Photodiode (PD) arrays do not violate the second law of thermodynamics. In this paper, we explore the trade-off between PD array photo current and PD size when arrays with the same geometrical fill factor are considered. For this study, we assume a square matrix arrangement of PD. We apply the principles of energy conservation and, by extension, the second law of thermodynamics to demonstrate that reducing the size of individual PD in the array results in a decrease in photocurrent. This decrease is anticipated even when the geometrical fill factor of the array remains constant, i.e., even if the number of PDs in the array is increased. The photocurrent and size trade-off leads to the photocurrent bandwidth trade-off. The trade-off indicates that the PD array photocurrent is inversely proportional to its bandwidth. The derivation of this trade-off relation assumes a uniform irradiance distribution across the photodetector array. However, our findings show that this trade-off holds true for nearly uniform irradiance distributions and even for non-uniform distributions, such as those encountered with a compound parabolic concentrator (CPC). Our simulation results align closely with theoretical predictions. The implications of this study highlight the importance of considering the trade-off when designing optical wireless communication (OWC) or visible light communication (VLC) links for high data throughput.

Transparent web proxies have been widely deployed on the Internet, bridging the communications between clients and servers and providing desirable benefits to both sides, such as load balancing, security monitoring, and privacy enhancement. Meanwhile, they work silently as clients and servers may not be aware of their existence. However, due to their invisibility and stealthiness, transparent proxies remain understudied for their behaviors, suspicious activities, and potential vulnerabilities that could be exploited by attackers. To better understand transparent proxies, we design and develop a framework to systematically investigate them in the wild. We identify two major types of transparent web proxies, named FDR and CPV, respectively. FDR is a type of transparent proxy that independently performs Forced DNS Resolution during interception. CPV is a type of transparent proxy that presents Cache Poisoning Vulnerability. We perform a large-scale measurement to detect each type of transparent web proxy and scrutinize their security implications. In total, we observe 32,246 FDR and 11,286 CPV cases through our acquired vantage points. We confirm that these two types of transparent proxies are distributed globally — FDRs are observed in 98 countries and CPVs are observed in 51 countries. Our work highlights the issues of vulnerable transparent proxies and provides insights for mitigating such problems.

In this paper, multi-tier LiFi networks are studied in terms of energy efficiency (EE) and spectral efficiency (SE), which are crucial metrics for LiFi system design. We derived a closed-form expression of the user association probability for different tiers using stochastic geometry based Poisson Voronoi Tessellation (PVT) LiFi network. The performance metrics of the network, EE and SE, are analyzed in terms of different parameters such as transmit power and Lambertian index. Performance evaluations and numerical results show that multi-tier LiFi networks have an optimum transmit power in which EE is maximized. Besides, increasing the transmit power does not increase SE after passing a threshold point. The resulting trade-off between EE and SE is presented.

In this paper we investigate the impact of the passband shift (PS) phenomenon on optical wireless communication (OWC) systems based on wavelength division (WD). We first introduce the associated challenges, then we discuss the mathematical framework needed to evaluate the performance of systems based on WD when the impact of the PS phenomenon is taken into account. We introduce the concept of spectral overlap (SO) and discuss its role in the design of WD solutions. Results show that this design phase has to take the SO into account, and that its careful balance with the channel gain is essential when multiple colours are used for parallel communication in OWC.

SGD (Stochastic Gradient Descent) is a popular algorithm for large scale optimization problems due to its low iterative cost. However, SGD can not achieve linear convergence rate as FGD (Full Gradient Descent) because of the inherent gradient variance. To attack the problem, mini-batch SGD was proposed to get a trade-off in terms of convergence rate and iteration cost. In this paper, a general CVI (ConvergenceVariance Inequality) equation is presented to state formally the interaction of convergence rate and gradient variance. Then a novel algorithm named SSAG (Stochastic Stratified Average Gradient) is introduced to reduce gradient variance based on two techniques, stratified sampling and averaging over iterations that is a key idea in SAG (Stochastic Average Gradient). Furthermore, SSAG can achieve linear convergence rate of O((1 - μ/8C L)k) at smaller storage and iterative costs, where C ≥ 2 is the category number of training data. This convergence rate depends mainly on the variance between classes, but not on the variance within the classes. In the case of C ≪ N (N is the training data size), SSAG's convergence rate is much better than SAG's convergence rate of O((1 - μ/8N L)k). Our experimental results show SSAG outperforms SAG and many other algorithms.