Optimisation of Mobile Communication Networks - OMCO NET

The mini conference “Optimisation of Mobile Communication Networks” focuses on advanced methods for search and optimisation applied to wireless communication networks. It is sponsored by Research & Enterprise Fund Southampton Solent University. The conference strives to widen knowledge on advanced search methods capable of optimisation of wireless communications networks. The aim is to provide a forum for exchange of recent knowledge, new ideas and trends in this progressive and challenging area. The conference will popularise new successful approaches on resolving hard tasks such as minimisation of transmit power, cooperative and optimal routing

Using MapReduce Streaming for Distributed Life Simulation on the Cloud

Distributed software simulations are indispensable in the study of large-scale life models but often require the use of technically complex lower-level distributed computing frameworks, such as MPI. We propose to overcome the complexity challenge by applying the emerging MapReduce (MR) model to distributed life simulations and by running such simulations on the cloud. Technically, we design optimized MR streaming algorithms for discrete and continuous versions of Conway’s life according to a general MR streaming pattern. We chose life because it is simple enough as a testbed for MR’s applicability to a-life simulations and general enough to make our results applicable to various lattice-based a-life models. We implement and empirically evaluate our algorithms’ performance on Amazon’s Elastic MR cloud. Our experiments demonstrate that a single MR optimization technique called strip partitioning can reduce the execution time of continuous life simulations by 64%. To the best of our knowledge, we are the first to propose and evaluate MR streaming algorithms for lattice-based simulations. Our algorithms can serve as prototypes in the development of novel MR simulation algorithms for large-scale lattice-based a-life models.https://digitalcommons.chapman.edu/scs_books/1014/thumbnail.jp

Sub-MHz ultrasound for thick section and high attenuation materials.

This thesis described research on materials that exhibit a high degree of attenuation over the sound energy, especially those that are thick and bulky, where penetration of ultrasonic signals becomes difficult. Materials such as viscoelastic polymers, composites (especially multi-layered structures) and also concrete are among the so-called high ultrasonic attenuation materials. Hence, there is a huge need to develop advanced tools, devices and post-processing algorithm that can help to evaluate their integrity. This research thus focused on designing an ultrasonic system which is capable of examining the internal integrity of highly attenuating materials. To reach this aim, an innovative combination of Sub-MHz frequencies (below 1 MHz) excitations in the form of coded waveforms such as chirps and binary coded, together with specifically realized piezo-composite transducers was used for the research activity. The system was then used in combination with advanced signal processing techniques, i.e. pulse compression and other algorithms to enhance the acquired signal quality. Industrial samples of polyurethane structure used in deep-sea oil and gas industries, ceramic bricks used in furnaces, multi-layered structures used in the aerospace industries were tested using the developed system. All the tested samples had different properties that require different approaches during the experiment as well as the data analysis. As a consequence, the research activity focused not only on the use of the innovative sub-MHz inspection system above-described, but also on developing novel algorithms for the data processing tailored for each particular inspected material. It was shown that the system, is capable of revealing anomalies (i.e. cracks, manufacturing and artificial defects) within the tested samples. Furthermore, the advanced signal processing and image reconstruction techniques exploited helped in retrieving the correct shape and dimensions of those defect with respect to the standard imaging procedure. This research work can hopefully be a meaningful contribution towards solving the NDT problems within these industries

A Summary of the Naval Postgraduate School Research Program, 1986

This report contains 227 summaries of research projects which were carried out under funding to the Naval Postgraduate School Research Program. This research was conducted under the areas of Computer Science, Mathematics, Administrative Sciences, Operations Research, National Security Affairs, Physics, Electrical and Computer Engineering, Meteorology, Aeronautics, Oceanography, and Mechanical Engineering. The table of contents identifies specific research topics.Approved for public release; distribution is unlimited

Indoor and Outdoor Location Estimation in Large Areas Using Received Signal Strength

PhDLocation estimation when deployed on wireless networks supports a range of services including user tracking and monitoring, health care support and push and pull marketing. The main subject of this thesis is improving indoor and outdoor location estimation accuracy using received signal strength (RSS) from neighbouring base stations (BSs) or access points (APs), without using the global positioning system (GPS) or triangulation methods. For the outdoor environment, state-of-the-art deterministic and probabilistic algorithms are adapted to exploit principal components (PCs) and clustering. The accuracy is compared with K-nearest neighbour (KNN) algorithms using different partitioning models. The proposed scheme clusters the RSS tuples based on deviations from an estimated RSS attenuation model and then transforms the raw RSS in each cluster into new uncorrelated dimensions, using PCs. As well as simple global dimensionality reduction using PCs, the data reduction and rotation within each cluster improves estimation accuracy because a) each cluster can model the different local RSS distributions and b) it efficiently preserves the RSS correlations that are observed (some of which are substantial) in local regions and which independence approximations ignore. Different simulated and real environments are used for the comparisons. Experimental results show that positioning accuracy is significantly improved and fewer training samples are needed compared with traditional methods. Furthermore, a technique to adjust RSS data so that radio maps collected in different environmental conditions can be used together to enhance accuracy is also demonstrated. Additionally, in the radio coverage domain, a non-parametric probability approach is used for the radio reliability estimation and a semi-supervised learning model is proposed for the monitoring model training and evolution according to real-time mobile users’ RSS feedback. For the indoor environment, an approach for a large multi-story indoor location estimaiii tion using clustering and rank order matching is described. The accuracies using WiFi RSS alone, cellular GSM RSS alone and integrated WiFi and GSM RSS are presented. The methods were tested on real indoor environments. A hierarchical clustering method is used to partition the RSS space, where a cluster is defined as a set of mobile users who share exactly the same strongest RSS ranking set of transmitters. The experimental results show that while integrating of WiFi RSS with GSM RSS creates a marginal improvement, the GSM data can be used to ameliorate the loss of accuracy when AP