64 research outputs found
Enhancing quantum entropy in vacuum-based quantum random number generator
Information-theoretically provable unique true random numbers, which cannot
be correlated or controlled by an attacker, can be generated based on quantum
measurement of vacuum state and universal-hashing randomness extraction.
Quantum entropy in the measurements decides the quality and security of the
random number generator. At the same time, it directly determine the extraction
ratio of true randomness from the raw data, in other words, it affects quantum
random numbers generating rate obviously. In this work, considering the effects
of classical noise, the best way to enhance quantum entropy in the vacuum-based
quantum random number generator is explored in the optimum dynamical
analog-digital converter (ADC) range scenario. The influence of classical noise
excursion, which may be intrinsic to a system or deliberately induced by an
eavesdropper, on the quantum entropy is derived. We propose enhancing local
oscillator intensity rather than electrical gain for noise-independent
amplification of quadrature fluctuation of vacuum state. Abundant quantum
entropy is extractable from the raw data even when classical noise excursion is
large. Experimentally, an extraction ratio of true randomness of 85.3% is
achieved by finite enhancement of the local oscillator power when classical
noise excursions of the raw data is obvious.Comment: 12 pages,8 figure
R-bUCRP: A Novel Reputation-Based Uneven Clustering Routing Protocol for Cognitive Wireless Sensor Networks
Energy of nodes is an important factor that affects the performance of Wireless Sensor Networks (WSNs), especially in the case of existing selfish nodes, which attracted many researchers’ attention recently. In this paper, we present a reputation-based uneven clustering routing protocol (R-bUCRP) considering both energy saving and reputation assessment. In the cluster establishment phase, we adopt an uneven clustering mechanism which controls the competitive scope of cluster head candidates to save the energy of WSNs. In the cluster heads election phase, the residual energy and reputation value are used as the indexes to select the optimal cluster head, where the reputation mechanism is introduced to support reputation assessment. Simulation results show that the proposed R-bUCRP can save node energy consumption, balance network energy distribution, and prolong network lifetime
P-bRS: A Physarum-Based Routing Scheme for Wireless Sensor Networks
Routing in wireless sensor networks (WSNs) is an extremely challenging issue due to the features of WSNs. Inspired by the large and single-celled amoeboid organism, slime mold Physarum polycephalum, we establish a novel selecting next hop model (SNH). Based on this model, we present a novel Physarum-based routing scheme (P-bRS) for WSNs to balance routing efficiency and energy equilibrium. In P-bRS, a sensor node can choose the proper next hop by using SNH which comprehensively considers the distance, energy residue, and location of the next hop. The simulation results show how P-bRS can achieve the effective trade-off between routing efficiency and energy equilibrium compared to two famous algorithms
Cognitive internet of things: concepts and application example,”
Abstract Internet of Things (IoT) is a heterogeneous, mixed and uncertain ubiquitous network, the application prospect of which is extensive in the field of modern intelligent service. Having done a deep investigation on the discrepancies between service offering and application requirement, we believed that current IoT lacks enough intelligence and cannot achieve the expected increasing applications' performance. By integrating intelligent thought into IoT, we presented a new concept of Cognitive Internet of Things (CIoT) in this paper. CIoT can apperceive current network conditions, analyze the perceived knowledge, make intelligent decisions, and perform adaptive actions, which aim to maximize network performance. We modeled the CIoT network topology and designed cognition-process-related technologies, analyzed the payoffs of cooperative cognition based on game theory, which illustrates those novel designs can endows IoT with intelligence and fully improve system's performance. Finally, an application example was introduced based on the concept of CIoT
Reputation Revision Method for Selecting Cloud Services Based on Prior Knowledge and a Market Mechanism
The trust levels of cloud services should be evaluated to ensure their reliability. The effectiveness of these evaluations has major effects on user satisfaction, which is increasingly important. However, it is difficult to provide objective evaluations in open and dynamic environments because of the possibilities of malicious evaluations, individual preferences, and intentional praise. In this study, we propose a novel unfair rating filtering method for a reputation revision system. This method uses prior knowledge as the basis of similarity when calculating the average rating, which facilitates the recognition and filtering of unfair ratings. In addition, the overall performance is increased by a market mechanism that allows users and service providers to adjust their choice of services and service configuration in a timely manner. The experimental results showed that this method filtered unfair ratings in an effective manner, which greatly improved the precision of the reputation revision system
P-bRS: A Physarum-Based Routing Scheme for Wireless Sensor Networks
Routing in wireless sensor networks (WSNs) is an extremely challenging issue due to the features of WSNs. Inspired by the large and single-celled amoeboid organism, slime mold Physarum polycephalum, we establish a novel selecting next hop model (SNH). Based on this model, we present a novel Physarum-based routing scheme (P-bRS) for WSNs to balance routing efficiency and energy equilibrium. In P-bRS, a sensor node can choose the proper next hop by using SNH which comprehensively considers the distance, energy residue, and location of the next hop. The simulation results show how P-bRS can achieve the effective trade-off between routing efficiency and energy equilibrium compared to two famous algorithms
Ultra-Low-Frequency Radio Astronomy Observations from a Selenocentric Orbit: first results of the Longjiang-2 experiment
This paper introduces the first results of observations with the
Ultra-Long-Wavelength (ULW) -- Low Frequency Interferometer and Spectrometer
(LFIS) on board the selenocentric satellite Longjiang-2. We present a brief
description of the satellite and focus on the LFIS payload. The in-orbit
commissioning confirmed a reliable operational status of the instrumentation.
We also present results of a transition observation, which offers unique
measurements on several novel aspects. We estimate the RFI suppression required
for such a radio astronomy instrumentation at the Moon distances from Earth to
be of the order of 80 dB. We analyse a method of separating Earth- and
satellite-originated radio frequency interference (RFI). It is found that the
RFI level at frequencies lower than a few MHz is smaller than the receiver
noise floor.Comment: Accepted for publication in Experimental Astronomy; 22 pages, 11
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