Orbital-angular-momentum-resolved diagnostics for tracking internal phase evolution in multi-bound solitons

The generation of multi-bound solitons is a fascinating subject of investigation in many conservative and dissipative systems, such as photonics, fluid mechanics, Bose-Einstein condensates, and so on. In this study, we demonstrate the successful extraction of phase dynamics between solitons in bound multiple solitons with up to seven constituents in a mode-locked Er laser system. By mapping the internal phase motions of multi-bound solitons to the spatial phase movement of cylindrical vector beams using orbital angular momentum (OAM)-based diagnostics, different categories of internal pulsations are revealed. We show that bound state of four solitons exhibits linear drifting relative phase evolution dynamics; while for bound multiple solitons with constituents from five to seven pulses, stationary relative phase dynamics are observed. These findings highlight the possibility of the OAM-based method access to the internal motion of multi-soliton molecules with more freedom of degrees and fuel the analogy with research on chemistry molecule complex

Why It Takes So Long to Connect to a WiFi Access Point

Today's WiFi networks deliver a large fraction of traffic. However, the performance and quality of WiFi networks are still far from satisfactory. Among many popular quality metrics (throughput, latency), the probability of successfully connecting to WiFi APs and the time cost of the WiFi connection set-up process are the two of the most critical metrics that affect WiFi users' experience. To understand the WiFi connection set-up process in real-world settings, we carry out measurement studies on $5$ million mobile users from $4$ representative cities associating with $7$ million APs in $0.4$ billion WiFi sessions, collected from a mobile "WiFi Manager" App that tops the Android/iOS App market. To the best of our knowledge, we are the first to do such large scale study on: how large the WiFi connection set-up time cost is, what factors affect the WiFi connection set-up process, and what can be done to reduce the WiFi connection set-up time cost. Based on the measurement analysis, we develop a machine learning based AP selection strategy that can significantly improve WiFi connection set-up performance, against the conventional strategy purely based on signal strength, by reducing the connection set-up failures from $33\%$ to $3.6\%$ and reducing $80\%$ time costs of the connection set-up processes by more than $10$ times.Comment: 11pages, conferenc

Unsupervised Anomaly Detection via Variational Auto-Encoder for Seasonal KPIs in Web Applications

To ensure undisrupted business, large Internet companies need to closely monitor various KPIs (e.g., Page Views, number of online users, and number of orders) of its Web applications, to accurately detect anomalies and trigger timely troubleshooting/mitigation. However, anomaly detection for these seasonal KPIs with various patterns and data quality has been a great challenge, especially without labels. In this paper, we proposed Donut, an unsupervised anomaly detection algorithm based on VAE. Thanks to a few of our key techniques, Donut greatly outperforms a state-of-arts supervised ensemble approach and a baseline VAE approach, and its best F-scores range from 0.75 to 0.9 for the studied KPIs from a top global Internet company. We come up with a novel KDE interpretation of reconstruction for Donut, making it the first VAE-based anomaly detection algorithm with solid theoretical explanation.Comment: 12 pages (including references), 17 figures, submitted to WWW 2018: The 2018 Web Conference, April 23--27, 2018, Lyon, France. The contents discarded from the conference version due to the 9-page limitation are also included in this versio

BDS+: An Inter-Datacenter Data Replication System With Dynamic Bandwidth Separation

Many important cloud services require replicating massive data from one datacenter (DC) to multiple DCs. While the performance of pair-wise inter-DC data transfers has been much improved, prior solutions are insufficient to optimize bulk-data multicast, as they fail to explore the rich inter-DC overlay paths that exist in geo-distributed DCs, as well as the remaining bandwidth reserved for online traffic under fixed bandwidth separation scheme. To take advantage of these opportunities, we present BDS+, a near-optimal network system for large-scale inter-DC data replication. BDS+ is an application-level multicast overlay network with a fully centralized architecture, allowing a central controller to maintain an up-to-date global view of data delivery status of intermediate servers, in order to fully utilize the available overlay paths. Furthermore, in each overlay path, it leverages dynamic bandwidth separation to make use of the remaining available bandwidth reserved for online traffic. By constantly estimating online traffic demand and rescheduling bulk-data transfers accordingly, BDS+ can further speed up the massive data multicast. Through a pilot deployment in one of the largest online service providers and large-scale real-trace simulations, we show that BDS+ can achieve 3-5 x speedup over the provider's existing system and several well-known overlay routing baselines of static bandwidth separation. Moreover, dynamic bandwidth separation can further reduce the completion time of bulk data transfers by 1.2 to 1.3 times

Designing Buffer Capacity of Crosspoint-Queued Switch

Part 1: Systems, Networks and ArchitecturesInternational audienceWe use both theoretical analysis and simulations to study crosspoint-queued(CQ) buffer size’s impact on CQ switch’s throughput and delay performance under different traffic models, input loads, and scheduling algorithms. In this paper, 1) we present an exact closed-form formula for the CQ switch’s throughput and a non-closed-form but convergent formula for its delay using static non-work-conserving random scheduling algorithms with any given buffer size under independent Bernoulli traffic; 2) we show that the above results can serve as a conservative guidance on deciding the needed buffer size in pure CQ switches using work-conserving algorithms such as random, under independent Bernoulli traffic. Furthermore, our simulation results under real-trace traffic show that simple round-robin and random work-conserving algorithms can achieve quite good throughput and delay performance with feasible crosspoint buffer size. Our work reveals the impact of buffer size on CQ switches’ performance and provides a theoretical guidance on designing the buffer size in pure CQ switch, which is an important step towards building ultra-high-speed switching fabrics

Incidence, temporal trends and risk factors of puerperal infection in Mainland China: a meta-analysis of epidemiological studies from recent decade (2010–2020)

Abstract Background Puerperal infection (PI) is a severe threat to maternal health. The incidence and risk of PI should be accurately quantified and conveyed for prior decision-making. This study aims to assess the quality of the published literature on the epidemiology of PI, and synthesize them to identify the temporal trends and risk factors of PI occurring in Mainland China. Methods This review was registered in PROSPERO (CRD42021267399). Putting a time frame on 2010 to March 2022, we searched Cochrane library, Embase, Google Scholar, MEDLINE, Web of Science, China biology medicine, China national knowledge infrastructure and Chinese medical current contents, and performed a meta-analysis and meta-regression to pool the incidence of PI and the effects of risk factors on PI. Results A total of 49 eligible studies with 133,938 participants from 17 provinces were included. The pooled incidence of PI was 4.95% (95%CIs, 4.46–5.43), and there was a statistical association between the incidence of PI following caesarean section and the median year of data collection. Gestational hypertension (OR = 2.14), Gestational diabetes mellitus (OR = 1.82), primipara (OR = 0.81), genital tract inflammation (OR = 2.51), anemia during pregnancy (OR = 2.28), caesarean section (OR = 2.03), episiotomy (OR = 2.64), premature rupture of membrane (OR = 2.54), prolonged labor (OR = 1.32), placenta remnant (OR = 2.59) and postpartum hemorrhage (OR = 2.43) have significant association with PI. Conclusions Maternal infection remains a crucial complication during puerperium in Mainland China, which showed a nationwide temporal rising following caesarean section in the past decade. The opportunity to prevent unnecessary PI exists in several simple but necessary measures and it’s urgent for clinicians and policymakers to focus joint efforts on promoting the bundle of evidence-based practices