Location based services in wireless ad hoc networks

In this dissertation, we investigate location based services in wireless ad hoc networks from four different aspects - i) location privacy in wireless sensor networks (privacy), ii) end-to-end secure communication in randomly deployed wireless sensor networks (security), iii) quality versus latency trade-off in content retrieval under ad hoc node mobility (performance) and iv) location clustering based Sybil attack detection in vehicular ad hoc networks (trust). The first contribution of this dissertation is in addressing location privacy in wireless sensor networks. We propose a non-cooperative sensor localization algorithm showing how an external entity can stealthily invade into the location privacy of sensors in a network. We then design a location privacy preserving tracking algorithm for defending against such adversarial localization attacks. Next we investigate secure end-to-end communication in randomly deployed wireless sensor networks. Here, due to lack of control on sensors\u27 locations post deployment, pre-fixing pairwise keys between sensors is not feasible especially under larger scale random deployments. Towards this premise, we propose differentiated key pre-distribution for secure end-to-end secure communication, and show how it improves existing routing algorithms. Our next contribution is in addressing quality versus latency trade-off in content retrieval under ad hoc node mobility. We propose a two-tiered architecture for efficient content retrieval in such environment. Finally we investigate Sybil attack detection in vehicular ad hoc networks. A Sybil attacker can create and use multiple counterfeit identities risking trust of a vehicular ad hoc network, and then easily escape the location of the attack avoiding detection. We propose a location based clustering of nodes leveraging vehicle platoon dispersion for detection of Sybil attacks in vehicular ad hoc networks --Abstract, page iii

Energy harvesting and wireless transfer in sensor network applications: Concepts and experiences

Advances in micro-electronics and miniaturized mechanical systems are redefining the scope and extent of the energy constraints found in battery-operated wireless sensor networks (WSNs). On one hand, ambient energy harvesting may prolong the systems lifetime or possibly enable perpetual operation. On the other hand, wireless energy transfer allows systems to decouple the energy sources from the sensing locations, enabling deployments previously unfeasible. As a result of applying these technologies to WSNs, the assumption of a finite energy budget is replaced with that of potentially infinite, yet intermittent, energy supply, profoundly impacting the design, implementation, and operation of WSNs. This article discusses these aspects by surveying paradigmatic examples of existing solutions in both fields and by reporting on real-world experiences found in the literature. The discussion is instrumental in providing a foundation for selecting the most appropriate energy harvesting or wireless transfer technology based on the application at hand. We conclude by outlining research directions originating from the fundamental change of perspective that energy harvesting and wireless transfer bring about

Efficient and Error-bounded Spatiotemporal Quantile Monitoring in Edge Computing Environments

Underlying many types of data analytics, a spatiotemporal quantile monitoring (SQM) query continuously returns the quantiles of a dataset observed in a spatiotemporal range. In this paper, we study SQM in an Internet of Things (IoT) based edge computing environment, where concurrent SQM queries share the same infrastructure asynchronously. To minimize query latency while providing result accuracy guarantees, we design a processing framework that virtualizes edge-resident data sketches for quantile computing. In the framework, a coordinator edge node manages edge sketches and synchronizes edge sketch processing and query executions. The co-ordinator also controls the processed data fractions of edge sketches, which helps to achieve the optimal latency with error-bounded results for each single query. To support concurrent queries, we employ a grid to decompose queries into subqueries and process them efficiently using shared edge sketches. We also devise a relaxation algorithm to converge to optimal latencies for those subqueries whose result errors are still bounded. We evaluate our proposals using two high-speed streaming datasets in a simulated IoT setting with edge nodes. The results show that our proposals achieve efficient, scalable, and error-bounded SQM

Evolutionary Game Theoretic Multi-Objective Optimization Algorithms and Their Applications

Multi-objective optimization problems require more than one objective functions to be optimized simultaneously. They are widely applied in many science fields, including engineering, economics and logistics where optimal decisions need to be taken in the presence of trade-offs between two or more conicting objectives. Most of the real world multi-objective optimization problems are NP-Hard problems. It may be too computationally costly to find an exact solution but sometimes a near optimal solution is sufficient. In these cases, Multi-Objective Evolutionary Algorithms (MOEAs) provide good approximate solutions to problems that cannot be solved easily using other techniques. However Evolutionary Algorithm is not stable due to its random nature, it may produce very different results every time it runs. This dissertation proposes an Evolutionary Game Theory (EGT) framework based algorithm (EGTMOA) that provides optimality and stability at the same time. EGTMOA combines the notion of stability from EGT and optimality from MOEA to form a novel and promising algorithm to solve multi-objective optimization problems. This dissertation studies three different multi-objective optimization applications, Cloud Virtual Machine Placement, Body Sensor Networks, and Multi-Hub Molecular Communication along with their proposed EGTMOA framework based algorithms. Experiment results show that EGTMOAs outperform many well known multi-objective evolutionary algorithms in stability, performance and runtime

Decentralized Collision-Free Control of Multiple Robots in 2D and 3D Spaces

Decentralized control of robots has attracted huge research interests. However, some of the research used unrealistic assumptions without collision avoidance. This report focuses on the collision-free control for multiple robots in both complete coverage and search tasks in 2D and 3D areas which are arbitrary unknown. All algorithms are decentralized as robots have limited abilities and they are mathematically proved. The report starts with the grid selection in the two tasks. Grid patterns simplify the representation of the area and robots only need to move straightly between neighbor vertices. For the 100% complete 2D coverage, the equilateral triangular grid is proposed. For the complete coverage ignoring the boundary effect, the grid with the fewest vertices is calculated in every situation for both 2D and 3D areas. The second part is for the complete coverage in 2D and 3D areas. A decentralized collision-free algorithm with the above selected grid is presented driving robots to sections which are furthest from the reference point. The area can be static or expanding, and the algorithm is simulated in MATLAB. Thirdly, three grid-based decentralized random algorithms with collision avoidance are provided to search targets in 2D or 3D areas. The number of targets can be known or unknown. In the first algorithm, robots choose vacant neighbors randomly with priorities on unvisited ones while the second one adds the repulsive force to disperse robots if they are close. In the third algorithm, if surrounded by visited vertices, the robot will use the breadth-first search algorithm to go to one of the nearest unvisited vertices via the grid. The second search algorithm is verified on Pioneer 3-DX robots. The general way to generate the formula to estimate the search time is demonstrated. Algorithms are compared with five other algorithms in MATLAB to show their effectiveness

Key management for wireless sensor network security

Wireless Sensor Networks (WSNs) have attracted great attention not only in industry but also in academia due to their enormous application potential and unique security challenges. A typical sensor network can be seen as a combination of a number of low-cost sensor nodes which have very limited computation and communication capability, memory space, and energy supply. The nodes are self-organized into a network to sense or monitor surrounding information in an unattended environment, while the self-organization property makes the networks vulnerable to various attacks.Many cryptographic mechanisms that solve network security problems rely directly on secure and efficient key management making key management a fundamental research topic in the field of WSNs security. Although key management for WSNs has been studied over the last years, the majority of the literature has focused on some assumed vulnerabilities along with corresponding countermeasures. Specific application, which is an important factor in determining the feasibility of the scheme, has been overlooked to a large extent in the existing literature.This thesis is an effort to develop a key management framework and specific schemes for WSNs by which different types of keys can be established and also can be distributed in a self-healing manner; explicit/ implicit authentication can be integrated according to the security requirements of expected applications. The proposed solutions would provide reliable and robust security infrastructure for facilitating secure communications in WSNs.There are five main parts in the thesis. In Part I, we begin with an introduction to the research background, problems definition and overview of existing solutions. From Part II to Part IV, we propose specific solutions, including purely Symmetric Key Cryptography based solutions, purely Public Key Cryptography based solutions, and a hybrid solution. While there is always a trade-off between security and performance, analysis and experimental results prove that each proposed solution can achieve the expected security aims with acceptable overheads for some specific applications. Finally, we recapitulate the main contribution of our work and identify future research directions in Part V

Design and implementation of a multi-modal sensor with on-chip security

With the advancement of technology, wearable devices for fitness tracking, patient monitoring, diagnosis, and disease prevention are finding ways to be woven into modern world reality. CMOS sensors are known to be compact, with low power consumption, making them an inseparable part of wireless medical applications and Internet of Things (IoT). Digital/semi-digital output, by the translation of transmitting data into the frequency domain, takes advantages of both the analog and digital world. However, one of the most critical measures of communication, security, is ignored and not considered for fabrication of an integrated chip. With the advancement of Moore\u27s law and the possibility of having a higher number of transistors and more complex circuits, the feasibility of having on-chip security measures is drawing more attention. One of the fundamental means of secure communication is real-time encryption. Encryption/ciphering occurs when we encode a signal or data, and prevents unauthorized parties from reading or understanding this information. Encryption is the process of transmitting sensitive data securely and with privacy. This measure of security is essential since in biomedical devices, the attacker/hacker can endanger users of IoT or wearable sensors (e.g. attacks at implanted biosensors can cause fatal harm to the user). This work develops 1) A low power and compact multi-modal sensor that can measure temperature and impedance with a quasi-digital output and 2) a low power on-chip signal cipher for real-time data transfer

Collocation of Sensing, Computing, and Actuation in Low-Power Wireless Nodes for Smart Structure Applications in Civil and Mechanical Systems.

Effective management of civil structures requires both data and a physical means to mitigate the negative consequences of the effects of extreme loading events. This thesis presents a smart structure framework characterized by low-cost wireless nodes with collocated sensing, computing, and actuation capabilities. These nodes are intended to function as an automated first line of defense during extreme loading events, providing both rapid assessment of structural condition (i.e., health) and automated response (i.e., control). Low-cost wireless sensing and actuation nodes promote dense instrumentations that can provide great insight into the dynamic behavior and condition of structures. However, wireless networks should not be viewed merely as one-to-one replacements for traditional tethered systems. Rather, the goal of this thesis is to demonstrate the embedment of computationally expedient approaches for traditional smart structure tasks (i.e., load estimation, structural health monitoring, and structural control) implemented within wireless sensor and actuation networks. The distributed nature of these computing resources, coupled with limitations on power and communication bandwidth, require unique decentralized data processing algorithms that can operate effectively within the decentralized wireless smart structure environment. To accomplish this goal, this thesis first presents the development and validation of a novel wireless sensing and actuation platform necessary to meet the specific requirements of this thesis work. Then, using this wireless system, a method for estimating wind loading from measured wind turbine tower response is experimentally validated. This method can generate reference loading data that may be used to improve the design economy of future turbines. In addition, a wireless structural health monitoring method based on a physical parameterization of time-series model coefficients is presented for damage detection in post-earthquake scenarios. This method employs a physics-based method of evaluating and integrating damage indications derived from individual sensors within the network. Finally, a partially-decentralized method for wireless structural control is presented in which the wireless network dynamically trades bandwidth for performance of actuators engaged in feedback control. This method provides a means to allocate scarce bandwidth resources while still allowing the wireless controllers to improve performance by identifying and broadcasting only the most valuable feedback data over the network.Ph.D.Civil EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/75812/1/asgard_1.pd