Sliding windows over uncertain data streams

Uncertain data streams can have tuples with both value and existential uncertainty. A tuple has value uncertainty when it can assume multiple possible values. A tuple is existentially uncertain when the sum of the probabilities of its possible values is $$<$$<1. A situation where existential uncertainty can arise is when applying relational operators to streams with value uncertainty. Several prior works have focused on querying and mining data streams with both value and existential uncertainty. However, none of them have studied, in depth, the implications of existential uncertainty on sliding window processing, even though it naturally arises when processing uncertain data. In this work, we study the challenges arising from existential uncertainty, more specifically the management of count-based sliding windows, which are a basic building block of stream processing applications. We extend the semantics of sliding window to define the novel concept of uncertain sliding windows and provide both exact and approximate algorithms for managing windows under existential uncertainty. We also show how current state-of-the-art techniques for answering similarity join queries can be easily adapted to be used with uncertain sliding windows. We evaluate our proposed techniques under a variety of configurations using real data. The results show that the algorithms used to maintain uncertain sliding windows can efficiently operate while providing a high-quality approximation in query answering. In addition, we show that sort-based similarity join algorithms can perform better than index-based techniques (on 17 real datasets) when the number of possible values per tuple is low, as in many real-world applications. © 2014, Springer-Verlag London

Field trial of SDN-controlled probabilistic constellation shaping supporting multiple rates over a coupled-core multi-core fiber

A SDN controller configures probabilistic constellation shaping through NETCONF optimizing spectral efficiency according to the path length or degradations due to soft failure. The integrated data and control planes are demonstrated with multiple rates (800-850-900-950-1000Gb/s) in a field trial employing multi-core fiber with 4-coupled cores

Rate Optimized Probabilistic Shaping-Based Transmission Over Field Deployed Coupled-Core 4-Core-Fiber

Multi-core fiber (MCF) transmission is a promising solution to support ever-increasing future traffic demands. Compared with uncoupled-core MCFs [1], the induced strong coupling in coupled-core (CC)-MCFs reduces the nonlinearity impact [2]. Transmission in these fibers leverages both spatial and wavelength division multiplexing and it has been experimentally tested mainly considering uniform quadrature amplitude modulation (QAM) formats [3]. Spectral efficiency can be further optimized by employing probabilistic shaping (PS) but the joint use of CC-MCF and PS has been rarely investigated [4]. In this paper, we present a transmission of PS signals through an infrastructure based on a CC-four core fiber (CC-4CF) deployed in the city of L'Aquila, Italy [5]. We ran experiments comparing the performance of standard polarization multiplexed 16QAM and PS-32QAM signals at a symbol rate of 30 GBaud: 800 Gbps net rate considering the spatial super-channel over four cores. We used the generalized mutual information (GMI) as performance metric and averaged over the 8 polarizations concidering the central channel. A realistic threshold (GMIth) of 3.6 bits/symbol (per spatial mode and polarization) has been set as a target: it is a typical value that guarantees post-FEC error-free transmission for most realistic SD-FEC

Measurement of Propagation Constants of Graded Index Multi-mode Fiber Using Rayleigh Backscattered Light

We measure the distributed differential group delay and effective refractive index difference between all 9 mode groups of a graded index multi-mode fiber using optical frequency domain reflectometry by cross correlating Raleigh backscatter signals. (C) 2021 The Author(s

Risk-aware path selection with time-varying, uncertain travel costs: a time series approach

We address the problem of choosing the best paths among a set of candidate paths between the same origin–destination pair. This functionality is used extensively when constructing origin–destination matrices in logistics and flex transportation. Because the cost of a path, e.g., travel time, varies over time and is uncertain, there is generally no single best path. We partition time into intervals and represent the cost of a path during an interval as a random variable, resulting in an uncertain time series for each path. When facing uncertainties, users generally have different risk preferences, e.g., risk-loving or risk-averse, and thus prefer different paths. We develop techniques that, for each time interval, are able to find paths with non-dominated lowest costs while taking the users’ risk preferences into account. We represent risk by means of utility function categories and show how the use of first-order and two kinds of second-order stochastic dominance relationships among random variables makes it possible to find all paths with non-dominated lowest costs. We report on empirical studies with large uncertain time series collections derived from a 2-year GPS data set. The study offers insight into the performance of the proposed techniques, and it indicates that the best techniques combine to offer an efficient and robust solution.</p

Real-Time MIMO Transmission over Field-Deployed Coupled-Core Multi-Core Fibers

We perform parallel continuous measurements of deployed SDM fibers u sing real-time coherent receivers implemented on FPGAs. Fast readouts enabling real-time tracking of the DSP implementation, showing that coupled-core fibers are compatible with real-time DSP implementations

10-Mode-Multiplexed Transmitter Employing 2-D VCSEL Matrix

A mode-multiplexed transmitter combining a 2-D VCSEL matrix on a Si interposer and a multi-plane light converter is demonstrated. This enables 200-Gb/s transmission using 10G-class VCSELs over 100-m multimode fiber with direct detection and 28-km few-mode fiber with coherent detection