RSSI and LQI Data Clustering Techniques to Determine the Number of Nodes in Wireless Sensor Networks

With the rapid proliferation of wireless sensor networks, different network topologies are likely to exist in the same geographical region, each of which is able to perform its own functions individually. However, these networks are prone to cause interference to neighbor networks, such as data duplication or interception. How to detect, determine, and locate the unknown wireless topologies in a given geographical area has become a significant issue in the wireless industry. This problem is especially acute in military use, such as spy-nodes detection and communication orientation systems. In this paper, three different clustering methods are applied to classify the RSSI and LQI data recorded from the unknown wireless topology into a certain number of groups in order to determine the number of active sensor nodes in the unknown wireless topology. The results show that RSSI and LQI data are capable of determining the number of active communication nodes in wireless topologies

System for Detection of Malicious Wireless Device Patterns

The research within presents the use of Hidden Markov Models (HMM) for the detection of wireless devices in highly noisy environments using their unintended electromagnetic emissions (UEE). All electromagnetic devices emit such radiation that is unique to the electronics, housing, and other device attributes. This pattern recognition system can provide continuous detection analysis and can provide ideal information regarding the distance to an unknown device. An experiment was performed where UEE of a device was detected by a spectrum analyzer. Experimental result shows that our model can accurately detect if there is a device nearby emitting UEE or not

Using Social Networking Game to Teach Operations Research and Management Science Fundamental Concepts

This paper presents our experience using the popular game FarmVille by Zynga® to teach the fundamentals of linear programming and integer programming concepts to undergraduate students in an introductory operations research course. FarmVille is a popular game within the social networking website Facebook®. A month-long contest was introduced amongst the students with the goal to be the best individual farmer by striving to reach high levels of revenue, experience, and aesthetic appeal of their own unique farm. The contest is to demonstrate the concepts of problem formulation, solution methods, multiple and competing objectives, implementation of policy, and reformulation. The students were surveyed at the beginning of the semester to gain insight into their perceptions of the course. The students were also surveyed regarding the FarmVille Challenge, to gauge the effectiveness of the pedagogy and students\u27 opinions of the hand on approach. The paper demonstrates through surveyed results that the students favored this instruction. The students surveyed agree that this was an engaging and thought provoking exercise and saw the true application of multiple key fundamentals of operations research

Transceivers as a Resource: Scheduling Time and Bandwidth in Software-Defined Radio

In the future, software-defined radio may enable a mobile device to support multiple wireless protocols implemented as software applications. These applications, often referred to as waveform applications, could be added, updated, or removed from a software-radio device to meet changing demands. Current software-defined radio solutions grant an active waveform exclusive ownership of a specific transceiver or analog front-end. Since a wireless device has a limited number of front-ends, this approach puts a hard constraint on the number of concurrent waveform applications a device can support. A growing trend in software-defined radio research is to virtualize front-ends to allow sharing and reuse among active waveform applications. This poses a difficult scheduling challenge. This article proposes a new approach in which shared access to front-ends is managed by a mixed-integer linear programming model. This model ties together the technique of time-division sharing and front-end bandwidth channelization. This scheduling model is evaluated in simulation under several different scenarios and workloads. Simulation results show that the proposed approach reduces hardware contention and missed radio accesses compared to existing techniques

Strategies for Using Technology When Grading Problem-Based Classes

More and more work is being done today using technology. Email and digital drop boxes are useful tools for professors; however the challenge comes when one is teaching a quantitative class. The issue of using technology to manage work in a quantitative class is increasing as more engineering programs embrace distance education. In this paper we will review the advantages and disadvantages of several methods of collecting, grading, and returning homework assignments to students. The techniques considered include faxing, PDF grading using a Wacom Tablet, and various email approaches. Student survey results are also included in the paper

Two-Semester Agile Systems Engineering Design Course: Investigation and Exploration of Immersive Training Technologies

The teaching of systems engineering is a daunting task that involves the development of curriculum capable of teaching students the systems engineering process, the design aspects of engineering, and the interdisciplinary knowledge of a variety of fields. Design is widely considered to be the central or the major distinguishing activity of engineering1. Design can be considered as the center of system engineering, in which engineers employ an interdisciplinary approach to design effective solutions to meet social needs. However, systems engineering requires that traditional academic boundaries be crossed and intertwined with other fields of engineering as well as business, socio-political, and other disciplines that clearly interacts with or are directly affected by the system under consideration. Systems engineering requires different design thinking, as it requires in depth knowledge often beyond the traditional engineering classification boundaries. For example, an electrical engineer must also in many cases have knowledge of software engineering, or safety engineering when designing a cell phone circuit

Classification of Rest and Active Periods in Actigraphy Data using PCA

In this paper we highlight a clustering algorithm for the purpose of identifying sleep and wake periods directly from actigraphy signals. The paper makes use of statistical Principal Component Analysis to identify periods of rest and activity. The aim of the proposed methodology is to develop a quick and efficient method to determine the sleep duration of an individual. In addition, a robust method that can identify sleep periods in the accelerometer data when duration, time of day varies by individual. A selected group of 10 individual\u27s sensor data consisting of actigraphy from an accelerometer (3-axis), near body temperature, and lux sensors from a single GENEActiv watch worn on the non-dominant hand. The actigraphy of each individual was collected 24 hours a day for a period spanning 80 days. We highlight that a simple data preprocessing stage followed with a 2 phase clustering method provides results that align with previously validated methodologies

Enhancing Undergraduate Engineering Education of Lean Methods using Simulation Learning Modules Within a Virtual Environment

This paper highlights the use of an integrated user-centered virtual learning environment throughextensible simulation learning modules that is currently being developed to enhance undergraduate curricula to meet the industrial needs for engineers with education in lean. The purpose of the research is to address these expectations by developing learning modules that incorporate lean simulation models into various Engineering Management, Industrial Engineering, and Mechanical Engineering courses at Missouri S&T, Texas Tech, and South Dakota State, respectively. In recent years, increasing global competition, rapidly changing technology, and a deficit of U.S. engineering graduates have intensified the need to produce graduating engineers who are effective problem solvers and analytical thinkers, yet who can also collaborate on interdisciplinary teams to address complex, real-world systems. A key area of competence for many engineering undergraduate, as well as graduate, disciplines is the application of structured problem solving methods, e.g., lean, to improve the performance of organizational processes. This virtual learning environment will enhance undergraduate engineering education by utilizing technology as a learning tool in lean, by fostering student development through active learning in the classroom, and through projects based on current real-world challenges, thus improving student learning, motivation, and retention. The paper highlights the learning modules to be developed in the virtual learning environment. The long-term goal is to evaluate the impact of the curriculum changes on student learning, outreach, and industrial collaboration

Shape Analysis of Traffic Flow Curves using a Hybrid Computational Analysis

This paper highlights and validates the use of shape analysis using Mathematical Morphology tools as a means to develop meaningful clustering of historical data. Furthermore, through clustering more appropriate grouping can be accomplished that can result in the better parameterization or estimation of models. This results in more effective prediction model development. Hence, in an effort to highlight this within the research herein, a Back-Propagation Neural Network is used to validate the classification achieved through the employment of MM tools. Specifically, the Granulometric Size Distribution (GSD) is used to achieve clustering of daily traffic flow patterns based solely on their shape. To ascertain the significance of shape in traffic analysis, a comparative classification analysis of original data and GSD transformed data is carried out. The results demonstrate the significance of functional shape in traffic analysis. In addition, the results validate the need for clustering prior to prediction. It is determined that a span of two through four years of traffic data is found sufficient for training to produce satisfactory BPNN performance

Mitigating the stochastic effects of fading in mobile wireless ad-hoc networks

This research considers the impact of fast fading effects on the discovery and maintenance of communication routes in mobile wireless ad-hoc networks. Moreover, it is a upon this consideration that fast fading directly impacts the performance of the underlying communication protocols for such networks. It is illustrated herein that protocol design should be based upon the consideration of the operating environments to which such networks are deployed. This research provides a statistical interpretation of link quality based on the instantaneous received power under various multi-path fading models, for which associated Type 1 and 2 errors are defined. Based on this viewpoint, this document proposes the embedding GPS information into a protocol in order to block the inclusion of unreliable links within the route of communication. This implementation results in a dramatic enhancement of the end-to-end performance of the mobile wireless ad-hoc communication network. Thus, this dissertation presents a general introduction to wireless communication networks and their inherent issues, and elaborates in detail this new statistical interpretation of fast fading and the results obtained from employing GPS information to realize an efficient protocol design methodology