Dynamically Adjusting the Mining Capacity in Cryptocurrency with Binary Blockchain

Many cryptocurrencies rely on Blockchain for its operation. Blockchain serves as a public ledger where all the completed transactions can be looked up. To place transactions in the Blockchain, a mining operation must be performed. However, due to a limited mining capacity, the transaction confirmation time is increasing. To mitigate this problem many ideas have been proposed, but they all come with own challenges. We propose a novel parallel mining method that can adjust the mining capacity dynamically depending on the congestion level. It does not require an increase in the block size or a reduction of the block confirmation time. The proposed scheme can increase the number of parallel blockchains when the mining congestion is experienced, which is especially effective under DDoS attack situation. We describe how and when the Blockchain is split or merged, how to solve the imbalanced mining problem, and how to adjust the difficulty levels and rewards. We then show the simulation results comparing the performance of binary blockchain and the traditional single blockchain

Study of Potential Integrated Management of Water Resources in Las Vegas Valley

Water resource management under short term system perturbations such as storms and longer-term systemic changes caused by climate change such as droughts is a challenge when multiple agencies are involved. To address this challenge this research focuses on water management under changing climate conditions and population growth through understanding the agency water jurisdictions, management strategies, and modes of operation in Las Vegas Valley. A framework for integrated management through sharing data and models is presented that combines drinking water supply, flood control, and waste water treatment. This framework can be adopted to improve coordination among different water management agencies

A Consumer Level Simulation Model For Demand Response Analysis On Smart Grid

With the growing awareness of the need for Smart Grid, various countries are taking initiatives for developing Smart Grid. However, there is limited research on utilizing Smart Grid for Demand-Response (DR). This study advances the current system of DR by creating a Smart Grid Simulator that allows an intuitive demand response analysis. The simulator demonstrates that substantial amount of electric power can be reduced efficiently by selective demand control over Smart Grid. The graphical interface allows generating the electrical usage data and displays both individual and aggregate usage data over time. This research employs U.S. census data for accurate estimate of family and life style as electric power usage is simulated by taking various inputs including the number of houses, family size, work and life patterns, etc. This study explores potential Privacy issues in Smart Grid and suggests data anonymization as a viable solution for preventing them. Moreover, this study proposes directions for future research on electric devices control using Smart Grid Simulator

Hadoop Performance Analysis Model with Deep Data Locality

Background: Hadoop has become the base framework on the big data system via the simple concept that moving computation is cheaper than moving data. Hadoop increases a data locality in the Hadoop Distributed File System (HDFS) to improve the performance of the system. The network traffic among nodes in the big data system is reduced by increasing a data-local on the machine. Traditional research increased the data-local on one of the MapReduce stages to increase the Hadoop performance. However, there is currently no mathematical performance model for the data locality on the Hadoop. Methods: This study made the Hadoop performance analysis model with data locality for analyzing the entire process of MapReduce. In this paper, the data locality concept on the map stage and shuffle stage was explained. Also, this research showed how to apply the Hadoop performance analysis model to increase the performance of the Hadoop system by making the deep data locality. Results: This research proved the deep data locality for increasing performance of Hadoop via three tests, such as, a simulation base test, a cloud test and a physical test. According to the test, the authors improved the Hadoop system by over 34% by using the deep data locality. Conclusions: The deep data locality improved the Hadoop performance by reducing the data movement in HDFS

Privacy-preserving Data Mining on Hospitality Big Data

In this paper we present a summary of our activity associated with the security and encryption the big data on the hotels big data. We give a brief introduction to some techniques for security the data set in large scale, we then look into the homomorphism and Map Reduce environment. With the advances in computer architecture and silicon technology, processing large data set becomes possible after some fundamental data storage and processing algorithm been proposed and implemented. Analyzing the big data opened many opportunities for scientists in different research and application areas. Hospitality industry, for example, collects and keeps customers information, which proposed some significant challenges to be addressed. The first challenge how to save and keep all these massive data set; and the second challenge is securing this sensitive information. In this paper we will discuss Parallel Homomorphic Encryption (PHE) security method which can be used in companies’ information storage, processing and management

sUTM System API at UNLV: Small UAS Traffic Management System API

This file contains the set of APIs for small unmanned aircraft systems (UAS) Traffic Management (sUTM). The sUTM server hosts a web service that allows any software or device that can use the Internet to utilize the server’s sUAS traffic management (sUTM) functions through these application programming interfaces (API). This library was developed as part of the MS thesis by Monetta Shaw in Spring 2016, A web based solution for small unmanned aircraft systems (sUAS) traffic management . The summary of the library and its usage instructions are described in the thesis

Research poster: HTSMA: a hybrid temporal-spatial multi-channel assignment scheme in heterogeneous wireless mesh networks

Research poste

Measurement of Human Walking Movements by Using a Mobile Health App: Motion Sensor Data Analysis

Background: This study presents a new approach to measure and analyze the walking balance of humans by collecting motion sensor data in a smartphone. Objective: We aimed to develop a mobile health (mHealth) app that can measure the walking movements of human individuals and analyze the differences in the walking movements of different individuals based on their health conditions. A smartphone\u27s motion sensors were used to measure the walking movements and analyze the rotation matrix data by calculating the variation of each xyz rotation, which shows the variables in walking-related movement data over time. Methods: Data were collected from 3 participants, that is, 2 healthy individuals (1 female and 1 male) and 1 male with back pain. The participant with back pain injured his back during strenuous exercise but he did not have any issues in walking. The participants wore the smartphone in the middle of their waistline (as the center of gravity) while walking. They were instructed to walk straight at their own pace in an indoor hallway of a building. The walked a distance of approximately 400 feet. They walked for 2-3 minutes in a straight line and then returned to the starting location. A rotation vector in the smartphone, calculated by the rotation matrix, was used to measure the pitch, roll, and yaw angles of the human body while walking. Each xyz-rotation vector datum was recalculated to find the variation in each participant\u27s walking movement. Results: The male participant with back pain showed a diminished level of walking balance with a wider range of xyz-axis variations in the rotations compared to those of the healthy participants. The standard deviation in the xyz-axis of the male participant with back pain was larger than that of the healthy male participant. Moreover, the participant with back pain had the widest combined range of right-to-left and forward-to-backward motions. The healthy male participant showed smaller standard deviation while walking than the male participant with back pain and the female healthy participant, indicating that the healthy male participant had a well-balanced walking movement. The walking movement of the female healthy participant showed symmetry in the left-to-right (x-axis) and up-to-down (y-axis) motions in the x-y variations of rotation vectors, indicating that she had lesser bias in gait than the others. Conclusions: This study shows that our mHealth app based on smartphone sensors and rotation vectors can measure the variations in the walking movements of different individuals. Further studies are needed to measure and compare walking movements by age, gender, as well as types of health problems or disease. This app can help in finding differences in gait in people with diseases that affect gait

New Power Saving Algorithm Considering Associated STAs and Consecutive Traffics in WLAN AP

Recently, as the use of wireless Internet increases, access point (AP) installation has increased rapidly, only to increase the total power consumed by AP in wireless local area network (WLAN). Because an AP always wakes up regardless of the real use, the unnecessary power by the AP may be consumed. If we consider environments such as office or home, where an AP is used during certain hours of a day, an enormous amount of power waste may occur. This increase of power waste is contrary to the trend to reduce the cost of power production, and has a negative influence on natural environments. Therefore, it is necessary to improve the power efficiency; i.e., the power consumed by the AP need to be reduced. In this paper, we propose a power saving algorithm according to the existence of associated stations (STAs) and consecutive traffics in WLAN. The proposed algorithm applies a new sleep state to WLAN AP. According to the analysis result, the proposed algorithm consumes less power approximately 29% than the conventional (not using power saving algorithm)