Generic remote communication systems for the factories of the future

This paper reports on the benefits of the remote communication systems and presents two prototype systems for communication with microprocessor based machines and devices including household appliances. The wireless prototype version can also be used in remote and wireless programming of any device with a microprocessor or microcontroller. It is a known fact that the researchers often become too embraced with technical breakthroughs and forget about communicating with the audience for whom the findings of their research is intended. To this end, initial emphasis is on the benefits of the systems, but later in the paper the technical merits of the research work are explained. The prime aim of the project has been to develop the know-how for remote programming, control and up-dating of programs in microcontroller based devices using wired and wireless techniques. An earlier wireless communication system using laser encapsulation techniques developed for a factory of the future site [1] was revisited with a view to incorporate the latest technologies where appropriate. The earlier system adopting Code Division Multi Access with a Pseudo Random Noise Spectrum (CDMA-PRNS) incorporating wideband Spread Spectrum (SS) using Hierarchical Genetic Algorithm (HGA) was found to provide a basis for establishing a working Wireless Local Area Network (WLAN) for many applications including in the manufacturing, where noise has been a problem for their use

Coverage in WLAN with minimum number of access points

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Optimal placement of access point in WLAN based on a new algorithm

When designing wireless communication systems, it is very important to know the optimum numbers and locations for the access points (APs). The impact of incorrect placement of APs is significant. If they are placed too far apart, they will generate a coverage gap, but if they are too close to each other, this will lead to excessive co-channel interferences. In this paper we describe a mathematical model developed to find the optimal number and location of APs. To solve the problem, we use the Discrete Gradient optimization algorithm developed at the University of Ballarat. Results indicate that our model is able to solve optimal coverage problems for different numbers of users

Optimization of Heterogeneous UAV Communications Using the Multiobjective Quadratic Assignment Problem

The Air Force has placed a high priority on developing new and innovative ways to use Unmanned Aerial Vehicles (UAVs). The Defense Advanced Research Projects Agency (DARPA) currently funds many projects that deal with the advancement of UAV research. The ultimate goal of the Air Force is to use UAVs in operations that are highly dangerous to pilots, mainly the suppression of enemy air defenses (SEAD). With this goal in mind, formation structuring of autonomous or semi-autonomous UAVs is of future importance. This particular research investigates the optimization of heterogeneous UAV multi-channel communications in formation. The problem maps to the multiobjective Quadratic Assignment Problem (mQAP). Optimization of this problem is done through the use of a Multiobjective Evolutionary Algorithm (MOEA) called the Multiobjective Messy Genetic Algorithm - II (MOMGA-II). Experimentation validates the attainment of an acceptable Pareto Front for a variety of mQAP benchmarks. It was observed that building block size can affect the location vectors along the current Pareto Front. The competitive templates used during testing perform best when they are randomized before each building block size evaluation. This tuning of the MOMGA-II parameters creates a more effective algorithm for the variety of mQAP benchmarks, when compared to the initial experiments. Thus this algorithmic approach would be useful for Air Force decision makers in determining the placement of UAVs in formations