key management scheme. By delaying key update operations in dirty key paths, the number of duplicate key update messages for auxiliary nodes can be reduced, which also brings down the energy cost. We show through experiments that our RKLT scheme requires fewer rekeying messages than those in the existing group key management schemes.
In mobile ad hoc networks, the nodes are powered by batteries. So one of the most important merits when evaluating a given protocol is its ability to decrease node energy consumption and prolong network lifetime. Conc...
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Daily evaluation of the power grid enterprises often involve large amounts of data, and most of the work is tedious, power supply capacity as an important embodiment of corporate responsibility needs good evaluations....
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The goal of this paper is to propose a way to processing data from service providing networks using reputation mechanism to user application in agent-based network environment. In this process, it must concern about a...
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This paper proposes an enhanced pattern discovery algorithm for data streams processing of sensornetworks, in order to improve the performance of SPIRIT. The new algorithm adapts the optimized correction for tracking...
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Data aggregation is an important task in data centric heterogeneous wireless sensornetworks because of its varying power and computational capabilities. Due to the deployment of sensor nodes in large numbers for diff...
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ISBN:
(纸本)9783642144776
Data aggregation is an important task in data centric heterogeneous wireless sensornetworks because of its varying power and computational capabilities. Due to the deployment of sensor nodes in large numbers for different applications, a single node is not sufficient for performing data aggregation. Hence multiple nodes are required to summarize the relevant information from huge data sets. The process of data aggregation is vulnerable to many threats like loss of cryptographic keys, false data injection etc. To address these issues, we present the Secure Data Aggregation with Key Management (SDAKM) scheme. It provides a secure framework for the data centric heterogeneous wireless sensornetworks using additive privacy homomorphism. It uses the heterogeneity of the sensor nodes for performing encrypted data processing and also provides an efficient key management scheme for data communication among sensor nodes in the network. This scheme offers higher security and has less computing overhead as it uses additive privacy homomorphism.
Traditional key management techniques, such as public key cryptography or key distribution center (e.g., Kerberos), are often not effective for wireless sensornetworks for the serious limitations in terms of computat...
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ISBN:
(纸本)9780769540207
Traditional key management techniques, such as public key cryptography or key distribution center (e.g., Kerberos), are often not effective for wireless sensornetworks for the serious limitations in terms of computational power, energy supply, network bandwidth and defection of centra authority. In order to balance the security and efficiency, we propose a new scheme by employing LU Composition techniques for mutualauthenticated pairwise key establishment and integrating LU Matrix with Elliptic Curve Diffie-Hellman for anonymous pathkey establishment. At the meantime, it can achieve efficient group key agreement and management by tree-based extension of LU Matrix Composition key exchange protocol(TGLU). Theoretical analysis shows that the new scheme has better performance and provides authenticity and anonymity for sensor to establish multiple kinds of keys, compared with previous related works.
In industrial applications of wireless sensornetworks (WSNs), due to the constraints of limited bandwidth and power, it is not easy to transmit vibration signals in a real-time manner. To address this problem, compre...
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ISBN:
(纸本)9787510020841
In industrial applications of wireless sensornetworks (WSNs), due to the constraints of limited bandwidth and power, it is not easy to transmit vibration signals in a real-time manner. To address this problem, compressive sensing is exploited to perform vibration signal compression with low computational complexity, which reduces volume of transmitted data and increase transmission efficiency and real-time performance. The fundamentals of compressive sensing enabled signal communication include exploring the inherent sparsity of vibration signals in the frequency domain, compressing the signal with a random Gaussian sampling matrix, and reconstructing the original signal by L-1 norm optimization. A distributed computing paradigm is also proposed to improve the performance of reconstruction by fusing the information of multiple sensor nodes. Experiments show that the proposed distributed compressive sensing enabled signal communication can decrease computational load, improve real-time performance and satisfy the constraints, making it a promising technology for communication in WSNs.
This paper describes wireless wearable and ambient sensors that cooperate to monitor a person39;s vital signs such as heart rate and blood pressure during daily activities. Each wearable sensor is attached on differ...
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Future Ubiquitous sensornetworks (USNs) are expected to sense and combine multiple descriptions of user contexts, providing a huge potential for the development of revolutionary context-aware applications bridging th...
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Future Ubiquitous sensornetworks (USNs) are expected to sense and combine multiple descriptions of user contexts, providing a huge potential for the development of revolutionary context-aware applications bridging the physical and digital worlds. Current sensor Web initiatives aim to support ubiquitous access to sensornetworks, but to make them really useful for context-aware applications there is still a strong need to develop new mechanisms for enriching sensor data with high-level information, which would constitute a step towards Semantic sensornetworks. In this paper, state-charts technology, described according to the W3C SCXML language, combined with the functionalities arising from Semantic Web technologies, are proposed as an efficient, simple and flexible means to make progress towards these objectives. Working with sensor Web data, we propose SCXML-based semantic processing to produce high-level information through automatic embedding of semantic annotations, as well as the identification of relevant contexts. Both of these approaches are useful in a wide range of application domains. The capabilities and limitations of an SCXML processing architecture are also discussed in the context of its implementation over an OSGi framework and its integration into an experimental Telco USN Platform based on OGC® sensor Web Enablement guidelines.
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