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Basheer, Al-QassabReliability of Data Collection and Transmission in Wireless Sensor Networks
Master of Science in Engineering, Youngstown State University, 2013, Department of Electrical and Computer Engineering
A network of wireless sensor nodes that are connected to a centralized base station is presented to conduct a study on reliability of data collection and transmission in wireless sensor networks (WSNs) with focus on data loss and data duplication. Software applications for specific sensor nodes called Sun SPOTs are presented, and programming techniques, for example packet transmitting time delay and data checking for loss and duplication, are implemented in these software applications to improve the functionality of the network. Acceleration data on a vibration plate are collected at sampling frequency of 100 Hz to validate the operation of the network. Additionally, the wireless sensor network is optimized to enhance the synchronization of data collection from different nodes. The result of this research shows that the reliability of the network is related to data sampling frequency, synchronization of the wireless data traffic, wireless sensor node signal strength, and wireless data routing protocols. The indoor tests on signal strength show the limitation of -70 dBm and higher for optimum data collection without data or packet loss.

Committee:

Li Frank, Ph.D. (Advisor); Munro Philip, Ph.D. (Committee Member); Mossayebi Faramarz, Ph.D. (Committee Member)

Subjects:

Computer Engineering; Electrical Engineering; Engineering; Information Technology

Keywords:

Wireless sensor networks; WSN; data collection; data transmission; reliability of wireless sensor networks

Li, HailongAnalytical Model for Energy Management in Wireless Sensor Networks
PhD, University of Cincinnati, 2013, Engineering and Applied Science: Computer Science and Engineering
Wireless sensor networks (WSNs) are one type of ad hoc networks with data-collecting function. Because of the low-power, low-cost features, WSN attracts much attention from both academia and industry. However, since WSN is driven by batteries and the multi-hop transmission pattern introduces energy hole problem, energy management of WSN became one of fundamental issues. In this dissertation, we study the energy management strategies for WSNs. Firstly, we propose a packets propagation scheme for both deterministic and random deployment of WSNs so to prolong their lifetime. The essence of packets propagation scheme is to control transmission power so as to balance the energy consumption for the entire WSN. Secondly, a characteristic correlation based data aggregation approach is presented. Redundant information during data collection can be effectively mitigated so as to reduce the packets transmission in the WSN. Lifetime of WSN is increased with limited overhead. Thirdly, we also provide a two-tier lifetime optimization strategy for wireless visual sensor network (VSN). By deploying redundant cheaper relay nodes into existing VSN, the lifetime of VSN is maximized with minimal cost. Fourthly, our two-tier visual sensor network deployment is further extended considering multiple base stations and image compression technique. Last but not the least, description of UC AirNet WSN project is presented. At the end, we also consider future research topics on energy management schemes for WSN.

Committee:

Dharma Agrawal, D.Sc. (Committee Chair); Kenneth Berman, Ph.D. (Committee Member); Yizong Cheng, Ph.D. (Committee Member); Chia Han, Ph.D. (Committee Member); Wen Ben Jone, Ph.D. (Committee Member)

Subjects:

Computer Engineering

Keywords:

Wireless Sensor Networks;Wireless Visual Sensor Network;Energy Management;Data Aggregation;Gaussian Random Distribution;Lifetime Optimization;

JAIN, NEHAENERGY AWARE AND ADAPTIVE ROUTING PROTOCOLS IN WIRELESS SENSOR NETWORKS
PhD, University of Cincinnati, 2004, Engineering : Computer Science and Engineering
Recent technological advances have enabled distributed micro-sensing for large scale information gathering through a network of tiny, low power devices or nodes equipped with programmable computing, multiple sensing and communication capabilities. This network of sensor nodes, known as a wireless sensor network, has revolutionized remote monitoring applications because of its ease of deployment, ad hoc connectivity and cost-effectiveness. In this dissertation, we design distributed routing protocols for minimizing energy consumption in a sensor network. There are two main contributions of this work. The first contribution is the design of an energy aware multiple path routing protocol to route heavy data traffic between a source and a destination node in a sensor network. The protocol spreads the routing load between the source and destination nodes over a large number of sensor nodes to minimize disparity in the energy levels of the sensor nodes. We also grade the multiple paths based on their route length to support time critical queries on the shortest available paths. The second contribution is the design of a communication architecture that supports distributed query processing to evaluate spatio-temporal queries within the network. We represent these queries by query trees and distribute query operators to appropriate sensor nodes. As operator execution demands high computation capability, we propose use of a heterogenous sensor network where query operators are assigned to sparsely deployed resource-rich nodes within a dense network of low power sensor nodes. We design an adaptive, decentralized, low communication overhead algorithm to determine an operator placement on the resource-rich nodes in the network to minimize cost of transmitting data in the routing tree constructed to continuously retrieve data from a set of spatially distributed geographical regions to the sink. To the best of our knowledge, this is the first attempt to build an energy aware routing infrastructure to enable in-network processing of spatio-temporal queries. In order to maximize energy savings the proposed multiple path routing protocol can be used to route data between the nodes that form the routing tree.

Committee:

Dr. Dharma Agrawal (Advisor)

Subjects:

Computer Science

Keywords:

Wireless Sensor Networks; Routing Protocols; Energy Aware; Decentralized algorithms

Yoon, Suk-UnDynamic Radio Resource Allocation in Wireless Sensor and Cognitive Radio Networks
Master of Science, The Ohio State University, 2009, Electrical and Computer Engineering

In wireless networks, it is required to change an operating frequency as part of the radio resource management due to strong interference or system requirements of accessing radio resources. In this thesis, we propose two radio resource management schemes in wireless sensor networks and cognitive radio networks. In the proposed schemes, sensor networks switch to a new channel when they detect strong interference and a secondary user in cognitive radio networks moves to a new spectrum when it detects or predicts the presence of a primary user.

In the first part of the thesis, we propose a channel hopping scheme which can be used for interfered wireless networks. With the additive functionality of a channel hopping mechanism on the sensor network stack, we aim to avoid the interference from other sensor nodes and wireless technologies on ISM band as well as avoid narrow-band jamming. For simple and reliable channel hopping, we introduce an Adaptive Channel Hopping scheme, a spectrum environment aware channel hopping scheme, for interference robust wireless sensor networks. When the channel status becomes suboptimal to communicate, the adaptive channel hopping lets the sensors switch to a new clean channel. To generate channel selection/scanning orders which minimize channel hopping latency, we use two parameters which are link quality indicator (LQI) and channel weighting. The proposed adaptive channel hopping scheme is evaluated through simulations. Simulation results indicate that the proposed scheme significantly reduces the channel hopping latency and selects the best quality channel.

In the second part of the thesis, we propose a novel approach to spectrum management in cognitive radio networks. To support flexible use of spectrum, cognitive radio networks employ spectrum mobility management schemes, including spectrum handoff, which refers to the switching of the operating spectrum due to changes in licensed (primary) user activity. Spectrum handoff inevitably results in temporary disruption of communication for the unlicensed (secondary) user operating in a licensed band opportunistically. Minimization of secondary user service disruption is an important objective of spectrum handoff schemes. In this thesis, we introduce a new type of spectrum handoff called Voluntary Spectrum Handoff assisted by a primary user spectrum usage estimation scheme. The two mechanisms proposed under voluntary spectrum handoff method estimate opportune times to initiate unforced spectrum handoff events to facilitate setup and signaling of alternative channels without having communication disruption, which occurs when a secondary user is forced out of an operating spectrum due to primary user activity. To estimate primary user spectrum usage, channel usage information is continuously updated with a fixed spectrum sensing window and a variable history window. Proposed voluntary spectrum handoff and primary usage estimation schemes are evaluated through extensive simulations. Simulation results indicate that the proposed schemes significantly reduce the communication disruption duration due to handoffs.

Committee:

Eylem Ekici (Advisor); Bradley Clymer, D. (Committee Member)

Subjects:

Engineering

Keywords:

Channel Hopping; Wireless Sensor Networks; Spectrum Handoff; Cognitive Radio Networks

Naik, Vinayak ShashikantReliable and secure data transport in large scale wireless networks of embedded devices
Doctor of Philosophy, The Ohio State University, 2006, Computer and Information Science
Recent advances in semiconductor technology have resulted in techniques that can build miniaturized radios and sensor-actuators, which can be deployed in the physical world in a large scale. These inexpensive devices can be used to provide coordinated dense sensing, processing, and communicating. Combining these capabilities with robust system software will empower physical sciences with real-time data of high fidelity. To realize this opportunity, computer scientists must address new challenges posed for development of robust system software for the large scale resource constrained wireless networks of embedded devices (sensors). These devices have limited resources in terms of processing, memory, radio bandwidth, and energy. Further, once deployed these devices will necessarily remain untouched and expect to work for an extended period of time. All though Internet is a large scale network, all of the above mentioned constrained do not apply to the nodes in the Internet. Therefore, network services must be designed specifically for the large scale wireless sensor networks. The network services for large scale sensor network must have low time complexity and memory complexity. We provide low complexity reliable and secure data transport for large scale wireless networks of embedded devices. We focus on bulk data transport for two of the most commonly used services, viz. data dissemination and data collection. Our services are better than the state-of-the-art. We address the problem of key maintenance for providing secured communication in the presence of key compromise and denial-of-service attacks. We also investigate the use of testbed to facilitate experimentations for large scale wireless networks.

Committee:

Anish Arora (Advisor)

Subjects:

Computer Science

Keywords:

Network protocols; Real-time systems and embedded systems; Wireless; Wireless sensor networks; Computer security

Vural, SerdarInformation propagation in wireless sensor networks using directional antennas
Doctor of Philosophy, The Ohio State University, 2007, Electrical Engineering
The information propagation capability of Wireless Sensor Networks (WSN) is directly related with the properties of multihop paths. Two main measures of the multihop data propagation capability are the maximum Euclidean distance that can be covered in a multihop path and the effectiveness of the medium access control (MAC) protocol. To achieve high propagation capacity, MAC protocols should enhance the channel use by maximizing simultaneous traffics and reducing end-to-end delay in high data load scenarios often encountered in WSN data collection applications. In this regards, directional antennas offer various benefits such as the extended communication ranges, spatial reuse capability, and reduced interference patterns that enable higher network performance compared to omnidirectional antennas. In this thesis, the maximum multihop Euclidean distance covered by directional packet transmissions is evaluated for both linear and planar WSNs using analytical modeling of distance distributions. Expressions for calculating the distribution parameters are derived and provided. Comparison of experimental and analytical results demonstrate the high accuracy of the proposed models in estimating distance distributions. Furthermore, a WSN security application which utilizes the derived models for verifying sensor locations is presented. The second contribution of this thesis is the Smart Antenna-Based MAC (SAMAC) protocol designed for multihop data collection applications for WSNs with sectored antennas. A detailed protocol description as well as performance evaluation results are provided. Simulation results demonstrate that SAMAC with sectored antennas improves end-to-end delay, data throughput, and data delivery ratio under high data generation rates and highly loaded traffic conditions compared to IEEE 802.11 with omnidirectional antennas.

Committee:

Eylem Ekici (Advisor)

Keywords:

wireless sensor networks; directional antennas; information propagation

Chellappan, SriramOn deployment and security in mobile wireless sensor networks
Doctor of Philosophy, The Ohio State University, 2007, Computer and Information Science

Wireless sensor networks have become increasingly pervasive with promises to fulfill many of our critical necessities today. One issue that has permeated sensor networks recently is mobility. Broadly, mobility in sensor networks can be categorized into two classes: Internal mobility and External mobility. Internal mobility is the class where sensors themselves can move from one location to another, while external mobility is the class where certain external agents (not sensors) move in the network. Both mobility classes have patent and significant impacts to sensor networks operation. However, being an emerging topic, a clear understanding of opportunities and challenges of sensor networks mobility is lacking today, and hence is an important need of the hour. In this dissertation, we make contributions in both classes of sensor networks mobility.

First, we study the issue of how sensors can use their mobility to enhance quality of network deployment. We define two representative mobility assisted sensor network deployment problems. In our mobility model, there are hard limitations in both sensors' mobility pattern and distance. Such limitations are natural due to constraints on sensors' form-factor and energy. We identify critical challenges arising in deployment under such hard mobility limitations. We then propose a suit of sensor mobility algorithms for our deployment problems, and demonstrate their performance using theoretical analysis and extensive simulations.

Second, we study the issue of external mobility in sensor networks from a security perspective. We identify a unique security threat in sensor networks called physical attacks. We define a representative model of physical attacks, wherein an external mobile agent (human being or robot) moves in the network detecting inherent physical/ electronic sensor signals to localize sensors, and then physically destroys them. We formally model such attacks in sensor networks, demonstrate their destruction potential, identify variations, and finally propose countermeasure guidelines against them.

With the emergence of mobility in wireless sensor networks, coupled with its significances, we hope that our work in this dissertation can provide strong foundations and further motivations for researchers to explore this topic that promises to revolutionarize sensor networks research in the near future and beyond.

Committee:

Dong Xuan (Advisor); Eylem Ekici (Other); Ten Lai (Other)

Subjects:

Computer Science

Keywords:

Wireless Sensor Networks;

Chowdhury, Tashnim Jabir ShovonA distributed cooperative algorithm for localization in wireless sensor networks using Gaussian mixture modeling
Master of Science, University of Toledo, 2016, Electrical Engineering
Wireless sensor networks are defined as spatially distributed autonomous sensors to monitor certain physical or environmental conditions like temperature, pressure, sound, etc. and incorporate the collected data to pass to a central location through a network. Multifarious applications including cyber-physical systems, military, eHealth, environmental monitoring, weather forecasting, etc. make localization a crucial part of wireless sensor networks. Since accuracy and low computational time of the localization, in case of some applications like emergency police or medical services, is very important, the main objective of any localization algorithm should be to attain more accurate and less time consuming scheme. This thesis presents a cooperative sensor network localization scheme that approximates measurement error statistics by Gaussian mixture. Expectation Maximization (EM) algorithm has been implemented to approximate maximum-likelihood estimator of the unknown sensor positions and Gaussian mixture model (GMM) parameters. To estimate the sensor positions we have adopted several algorithms including Broyden-Fletcher-Goldfarb-Shanno (BFGS) Quasi-Newton (QN), Davidon-Fletcher-Powell (DFP), and Cooperative Least Square (LS) algorithm. The distributive form of the algorithms meet the scalability requirements of sparse sensor networks. The algorithms have been analyzed for different number of network sizes. Cramer Rao Lower Bound (CRLB) has been presented and utilized to evaluate the performance of the algorithms. Through Monte Carlo simulation we show the superior performance of BFGS-QN over DFP and cooperative LS in terms of localization accuracy. Moreover the results demonstrate that Root Mean Square Error (RMSE) of BFGS-QN is closer to derived CRLB than both DFP and cooperative LS.

Committee:

Jared Oluoch (Committee Chair); Vijay Devabhaktuni (Committee Co-Chair); Junghwan Kim (Committee Member)

Subjects:

Electrical Engineering

Keywords:

Localization; wireless sensor networks; Gaussian mixture modeling; EM algorithm

Katneni, NarendranadDeployment Strategies and Mechanisms for Intrusion Detection In Wireless Sensor Networks
MS, University of Cincinnati, 2012, Engineering and Applied Science: Computer Science

Wireless Sensor Networks (WSNs) play a big role in many real life scenarios and are used in a wide range of applications. That includes military, industrial and civilian security and this requires stability, performance and affordability of WSNs. Deployment schemes of sensors play an important role in the design of WSN and contribute to improving its security. There are various deployment schemes that have their own strengths and weaknesses and each one suits best for a particular set of applications.

In this thesis, we focus particularly on “Intrusion Detection”, which is an application of WSNs. We study the existing deployment schemes such as Uniform, Gaussian and identify their strengths and limitations. We then propose two new deployment techniques called Hybrid Gaussian-Ring Deployment and Reverse Gaussian Deployment. Hybrid Gaussian-Ring offers better border protection and network connectivity, whereas Reverse Gaussian performs better in protecting multiple facilities located within the area protected by the WSN.

Subsequently, we study about Regular Deployment schemes, their applications and their differences from the probabilistic deployment schemes. These are more useful when the area of deployment of WSN is more accessible and non-hostile. We then analyze the performance of various regular deployment schemes and establish which of these is best suited for intrusion detection.

Committee:

Dharma Agrawal, DSc (Committee Chair); Yizong Cheng, PhD (Committee Member); Yiming Hu, PhD (Committee Member)

Subjects:

Computer Science

Keywords:

Wireless Sensor Networks; Intrusion Detection; Sensor Deployment; Gaussian Deployment; Regular Deployment; Security

Kulathumani, VinodkrishnanNetwork Abstractions for Designing Reliable Applications Using Wireless Sensor Networks
Doctor of Philosophy, The Ohio State University, 2008, Computer and Information Science

Applications of wireless sensor networks are moving from simply monitoring based to control based ones and from static network based to pervasive and mobility-centric ones. But while the applications are rising in scale and complexity, the underlying network is still resource-constrained and bandwidth limited, prone to contention and fading. Thus the demands of applications are growing at a faster rate than the resources in the underlying network. My thesis has addressed the challenge of reliable application design using wireless sensor networks, by the design and implementation of network abstractions that bridge the gap between the application and the network and provide performance guarantees to applications.

My dissertation considers the reliable design of 4 wireless sensor network applications: (1) distributed pursuer evader tracking with requirement of eventual catch, (2) distributed pursuer evader tracking with optimal interception, (3) object classification and track monitoring and (4) distributed control of flexible structures. For each of these applications, we come up with an appropriate design considering limitations of the underlying network and characterize the network abstractions that meet application requirements. The network abstractions are then implemented appropriately sometimes using middle-ware services running in the form distributed / centralized programs, sometimes by suitably designing the network with the right density, placement of sensors or sometimes using both.

Committee:

Anish Arora (Advisor); Prasun Sinha (Committee Member); Paul Sivilotti (Committee Member); Tamal Dey (Committee Member)

Subjects:

Computer Science

Keywords:

Wireless sensor networks; middleware services; network abstractions; application; tracking; classification; distributed control

Gaur, AmitSecured Communication in Wireless Sensor Network (WSN) and Authentic Associations in Wireless Mesh Networks
MS, University of Cincinnati, 2010, Engineering and Applied Science: Computer Science
Wireless sensors are low power devices with small transmission range, restricted computation power, limited amount of memory and with portable power supply. Wireless Sensor Network (WSN) is a collection of such sensors where the number of sensors can vary from few hundreds to thousands. Performing secure pair-wise communication between sensors is a really difficult task due to inherent characteristics such as lack of any fixed infrastructure. As memory and power consumption are most stringent requirements for these devices, use of conventional techniques for secured communication are totally out of question. This thesis introduces scheme that enables a complete pair-wise secure connectivity between any two adjacent sensor nodes in spite of using small key ring (KR) for sensors. The Proposed Scheme (ELKPD) doesn't require any additional hardware while providing keys to the sensors irrespective of their location. Also, proposed scheme is easily scalable which allows enables addition of sensor nodes without any computational or hardware overheads. Due to the varying degree of mobility of Mesh Clients has provided much more flexibility in Wireless Mesh Networks. And establishing an Authentic Association among entities is a non -trivial problem. In this thesis, we introduce a Polynomial Based scheme which not only provides high pair-wise connectivity, low communication and storage overhead and high scalability but also makes on the fly Authentic Association feasible. The proposed scheme is also observed to be resilient against both the traffic analysis and the node capture attacks.

Committee:

Dharma Agrawal, DSc (Committee Chair); Raj Bhatnagar, PhD (Committee Member); Carla Purdy, C, PhD (Committee Member)

Subjects:

Computer Science

Keywords:

security;wireless sensor networks;key-predistribution;wireless mesh networks;bi-variate polynomials

Abuaitah, Giovani RimonANOMALIES IN SENSOR NETWORK DEPLOYMENTS: ANALYSIS, MODELING, AND DETECTION
Doctor of Philosophy (PhD), Wright State University, 2013, Computer Science and Engineering PhD
A sensor network serves as a vital source for collecting raw sensory data. Sensor data are later processed, analyzed, visualized, and reasoned over with the help of several decision making tools. A decision making process can be disastrously misled by a small portion of anomalous sensor readings. Therefore, there has been a vast demand for mechanisms that identify and then eliminate such anomalies in order to ensure the quality, integrity, and/or trustworthiness of the raw sensory data before they can even be interpreted. Prior to identifying anomalies, it is essential to understand the various anomalous behaviors prevalent in a sensor network deployment. Therefore, we begin this work by providing a comprehensive study of anomalies that exist in a sensor network deployment, or are likely to exist in future deployments. After this thorough systematic analysis, we identify those anomalies that, in fact, hinder the quality and/or trustworthiness of the collected sensor data. One approach towards the reduction of the negative impact of misleading sensor readings is to perform off-line analysis after storing a large amount of sensor data into a centralized database. To this end, in this work, we propose an off-line abnormal node detection mechanism rooted in machine learning and data mining. Our proposed mechanism achieves high detection accuracy with low false positives. The major disadvantage of a centralized architecture is the tremendous amount of energy wasted while communicating the sensor readings. Therefore, we further propose an on-line distributed anomaly detection framework that is capable of accurately and rapidly identifying data-centric anomalies in-network, while at the same time maintaining a low energy profile. Unlike previous approaches, our proposed framework utilizes a very small amount of data memory through on-line extraction of few statistical features over the sensor data stream. In addition, previous detection mechanisms leverage sensor datasets obtained from an earlier deployment or use synthetic data to test their effectiveness. Our framework, on the other hand, has been entirely implemented in TinyOS as a prototype readily deployable into existing sensor networks, alongside other essential protocols such as sensor data collection protocols. An advantage of our system is the fact that it relies on supervised learning. Supervised machine learning algorithms usually achieve higher accuracy than their unsupervised counterparts given a highly representative common ground truth. Thus, in this work, we also design highly expressive anomaly models that may be leveraged to inject anomalous readings into existing sensor network deployments. In order to do so, we have developed a tool called SNMiner which enables us not only to inject anomalies into a network of sensors, but also to extract important statistical features and evaluate the accuracy of a number of supervised machine learning algorithms.

Committee:

Bin Wang, Ph.D. (Advisor); Yong Pei, Ph.D. (Committee Member); Keke Chen, Ph.D. (Committee Member); Shu Schiller, Ph.D. (Committee Member)

Subjects:

Computer Engineering; Computer Science

Keywords:

anomaly detection; online anomaly detection; anomaly analysis; anomaly modeling; SNMiner; ABANDON; POND; sensor network deployments; wireless sensor networks

PALADUGU, KARTHIKADCLAD: DISTRIBUTED CLUSTER BASED LOCALIZATION ANOMALY DETECTION IN WIRELESS SENSOR NETWORKS USING SINGLE MOBILE BEACON
MS, University of Cincinnati, 2007, Engineering : Electrical Engineering
In the last few years, Wireless Sensor Networks (WSNs) have emerged as a disrupting technology for myriad military and civilian applications. They demand an accurate location of the event detected and is done by using a mobile beacon node to provide accurate location and assume a benign environment. However, in a hostile environment, such a node can be easily tampered by an adversary. In this paper, we propose a distributed cluster based anomaly detection scheme by assigning few randomly chosen cluster heads a critical task of estimating the reliability of the mobile beacon node. As localization of remaining sensors is cautiously performed only after verifying the authenticity of the mobile beacon node, a considerable overhead is saved in the incorrect localization of the entire network. We perform extensive simulation for different attacks and observe our scheme to have a high detection rate of 99% and a low false positive rate of 20%.

Committee:

Dr. Dharma Agrawal (Advisor)

Keywords:

Localization Anomaly Detection; Wireless Sensor Networks; Single Mobile Beacon

Li, JingDuty Cycling for Energy Efficiency in Wireless Sensor Networks and Applications
Doctor of Philosophy, The Ohio State University, 2012, Computer Science and Engineering

Wireless sensor networks (WSNs) offer a powerful combination of distributed sensing, computing and communication, which enable a broad spectrum of applications and, at the same time, lead numerous challenges due to their distinctiveness, primarily the non-negligible power consumption from especially radio activities and stringent energy constraints to which sensor nodes are typically subjected. The distinguishing traits of sensor networks have a direct impact on their protocol design at each layer, especially at the Medium Access Control (MAC) layer since it manages transmission scheduling as well as duty cycling for energy conservation. To maximize energy efficiency of WSNs, my thesis studies duty cycling in time and frequency domains for both MAC schedulers and applications. The first part of the thesis focuses on energy efficiency at the MAC layer, including modeling, evaluating and designing MAC schedulers with duty cycling; the second part of the dissertation investigates energy efficiency in applications, which introduces two duty-cycled sensor applications that are deployed in a large building.

In the first part of this dissertation, I begin by studying the impact of perfect duty cycling, in addition to perfect transmission scheduling, on the capacity of random wireless networks with single and multiple channels. The analysis of the duty-cycled throughput reveals nontrivial scaling gains resulting from the ability to avoid interference by spreading interferers to mutually exclusive times, which corroborates the importance of efficient co-scheduling of both transmissions and duty cycling for energy efficiency. Since duty cycling and transmission scheduling are controlled by MAC schedulers, I analytically quantify the gap between the duty-cycled throughput with an optimal scheduler and with existing MAC schedulers.

In order to characterize energy efficiency achieved by existing MACs, I classify CSMA-based MAC protocols in terms of critical MAC-design factors into four classes and introduce an analytical framework for performance modeling of each class as a function of key protocol parameters. I instantiate the framework to evaluate various performance metrics of MACs across the configuration space. A surprising finding is that one MAC class consistently achieves the best or close-to-the-best performance across much of the configuration space. Moreover, via the analytical model, I discover a distributed way of adapting duty cycle at the MAC layer to changing traffics for optimality of performance. In terms of energy efficiency in the frequency domain, I propose Chameleon, which is a light-weight MAC protocol that maximizes energy efficiency over the spectrum by scheduling traffics across multiple frequencies with duty cycling.

In the second part of this dissertation, I present two long-lived sensor networks deployed in a large building. Towards duty cycling Heating, Ventilation, and Air Conditioning systems of large buildings such that comfort and efficiency can be maintained simultaneously, I described ThermoNet, which is a system for temperature monitoring in large buildings. Access to fine grain information reveals temporal and spatial dynamics that help quantify the level of (non-)compliance with the building's thermal comfort standards and identify ill-conditioned rooms that need maintenance. For another application, to increase the battery life of the elevator network from a couple of days to several years, I introduce a self-stabilizing token-ring protocol that maintains duty-cycle coordination across the partitions of a static network of nodes.

Committee:

Anish Arora (Advisor); Ten-Hwang Lai (Committee Member); Ness Shroff (Committee Member)

Subjects:

Computer Engineering; Computer Science

Keywords:

wireless sensor networks; energy efficiency; MAC protocol; applications; performance; modeling;

Srivastava, RahulEfficient Energy Management in Wireless Sensor Networks
Doctor of Philosophy, The Ohio State University, 2010, Electrical and Computer Engineering

Recent advances in wireless networking and data acquisition have enabled us with a unique capability to remotely sense our environment. Data acquisition networks can be used to sense natural as well as human-created phenomena. As these applications may require deployment in remote and hard-to-reach areas, it is critical to ensure that such wireless sensor networks are capable of operating unattended for long durations. The lack of easy access to a continuous power source in most scenarios and the limited lifetime of batteries have hindered the deployment of such networks. Consequently, the central objective in wireless sensor network design is to utilize the available energy as efficiently as possible. In this thesis, we study the design of optimal or near-optimal energy management schemes for various wireless sensor networks composed of nodes with different capabilities.

Firstly, we derive theoretical upper bounds on the performance of a transmission scheduler for sensor networks. We do this by calculating the information theoretic channel capacity of finite-state Markov channels with imperfect feedback containing different grades of channel state information including that, obtained through Automatic Repeat Request (ARQ) feedback. Secondly, we consider the problem of energy optimal transmission scheduling over a finite state Markov channel with imperfect feedback. We propose a transmission controller that utilizes different "grades" of channel state information to schedule packet transmissions in an energy-optimal way, while meeting a deadline constraint for all packets waiting in the transmission queue. Our scheduler is readily implementable and it is based on the dynamic programming solution to the finite-horizon transmission control problem. We illustrate that our scheduler achieves a given throughput at a power level that is fairly close to the information-theoretic limit. Finally, we consider the problem of energy management in nodes with energy replenishment capabilities. Here, we derive the performance limits of sensor nodes with limited energy, being replenished at a variable and random rate. We provide a simple localized energy management scheme for nodes with limited energy storage space, and show that our scheme achieves a performance asymptotically close to that available with an unlimited energy source. Based on the insights developed, we address the problem of energy management for energy-replenishing nodes with finite data buffer capacities as well as limited energy storage space. To this end, we give an energy management scheme that is provably asymptotically optimal.

Committee:

Can Emre Koksal, PhD (Committee Chair); Ness B. Shroff, PhD (Committee Member); Eylem Ekici, PhD (Committee Member)

Subjects:

Electrical Engineering

Keywords:

Wireless Sensor Networks; Energy Management

CHUGH, SHRUTIAN ENERGY EFFICIENT COLLABORATIVE FRAMEWORK FOR EVENT NOTIFICATION AND DATA AGGREGATION IN WIRELESS SENSOR NETWORKS
MS, University of Cincinnati, 2004, Engineering : Computer Science
Wireless sensor networks consist of a large number of low power devices equipped with RF links for communication that have numerous military, civil and environmental monitoring applications. The energy constraints due to limited battery power present several design challenges. In this thesis we propose a cluster based framework and a localized and deterministic schedule based on TDMA/FDMA MAC protocol for the nodes in a neighborhood to communicate with each other. We also present a three phase collaboration algorithm that entails exchanging messages to determine the local maximum in a region in terms of received energy from the source. This helps in minimizing the redundancy in reporting events and saves energy. We also introduce a robust data aggregation approach for queries targeting selective regions of the network. Extensive simulations show that there is a significant reduction in the overall network traffic and in the energy expended by the nodes.

Committee:

Dr. DHARMA AGRAWAL (Advisor)

Subjects:

Computer Science

Keywords:

Wireless Sensor Networks; Collaborative Processing; Event Notification; Data Aggregation

Narayanan, SriramProportional Fairness in Regular Topologies of Wireless Sensor Networks
MS, University of Cincinnati, 2011, Engineering and Applied Science: Computer Science
Wireless Sensor Networks (WSNs) are being used in a wide variety of commercial civilian applications which favour regular deployment of sensor nodes (SNs) over a random deployment due to its simplicity of planning, ease of maintenance and precise node location information. In such regular deployments, it is necessary to ensure that every SN is allocated a fair share of the network’s resources in order to successfully obtain the sensed information from every portion of the area covered by the WSN. However, in the interest of maintaining the best possible network performance, the total throughput of the WSN needs to be maximized. Thus, we consider the problem of proportionally fair rate allocation to the SNs in regular WSNs to achieve maximum throughput while ensuring that every SN is allocated a fair portion of the available bandwidth. We follow a cross layer approach, considering both the transport layer session rates and the link layer transmission probabilities required to achieve the maximum total proportionally fair throughput for the square, hexagonal, and triangular topologies of WSN. Closed form expressions for each topology are derived, and they enable us to determine which topology has the best performance at different network sizes. Network simulations conducted in Qualnet and experiments conducted using TELOSB SNs validate our theoretical results and shed light on future directions of work.

Committee:

Dharma Agrawal, DSc (Committee Chair); Chia Han, PhD (Committee Member); George Purdy, PhD (Committee Member)

Subjects:

Computer Science

Keywords:

Wireless Sensor Networks;Regular Topologies;Proportional Fairness

BANDEKAR, ASHUTOSHA Secure and Low-Power Consumption Communication Mechanism for IoT (Internet of Things) and Wireless Sensor Networks
Master of Science, University of Toledo, 2017, Electrical Engineering
Internet of Things (IoT), the newer generation of traditional wireless sensor network devices, offer wide variety of applications in various areas including military, medicine, home automation, remote monitoring, etc. Due to their wide usage and recent large-scale DDoS (distributed denial of service) attacks using millions of these devices, security of these devices have become an important aspect to address. Additionally, security implementation needs to be power efficient considering the limited power resource available to these wireless devices. Since users, as well as attackers, can control or access IoT devices remotely using smartphone or a computer, any attack on these devices can result in disasters. This thesis is directed towards development and implementation of a secure and power-efficient communication mechanism on these low-power devices. First, we performed a detailed analysis of the power consumption of these devices for different environment variables including temperature, lighting and location (in/outdoor), to understand effects of these parameters on device power consumption. Second, we proposed and implemented a novel security algorithm to detect and mitigate RPL (routing protocol layer) attacks in IoT networks. We evaluated changes in the behavior of IoT devices before and after the implementation of our proposed algorithm in terms of the change in battery life and power consumption. The proposed security implementation has the novel approach of using the RSSI (received signal strength indicator) tunneling to detect and mitigate RPL (routing protocol layer) attacks. Finally, we conducted experiments in simulation as well as on first generation real-world sensor nodes (Zolertia Z1 motes) to evaluate the power efficiency of our proposed algorithm. We conclude the thesis with insights on (a) the effect of interference present in the atmosphere on battery life, (b) security provided by the proposed algorithm, and (c) power-efficiency of the proposed security algorithm for IoT devices.

Committee:

Ahmad Javaid (Committee Chair); Alam Mansoor (Committee Member); Hond Wang (Committee Member)

Subjects:

Computer Science

Keywords:

IoT, Wireless sensor networks, Security

Tian, YuanEnergy-efficient computation and communication scheduling for cluster-based in-network processing in large-scale wireless sensor networks
Doctor of Philosophy, The Ohio State University, 2006, Electrical Engineering
Emerging Wireless Sensor Networks (WSN) applications demand considerable computation capacity for in-network processing. To achieve the required processing capacity, cross-layer collaborative in-network processing among sensors emerges as a promising solution: Sensors not only process information at the application layer, but also synchronize their communication activities to exchange partially processed data for parallel processing. Task mapping and scheduling plays an important role in parallel processing. Though this problem has been extensively studied in the high performance computing area, its counterpart in WSNs remains largely unexplored. Scheduling computation and communication events is a challenging problem in WSNs due to limited resource availability and shared communication medium. This research investigates the energy-efficient task mapping and scheduling problem in large-scale WSNs composed of homogeneous wireless sensors. A hierarchical WSN architecture is assumed to be composed of sensor clusters, where applications are iteratively executed. Given this environment, task mapping and scheduling in single-hop clustered WSNs is investigated for energy-constrained applications. Based on the proposed Hyper-DAG model and single-hop channel model, the EcoMapS solution minimizes schedule lengths subject to energy consumption constraints. Secondly, real-time applications are also considered in single-hop clustered WSNs. Incorporating the novel Dynamic Voltage Scaling (DVS) algorithm, the RT-MapS solution provides deadline guarantee with the minimum balanced energy consumption. Next, the task mapping and scheduling problem is further addressed in its general form for multi-hop clustered WSNs. A novel multi-hop channel model is developed, and a multi-hop communication scheduling algorithm is presented, based on which the MTMS solution minimizes application energy consumption subject to deadline constraints. Finally, low-complexity sensor failure handling algorithms are developed to recover network functionality when sensors failures occur in single-hop and multi-hop clustered WSNs.

Committee:

Fusun Ozguner (Advisor)

Keywords:

wireless sensor networks; clusered networks; task mapping and scheduling

Liu, ShaENERGY EFFICIENT MAC LAYER DESIGN FOR WIRELESS SENSOR NETWORKS
Doctor of Philosophy, The Ohio State University, 2008, Computer and Information Science

Energy efficient communication is a critical design objective for wireless sensor networks which are usually highly energy constrained. In addition, the throughput and latency performance is also important for several sensor network applications. To simultaneously achieve the seemingly contradictory goals, this dissertation identifies the three major sources of energy wastage in communications, i.e., idle listening, overhearing, and packet retransmissions, and proposes three mechanisms to optimize the energy consumption while maintaining high throughput and low latency.

To deal with the idle listening problem, we design a new low duty-cycle MAC layer protocol called Convergent MAC (CMAC). CMAC can work at low duty cycles and requires no synchronization when there is no traffic. When carrying traffic, CMAC first uses anycast to wake up forwarding nodes, and then converges gradually from route-suboptimal anycast to route-optimal unicast. Experiments and simulations show that CMAC significantly outperforms other duty cycling protocols in terms of latency, throughput and energy efficiency.

The MAC layer anycast technique is also an efficient technique to cope with low link quality and interference in wireless sensor networks. By utilizing the nature of broadcast wireless communication medium and allowing multiple nodes in the forwarding set to compete to be the packet forwarder, links with poor reception quality but good progress in a given routing metric space can be opportunistically used to forward packets. However, the impact of unreliable communication in the reverse channel on anycasting has not been studied before. The second part of this dissertation analyzes the impact of unreliability of reverse links on the performance of existing anycast protocols, proposes a new metric characterizing the number of transmissions in the network for anycast based MAC protocols, and presents an efficient solution for computing the forwarding sets.

The third part of this dissertation is dedicated to optimizing the schedule of packet retransmissions. CSMA relies on carrier sensing to decide if retransmissions should be performed immediately. However, in cases where the poor channel quality persists or packet losses are due to interference undetectable by carrier sensing, the channel assessment alone is not a good indicator of successful transmissions. To schedule retransmissions at appropriate moments, we propose a new technique called transmission pushback to reduce such losses by delaying retransmissions. This technique overcomes periods of poor channel quality while ensuring a throughput matching the incoming packet rate. In order to determine the optimal pushback period, we devise an adaptive channel prediction technique based on estimating the parameters of a simple hidden Markov model (HMM) which represents the channel. We dynamically update the parameters of the HMM based solely on the ACK sequence for the previous packet transmissions. By considering both the packet incoming rate and the packet loss pattern, the appropriate pushback period is calculated and applied for future retransmissions.

Committee:

Prasun Sinha (Advisor); Anish Arora (Committee Member); Dong Xuan (Committee Member)

Subjects:

Computer Science

Keywords:

MAC; Routing; Duty Cycle; Link Quality; Energy Efficiency; Throughput; Latency; Wireless Sensor Networks;

Venkataraman, AparnaDynamic Deployment strategies in Ad-Hoc Sensor networks to optimize Coverage and Connectivity in Unknown Event Boundary detection
MS, University of Cincinnati, 2011, Engineering and Applied Science: Computer Science
There are many ways to geographically determine the boundary of an event based on its location and its nature through Satellite imaging and other learning mechanisms. In these methods, the availability of resources to perform the detection, their capabilities, actual time available to determine the event and its accessibility are constraints. At times, the satellite images may not be sufficient to get complete information about an event. Here we consider a particular case where the aim is to detect the actual boundary of an event based on its estimated boundary with the above constraints. A typical situation would be to determine the actual boundary of fire given the smoke area, or to estimate the concentration of chemical content, ideally any situation where sensors need to be used in an unmanned situation. We use a deploying agent to drop the sensors and there is a Base Station (BS) to which the event details are communicated by connectivity through localization with neighboring sensors. The research targets dynamic deployment of sensors with coverage and connectivity handled simultaneously as the information can reach the base station only if the sensors are able to connect to it. This is critical for real time applications. So we use an intelligent distribution scheme to test the behavior of different kinds of deployments using random, Gaussian, controlled random and combinational methods to deploy sensors. The set of parameters which are constraints are the communication radius of the base station, sensors & the event, the proximity of the event from the base station and location determination of the event based on the current state of the system. We use a weighted approach with more sensors around the event border and lesser inside to be able to detect the event and yet preserve the sensors as they might be lost due to fire or damage depending on the event. Additionally partial event boundary detection is used as experiment results show that we can reduce the number of sensors by nearly 50% when 80% of the sensors deployed are connected as against 100% connectivity. Test cases also involve multiple BS & deploying agents with parallel control. This will be useful in emergency situations and specifically in situations which do not have pre-deployed sensors wherein, time and resources available are important constraints.

Committee:

Dharma Agrawal, DSc (Committee Chair); Raj Bhatnagar, PhD (Committee Member); George Purdy, PhD (Committee Member)

Subjects:

Computer Science

Keywords:

Dynamic network deployment strategies; realtime partial boundary detection; ad-hoc wireless sensor networks; localization; coverage connectivity detectivity; unknown event boundary detection

Bheemidi, Dheeraj ReddyA Wrapper-based Approach to Sustained Time Synchronization in Wireless Sensor Networks
Master of Science in Electrical Engineering, Cleveland State University, 2008, Fenn College of Engineering

Time synchronization is an important service for wireless sensor network applications. Nodes in the network stay synchronized by exchanging periodic messages that carry local timestamps. Several algorithms have been proposed in the literature that are suited to different kinds of application scenarios. A common problem across these time synchronization algorithms is that the energy cost of message exchange is high. In fact, the cost of radio communication far outstrips the cost of performing local operations on the processor. If the message exchanges were stopped, nodes will fall out of sync, and may no longer be able to meet application requirements.

This thesis presents a wrapper-based approach to sustained time synchronization for wireless sensor networks. As such, this solution Booster for Time Synchronization Protocol (BTSP) will act as a wrapper around a given time synchronization protocol, and will apply local corrector operations to extend the time duration between two message exchanges between nodes. The wrapper performs at least as good as the original protocol provided, reduces the number of message exchanges on average, and consequently the energy consumed, significantly. BTSP has been implemented for TinyOS and evaluated on XSM motes in conjunction with TPSN, a popular time synchronization protocol for sensor networks.

Committee:

Nigamanth Sridhar, PhD (Committee Chair); Chansu Yu, PhD (Committee Member); Wenbing Zhao, PhD (Committee Member)

Subjects:

Computer Science; Electrical Engineering

Keywords:

Wireless Sensor Networks; Time Synchronization; BTSP Wrapper; Energy saving; TinyOS; booster for time synchronization

Reddy, Prashanth G.EFFICIENT TIME OF ARRIVAL CALCULATION FOR ACOUSTIC SOURCE LOCALIZATION USING WIRELESS SENSOR NETWORKS
Master of Science in Electrical Engineering, Cleveland State University, 2011, Fenn College of Engineering
Acoustic source localization is a very useful tool in surveillance and tracking applications. Potential exists for ubiquitous presence of acoustic source localization systems. However, due to several significant challenges they are currently limited in their applications. Wireless Sensor Networks (WSN) offer a feasible solution that can allow for large, ever present acoustic localization systems. Some fundamental challenges remain. This thesis presents some ideas for helping solve the challenging problems faced by networked acoustic localization systems. We make use of a low-power WSN designed specifically for distributed acoustic source localization. Our ideas are based on three important observations. First, sounds emanating from a source will be free of reflections at the beginning of the sound. We make use of this observation by selectively processing only the initial parts of a sound to be localized. Second, the significant features of a sound are more robust to various interference sources. We perform key feature recognition such as the locations of significant zero crossings and local peaks. Third, these features which are compressed descriptors, can also be used for distributed pattern matching. For this we perform basic pattern analysis by comparing sampled signals from various nodes in order to determine better Time Of Arrivals (TOA). Our implementation tests these ideas in a predictable test environment. A complete system for general sounds is left for future work.

Committee:

Nigamanth Sridhar, PhD (Committee Chair); Murad Hizlan, PhD (Committee Member); Wenbing Zhao, PhD (Committee Member)

Subjects:

Electrical Engineering

Keywords:

Localization;TOA;TDOA;Wireless Sensor Networks;WSN;Acoustic;Time of Arrival;Acoustic Source Localization

Xie, Qing YanK-Centers Dynamic Clustering Algorithms and Applications
PhD, University of Cincinnati, 2013, Engineering and Applied Science: Computer Science and Engineering
Every day large and increasing amounts of unstructured information are created, putting ever more demands on retrieval methods, classification, automatic data analysis and management. Clustering is an important and efficient way for organizing and analyzing information and data. One of the most widely used dynamic clustering algorithms is K-Means clustering. This dissertation presents our K-Centers Min-Max dynamic clustering algorithm (KCMM) and K-Centers Mean-shift Reverse Mean-shift dynamic clustering algorithm (KCMRM). These algorithms are designed to modify K-Means in order to achieve improved performance and help with specific goals in certain domains. These two algorithms can be applied to many fields such as wireless sensor networks, server or facility location optimization, and molecular networks. Their application in wireless sensor networks are described in this dissertation. The K-Centers Min-Max clustering algorithm uses a smallest enclosing disk/sphere algorithm to attain a minimum of the maximum distance between a cluster node and data nodes. Our approach results in fewer iterations, and shorter maximum intra-cluster distances than the standard K-Means clustering algorithm with either uniform distribution or normal distribution. Most notably, it can achieve much better performance when the size of clusters is large, or when the clusters includes large numbers of member nodes in normal distribution. The K-Centers Mean-shift Reverse Mean-shift clustering algorithm is proposed to solve the "empty cluster" problem which is caused by random deployment. It employs a Gaussian function as a kernel function, discovers the relationship between mean shift and gradient ascent on the estimated density surface, and iteratively moves cluster nodes away from their weighted means. This results in cluster nodes which better accommodate the distribution of data nodes. The K-Centers Mean-shift Reverse Mean-shift algorithm can not only reduce the number of empty clusters, but can also make the sizes of clusters are more evenly balanced compared to K-Means and K-Centers Min-Max clustering algorithms. In wireless sensor networks, addressing energy dissipation is a key issue. For heterogeneous wireless sensor networks, energy consumption to transmit data is proportional to the distance between sensor nodes and cluster heads or to a base station. Clustering is one of the best methods to reduce energy dissipation and extend network lifetimes. The K-Centers Min-Max and K-Centers Mean-shift Reverse Mean-shift clustering algorithms are applied to two proposed protocols, KCMM and KCMRM, for wireless sensor networks. Desirable features of the proposed clustering protocols KCMM and KCMRM include: energy efficiency; distributed and localized data aggregation; adaptation to changes in sensor distribution; robustness to partial damage; and self-recovery. Besides the above features, KCMRM protocol can make use of cluster heads efficiently and can reduce empty clusters.

Committee:

Yizong Cheng, Ph.D. (Committee Chair); Kenneth Berman, Ph.D. (Committee Member); Wen Ben Jone, Ph.D. (Committee Member); Anca Ralescu, Ph.D. (Committee Member); Xuefu Zhou, Ph.D. (Committee Member)

Subjects:

Computer Science

Keywords:

Clustering algorithm;K-Means;K-Centers Min-Max clustering algorithm;mean-shift;K-Centers Mean-shift Reverse Mean-shift;wireless sensor networks

Shoaib, NaveedA Portable and Improved Implementation of the Diffie-Hellman Protocol for Wireless Sensor Networks
Master of Science in Mathematics, Youngstown State University, 2009, Department of Mathematics and Statistics
Wireless sensor nodes generally face serious limitations in terms of computational power, energy supply, and network bandwidth. One of the biggest challenges faced by researches today is to provide effective and secure techniques for establishing cryptographic keys between wireless sensor networks. Public-key algorithms (such as the Diffie-Hellman key-exchange protocol) generally have high energy requirements because they require computational expensive operations. So far, due to the limited computation power of the wireless sensor devices, the Diffie-Hellman protocol is considered to be beyond the capabilities of today's sensor networks. We analyzed existing methods of implementing Diffie-Hellman and proposed a new improved method of implementing the Diffie-Hellman key-exchange protocol for establishing secure keys between wireless sensor nodes. We also provide an easy-to-use implementation of the Elliptic Curve Diffie-Hellman key-exchange protocol for use in wireless sensor networks.

Committee:

Graciela Perera, PhD (Advisor); John Sullins, PhD (Committee Member); Jamal Tartir, PhD (Committee Member)

Subjects:

Communication; Computer Science; Information Systems; Mathematics

Keywords:

Wireless Sensor Networks; Sun SPOTS; Diffie-Hellman Key-Exchange Protocol; Elliptic Curve Cryptography; Elliptic Curve Diffie-Hellman; Portable Diffie-Hellman

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