Real-Time and Energy-Efficient Routing for Industrial Wireless Sensor-Actuator Networks

With the emergence of industrial standards such as WirelessHART, process industries are adopting Wireless Sensor-Actuator Networks (WSANs) that enable sensors and actuators to communicate through low-power wireless mesh networks. Industrial monitoring and control applications require real-time communication among sensors, controllers and actuators within end-to-end deadlines. Deadline misses may lead to production inefficiency, equipment destruction to irreparable financial and environmental impacts. Moreover, due to the large geographic area and harsh conditions of many industrial plants, it is labor-intensive or dan- gerous to change batteries of field devices. It is therefore important to achieve long network lifetime with battery-powered devices. This dissertation tackles these challenges and make a series of contributions. (1) We present a new end-to-end delay analysis for feedback control loops whose transmissions are scheduled based on the Earliest Deadline First policy. (2) We propose a new real-time routing algorithm that increases the real-time capacity of WSANs by exploiting the insights of the delay analysis. (3) We develop an energy-efficient routing algorithm to improve the network lifetime while maintaining path diversity for reliable communication. (4) Finally, we design a distributed game-theoretic algorithm to allocate sensing applications with near-optimal quality of sensing

Theoretical Exploration on the Magnetic Properties of Ferromagnetic Metallic Glass: An Ising Model on Random Recursive Lattice

The ferromagnetic Ising spins are modeled on a recursive lattice constructed from random-angled rhombus units with stochastic configurations, to study the magnetic properties of the bulk Fe-based metallic glass. The integration of spins on the structural glass model well represents the magnetic moments in the glassy metal. The model is exactly solved by the recursive calculation technique. The magnetization of the amorphous Ising spins, i.e. the glassy metallic magnet is investigated by our modeling and calculation on a theoretical base. The results show that the glassy metallic magnets has a lower Curie temperature, weaker magnetization, and higher entropy comparing to the regular ferromagnet in crystal form. These findings can be understood with the randomness of the amorphous system, and agrees well with others' experimental observations.Comment: 11 pages, 5 figure

BotShape: A Novel Social Bots Detection Approach via Behavioral Patterns

An essential topic in online social network security is how to accurately detect bot accounts and relieve their harmful impacts (e.g., misinformation, rumor, and spam) on genuine users. Based on a real-world data set, we construct behavioral sequences from raw event logs. After extracting critical characteristics from behavioral time series, we observe differences between bots and genuine users and similar patterns among bot accounts. We present a novel social bot detection system BotShape, to automatically catch behavioral sequences and characteristics as features for classifiers to detect bots. We evaluate the detection performance of our system in ground-truth instances, showing an average accuracy of 98.52% and an average f1-score of 96.65% on various types of classifiers. After comparing it with other research, we conclude that BotShape is a novel approach to profiling an account, which could improve performance for most methods by providing significant behavioral features.Comment: CDKP 202