Since biometric data are unique and permanent characteristics of individuals, the privacy protection of biometric authentication schemes has become a common concern of the public. Recently, Tang et al. proposed a biom...
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The dynamic nature of wireless communication and the stringent energy constraints are major challenges for the design of low-power wireless sensor network applications. The link quality of a wireless link is known for...
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ISBN:
(纸本)9784907764319
The dynamic nature of wireless communication and the stringent energy constraints are major challenges for the design of low-power wireless sensor network applications. The link quality of a wireless link is known for its great variability, dependent on the distance between nodes, the antenna's radiation characteristic, multipath, diffraction, scattering and many more. Especially for indoor and urban deployments, there are numerous factors impacting the wireless channel. In an extensive experimental study contained in the first part of this paper, we show the magnitude of this problem for current Wireless Sensor networks (WSNs) and that based on the overall connectivity graph of a typical multihop WSN, a large portion of the links actually exhibit very poor characteristics. We present a pattern based estimation technique that allows assessing the quality of a link at startup and as a result to construct an optimal neighbor table right at the beginning using a minimum of resources only. Our estimation technique is superior compared to other approaches where protocols continue to decide on the fly which links to use expending valuable energy both for unnecessary retransmissions and recursive link estimation.
In this paper, a data-driven non-model-based approach is proposed for the adaptive optimal control of connected vehicles, comprised of n human-driven vehicles only transmitting motional data and an autonomous vehicle ...
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The concept of the Sagnac effect in a slow-light medium and resonator structure with a high group dispersion is investigated. It is found that a slow-light medium can be utilized for relative motion sensing, and a slo...
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Wireless sensor networks are open architectures, so any potential threat can easily intercept, wiretap and counterfeit the information. Therefore, the safety of WSN is very important. Since any single key system canno...
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The pursuit of energy efficiency is becoming more and more important in hardware and software designs. This research explores energy-efficient scheduling for a periodic real-time task with uncertain execution time in ...
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The pursuit of energy efficiency is becoming more and more important in hardware and software designs. This research explores energy-efficient scheduling for a periodic real-time task with uncertain execution time in dynamic voltage scaling (DVS) systems with non-negligible leakage/static power consumption. Distinct from the assumption of non-reducible static power consumption in the literature, this paper considers the possibility to reduce it by turning a processor to a dormant mode. We propose an algorithm to derive an optimal frequency assignment to minimize the expected energy consumption without procrastination, while another extended algorithm is developed to apply procrastination scheduling for further energy reduction. Experimental results show that the proposed algorithms can effectively minimize the expected energy consumption.
Efficient utilization of spectral bands in a dynamic environment with a continuously changing occupation rate is challenging. Static spectral allocations preclude the use of unoccupied spectrum, unless the spectrum ma...
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ISBN:
(纸本)9781467300810
Efficient utilization of spectral bands in a dynamic environment with a continuously changing occupation rate is challenging. Static spectral allocations preclude the use of unoccupied spectrum, unless the spectrum manager has released the allocation to another mission. Standard spectral sensing techniques employ swept narrowband receivers. While effective in creating a composite, these techniques are ineffective at identifying short duration signals. Real-time spectral analysis techniques are effective at capturing short duration transmissions, but usually have narrow band capabilities, limited dynamic range and are relatively expensive. Timely accurate sensing of wide spectral band using traditional spectral estimations at the Nyquist rate (or higher) is another challenge due to the high data rate. Compressed sensing (CS) techniques utilize signal-to-information rate processing when signals are sparse in a specific domain. Dynamic spectrum access (often considered a critical component of a cognitive radio (CR)) can reutilize temporally unoccupied spectrum. An accurate estimate of the current state of spectral occupancy is critical to the autonomous decision processes involved in dynamic spectrum access. From this perspective, CS is being studied as an enhancement to dynamic spectrum access strategies. This study addresses feasibility issues for the development of autonomous CS-CR systems that are capable of performing spectrum sensing and recovery without a priori information about the spectral occupancy. Since recovery requires computationally intense non-linear optimization, we perform a single platform trade study on CS methodologies (BP-PD, BP-SPG, ROMP, Edge Detection, and Sequential Recovery) for efficient wideband recovery relative to execution time and reconstruction error. We propose adaptive coarse detection, and exact recovery based on adaptive edge detection. We present the results using continuous waves and pulses (MATlab or GRC generated, or USRP mea
PROBLEM In recent years,the rapid development of artificial intelligence (AI) technology,especially machine learning and deep learning, is profoundly changing human production and *** various fields,such as robotics,f...
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PROBLEM In recent years,the rapid development of artificial intelligence (AI) technology,especially machine learning and deep learning, is profoundly changing human production and *** various fields,such as robotics,face recognition,autonomous driving and healthcare,AI is playing an important ***,although AI is promoting the technological revolution and industrial progress,its security risks are often *** studies have found that the wellperforming deep learning models are extremely vulnerable to adversarial examples [1-3].The adversarial examples are crafted by applying small,humanimperceptible perturbations to natural examples,but can mislead deep learning models to make wrong *** vulnerability of deep learning models to adversarial examples can raise security and safety threats to various realworld applications.
Voice over IP (VoIP) service providers implementing different protocols in their core networks are required to coordinate in order to provision, support and deliver voice services to end clients. This paper presents a...
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ISBN:
(纸本)9789639799240
Voice over IP (VoIP) service providers implementing different protocols in their core networks are required to coordinate in order to provision, support and deliver voice services to end clients. This paper presents a performance measurement experience for the transport of voice services across multiple heterogeneous wired networks. Our test results show that Multiple Protocol label Switching (MPLS) protocol slightly outperforms IP in delivering voice services. Moreover, the type of call signaling protocol used, tunneling category adopted and the type of Virtual Private Network (VPN) implemented affect the overall quality and performance of voice services in terms of jitter and delay.
This paper studies the distributed feedback optimization problem for linear multi-agent systems without precise knowledge of local costs and agent dynamics. The proposed solution is based on a hierarchical approach th...
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