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Title: MINIMIZING MAXIMUM PATH DELAY IN MULTIPATH CONNECTIONS
Creator: Devetak, Fabrizio U
Date: 2013, 2013-07
Description: Minimizing packet delay (or packet latency, as it is often called) is an impor- tant goal in modern telecommunication networks. In a network...
Show moreMinimizing packet delay (or packet latency, as it is often called) is an impor- tant goal in modern telecommunication networks. In a network with given physical and topological characteristics, uneven distribution of tra c between nodes may re- sult in parts of the network being underutilized while other parts may experience congestion and its related e ect of higher delays, and even packet loss if bu ers be- come overloaded. Overload results in longer queuing delays, which are a major, if not the major, source of packet delay. Internet nodes typically route based on a single best (shortest) path without taking into account link occupancy and without taking full advantage of all available network resources. So a method for improving network performance is to allow nodes to use multiple paths to route packets to a given desti- nation. In this research project the main objective is to nd the best algorithm that, applied to a multi-commodity network, produces multi-path ow assignments that minimize the maximum cross-network delay. The motivation for this objective is the tighter requirements for quality of service coming from real-time streaming services, such as voice and video, which restrict the maximum source-destination packet delay. An analytical approach, based on Lagrange Multipliers, was investigated which led to the design of an iterative algorithm that can be proved to converge to the opti- mal path and ow con guration. From that algorithm a simpli ed heuristic algorithm was derived, that achieves results close to optimal. Another heuristic but more intu- itive algorithm, similar to the algorithm described in [6], was also investigated and found to also o ers good results and to be computationally e cient. The two heuristic algorithms were simulated with Java programs and, as a benchmark, the single path algorithm that is commonly used in the Internet was also simulated. That simulation was also done with Java programs. Performance comparisons for the three types of simulations is also provided. For a more realistic evaluation, the intuitive heuristic algorithm was also simu- viii lated in the NS-3 simulation environment (in addition to the Java simulation). NS-3 is a state-of-the-art industry standard widely used in the academic world, and for it a distributed routing protocol, that implements the maximum delay minimization algorithms without centralized control, was designed.
PH.D in Computer Engineering, July 2013
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Title: REAL-TIME INTRUSION DETECTION FOR VOIP OVER WIRELESS NETWORKS
Creator: Tang, Jin
Date: 2012-07-16, 2012-07
Description: Voice over IP (VoIP) has emerged as a prevailing application in recent years. At the same time, with the increasing coverage of the IEEE 802...
Show moreVoice over IP (VoIP) has emerged as a prevailing application in recent years. At the same time, with the increasing coverage of the IEEE 802.11 based wireless networks, VoIP over wireless networks is drawing extensive attention in both academia and industry. Due to the openness and distributed nature of the protocols involved in VoIP over wireless, such as the session initiation protocol (SIP) and the IEEE 802.11 standard, it becomes easy for malicious users in the network to achieve their own gain or disrupt the service by deviating from the normal protocol behaviors. The main objective of this research is to develop real-time intrusion detection techniques that can quickly track down the malicious behaviors which manipulate the vulnerabilities from either VoIP or 802.11 protocols. Further, we will achieve the objective without requiring modification to the relevant standard protocols, and develop analytical tools to guide the detection system design for guaranteed performance. Specifically, for the malicious selfish misbehavior utilizing vulnerabilities of the 802.11 protocol, we design a real-time detector, termed as the fair share detector (FS detector), which exploits the non-parametric cumulative sum (CUSUM) test to quickly find a selfish malicious node without any a priori knowledge of the statistics of the selfish misbehavior. And while most of the existing schemes for selfish misbehavior detection depend on heuristic parameter configuration and experimental performance evaluation, we develop a Markov chain based analytical model to systematically study the FS detector. Based on the analytical model, we can quantitatively compute the system configuration parameters for guaranteed performance. Further, to achieve better detection performance, we enhance the FS detector to develop an adaptive detector with the Markov decision process (MDP). Then based on a reward function defined by us, we are able to determine an optimal decision policy to maximize the overall system benefit through a linear programming formulation. The optimal policy also indicates the operation of the adaptive detector, which yields better performance in both false positive rate and detection delay. For attacks on the SIP layer, we first focus on the well-known flooding attack and develop an online scheme to detect and subsequently prevent the attack, by integrating a novel three-dimensional sketch design with the Hellinger distance detection technique. Also, we address the stealthy attack, where intelligent attackers can afford long time to attack the system, and only incur minor changes to the system within each sampling period. To identify such attacks in the early stage for a timely response, we propose a detection scheme based on the signal processing technique wavelet, which is able to quickly expose the changes induced by the attacks. Moreover, we identify a new type of malformed message attack that can manipulate both the “Session-Expires” header in the SIP message and openness of wireless protocols to severely drain the network resources. We develop a detection method based on the Anderson-Darling test to deal with such attacks. In the future work, we will continue with the CUSUM-based framework for selfish misbehavior detection over practical multi-hop wireless networks with guaranteed performance. It is expected that we can generate distributed CUSUM-based detection mechanisms for the multi-hop networks, analytical tools for the distributed detection system, and configuration parameter selection methods for guaranteed detection performance. Moreover, as attackers can employ the openness of the 802.11 protocols to generate more severe and harder-to-detect attacks to the SIP based VoIP system, to further enhance the detection performance, we plan to develop cross-layer intrusion detection techniques for the system.
Ph.D. in Computer Engineering, July 2012
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Title: WIRELESS SENSOR NETWORK BASED BUILDING AUTOMATION SYSTEM
Creator: Yi, Peizhong
Date: 2012-07-11, 2012-07
Description: Smart grid adds intelligence and bidirectional communication capabilities to today’s power grid, enabling utilities to provide real-time...
Show moreSmart grid adds intelligence and bidirectional communication capabilities to today’s power grid, enabling utilities to provide real-time-pricing (RTP) information to their customers via smart meters. This facilitates customer participation in demand response programs to reduce peak electricity demand. ZigBee, as a wireless technology characterized by low cost, power, data rate, and complexity, is ideal for smart grid applications. Unfortunately, almost all ZigBee channels overlap with Wireless Local Area Networks (WLAN) channels, resulting in severe performance degradation. In this dissertation, firstly, practical ZigBee deployment guidelines under WLAN interference are presented. “Safe Distance” and “Safe Offset Frequency” are identified by means of a comprehensive approach consisting of theoretical analysis, software simulation, and empirical measurement. In addition, a frequency-agility based interference avoidance algorithm is proposed and is implemented. The proposed algorithm detects interference and adaptively switches nodes to “safe” channels dynamically to avoid interference with low latency and energy overhead. Later we propose a real-time residential demand response scheme based on price information provided by ZigBee enabled smart meters. We model the price signal as a random process with known deterministic components, and formulate the problem of cost-minimization as a stochastic scheduling problem. A constraint on the total power consumption is considered to avoid peak shifting. An opportunistic scheduling algorithm consisting of two stages is proposed. Each user is tentatively scheduled based on the optimal stopping approach as if there is no power constraint at the first stage, while the power constraint is taken into account at the second stage. The proposed scheduling algorithm can be implemented in either a centralized or distributed fashion. Simulations validate proposed scheme can evidently reduce the cost of electricity users. At last, an optimal and automatic residential load scheduling scheme with distributed storage system based on our price prediction scheme is proposed. The price prediction scheme forecasts the future 24-hour prices according to day-ahead pricing and RTP history. Our designed scheme adopts integer programming computation to provide simple solution for customers to minimize the total cost including electricity expenditure and storage degradation while satisfying customer time requirement. The performance of proposed scheme is then evaluated through simulation.
Ph.D. in Electrical Engineering, July 2012
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Title: DIGITAL CONTROL OF 2-QUADRANT AND 4-QUADRANT SWITCHED RELUCTANCE MOTOR DRIVES
Creator: Shao, Baiming
Date: 2011-04-19, 2011-05
Description: Switched reluctance machines (SRMs) are attractive because of their manufacturing simplicity and high reliability. They do not have any...
Show moreSwitched reluctance machines (SRMs) are attractive because of their manufacturing simplicity and high reliability. They do not have any windings or permanent magnets on the rotor, which makes them robust and easy to maintain. On the other hand, SRMs are highly non-linear since they work in saturation. This causes problems such as high torque ripple and system noise. In addition, mutual inductance needs to be considered for the high performance systems such as electric vehicle or aerospace applications. This effect could become critical when more than one phase is conducting. This also makes them difficult for modeling and control. Significant research on different SRM control techniques has been done in order to improve the performance of the controller and present a good solution for the industrial applications with a reasonable cost. Conventional control techniques for SRMs include chopped current control (CCC), angular position control (APC), and pulse-width modulation (PWM). Proportional-integral (PI) and other linear controllers are also used in the drive systems. However, because of the non-linearity of the machine, classic linear control techniques are not ideal for SRMs as they have challenging control issues in wide speed ranges. Different methods have been presented to implement non-linear control techniques for SRM drives or linearize the SRM motor equations. Many SRM controllers are using one or more look-up tables. The behavior of the controller is adjusting in real-time depending on the data in the look-up tables. This could increase the cost and complexity of the system. In this Ph.D. dissertation, an advanced digital control concept is presented for SRMs in both motoring and generating modes. By treating the system digitally, the controller switches between two pre-defined states to get the desired output. The proposed control technique does not need any look up tables, is not sensitive to the motor parameter variations, is low cost, and has a wide speed range. Simulation and experimental results are presented to verify the proposed digital control approach.
Ph.D. in Electrical and Computer Engineering, May 2011
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Title: SEQUENTIAL MONTE CARLO METHODS FOR PARAMETER ESTIMATION, DYNAMIC STATE ESTIMATION AND CONTROL IN POWER SYSTEMS
Creator: Maldonado, Daniel Adrian
Date: 2017, 2017-05
Description: The estimation, operation and control of electrical power systems have always contained a degree of uncertainty. It is expected that, with the...
Show moreThe estimation, operation and control of electrical power systems have always contained a degree of uncertainty. It is expected that, with the introduction of technologies such as distributed generation and demand-side management, the ability of system operators to forecast the dynamic behavior of the system will deteriorate and as a result, the cost of keeping the system together will increase. Sequential Monte Carlo or Particle Filtering is a family of algorithms to efficiently perform inference in non-linear dynamic systems by exploiting their structure without assuming any linearity or normality structure. In this thesis we provide two novel ways of employing these algorithms for inference and control of power systems. First, we motivate the use Bayesian statistics in load modelling by introducing a novel statistical model to capture the aggregated response of a set of loads. We then use the model to characterize load with measurement data and prior information using the Sequential Monte Carlo algorithm. Second, we introduce the Model Predictive Control for power system stabilization. We present the use of the Sequential Monte Carlo algorithm as a way of solving the stochastic Model Predictive Control problem and we compare its performance to existing regulators. In addition, Model Predictive Control is applied to load shedding Finally, we test the performance of the algorithm in a large power system scenario.
Ph.D. in Electrical Engineering, May 2017
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Title: OPTIMAL LOAD SCHEDULING IN COMMERCIAL AND RESIDENTIAL MICROGRIDS
Creator: Ganji Tanha, Mohammad Mahdi
Date: 2015, 2015-05
Description: Residential and commercial electricity customers use more than two third of the total energy consumed in the United States, representing a...
Show moreResidential and commercial electricity customers use more than two third of the total energy consumed in the United States, representing a significant resource of demand response. Price-based demand response, which is in response to changes in electricity prices, represents the adjustments in load through optimal load scheduling (OLS). In this study, an efficient model for OLS is developed for residential and commercial microgrids which include aggregated loads in single-units and communal loads. Single unit loads which include fixed, adjustable and shiftable loads are controllable by the unit occupants. Communal loads which include pool pumps, elevators and central heating/cooling systems are shared among the units. In order to optimally schedule residential and commercial loads, a community-based optimal load scheduling (CBOLS) is proposed in this thesis. The CBOLS schedule considers hourly market prices, occupants’ comfort level, and microgrid operation constraints. The CBOLS’ objective in residential and commercial microgrids is the constrained minimization of the total cost of supplying the aggregator load, defined as the microgrid load minus the microgrid generation. This problem is represented by a large-scale mixed-integer optimization for supplying singleunit and communal loads. The Lagrangian relaxation methodology is used to relax the linking communal load constraint and decompose the independent single-unit functions into subproblems which can be solved in parallel. The optimal solution is acceptable if the aggregator load limit and the duality gap are within the bounds. If any of the proposed criteria is not satisfied, the Lagrangian multiplier will be updated and a new optimal load schedule will be regenerated until both constraints are satisfied. The proposed method is applied to several case studies and the results are presented for the Galvin Center load on the 16th floor of the IIT Tower in Chicago.
Ph.D. in Electrical and Computer Engineering, May 2015
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Title: MODELING AND PERFORMANCE ANALYSIS OF DISTRIBUTED COMPUTER NETWORKS WITH DIFFERENTIATED SERVICES
Creator: Monsef, Ehsan
Date: 2015, 2015-07
Description: The rapid growth of data usage in wired and wireless networks has witnessed an increase in diversity of user tra c in the last few decades. A...
Show moreThe rapid growth of data usage in wired and wireless networks has witnessed an increase in diversity of user tra c in the last few decades. A network with di eren- tiated services guarantees the provision of Quality of service(QoS) for di erent tra c classes by incorporating various class-based scheduling disciplines. Recently, there has been interest in the study of network performance modeling in networks with di erentiated services. In particular, the performance modeling of di erentiated ser- vice networks in distributed architectures has attracted several network communities. The heterogeneity of user tra c can have major impact on the overall performance of resource allocation problems in computer networks. This work aims at shedding light on the performance modeling of distributed wired and wireless environments with di erentiated services. We study the performance of priority-based distributed schemes for several important network applications: (i) network routing(load balanc- ing) in wired network (ii) network selection in wireless environment (iii) scheduling in Body Area Networks and (vi) Interference mitigation scheme for Wireless Body Area Networks. We will utilize Game-theoretic models to model the interaction between network entities and evaluate the system performance analytically and empirically. Our main objective is to investigate the degree in which various service di erentiation mechanisms have impact on the overall performance of distributed networks. We an- alyze several important equilibria properties such as existence, convergence time, and ine ciency for the studied network scenarios. Extensive simulations are conducted to empirically evaluate our game-theoretic analysis for di erent network applications. First, we study a network of parallel links where each link incorporates General Processor Sharing scheduling mechanism. Using the non-cooperative game model, we investigate the existence and uniqueness of equilibrium points. We study the e ciency of equilibria by deriving an upper bound on the Price of Anarchy (PoA). Finally, we utilize the simulation to compare our PoA bound with actual bound. Second, we study wireless network selection in a distributed environment with Discriminatory Processor Sharing (DPS) scheduling discipline. We consider a set of wireless clients in a network composed of multiple base stations with di erentiated services. The goal of each wireless client is to assign itself to a wireless base station that gives the higher throughput. We formulate the interaction between clients as a weighted congestion game and investigate the existence of equilibria. We show that the equilibrium does not necessarily exists for a general network model. We give several regimes under which the equilibrium is guaranteed to exist. These regimes are implemented either on the base stations or wireless clients. Furthermore, we derive several upper bounds on the equilibrium convergence time and give an extensive simulation to evaluate our results. Third, we consider the interaction between autonomous Wireless Body Area Networks(WBAN) in a crowded environment such as hospital. We propose a dis- tributed approach that mitigates the inter-WBAN interference using the game theory models. The interaction between WBANs is modeled as an in nite repeated game. We propose a "grim" strategy for the formulated game and prove the SPE property under speci c conditions. Furthermore, we investigate the equilibrium by comparing that to a sub-optimal Pareto strategy. We test our results using a speci c simulator designed for WBAN. Finally, we propose a new QoS framework for WBAN architecture. The goal of this framework is to implement a separate QoS layer in the design of WBAN stack protocol so that it becomes independent of the application layer. The framework o ers an application pro le interface where each application can submit its QoS require- ments. The implementation of QoS framework in a separate layer and independent of application layer enables more scalable WBAN application development.
Ph.D. in Computer Engineering, July 2015
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Title: CHIRPLET SIGNAL DECOMPOSITION AND PARAMETER ESTIMATION ALGORITHMS FOR ULTRASONIC SIGNAL ANALYSIS
Creator: Kasaeifard, Alireza
Date: 2012-12-03, 2012-12
Description: In ultrasonic imaging systems, shape, size and orientation of the reflectors and the physical properties of the propagation path govern the...
Show moreIn ultrasonic imaging systems, shape, size and orientation of the reflectors and the physical properties of the propagation path govern the patterns of backscattered echoes. However, the backscattered echoes often interfere with each other due to closed locations, orientations and size of reflectors and may be corrupted by noise. Hence, signal modeling and parameter estimation of the ultrasonic echoes are essential for image analysis, detection, classification and diagnosis. Certain important information like position, shape and size of the reflectors can be represented by chirplet signal parameters. Similarly, in other important application area of signal modeling such as radar, sonar and speech, chirplet signal parameters are also critical. The objective of this study is to analyze the pattern of ultrasonic echoes using chirplet signal decomposition and parameter estimation techniques. Signal processing method for decomposing multiple interfering ultrasonic echoes is a major and challenging problem. The chirplet signal decomposition algorithms designed and analyzed in this investigation are based on the Fractional Fourier Transform (FrFT) and elliptic template matching applied to time-frequency distributions of ultrasonic signals. This study has a broad range of applications of importance in signal detection, estimation, and pattern recognition. Fractional Fourier Transform based Chirplet Signal Decomposition (FrFT-CSD) algorithm is proposed to analyze ultrasonic signals for NDE applications. Particularly, this method is utilized to isolate dominant chirplet echoes for successive steps in signal decomposition and parameter estimation. FrFT rotates the signal with an optimal transform order. The search of optimal transform order is conducted by determining the highest kurtosis value of the signal in the transformed domain. A simulation study reveals xi the relationship among the kurtosis, the transform order of FrFT, and the chirp rate parameter in the simulated ultrasonic echoes. Benchmark and ultrasonic experimental data are used to evaluate the FrFT-CSD algorithm. Signal processing results show that FrFT-CSD not only reconstructs signal successfully, but also characterizes echoes and estimates echo parameters accurately. To accelerate echo estimation algorithm, we present a novel method for estimating the parameters of chirp echo by means of ellipse fitting in the Time-Frequency (TF) domain. Wigner-Ville Distribution (WVD) and Short-Time Fourier Transform (STFT) of chirplets are in the form of concentric ellipses in the TF plane. The elements of ellipse such as long axis, short axis and the slope of the ellipse correspond to the chirplet parameters and this can be used for parameter estimation. To demonstrate the parameter estimation performance of ellipse fitting method, the algorithm is used to decompose an ultrasonic experimental signal consisting of many interfering echoes acquired in nondestructive testing of a steel block. The comparison between the reconstructed signal and the experimental result shows that the decomposition has been successfully performed in the presence of measurement noise and interference from microstructure scattering echoes. The Ellipse Fitting Method (EFM) employs short-time Fourier transform as the main computational load of the algorithm that makes it a good candidate for real-time applications using FFT hardware accelerators. In this study we also present a Field-Programmable Gate-Array (FPGA) implementation that is able to perform chirplet signal decomposition using EFM. The EFM algorithm has been implemented as a system-on-chip consisting hardware architecture and software code on a Xilinx Virtex-5 FPGA. The xii designed hardware architecture is a combination of an embedded Microblaze processor, IP cores, communication buses, and I/Os. The software component represents a portion of the estimation algorithm that runs on the Microblaze processor. The EFM algorithm is used to decompose an ultrasonic experimental signal consisting of many interfering echoes.. The profiling analysis shows the major portion of the execution time (i.e., 94%) is for the FFT computations. By adding and interfacing the FFT IP-core accelerator to Microblaze, the estimation time for each chirp echo is reduced by 85% (i.e. from 550 ms to 82 ms). This reduction in echo estimation is highly desirable and makes the real-time parameteric signal analysis practical.
PH.D in Electrical Engineering, December 2012
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Title: A NOVEL SWITCHED RELUCTANCE MOTOR BASED PROPULSION DRIVE FOR ELECTRIC AND PLUG-IN HYBRID ELECTRIC VEHICLES
Creator: Bilgin, Berker
Date: 2011-07, 2011-07
Description: Hybrid and Plug-in hybrid electric vehicles (HEVs and PHEVs) have received increasing attention from the automotive industry over the recent...
Show moreHybrid and Plug-in hybrid electric vehicles (HEVs and PHEVs) have received increasing attention from the automotive industry over the recent years. They are typically more efficient and they produce lower emissions than similar ICE-based vehicles, which significantly reduces their negative impact on the environment. In this study, design considerations of two fundamental parts of plug-in vehicles, traction motor and battery charger circuit, have been investigated toward the drivetrain applications in a solar assisted plug-in electric auto rickshaw. Switched reluctance motors (SRM) have been seen as potential candidates for propulsion systems over the last few years. They are robust, capable of performance in harsh operating conditions and have a wide speed range. Conventional SRM configurations have a higher number of stator poles than rotor poles. This PhD. dissertation presents the advantages of a novel SRM configuration with the number of rotor poles greater than number of stator poles and investigates the challenges in its design. Practical design considerations have been proposed and by using them a 3 phase 5 hp 6/10 SRM is designed, constructed and tested. A PHEV is a series or parallel hybrid electric vehicle equipped with a high energy density battery to extend the mileage and get better fuel efficiency. Since the capacity of the battery is higher than the sum of the energy that can be supplied by the internal combustion engine and regained from the regenerative braking, external charging from the grid is necessary. This research also investigates the requirements of the battery charger circuit and proposes low cost topology composed of a PWM boost rectifier cascaded with a bidirectional DC/DC converter. Operation of the circuit has been x xvii analyzed by deriving its mathematical model. Feedback controller requirements to control the input and output current and DC bus voltage have been studied. Critical issues to be considered in parameter selection of the voltage and current controller are explained in terms of universal input operation. In order to verify the analysis presented, an experimental hardware setup has been built and tested.
Ph.D. in Electrical Engineering, July 2011
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Title: APPLICATION OF MACHINE LEARNING TO ELECTRICAL DATA ANALYSIS
Creator: Bao, Zhen
Date: 2017, 2017-05
Description: The dissertation is composed of four parts: modeling demand response capability by internet data centers processing batch computing jobs,...
Show moreThe dissertation is composed of four parts: modeling demand response capability by internet data centers processing batch computing jobs, cloud storage based power consumption management in internet data center, identifying hot socket problem in smart meters, and online event detection for non-intrusive load monitoring without knowing label. Mathematical models are constructed to fulfill the research of the four targets, and numerical examples are used to test the effectiveness of the models. The first two parts optimize jobs in Data Center in order to find the best way of utilizing the existing computing resources and storage. Mixed-integer programming (MIP) is used in the formulation. The purpose of the third part is to identify the hot socket problem in smart meter. Machine learning method has been used to locate the bad installation of smart meters by analyzing historical data from smart meters. The fourth part is non-intrusive load monitoring for residential load in houses. Signal processing and deep learning methods are used to identify the specific loads from high frequency signals.
Ph.D. in Electrical Engineering, May 2017
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Title: DESIGN AND OPTIMIZATION OF NEXT GENERATION WIRELESS NETWORKS
Creator: Shila, Devu Manikantan
Date: 2011-04-10, 2011-05
Description: A novel paradigm of communication, multi-hop wireless networks, have recently emerged both as a promising and cost-effective architecture to...
Show moreA novel paradigm of communication, multi-hop wireless networks, have recently emerged both as a promising and cost-effective architecture to meet the evergrowing demands and expectations of the users. In these class of networks, a collection of wireless nodes dynamically establish and maintain connectivity among themselves, thus, enabling users and nodes to seamlessly internetwork in areas with a little or no communication infrastructure. Due to the self-organizing and self-configuring nature, these networks make a suitable choice for variety of applications ranging from broadband home networking, intelligent transport system (ITS) to smart grid networking. In spite of the multiple aspects of advantages, however, research efforts have shown that when nodes are randomly or arbitrarily placed in a two-dimensional region, the amount of information that can be transmitted by each source-destination pair in a multi-hop fashion becomes vanishingly small, as number of nodes grows to a large level. Although, in the past, we have designed and developed several solutions to improve the efficiency of protocols for multi-hop wireless networks, the overall information-carrying capacity of these networks is still a critical issue to meet the increasing user requirements. Motivated by such an issue, in this dissertation we are concerned with the problem of optimizing the capacity of multi-hop wireless networks. First, we propose to use a combination of cooperative communications and multiple channels, which together has great potential to evade various issues that limits the capacity of wireless networks. Further, using the insights of the proposed approach, we design a channel allocation protocol at the MAC layer for wireless networks employing cooperative communications. We also construct an analytical model to optimize the parameters used in the MAC protocol design. Second, we study the performance improvement in a multi-hop wireless network by coupling it with the coverage and capacity of infrastructure networks, referred to as hybrid wireless networks. In doing so, we point out severe flaws in the existing research efforts and design a simple and practical power-aware routing policy, that can adapt to the operating environment, for hybrid wireless networks. In comparison to existing works, we clearly show the gain one could obtain on delay as well as on capacity in executing our design. Lastly, we propose to use transmission power of nodes to increase the amount of information sent across each wireless link. While prior solutions rely on minimum transmission power to improve spatial reuse or lifetime of nodes, we look at the power problem from a different perspective and show that one can obtain a significant gain in capacity by judiciously enhancing the power in a multi-channel multi-hop wireless network. To prove this interesting result, we essentially introduce the novel concept of a co-channel enlarging effect and then quantify the maximum power at which nodes can communicate on a given channel, without causing harmful interference to other simultaneously communicating pairs. We conclude this dissertation by identifying open issues that need further investigation.
Ph.D. in Computer Engineering, May 2011
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