Content Scheduling in Multimedia Interactive Mobile Games

In this paper, we study how to implement interactive multimedia services using a DVB-H broadcast channel combined with a point-to-point channel, such as 3G or GPRS. We study the problem in the context of a location-based interactive mobile game. The technical challenge is to schedule the sending of data over the broadcast channel while maintaining Quality-of-Service, that is, sending the right data to the right user at the right time to provide a seamless interactive experience. We explore design issues and problems related to the scheduling of content in the game, present a usecase study to describe scheduling problems and propose a content scheduling algorithm to solve these problems. Moreover, we provide a simulation of the system and the experimental results to show how different game parameters influence the in-time delivery of the multimedia content to the players. We conclude that most of the problems involved with our approach can be expressed as the problem of defining delivery deadlines for a scheduling algorithm

“If you can’t explain it simply, you don’t understand it well enough”

Discrete and disjunctive optimization

Solving Disjunctive Optimization Problems Using Distributed Methods

Disjunctive optimization problems are common in engineering design and operations problems. The disjunctions express the non-continous nature of the problems, where the disjoint subspaces denotes e.g. discrete decisions such selection of equipment. Another typical area is the production planning problem, where the decisions is the internal order of jobs to be performed. The methods presented aims at generelizing the optimizing of disjunctive problems. As all discrete optimization problems, such as Mixed Integer Optimization problems can be written as disjunctive problems the system can reformulate Mixed Interger (MILP) optimization problems as disjunctive optimization problems and solve the using distributed methods. The disjunctive problems are distrubuted and solved on client computers over the internet using standard MILP solvers. The importnat part is the distributing algorithm, that breaks the problem into subproblems for solving in parallel on distributed computer and collects corresponding results. This system can also be integrated to MINLP solvers, that solves MILP problems as subproblems, such as the alphaECP algorithm

EVALUATION OF AN ITERATIVE MATHEMATICAL OPTIMIZATION APPROACH FOR INDUSTRIAL SIZE BATCH SCHEDULING

This paper studies the use of a mathematical programming approach for industrial scale production scheduling. When using mathematical programming for shop floor or batch scheduling, already moderate size scheduling problems lead to Mixed Integer Linear Programs (MILP) that are hard to solve due to combinatorial complexity. In order to cope with this complexity, an iterative optimization method was developed. This iterative method and corresponding mathematical formulation is further extended to handle alternative machines and different objectives. The results are generated and visualized using tailored software for production scheduling. 1

Applying Iterative and Parallel Methods to Production Planning in the Pharmaceutical Industry ABSTRACT

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A Systematic Mapping Study on Edge Computing and Analytics

The vast amount of data provided by the Internet of Things and sensors, have given rise to edge computing and analytics. In edge computing and analytics, data processing and analysis on sensor input is performed in edge devices prior to sending the results to the cloud. This reduces required processing in the cloud while minimizing communication network utilization and allows cloud resources to be used for other tasks such as decision making. In this paper, we present a comprehensive, unbiased overview of state-of-the-art research on edge computing and analytics. Of the 47 identified papers, several have targeted task scheduling and power optimisation, while data management and engineering, image and facial recognition as well as anomaly detection were not well studied. Simulation remains the most used approach for validation, and research results based on implementations of edge systems in real life environments are still sparse.publishedVersionPeer reviewe