This paper proposes an Ambient-Adaptive Voltage Scaling (AAVS) driver for SPAD arrays that maintains quasi-linear photon detection across a wide range of illumination levels. The proposed system integrates an Adaptive Feedback-Controlled (AFC) V${}_{\mathbf {EX}}$modulator that continuously senses photon flux to regulate the excess bias voltage (V${}_{\mathbf {EX}}$) relative to the actual breakdown voltage (V${}_{\mathbf {BD}}$), coupled with a hybrid boost converter featuring adaptive V${}_{\mathbf {EX}}$calibration to generate 27.1–27.6V with sub-millivolt ripple. Measurement results demonstrate a 131 dB dynamic range ($10^{10}$–$10^{17}$photons/cm${}^{2}\cdot $s), 92.3% peak efficiency, and robust scalability supporting 128-SPAD arrays. The AAVS architecture enhances sensitivity under low-light conditions while effectively preventing saturation in high-light scenarios.

This paper proposes a flying-capacitor sharing dynamic four-path (FCSD-4P) hybrid converter, designed to achieve a duty cycle (D) ranging from 0% to 100%, addressing the conventional limitation of D2. In a 6V to 1.8V conversion, the converter achieves a peak efficiency of 94.2%.

This paper proposes a two-phase hybrid buck-boost converter, which meets the criteria of USB PD 3.1, with an auxiliary inductor LAUX to achieve soft switching by the zero voltage switching (ZVS) technique at light loads. Besides, two interleaving phases can reduce the inductor current to half of that conventional design. Benefiting from a coupled inductor with a negative mutual inductance (M$_{\mathrm {L(AC)}}$becomes small to achieve low output voltage ripple due to large equivalent inductance Leq in a steady state. Based on the loading current, the phase shedding can change the number of driving phases for high efficiency. Moreover, a transient enhancement circuit is proposed to speed up transient response time. The proposed circuit achieves the maximum inductor current ripple reduction of 9.09% and the maximum P$_{\mathrm {AC\_loss}}$reduction of 17.36% at D=0.5. Experimental results show 96.1% peak efficiency. In the case of the load step 0.5A to 5A, the recovery time and undershoot are reduced to$10.7\mu $s and 133mV, respectively, and in the case of the load step 5A to 0.5A, the recovery time and overshoot are reduced to$9.4\mu $s and 147mV, respectively.

We examine the current state of user network performance and opportunities to improve it from the vantage point of Facebook, a global content provider. Facebook serves over 2 billion users distributed around the world using a network of PoPs and interconnections spread across 6 continents. In this paper, we execute a large-scale, 10-day measurement study of metrics at the TCP and HTTP layers for production user traffic at all of Facebook's PoPs worldwide, collecting performance measurements for hundreds of trillions of sampled HTTP sessions. We discuss our approach to collecting and analyzing measurements, including a novel approach to characterizing user achievable goodput from the server side. We find that most user sessions have MinRTT less than 39ms and can support HD video. We investigate if it is possible to improve performance by incorporating performance information into Facebook's routing decisions; we find that default routing by Facebook is largely optimal. To our knowledge, our measurement study is the first characterization of user performance on today's Internet from the vantage point of a global content provider.

The IPv4 Record Route (RR) Option instructs routers to record their IP addresses in a packet. RR is subject to a nine hop limit and, traditionally, inconsistent support from routers. Recent changes in interdomain connectivity---the so-called "flattening Internet"---and new best practices for how routers should handle RR packets suggest that now is a good time to reassess the potential of the RR Option.

The Internet suffers from well-known performance, reliability, and security problems. However, proposed improvements have seen little adoption due to the difficulties of Internet-wide deployment. We observe that, instead of trying to solve these problems in the general case, it may be possible to make substantial progress by focusing on solutions tailored to the paths between popular content providers and their clients, which carry a large share of Internet traffic.

Automatic screen rotation improves viewing experience and usability of mobile devices, but current gravity-based approaches do not support postures such as lying on one side, and manual rotation switches require explicit user input. iRotateGrasp automatically rotates screens of mobile devices to match users' viewing orientations based on how users are grasping the devices. Our insight is that users' grasps are consistent for each orientation, but significantly differ between different orientations. Our prototype used a total of 44 capacitive sensors along the four sides and the back of an iPod Touch, and uses support vector machine (SVM) to recognize grasps at 25Hz. We collected 6-users' usage under 108 different combinations of posture, orienta-tion, touchscreen operation, and left/right/both hands. Our offline analysis showed that our grasp-based approach is promising, with 80.9% accuracy when training and testing on different users, and up to 96.7% if users are willing to train the system. Our user study (N=16) showed that iRo-tateGrasp had an accuracy of 78.8% and was 31.3% more accurate than gravity-based rotation.