Why High-Performance Modelling and Simulation for Big Data Applications Matters

Modelling and Simulation (M&S) offer adequate abstractions to manage the complexity of analysing big data in scientific and engineering domains. Unfortunately, big data problems are often not easily amenable to efficient and effective use of High Performance Computing (HPC) facilities and technologies. Furthermore, M&S communities typically lack the detailed expertise required to exploit the full potential of HPC solutions while HPC specialists may not be fully aware of specific modelling and simulation requirements and applications. The COST Action IC1406 High-Performance Modelling and Simulation for Big Data Applications has created a strategic framework to foster interaction between M&S experts from various application domains on the one hand and HPC experts on the other hand to develop effective solutions for big data applications. One of the tangible outcomes of the COST Action is a collection of case studies from various computing domains. Each case study brought together both HPC and M&S experts, giving witness of the effective cross-pollination facilitated by the COST Action. In this introductory article we argue why joining forces between M&S and HPC communities is both timely in the big data era and crucial for success in many application domains. Moreover, we provide an overview on the state of the art in the various research areas concerned

Localization in wireless sensor networks: classification and evaluation of techniques

Recent advances in technology have enabled the development of low cost, low power and multi functional wireless sensing devices. These devices are networked through setting up a Wireless Sensor Network (WSN). Sensors that form a WSN are expected to be remotely deployed in large numbers and to self-organize to perform distributed sensing and acting tasks. WSNs are growing rapidly in both size and complexity, and it is becoming increasingly difficult to develop and investigate such large and complex systems. In this paper we provide a brief introduction to WSN applications, i.e., properties, limitations and basic issues related to WSN design and development. We focus on an important aspect of the design: accurate localization of devices that form the network. The paper presents an overview of localization strategies and attempts to classify different techniques. A set of properties by which localization systems are evaluated are examined. We then describe a number of existing localization systems, and discuss the results of performance evaluation of some of them through simulation and experiments using a testbed implementation

A federated approach to parallel and distributed simulation of complex systems

The paper describes a Java-based framework called ASimJava that can be used to develop parallel and distributed simulators of complex real-life systems. Some important issues associated with the implementation of parallel and distributed simulations are discussed. Two principal paradigms for constructing simulations today are considered. Particular attention is paid to an approach for federating parallel and distributed simulators. We describe the design, performance and applications of the ASimJava framework. Two practical examples, namely, a simple manufacturing system and computer network simulations are provided to illustrate the effectiveness and range of applications of the presented software tool

Optimization schemes for wireless sensor network localization

Many applications of wireless sensor networks (WSN) require information about the geographical location of each sensor node. Self-organization and localization capabilities are one of the most important requirements in sensor networks. This paper provides an overview of centralized distance-based algorithms for estimating the positions of nodes in a sensor network. We discuss and compare three approaches: semidefinite programming, simulated annealing and two-phase stochastic optimization-a hybrid scheme that we have proposed. We analyze the properties of all listed methods and report the results of numerical tests. Particular attention is paid to our technique-the two-phase method-that uses a combination of trilateration, and stochastic optimization for performing sensor localization. We describe its performance in the case of centralized and distributed implementations

Multiobjective Approach to Localization in Wireless Sensor Networks

Wireless sensor network localization is a complex problem that can be solved using different types of methods and algorithms. Nowadays, it is a popular research topic. What becomes obvious is that there are several criteria which are essential when we consider wireless sensor networks. Our objective is to determine accurate estimates of nodes location under the constraints for hardware cost, energy consumption and computation capabilities. In this paper the application of stochastic optimization for performing localization of nodes is discussed. We describe two phase scheme that uses a combination of the trilateration method, along with the simulated annealing optimization algorithm. We investigate two variants of our technique, i.e., centralized and distributed. The attention is paid to the convergence of our algorithm for different network topologies and trade-off between its efficiency and localization accuracy

A Software Platform for Global Optimization

This paper addresses issues associated with the global optimization algorithms, which are methods to find optimal solutions for given problems. It focuses on an integrated software environment - global optimization object-oriented library (GOOL), which provides the graphical user interface together with the library of solvers for convex and nonconvex, unconstrained and constrained problems. We describe the design, performance and possible applications of the GOOL system. The practical example - price management problem - is provided to illustrate the effectiveness and range of applications of our software tool

Heavy Gas Cloud Boundary Estimation and Tracking using Mobile Sensors

This paper addresses issues concerned with design and managing of monitoring systems comprised of mobile wireless sensing devices (MANETs). The authors focus on self-organizing, cooperative and coherent networks that maintain a continuous communication with a central operator and adopt to changes in an unknown environment to achieve a given goal. The attention is focused on the development of MANET for heavy gas clouds detection and its boundary estimating and tracking. Two strategies for constructing the MANET are described, in which sensors explore the region of interest to detect the gas cloud, create temporary network topology and finally, cover the cloud boundary, and track the moving cloud. The utility and efficiency of the proposed strategies has been justified through simulation experiments