Future Industrial Internet-of-Things (IIoT) systems will require wireless solutions to connect sensors, actuators, and controllers as part of high data rate feedback-control loops over real-time flows. A key challenge in such networks is to provide predictable performance and adaptability in response to link quality variations. We address this challenge by developing RECeiver ORiented Policies (Recorp), which leverages the stability of IIoT workloads by combining offline policy synthesis and run-time adaptation. Compared to schedules that service a single flow in a slot, Recorp policies share slots among multiple flows by assigning a coordinator and a list of flows that may be serviced in the same slot. At run-time, the coordinator will execute one of the flows depending on which flows the coordinator has already received. A salient feature of Recorp is that it provides predictable performance: a policy meets the end-to-end reliability and deadline of flows when the link quality exceeds a user-specified threshold. Experiments show that across IIoT workloads, policies provided a median increase of 50% to 142% in real-time capacity and a median decrease of 27% to 70% in worst-case latency when schedules and policies are configured to meet an end-to-end reliability of 99%.

Basis Pursuit DeNoising (BPDN) is a version of sparse least squares, where there is an ℓ1penalty for the coefficients in addition to the sum of squares of the errors. To apply this technique to large data sets, parallel algorithms are needed. In this paper, we create a parallel version of a BPDN algorithm [11] that can compute exact solutions for an interval of values for the ℓ1penalty parameter that exploits the sparsity of the solutions, unlike stochastic gradient descent-type algorithms.

Abstract In this work we propose a new discretization method for the Laplace–Beltrami operator defined on point‐based surfaces. In contrast to the existing point‐based discretization techniques, our approach does not rely on any triangle mesh structure, turning out truly mesh‐free. Based on a combination of Smoothed Particle Hydrodynamics and an optimization procedure to estimate area elements, our discretization method results in accurate solutions while still being robust when facing abrupt changes in the density of points. Moreover, the proposed scheme results in numerically stable discrete operators. The effectiveness of the proposed technique is brought to bear in many practical applications. In particular, we use the eigenstructure of the discrete operator for filtering and shape segmentation. Point‐based surface deformation is another application that can be easily carried out from the proposed discretization method.

For a collection of sets in R d we consider the task of finding all sets in the collection that contain a given point. The parallel algorithm introduced in this paper is based on quadtrees and their generalizations to R d . Our algorithm solves a difficult problem faced by meshfree discretizations, and is based on the sequential algorithm of Han, Oliveira, and Stewart [3].

In this paper a new time-stepping method for simulating systems of rigid bodies is given. Unlike methods which take an instantaneous point of view, our method is based on impulse-momentum equations, and so does not need to explicitly resolve impulsive forces. On the other hand, our method is distinct from previous impulsive methods in that it does not require explicit collision checking and it can handle simultaneous impacts. Numerical results are given for one planar and one three dimensional example, which demonstrate the practicality of the method, and its convergence as the step size becomes small.

For a collection of sets in R d we consider the task of finding all sets in the collection that cover or contain a given point. The algorithms introduced in this paper are based on quadtrees and their generalizations to R d . The advantages of our new splitting algorithm to find the covering sets of a point over the basic algorithm are detailed by means of hit rates and the expected depth traversed in the quadtree search, numerically and theoretically. This solves a difficult problem faced by mesh-free discretizations of partial differential equations.

Homotopy algorithms to solve a nonlinear system of equations f(x) = 0 involve tracking the zero curve of a homotopy map p(a, λ, x) from λ = 0 until λ = 1. When the algorithm nears or crosses the hyperplane λ = 1, an “end game” phase is begun to compute the solution x¯ satisfying p(a, λ, x¯) = f(x¯) = 0. This note compares several end game strategies, including the one implemented in the normal flow code FIXPNF in the homotopy software package HOMPACK.