Decomposition Algorithms for Stochastic Programming on a Computational Grid

We describe algorithms for two-stage stochastic linear programming with recourse and their implementation on a grid computing platform. In particular, we examine serial and asynchronous versions of the L-shaped method and a trust-region method. The parallel platform of choice is the dynamic, heterogeneous, opportunistic platform provided by the Condor system. The algorithms are of master-worker type (with the workers being used to solve second-stage problems, and the MW runtime support library (which supports master-worker computations) is key to the implementation. Computational results are presented on large sample average approximations of problems from the literature.Comment: 44 page

On-Demand Employment, Worker Misclassification, and Labor Standards

[Excerpt] On-demand platform work, like other forms of contingent and temporary employment, destabilizes industries, undermines worker protections and living standards, and significantly contributes to wealth and income inequality

Employment and Working Conditions of Selected Types of Platform Work

Platform work is a form of employment that uses an online platform to match the supply of and demand for paid labour. In Europe, platform work is still small in scale but is rapidly developing. The types of work offered through platforms are ever-increasing, as are the challenges for existing regulatory frameworks. This report explores the working and employment conditions of three of the most common types of platform work in Europe. For each of these types, Eurofound assesses the physical and social environment, autonomy, employment status and access to social protection, and earnings and taxation based on interviews with platform workers. A comparative analysis of the regulatory frameworks applying to platform work in 18 EU Member States accompanies this review. This looks into workers’ employment status, the formal relationships between clients, workers and platforms, and the organisation and representation of workers and platforms

A fine-grain time-sharing Time Warp system

Although Parallel Discrete Event Simulation (PDES) platforms relying on the Time Warp (optimistic) synchronization protocol already allow for exploiting parallelism, several techniques have been proposed to further favor performance. Among them we can mention optimized approaches for state restore, as well as techniques for load balancing or (dynamically) controlling the speculation degree, the latter being specifically targeted at reducing the incidence of causality errors leading to waste of computation. However, in state of the art Time Warp systems, events’ processing is not preemptable, which may prevent the possibility to promptly react to the injection of higher priority (say lower timestamp) events. Delaying the processing of these events may, in turn, give rise to higher incidence of incorrect speculation. In this article we present the design and realization of a fine-grain time-sharing Time Warp system, to be run on multi-core Linux machines, which makes systematic use of event preemption in order to dynamically reassign the CPU to higher priority events/tasks. Our proposal is based on a truly dual mode execution, application vs platform, which includes a timer-interrupt based support for bringing control back to platform mode for possible CPU reassignment according to very fine grain periods. The latter facility is offered by an ad-hoc timer-interrupt management module for Linux, which we release, together with the overall time-sharing support, within the open source ROOT-Sim platform. An experimental assessment based on the classical PHOLD benchmark and two real world models is presented, which shows how our proposal effectively leads to the reduction of the incidence of causality errors, as compared to traditional Time Warp, especially when running with higher degrees of parallelism

Virtual teams: a new opportunity to develop a business

Virtual teams give many advantages to organizations, including increased knowledge sharing and improve organizational performance. Virtual teams have altered the expectations and boundaries of knowledge worker?s interactions and make a new opportunity to develop the business. In this paper, we present summary results of an online survey. The online questionnaire was emailed by using a simple random sampling method to 356 Malaysian manufacturing small and medium ?sized Enterprises (SMEs). The findings of this study show that SMEs in Malaysia are gaining to use virtual teams, and it can be concluded that virtual teams provide a new platform for developing the business in SMEs. Based on the study, we suggest avenues for future research that are important to advancing our understanding of virtual team effects on business growth