In Intelligent Transport Systems (ITS), the unavailable Road Side Unit (RSU) becomes an increasing serious safety-related problem because of its important role in ITS. However, there is no existing method to solve this problem effectively and stably nowadays. To solve the unavailable RSU problem, a novel 2-tier integrated communication system is proposed in this thesis to address the issue of unavailable RSU in ITS. Compared to some other solutions proposed in the previous research works, which mostly focus on improving the system performance by adjusting parameters of vehicular ad-hoc network among vehicles, the proposed 2-tier communication network, called ITS-LEO Integrated System (ILIS), is composed of conventional ITS system and Low Earth Orbit (LEO) mobile satellite system (MSS), where the LEO MSS is utilized as the complementary network when the RSU is unavailable. Since the LEO MSS primary message will get affected when overflowing messages from ITS to LEO MSS, we prioritize LEO MSS primary message over the overflowed message to minimize the effect, which is based on that the emergency message (EMsg) is given higher priority over routine message (RMsg) to get access to the channel in ITS. To optimize the utility of network resource, two different overflowing mechanisms are proposed in ILIS to improve system efficiency under different traffic density. Furthermore, we propose a bandwidth reservation protection mechanism for ILIS to increase the ITS network performance. A real-time simulation program in C++ is developed to evaluate the performance of ILIS in terms of Packet Loss Rate (PLR) and Delay, and simulation results show that adding LEO MSS as a complementary network to ITS is an effective way to solve the problem of an unavailable RSU.

In today’s era of the Internet of Things, it is crucial to study the real-time dependencies of the web, its failures and time delays. Today, smart grids, sensible homes, wise water networks, intelligent transportation, infrastructure systems that connect our world over are developing fast. The shared vision of such systems is typically associated with one single conception Internet of Things (IoT), where through the deployment of sensors, the entire physical infrastructure is firmly fastened with information and communication technologies; where intelligent observation and management is achieved via the usage of networked embedded devices. The performance of a real-time control depends not only on the reliability of the hardware and software used but also on the time delay in estimating the output, because of the effects of computing time delay on the control system performance. For a given fixed sampling interval, the delay and loss issues are the consequences of computing time delay. The delay problem occurs when the computing time delay is non-zero but smaller than the sampling interval, while the loss problem occurs when the computing time delay is greater than, or equal to, the sampling interval, i.e., loss of the control output. These two queries are analyzed as a means of evaluating real-time control systems. First, a general analysis of the effects of computing time delay is presented along with necessary conditions for system stability. In this thesis, we will focus on the experimental study of the closed loop control system in the internet of things to determine the cycle time constraints in case of link failure.

Reachability analysis is one of the earliest and most common techniques for protocol validation. It is well suited to checking the protocol syntactic properties since they are a direct consequence of the structure of the reachability tree. However, validations of unbounded protocols via reachability analysis always lead to the "state explosion" problem. To overcome this, a new approach in reachability analysis has been proposed by Vuong et al [Vuong 82a, 83a]. While not loosing any information on protocol syntactic properties, the Teachability tree constructed by the new approach for all non-FIFO and for a particular set of FIFO protocols (called well-ordered protocols) will become finite. This thesis is concerned with the implementation of an integrated package called VALIRA (VALIdation via Reachability Analysis) which bases on both the proposed technique and the conventional technique. Details and implementation of the various approaches used in VALIRA are presented in order to provide an insight to the package. Various features of the package are demonstrated with examples on different types of protocols, such as the FIFO, the non-FIFO, and the priority protocols. The use of VALIRA was found to be practical in general, despite some limitations of the package. Further enhancements on the VALIRA are also suggested. / Science, Faculty of / Computer Science, Department of / Graduate

With the increasing need for distributed processing and computer networking, the demand for open systems interconnection (OSI) has also increased. In [Davis-88], Davis et al propose a new generation portable protocol tester that will be able to provide conformance testing for OSI protocol implementations. In this thesis report, a specialized programmable hardware module, called protocol decoding accelerator (PDA), is designed to be used as the PDU decoder engine being defined in the Davis architecture. PDU decoding is the process of parsing the PDU header fields into a data structure that can be more readily used by other processes. Decoding can be time consuming because there is a large variety of PDU fields and formats. Conventional approach to PDU decoding is often implemented as software program designed for general purpose processor architecture. However, most general purpose processors do not handle PDU decoding efficiently. There are other VLSI protocol controllers, but they all have limited programmability and flexibility. The PDA is developed based on a simple instruction set with dedicated hardware to optimize important functions. Using selected PDU types and decoding programs from OSI layer 2 to 4 protocols, the resulting PDA design shows a minimum of 16 times faster average execution time and about five times smaller program size when compared to a 68000 system. / Applied Science, Faculty of / Electrical and Computer Engineering, Department of / Graduate

The lack of analytical models that can accurately describe large-scale networked systems makes empirical experimentation indispensable for understanding complex behaviors. Research on network testbeds for testing network protocols and distributed services, including physical, emulated, and federated testbeds, has made steady progress. Although the success of these testbeds is undeniable, they fail to provide: 1) scalability, for handling large-scale networks with hundreds or thousands of hosts and routers organized in different scenarios, 2) flexibility, for testing new protocols or applications in diverse settings, and 3) inter-operability, for combining simulated and real network entities in experiments. This dissertation tackles these issues in three different dimensions. First, we present SVEET, a system that enables inter-operability between real and simulated hosts. In order to increase the scalability of networks under study, SVEET enables time-dilated synchronization between real hosts and the discrete-event simulator. Realistic TCP congestion control algorithms are implemented in the simulator to allow seamless interactions between real and simulated hosts. SVEET is validated via extensive experiments and its capabilities are assessed through case studies involving real applications. Second, we present PrimoGENI, a system that allows a distributed discrete-event simulator, running in real-time, to interact with real network entities in a federated environment. PrimoGENI greatly enhances the flexibility of network experiments, through which a great variety of network conditions can be reproduced to examine what-if questions. Furthermore, PrimoGENI performs resource management functions, on behalf of the user, for instantiating network experiments on shared infrastructures. Finally, to further increase the scalability of network testbeds to handle large-scale high-capacity networks, we present a novel symbiotic simulation approach. We present SymbioSim, a testbed for large-scale network experimentation where a high-performance simulation system closely cooperates with an emulation system in a mutually beneficial way. On the one hand, the simulation system benefits from incorporating the traffic metadata from real applications in the emulation system to reproduce the realistic traffic conditions. On the other hand, the emulation system benefits from receiving the continuous updates from the simulation system to calibrate the traffic between real applications. Specific techniques that support the symbiotic approach include: 1) a model downscaling scheme that can significantly reduce the complexity of the large-scale simulation model, resulting in an efficient emulation system for modulating the high-capacity network traffic between real applications; 2) a queuing network model for the downscaled emulation system to accurately represent the network effects of the simulated traffic; and 3) techniques for reducing the synchronization overhead between the simulation and emulation systems.

Indiana University-Purdue University Indianapolis (IUPUI) / Many complex processes can be viewed as sequential events on a network. In this thesis, we study the interplay between a network and the event sequences on it. We first focus on predicting events on a known network. Examples of such include: modeling retweet cascades, forecasting earthquakes, and tracing the source of a pandemic. In specific, given the network structure, we solve two types of problems - (1) forecasting future events based on the historical events, and (2) identifying the initial event(s) based on some later observations of the dynamics. The inverse problem of inferring the unknown network topology or links, based on the events, is also of great important. Examples along this line include: constructing influence networks among Twitter users from their tweets, soliciting new members to join an event based on their participation history, and recommending positions for job seekers according to their work experience. Following this direction, we study two types of problems - (1) recovering influence networks, and (2) predicting links between a node and a group of nodes, from event sequences.

Capsule Networks are the next generation of image classifiers. Although they have several advantages over conventional Convolutional Neural Networks (CNNs), they remain computationally heavy. Since inference on Capsule Networks is timeconsuming, thier usage becomes limited to tasks in which latency is not essential. Approximation methods in Deep Learning help networks lose redundant parameters to increase speed and lower energy consumption. In the first part of this work, we go through an algorithm called zero-skipping. More than 50% of trained CNNs consist of zeros or values small enough to be considered zero. Since multiplication by zero is a trivial operation, the zero-skipping algorithm can play a massive role in speed increase throughout the network. We investigate the eligibility of Capsule Networks for this algorithm on two different datasets. Our results suggest that Capsule Networks contain enough zeros in their Primary Capsules to benefit from this algorithm. In the second part of this thesis, we investigate pruning as one of the most popular Neural Network approximation methods. Pruning is the act of finding and removing neurons which have low or no impact on the output. We run experiments on four different datasets. Pruning Capsule Networks results in the loss of redundant Primary Capsules. The results show a significant increase in speed with a minimal drop in accuracy. We also, discuss how dataset complexity affects the pruning strategy. / Graduate

The thesis describes a design and implementation of Nemea system module purposed on generation of records about simulated network attacks. This thesis also contains brief description of Nemea system and several network attacks. Finally, part of this work is description of simulated attacks and methods of simulations.

Artificial chemistries can be used to explore the generic properties of chemical reaction networks. In order to simulate for instance scenarios of prebiotic evolution the model must be close enough to real chemistry to allow at least semi-quantitative comparisons. One example is a previously described Toy Model that represents molecules as graphs, thereby neglecting 3D space, and employs a highly simplified version of the Extended H¨uckel Theory (EHT) to compute molecular properties. Here we show how the Toy Model can be extended to multiple phases by connecting the EHT calculations with chemical thermodynamics.

archives@tulane.edu / The thalamocortical network generates rhythmic oscillations of various frequencies that underlie different brain states. Importantly, the transition from a faster frequency of firing, spindle, to slower oscillations, spike and wave discharges, is indicative of the pathological epileptic seizure development. Previous investigations have shown that the complex interactions between neurons in the thalamocortical network based on intrinsic and synaptic properties give rise to the observed frequency changes. However, the exact mechanism of how perturbations in this circuit disrupt the oscillations is not known. In this project, we used a well-established thalamocortical network computational model to perform receptor conductance changes to see how the oscillatory activity in the thalamocortical network changes. Computational methods can be used to provide some mathematical explanations regarding the mechanism of oscillations. Therefore, we generated several phase resetting curves by perturbing neurons during its oscillating period. Our results showed that the frequency reduction under the pathological state in the thalamocortical network might be caused by hyper-synchronization of neuronal activities in this circuit mediated by glutamatergic AMPA receptors. Notably, thalamic reticular neurons are capable of firing at a faster or slower frequency depending on the timing of the input that they receive from other neurons. Overall, our results provided evidence to support the hypothesis that thalamic reticular neurons might be the ultimate pacemakers in the thalamocortical network. / 1 / Hanyun Wang