A New Variational Bayesian-Based Kalman Filter with Unknown Time-Varying Measurement Loss Probability and Non-Stationary Heavy-Tailed Measurement Noise

In this paper, a new variational Bayesian-based Kalman filter (KF) is presented to solve the filtering problem for a linear system with unknown time-varying measurement loss probability (UTVMLP) and non-stationary heavy-tailed measurement noise (NSHTMN). Firstly, the NSHTMN was modelled as a Gaussian-Student’s t-mixture distribution via employing a Bernoulli random variable (BM). Secondly, by utilizing another Bernoulli random variable (BL), the form of the likelihood function consisting of two mixture distributions was converted from a weight sum to an exponential product and a new hierarchical Gaussian state-space model was therefore established. Finally, the system state vector, BM, BL, the intermediate random variables, the mixing probability, and the UTVMLP were jointly inferred by employing the variational Bayesian technique. Simulation results revealed that in the scenario of NSHTMN, the proposed filter had a better performance than current algorithms and further improved the estimation accuracy of UTVMLP.

Throughput and Packet Loss Probability Analysis of Long Range Wide Area Network

Long Range Wide Area Network (LoRaWAN) is the one of the promising low power wide area network (LPWAN) technologies at present and is expected to grow in the foreseeable future as a tool to provide connectivity among small things. In this paper, we present a simple analytical model to compute the throughput and packet loss probability of Medium Access Control (MAC) for Class-A of LoRaWAN. This analysis results can be used as a reference for deploying the appropriate number of end-devices (EDs) that can be accepted in a gateway (GW) while maximizing network throughput or guaranteeing the packet loss rate of EDs.

Determination of Traffic Characteristics of Elastic Optical Networks Nodes with Reservation Mechanisms

With the ever-increasing demand for bandwidth, appropriate mechanisms that would provide reliable and optimum service level to designated or specified traffic classes during heavy traffic loads in networks are becoming particularly sought after. One of these mechanisms is the resource reservation mechanism, in which parts of the resources are available only to selected (pre-defined) services. While considering modern elastic optical networks (EONs) where advanced data transmission techniques are used, an attempt was made to develop a simulation program that would make it possible to determine the traffic characteristics of the nodes in EONs. This article discusses a simulation program that has the advantage of providing the possibility to determine the loss probability for individual service classes in the nodes of an EON where the resource reservation mechanism has been introduced. The initial assumption in the article is that a Clos optical switching network is used to construct the EON nodes. The results obtained with the simulator developed by the authors will allow the influence of the introduced reservation mechanism on the loss probability of calls of individual traffic classes that are offered to the system under consideration to be determined.

Optical data center switches design and analysis

Data centers are facing huge bottlenecks due to the emergence of high-speed data applications. To meet speed requirements, it is proposed to shift the current technologies toward optical communication-enabled data center (DC) devices. This paper discusses the recently proposed optical switch designs and proposes a novel switch design for optical DCs. The architectures proposed in the literature are compared in terms of notable parameters. Finally, proposed switch performance is measured in the network using Monte Carlo simulation and results are obtained in terms of packet loss probability, under a random traffic model while considering both nonperiodized and prioritized packets.

Vulnerability assessment of nearshore clam habitat subject to storm waves and surge

Present work studied the lesion mechanism of coastal clam and its vulnerability assessment subject to the hydrodynamic disturbance of extreme storm events. A clam habitat at the northeast coast of China was chosen for the demonstration study. Relocation failure after passive transport due to excessive substrate erosion or suffocation in anoxic burial under overburdening sedimentation was identified the major cause of negative biomass responses during the storm. Based on the biological propensity and physiological sensitivity of the clam, a tunable loss probability function correlating the mortality with the shell length and the seabed change was proposed. A hydrodynamic model was then adopted to compute the sediment transport and net changes in the seafloor in response to the comprehensive process of storm waves and surge. The spatial distribution of the damage states was evaluated based on the numerical results incorporating the loss probability function. The estimated damage was mainly concentrated along the wave shoaling and breaking belts parallel to the shoreline. High surge levels pushed the “damage belt” shoreward, in which case large waves were able to propagate close to the shoreline before breaking. The scientific findings are helpful to better understand the vulnerability of the clam habitat to the storm disturbance. The study result as well provides a practical methodology of the storm risk assessment for benthic communities in broader ecological and geophysical scopes. The methodology are expected to be further validated and improved by more widespread sampling on coastal ecosystem or mariculture that will withstand future storms.

RAID Level 6 and Level 6+ Reliability

Storage systems are built of fallible components but have to provide high degrees of reliability. Besides mirroring and triplicating data, redundant storage of information using erasure-correcting codes is the only possibility to have data survive device failure. We provide here exact formula for the data-loss probability of a disk array composed of several RAID Level 6 stripes. This two-failure tolerant is not only used in practice but can also provide a reference point for the assessment of other data organizations

Understanding draws in Elo rating algorithm

This work is concerned with the interpretation of the results produced by the well known Elo algorithm applied in various sport ratings. The interpretation consists in defining the probabilities of the game outcomes conditioned on the ratings of the players and should be based on the probabilistic rating-outcome model. Such a model is known in the binary games (win/loss), allowing us to interpret the rating results in terms of the win/loss probability. On the other hand, the model for the ternary outcomes (win/loss/draw) has not been yet shown even if the Elo algorithm has been used in ternary games from the very moment it was devised. Using the draw model proposed by Davidson in 1970, we derive a new Elo-Davidson algorithm, and show that the Elo algorithm is its particular instance. The parameters of the Elo-Davidson are then related to the frequency of draws which indicates that the Elo algorithm silently assumes games with 50% of draws. To remove this assumption, often unrealistic, the Elo-Davidson algorithm should be used as it improves the fit to the data. The behaviour of the algorithms is illustrated using the results from English Premier League.