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- All Subjects: Computer Engineering
- Genre: Academic theses
- Status: Published
Description
Imagine that we have a piece of matter that can change its physical properties like its shape, density, conductivity, or color in a programmable fashion based on either user input or autonomous sensing. This is the vision behind what is commonly known as programmable matter. Envisioning systems of nano-sensors devices, programmable matter consists of systems of simple computational elements, called particles, that can establish and release bonds, compute, and can actively move in a self-organized way. In this dissertation the feasibility of solving fundamental problems relevant for programmable matter is investigated. As a model for such self-organizing particle systems (SOPS), the geometric amoebot model is introduced. In this model, particles only have local information and have modest computational power. They achieve locomotion by expanding and contracting, which resembles the behavior of amoeba. Under this model, efficient local-control algorithms for the leader election problem in SOPS are presented. As a central problem for programmable matter, shape formation problems are then studied. The limitations of solving the leader election problem and the shape formation problem on a more general version of the amoebot model are also discussed. The \smart paint" problem is also studied which aims at having the particles self-organize in order to uniformly coat the surface of an object of arbitrary shape and size, forming multiple coating layers if necessary. A Universal Coating algorithm is presented and shown to be asymptotically worst-case optimal both in terms of time with high probability and work. In particular, the algorithm always terminates within a linear number of rounds with high probability. A linear lower bound on the competitive gap between fully local coating algorithms and coating algorithms that rely on global information is presented, which implies that the proposed algorithm is also optimal in a competitive sense. Simulation results show that the competitive ratio of the proposed algorithm may be better than linear in practice. Developed algorithms utilize only local control, require only constant-size memory particles, and are asymptotically optimal in terms of the total number of particle movements needed to reach the desired shape configuration.
ContributorsDerakhshandeh, Zahra (Author) / Richa, Andrea (Thesis advisor) / Sen, Arunabha (Thesis advisor) / Xue, Guoliang (Committee member) / Scheideler, Christian (Committee member) / Arizona State University (Publisher)
Created2017
Description
Mobile and Internet-of-Things (IoT) systems have been widely used in many aspects
of human’s life. These systems are storing and operating on more and more sensitive
data of users. Attackers may want to obtain the data to peek at users’ privacy or
pollute the data to cause system malfunction. In addition, these systems are not
user-friendly for some people such as children, senior citizens, and visually impaired
users. Therefore, it is of cardinal significance to improve both security and usability
of mobile and IoT systems. This report consists of four parts: one automatic locking
system for mobile devices, one systematic study of security issues in crowdsourced
indoor positioning systems, one usable indoor navigation system, and practical attacks
on home alarm IoT systems.
Chapter 1 overviews the challenges and existing solutions in these areas. Chapater
2 introduces a novel system ilock which can automatically and immediately lock the
mobile devices to prevent data theft. Chapter 3 proposes attacks and countermeasures
for crowdsourced indoor positioning systems. Chapter 4 presents a context-aware indoor
navigation system which is more user-friendly for visual impaired people. Chapter
5 investigates some novel attacks on commercial home alarm systems. Chapter 6
concludes the report and discuss the future work.
of human’s life. These systems are storing and operating on more and more sensitive
data of users. Attackers may want to obtain the data to peek at users’ privacy or
pollute the data to cause system malfunction. In addition, these systems are not
user-friendly for some people such as children, senior citizens, and visually impaired
users. Therefore, it is of cardinal significance to improve both security and usability
of mobile and IoT systems. This report consists of four parts: one automatic locking
system for mobile devices, one systematic study of security issues in crowdsourced
indoor positioning systems, one usable indoor navigation system, and practical attacks
on home alarm IoT systems.
Chapter 1 overviews the challenges and existing solutions in these areas. Chapater
2 introduces a novel system ilock which can automatically and immediately lock the
mobile devices to prevent data theft. Chapter 3 proposes attacks and countermeasures
for crowdsourced indoor positioning systems. Chapter 4 presents a context-aware indoor
navigation system which is more user-friendly for visual impaired people. Chapter
5 investigates some novel attacks on commercial home alarm systems. Chapter 6
concludes the report and discuss the future work.
ContributorsLi, Tao (Author) / Zhang, Yanchao (Thesis advisor) / Xue, Guoliang (Committee member) / Zhang, Junshan (Committee member) / Fan, Deliang (Committee member) / Arizona State University (Publisher)
Created2020