<p>The growing demand for faster, more reliable wireless connectivity has brought about the development of the 802.11ax (Wi-Fi 6/6E) amendment, which aims to satisfy the increasing need for seamless wireless connectivity and improved traffic handling. The 802.11ax amendment introduces noteworthy improvements to the 802.11 wireless standard that should greatly improve the efficiency of wireless networks. The body of existing research has seen several simulated 802.11ax environments and found great success, however, these additions remain largely untested in physical environments. This thesis undertakes the testing for 802.11ax MU-MIMO to determine if these simulated successes translate into real-world improvements. By using a classroom scenario, the study investigates the performance improvements purported by 802.11ax, specifically the updated and expanded DL and UL MU-MIMO in an environment with high client numbers and density. </p>

<div>Anonymous communication networks (ACNs) are critical to communication privacy over the internet as they enable</div><div>individuals to maintain their privacy from untrusted intermediaries and endpoints.</div><div>Typically, ACNs involve messages traveling through some intermediaries before arriving at their destinations, and therefore they introduce network latency and bandwidth overheads. </div><div><br></div><div>The goal of this work is to investigate the fundamental constraints of anonymous communication (AC) protocols.</div><div>We analyze the relationship between bandwidth overhead, latency overhead, and sender anonymity or recipient anonymity against a global passive (network-level) adversary. </div><div>We confirm the widely believed trilemma </div><div>that an AC protocol can only achieve two out of the following three properties: </div><div>strong anonymity (i.e., anonymity up to a negligible chance),</div><div>low bandwidth overhead, and low latency overhead. </div><div><br></div><div>We further study anonymity against a stronger global passive adversary that can additionally passively compromise some of the AC protocol nodes.</div><div>For a given number of compromised nodes, </div><div>we derive as a necessary constraint a relationship between bandwidth and latency overhead whose violation make it impossible for an AC protocol to achieve strong anonymity. </div><div>We analyze prominent AC protocols from the literature and depict to which extent those satisfy our necessary constraints. </div><div>Our fundamental necessary constraints offer a guideline not only for improving existing AC systems but also for designing novel AC protocols with non-traditional bandwidth and latency overhead choices.</div><div><br></div><div>Using the guidelines indicated by our fundamental necessary constraints we provide two efficient protocol constructions.</div><div>First, we design a mixnet-based AC protocol Streams that provides provable mixing guarantees with the expense of latency overhead. Streams realizes a trusted third party stop-and-go mix as long as each message stays in the system for $\omega(\log \eta)$ rounds.</div><div>Second, we offer a DC-net based design OrgAn that can provide strong sender anonymity with constant latency at the expense of bandwidth overhead. OrgAn solves the problem of regular requirements of key and slot agreement present in typical DC-net based protocols, by utilizing a client/relay/server architecture.</div>

<div>The Internet has substantially embraced mobility since last decade. Cellular data network carries majority of Internet mobile access traffic and become the de facto solution of accessing Internet in mobile fashion, while many clean-slate Internet mobility solutions were proposed but none of them has been largely deployed. Internet mobile users increasingly concern more about their privacy as both researches and real-world incidents show leaking of communication and location privacy could lead to serious consequences. Just the communication itself between mobile user and their peer users or websites could leak considerable privacy of mobile user, such as location history, to other parties. Additionally, comparing to ordinary Internet access, connecting through cellular network yet provides equivalent connection stability or longevity.</div><div><br></div><div>In this research we proposed a novelty paradigm that leverages concurrent far-side proxies to maximize network location privacy protection and minimize interruption and performance penalty brought by mobility. To avoid the deployment feasibility hurdle we also investigated the root causes impeding popularity of existing Internet mobility proposals and proposed guidelines on how to create an economical feasible solution for this goal. Based on these findings we designed a mobility support system offered as a value-added service by mobility service providers and built on elastic infrastructure that leverages various cloud aided designs, to satisfy economic feasibility and explore the architectural trade-offs among service QoS, economic viability, security and privacy. </div>

Current SDN controllers have been designed based on a monolithic approach that integrates all of services and applications into one single, huge program. The monolithic design of SDN controllers restricts programmers who build management applications to specific programming interfaces and services that a given SDN controller provides, making application development dependent on the controller, and thereby restricting portability of management applications across controllers. Furthermore, the monolithic approach means an SDN controller must be recompiled whenever a change is made, and does not provide an easy way to add new functionality or scale to handle large networks. To overcome the weaknesses inherent in the monolithic approach, the next generation of SDN controllers must use a distributed, microservice architecture that disaggregates the control plane by dividing the monolithic controller into a set of cooperative microservices. Disaggregation allows a programmer to choose a programming language that is appropriate for each microservice. In this dissertation, we describe steps taken towards disaggregating the SDN control plane, consider potential ways to achieve the goal, and discuss the advantages and disadvantages of each. We propose a distributed architecture that disaggregates controller software into a small controller core and a set of cooperative microservices. In addition, we present a software defined network programming framework called Umbrella that provides a set of abstractions that programmers can use for writing of SDN management applications independent of NB APIs that SDN controllers provide. Finally, we present an intent-based network programming framework called OSDF to provide a high-level policy based API for programming of network devices using SDN. <br>

With the fast development of 5G networks and the advancement in networking technologies, more and more new technologies such as internet of vehicles (IoV) is catching our eyes. With technologies of artificial intelligence and automatic control, IoV is transformed into an intelligent transportation system (ITS). The object of this thesis is to analyze the connectivity probability issues in vehicle ad hoc networks (VANETs), which is a subset of ITS. This will be achieved by a platoon-based two dimensional model. In order to make the results more accurate and more close to real scenario, different situations will be analyzed separately, and different types of platoon will be included. In addition, other system parameters are also discussed and stimulated. The results show that many parameters like the increases of traffic density, ratio of platoon, and lane numbers will improve connectivity probability. No-leader based platoons are easier to connect to the base stations compared to leader based platoons.

The term “IoT” has evolved to encompass a wide range of diffuse concepts, but the common thread among the myriad definitions has been the convergence of technology to bring <i>advanced conveniences</i> to our every day, but complicated, lives. A long-term focus of the Collaborative Robotics Lab, and a particular focus of many with interests in consumer assistance, has been the kitchen, which acts as the “nerve center” of the home in many cultures. However, despite the grand vision of revolutionizing the kitchen and improving our lifestyles with technology, what today’s IoT-integrated appliances and kitchen-focused conveniences offer is mainly limited to a remote control. While remote control is certainly convenient, it still requires human planning in both cognitive and physical loads in performing cooking activities. The goal of this thesis is to build a framework of the network of IoT-enabled kitchen appliances, <i>TupperwareEarth</i> for the “Internet of Kitchen Things” integrated with an inference engine that utilizes ontology as a knowledge database. From simple clustering of sensor data to recommender systems that employ crowd-sourced preference data, the cognitive burden is reduced with proactive suggestions to high-level queries based upon the current kitchen state. Through the progression of the studies in the “Internet of Kitchen Things,” <i>TupperwareEarth </i>aims to reduce human planning that involves both cognitive and physical loads of burden by inferring solutions to the activities of daily kitchen living using ontological semantics.

Internet goes mobile as billions of users are accessing the Internet through their smartphones. Cellular networks play an essential role in providing “anytime, anywhere” network access as the only large-scale wireless network infrastructure in operation. Mobility support is the salient feature indispensable to ensure seamless Internet connectivity to mobile devices wherever the devices go or are. Cellular network operators deploy a huge number of cell towers over geographical areas each with limited radio coverage. When the device moves out of the radio coverage of its serving cell(s), mobility support is performed to hand over its serving cell(s) to another, thereby ensuring uninterrupted network access.<br>Despite a large success at most places, we uncover that state-of-the-practice mobility support in operational cellular networks suffers from a variety of issues which result in unnecessary performance degradation to mobile devices. In this thesis, we dive into these issues in today’s mobility support and explore possible solutions with no or small changes to the existing network infrastructure.<br>We take a new perspective to study and enhance mobility support. We directly examine, troubleshoot and enhance the underlying procedure of mobility support, instead of higher-layer (application/transport) exploration and optimization in other existing studies. Rather than clean slate network-side solutions, we focus on device-side solutions which are compatible with 3GPP standards and operational network infrastructure, promising immediate benefits without requiring any changes on network side.<br>In particular, we address three technical questions by leveraging the power of the devices. First, how is mobility support performed in reality? We leverage device-side observation to monitor the handoff procedures that happen between the network and the device. We unveil that operator-specific configurations and policies play a decisive role under the standard mechanism and conduct a large-scale measurement study to characterize the extremely complex and diverse handoff configurations used by global operators over the world. Second, what is wrong with the existing mobility support? We conduct model-based reasoning and empirical study to examine network performance issues (e.g., handoff instability and unreachability, missed performance) which are caused by improper handoffs. Finally, how to enhance mobility support? We turn passive devices to proactive devices to enhance mobility support. Specifically, we make a showcase solution which exploits device-side inputs to intervene the default handoff procedure and thus indirectly influence the cell selection decision, thereby improving data speed to mobile devices. All the results in this thesis have been validated or evaluated in reality (over top-tier US carriers like AT&T, Verizon, T-Mobile, some even in global carrier networks).

The intrusion detection system has been widely studied and deployed by researchers for providing better security to computer networks. The increasing of the attack volume and the dramatic advancement of the machine learning make the cooperation between the intrusion detection system and machine learning a hot topic and a promising solution for the cybersecurity. Machine learning usually involves the training process using huge amount of sample data. Since the huge input data may cause a negative effect on the training and detection performance of the machine learning model. Feature selection becomes a crucial technique to rule out the irrelevant and redundant features from the dataset. This study applied a feature selection approach that combines the advanced feature selection algorithms and attacks characteristic features to produce the optimal feature subset for the machine learning model in network intrusion detection. The optimal feature subset was created using the CSE-CIC-IDS2018 dataset, which is the most up-to-date benchmark dataset with comprehensive attack diversity and features. The result of the experiment was produced using machine learning models with decision tree classifier and analyzed with respect to the accuracy, precision, recall, and f1 score.

<p>With the exponential growth and diversity of Internet of Things (IoT) devices, computational-intensive and delay-sensitive applications, such as object detection, smart homes, and smart grids, are emerging constantly. We can adopt the paradigm of cloud computing to offload computation-heavy tasks from IoT devices to a cloud server which can break through the limitation of IoT devices with more powerful resources. However, cloud computing architecture can cause high latency which is not suitable for IoT devices that have limited computing and storage capabilities. Edge computing has been introduced to improve this situation by deploying an edge device nearby IoT devices that can provide IoT devices computing resources with low latency compared to cloud computing. Nevertheless, the edge server may not be able to complete all the offloaded tasks from the devices in time when the requests are flooding. In such cases, the edge server can offload some of the requested tasks to a cloud server to further speed up the offloading process with more powerful cloud resources. In this paper, we aim to minimize the average completion time of tasks in an IoT edge-cloud environment, by optimizing the task offloading ratio from edge to cloud, based on Deep Deterministic Policy Gradient (DDPG), a type of Reinforcement Learning (RL) approach. We propose a dynamic task offloading decision mechanism deployed on the edge that can determine the amounts of computational resources to be processed in the cloud server considering multiple factors to complete a task. Simulation results demonstrate that our dynamic task offloading decision mechanism can improve the overall completion time of tasks than naïve approaches. </p>

<p dir="ltr">The Internet is a large network of globally interconnected devices p used to facilitate the exchange of information across different parties. As usage of the Internet is expected to grow in the future, the underlying infrastructure must be secure to ensure traffic reaches its intended destination without any disruptions. However, the primary routing protocol used on the Internet, the Border Gateway Protocol (BGP), while scalable and can properly route traffic between large networks, does not inherently have any security mechanisms built within the protocol. This leads to devices that use BGP over the internet to be susceptible to BGP Hijacking attacks, which involve maliciously injected routes into BGP’s Routing Information Base (RIB) to intentionally redirect traffic to another destination. Attempts to solve these issues in the past have been challenging due to the prevalence of devices that use BGP on the existing Internet infrastructure and the lack of backward compatibility for proposed solutions. The goal of this research is to categorize the different types of BGP Hijacking attacks that are possible on a network, identify indicators that an ongoing BGP Hijacking attack based on received routes from the Internet locally without access to machines from other locations or networks, and subsequently leverage these indicators to protect local networks from external BGP Hijacking attacks.</p>