Browsing by Author "Williamson, Carey L."

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    A Campus-Level View of DNS Traffic
    (2019-07-26) Zhang, Zhengping; Williamson, Carey L.; Arlitt, Martin F.; Williamson, Carey L.; Arlitt, Martin F.; Ghaderi, Majid; Aycock, John
    This thesis presents a characterization study of DNS traffic within the University of Calgary edge network. The traffic analysis is based on a one-week period of observation (from September 3, 2018 to September 9, 2018). We study the two directions (outbound and inbound) of the DNS traffic, representing the two roles that the campus plays in the DNS architecture, namely a user and a service provider. We selectively analyzed the traffic of a few campus DNS servers. In addition, we also examine several DNS-related anomalies. The measurement results show that a significant proportion of DNS messages come from misconfigurations or answers with short TTLs, which can both be improved to reduce the DNS traffic volume.
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    Congestion Control in Software-Defined Networks: A Simulation Study
    (2019-11) Gholizadeh, Reza; Williamson, Carey L.; Ghaderi, Majid; Costa Sousa, Mario
    Congestion is an underlying reason for performance degradation in computer networks. Current TCP congestion control has no information about the network. Hence, it increases the sending window to overflow the bottleneck link buffer, and backs off when packet drops are detected. Software-Defined Networking SDN is a new paradigm, which provides information about the network. In this thesis, we propose a novel centralized congestion control scheme for SDN. Our solution exploits the information provided by the SDN controller to prevent formation of persistent queues in bottleneck links. Also, we introduce an SDN Simulation Tool developed in Java, which facilitates simulation experiments. We used our tool to evaluate the proposed solution. The preliminary results shows the potential scalability and flexibility of the protocol.
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    Contributions to Information Theoretically Secure Communication
    (2020-05-15) Sharifian, Setareh; Safavi-Naini, Reihanah; Jacobson, Michael; Williamson, Carey L.; Ruhe, Günther; Simon, Christoph; Narayan, Prakash
    Secure communication ensures the integrity and confidentiality of communication between connected devices. An information-theoretic approach to secure communication gives the strongest confidentiality guarantee by assuming that the attacker has unlimited computing power. The earliest formal model and definition of information-theoretic secure communication is by Shannon, who employed a secret key shared between communicating parties to provide confidentiality. An alternative elegant information-theoretic approach to secure communication views the natural characteristics of the environment (i.e., channel’s noise) as a resource to build security functionalities. This approach was first proposed by Wyner, and the corresponding secure communication model is called the wiretap channel model. These two approaches introduce two primary resources for providing information-theoretic secure communication: the shared secret key and physical properties of the communication medium. In this thesis, we study how to employ the above two resources for secure message transmission. We study this by using channel’s noise in the wiretap channel model. In this model, a sender is connected to the receiver and the adversary through two noisy channels. We propose a new wiretap encoding scheme with strong secrecy that provides perfect secrecy and reliability, asymptotically. The construction treats the noise in the adversary’s channel as a source of randomness that is extracted and used to hide the message from the adversary. We realize the wiretap channel model using cooperative jamming to evaluate the performance of wiretap codes in practice. We consider a model called keyed wiretap channel that unifies Wyner’s model with Shannon’s model of perfect secrecy for information systems, and propose a keyed encoding schemes with strong secrecy and other properties that are attractive in practice. We also study two-party information-theoretic secret key agreement when the two parties have access to samples of a common source of randomness and use a single message transmission to arrive at a shared random key. We propose a secret key agreement protocol in this setting, prove its security, and show its superior performance compared to other known protocols with the same properties. Finally, we propose an information-theoretic secret key agreement over a virtual wiretap channel created by cooperative jamming.
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    Deadline-aware Service Function Orchestration under Demand Uncertainty
    (2020-01-17) Nguyen, Quang Minh; Ghaderi, Majid; Williamson, Carey L.; Fapojuwo, Abraham O.
    In network function virtualization (NFV), a service function chain (SFC) specifies a sequence of virtual network functions (VNFs) that user traffic has to traverse to realize a network service. A service can either be delivered by VNFs co-located within a single network infrastructure or geo-distributed over multiple distant cloud infrastructures. In either scenario, as the network resources are shared among multiple SFCs, optimal allocation of network resources to ensure the required quality of service while minimizing the deployment cost is a key challenge. This problem is commonly referred to as the SFC orchestration problem, which has been studied extensively in various settings. However, most existing works assume deterministic demands and resort to costly runtime resource reprovisioning to deal with dynamic demands. In this work, we formulate the co-located and geo-distributed SFC orchestration with demand uncertainty as robust optimization problems and develop exact and approximate algorithms to solve them. To avoid continuous resource reprovisioning, our algorithms utilize uncertain demand knowledge to compute proactive service orchestration solutions that can cope with fluctuations in dynamic service demands. The uncertain demand is modeled as a constrained uncertainty set whose cardinality can be adjusted to control the algorithm proactivity against demand fluctuations. We present extensive model-driven simulation results to study the behavior of the proposed algorithms in small and large scale problem instances and demonstrate their ability to achieve any desired proactivity-cost trade-off. We also evaluate the performance of our algorithms against other state-of-the-art algorithms in the literature. Mininet experiments are further conducted to validate the modeling of different components in our system model.
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    Design and Analysis of Uplink Transmission Performance Enhancement Methods for Data Collection in Internet-of-Things Networks
    (2020-04-28) Wang, Hai; Fapojuwo, Abraham O.; Messier, Geoffrey G.; Sesay, Abu B.; Williamson, Carey L.; Jiang, Hai
    With the increasing demands for the services provided by the Internet-of-Things (IoT) networks, tremendous efforts have been dedicated to enhance the performance of machine-to-machine (M2M) communications. However, due to the limited spectrum resources available for IoT networks, the uplink transmissions that are commonly used for data collection suffer performance degradation when the traffic load increases. To improve the uplink network performance under high traffic load, we propose new enhancement methods for the IoT networks with both single-hop and multi-hop configurations.Specifically, for single-hop networks, this thesis addresses three research objectives. First, successive interference cancellation (SIC) is implemented on top of the pure Aloha (PA) medium access control (MAC) mechanism. The problem is to perform the SIC under an unsynchronized packet transmission framework, and without introducing extra signaling overhead. To this end, a window-based SIC algorithm is presented for the network’s single gateway (GW). Second, in order to evaluate the performance of the SIC-based PA, a throughput model is developed and analyzed to study both the throughput and the packet delivery ratio (PDR) performance metrics. Third, the problem of enabling the SIC-based PA in an IoT network with multiple GWs is solved. The SIC algorithm for PA is redesigned to accommodate single-hop multi-GW networks. A throughput model is also proposed for the newly designed PA-based SIC in multi-GW networks. For the multi-hop IoT networks, the main research objective in this thesis is to allocate proper bandwidth for the nodes in the mesh networks. As a solution, a new distributed bandwidth allocation algorithm is designed. The proposed new design significantly improves the mesh network’s uplink transmission performance at high traffic load. Meanwhile, the new algorithm does not require the configuration of the hysteresis quantum, which makes it more practical than the current state-of-the-art distributed bandwidth allocation algorithms. The performance evaluation results obtained for both the single-hop and multi-hop IoT networks indicate that the proposed enhancement methods can significantly improve the uplink PDR, throughput, and latency for high traffic load scenarios.
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    Designing Interactive Behaviours for Smart Objects
    (2020-09-01) Ledo Maira, David; Oehlberg, Lora A.; Greenberg, Saul; Vermeulen, Jo; Williamson, Carey L.; Wylant, Barry; Hartmann, Björn D.
    In this thesis, I propose methods for repurposing existing hardware and software to enable designers to create live interactive prototypes for smart interactive objects without the need to write code or create custom circuitry. The advent of ubiquitous computing brought the promise of interactive artifacts that integrate into our everyday lives. While this has led to a myriad of “smart objects”, the problem is that it is difficult for interaction designers to devise interactive behaviours for such objects. For example, how might an interaction designer prototype behaviours for a smart speaker? How can they go beyond voice responses and, for instance, animate lights to show that the speaker is listening, or searching for an answer on the web? Designers today face three challenges: (1) needing multiple expertise of designing behaviour, form, circuitry, and programming the functionality; (2) lacking software tools to author fine-tuned dynamic behaviours; and (3) needing closer-to-product representations to physically manipulate the prototype. I overcome this gap through a method and two interactive systems. I propose a design metaphor: Soul–Body Prototyping, which suggests leveraging off-the-shelf mobile phones and watches to create smart object prototypes. By enclosing the mobile device (“soul”) into a physical enclosure (“body”), the designer can exploit the mobile device’s rich sensing, outputs, and internet connectivity. I then operationalize Soul–Body Prototyping through two proof-of-concept prototyping tools. Pineal features trigger-action behaviours which automatically generate 3D models for physical forms. These forms fit a mobile device and expose the necessary inputs and outputs. Astral is a tool where designers can mirror a portion of the desktop’s screen onto a mobile device, and create mappings that convert live mobile sensor data into mouse or keyboard events. Thus, the mobile device remote controls (and repurposes) familiar desktop applications for dynamic behaviour prototyping. Overall, my work contributes an alternative way to prototype smart interactive objects, which informs the design of future prototyping tools. Moreover, I investigate fundamental questions such as the meaning of interactive behaviour, as well as evaluation methods for prototyping tools and toolkits in HCI research.
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    Efficient Algorithms for Dynamic Cloud Resource Provisioning
    (2018-04-20) Zhou, Ruiting; Li, Zongpeng; Woelfel, Philipp; Krishnamurthy, Diwakar; Wu, Kui; Williamson, Carey L.
    Cloud computing has emerged as a new computing paradigm, with data centers proliferating in today’s Internet. Cloud service providers often adopt static resource provisioning to pack cloud resources to fixed types of virtual machines (VM), failing to address user demands efficiently and precisely. In this thesis, we focus on dynamic cloud resource provisioning, which provides realtime, on-demand access to cloud resources. We propose efficient algorithms to guide resource allocation and workload dispatching in cloud systems. We first study dynamic VM provisioning via an online auction algorithm. We generalize the existing literature by introducing computing jobs with completion deadlines. A cloud user bids for future cloud resources to execute its job. Each bid specifies (a) a resource profile of tailor-made VMs, (b) a utility, reflecting the amount that the user is willing to pay for executing its job, and (c) a soft deadline, specifying the preferred finish time of the job, as well as a penalty function that characterizes the cost of violating the deadline. We propose efficient cloud job auctions that execute in an online fashion, provide truthfulness guarantee, and achieve a good competitive ratio. We then discuss cloud container services, a more recent form of cloud resource provisioning. Compared to traditional VMs, cloud containers are more flexible and lightweight. We exploit this new algorithm design space, and study dynamic cloud container provisioning. We design efficient scheduling algorithms for complex computing jobs that are running on cloud containers. Our offline and online schedulers permit partial execution, allow a job to specify its job deadline, desired cloud containers, and inter-container dependence relations, and achieve near-optimal expected objective values. We further extend our study to cloud container clusters. Enterprise users often create clusters of inter-connected containers to provision complex services. Compared to traditional cloud services, key challenges in container cluster (CC) provisioning lie in the optimal placement of containers while considering inter-container traffic in a CC. The challenge further escalates when CCs are provisioned in an online fashion upon CC request arrivals. We investigate dynamic cloud CC provisioning, and propose an online algorithm to address the above challenges. Our online algorithm achieves computational and economical efficiencies.
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    Evaluating the Emergent Effects of (Multiple) Security Mechanisms via Evolutionary Algorithms
    (2018-11-30) Hudson, Jonathan William; Denzinger, Jörg; Williamson, Carey L.; Safavi-Naeini, Reyhaneh
    Security mechanisms provide protection against system penetration and exploitation by providing coverage for vulnerabilities. However, security mechanisms often have demanding operational requirements that necessitate access to system resources and control of monitoring points. At the same time, users have particular requirements from programs they install, how they interact with these programs, and what performance they expect from their computing system. These combined requirements create a selection problem where the user desires to balance security coverage, through a choice of security mechanism(s), with system performance and functionality. This problem is known as the Effective Security-in-Depth problem. First, this thesis introduces a genetic algorithm to enable an evolutionary search for interaction event sequences for the problem of Effective Security-in-Depth. This methodology required the development of a fitness function that integrated numerous system metrics while addressing the variance found in event sequence simulation and measurement. Next, the steps for effectively implementing this methodology as a software tool are described. Finally, this thesis introduces three processes to use the tool to select between single security mechanisms for different usage profiles, compare and contrast subsets of security mechanisms, and evaluate examples of emergent misbehaviour such as system failure. The initial experimental evaluation validates the ability of the search for interaction event sequences to make progress despite the challenges of stochastic system measurement. The remaining experimental evaluations demonstrate the success of an application of each of the three processes. The evaluation supports that the developed method, tool, and processes are a viable solution to the problem of Effective Security-in-Depth.
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    Improving Quality of Experience (QoE) of Dynamic Adaptive Streaming (DAS) Systems
    (2019-09-19) James, Cyriac; Wang, Mea; Krishnamurthy, Diwakar; Williamson, Carey L.; Alim, Usman R.; Liu, Yang
    Dynamic Adaptive Streaming (DAS) systems dominate today's video streaming over the Internet, and operate by adapting video quality based on network throughput variation using discrete quality levels. Despite their popularity, it lacks an effective adaptation that minimizes stalls and quality switches while maximizing visual quality, especially when available bandwidth varies. The conventional approach to adaptation is to make a decision on the next video segment quality based on prior throughput measurements. This approach is not robust to bandwidth fluctuation at small time scales, which can consequently lead to stalls, bandwidth waste, and unstable quality, mainly due to the inability to mitigate significant bandwidth reduction during the segment download. MultiPath TCP (MPTCP) is an emerging paradigm that could offer significant benefits to video streaming by harnessing bandwidth from multiple network interfaces, in particular on mobile and desktop devices with support for both WiFi and cellular networks. We first investigate this off-the-shelf solution to improve video streaming performance by harvesting additional bandwidth over always or intermittently available secondary link under different bandwidth variability conditions. Our measurement study yields mixed results. While beneficial to user experience when primary link bandwidth is unstable or constrained, MPTCP may not offer any advantage otherwise, and sometimes could be detrimental. We then propose BETA – Bandwidth-Efficient Temporal Adaptation, an agile approach that allows DAS players to refine the quality level within video segments on the fly, according to the actual bandwidth conditions experienced while downloading each segment. We define a new DAS-oriented transmission order of video frames within segments that facilitates decodability of partial frames, and paves the way for changing the paradigm from discrete to continuous bitrate ladders for DAS. BETA can work with any adaptation algorithm that runs on a DAS player to significantly improve robustness and efficiency in dynamic network environments and for low-latency streams, as well as dramatically reduce content storage and encoding infrastructure requirements.
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    Modelling Electric Vehicle Charging Network Capacity and Evacuation Route Capacity During Short-Notice Events
    (2020-04-30) MacDonald, Craig; Kattan, Lina; Layzell, David B.; Nowicki, Edwin Peter; Williamson, Carey L.
    Electric vehicles (EVs) may add new challenges during mass evacuations, both in the pre-departure and post-departure stage of a mass evacuation. The objective of this research is to better understand the magnitude of the impacts EVs may have during mass evacuations. Two models were created to examine the impacts pre-departure and post-departure. To determine pre-departure impacts, a G/G/c/N queueing model to estimate the number of vehicles that can be charged pre-departure during an evacuation was created. The outputs of this model are the number of vehicles that have or have not been served during the evacuation period, as well as average queue times and maximum queue lengths. To determine the post-departure impacts, a microscopic traffic simulation using SUMO was created to estimate the additional delay added by EVs that have stalled from lack of fuel. The outputs of this model are the number of vehicles that stall before reaching their destination, and the additional delay to other evacuees incurred as a result of those stalled EVs. The city of Prince George, British Columbia, was used as a case study with the goal of providing insights generalizable to other locations. Policy recommendations that could mitigate some of the negative impacts of EVs during mass evacuations were provided. It was found that for the present-day case of Prince George, there is not enough charging network capacity to service all vehicles before departure. Increasing the number of charging stations, providing earlier evacuation notices, and ensuring that there is a balanced makeup of level 3 fast-charging of different types were all found to be effective in increasing the number of EVs that received adequate charging before departure. It was found that although the delays incurred by stalled EVs on other evacuees were minor, a large number of EVs stalled from running out of fuel en route to their destination. Decreasing the spacing between charging stations along evacuation routes and increasing the capacity of EV charging stations networks at the origin location can reduce the number of EVs that stall en route to their destination.
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    On the Spectral Efficiency and Energy Efficiency Analysis of Cache-Enabled Heterogeneous Networks with Device-to-Device Communication and Cooperative Transmission
    (2021-01-07) Ochia, Okechukwu Emmanuel; Fapojuwo, Abraham O.; Messier, Geoffrey G.; Sesay, Abu B.; Williamson, Carey L.; Hossain, Ekram
    The Heterogeneous network (HetNet) is a viable candidate for achieving high spectral efficiency (SE) and energy efficiency (EE) in fifth-generation (5G) networks. Cache-enabled HetNets with device-to-device (D2D) communication can exploit the availability of cheap memory to improve file delivery and reduce file download latency. In HetNets with simultaneous requests for different file types, the design problems centered on what file to store and how to utilize limited caching capacity impact the SE and EE. In this thesis, an association scheme that computes the D2D communication range based on out-of-cell interference is proposed for establishing cellular and D2D links in a HetNet. The proposed interference-aware, D2D distance threshold-based association scheme achieves up to 67% gain in the SE and EE compared to the state-of-the-art minimum path loss-based association scheme. Further, a popularity and size-aware (PSA) caching scheme is proposed in a hybrid microwave/millimetre wave HetNet. The PSA caching scheme allocates memory blocks for caching according to Pareto, lognormal, and Gamma file size distributions based on empirical measurements and is different than the state-of-the-art probabilistic, size-weighted-popularity (SWP)-based, and most-popular-content (MPC) caching schemes that assume equal file size. Numerical results show that the proposed PSA caching scheme provides up to 33% increase in the cache hit probability compared to the probabilistic and MPC caching schemes. Besides, the PSA scheme achieves up to 17% gain in the file transmission success probability compared to the state of the art. Also, cooperative transmission among transmitters under the PSA caching scheme realizes up to 70% gain in the file transmission success probability compared to a non-cooperative transmission scheme. Lastly, the integration of large scale antenna arrays is proposed to enhance the transmission capacity of a cache-enabled HetNet with D2D communication. The results reveal that the transmission capacity of the HetNet scales linearly with the number of antenna elements per transmitter, provided that the number of antenna elements is not so large. The results in this thesis prove the usefulness of adopting content-aware caching and multiple transmission schemes to improve the performance of a HetNet with unlimited file requests and limited caching capacity.
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    Quality of Experience and Mobility-Aware Green Inter-Radio Access Technology Traffic Offloading
    (2016) Al Masri, Mohamed Ammar; Sesay, Abu B.; Ghannouchi, Fadhel; Fapojuwo, Abraham O.; Messier, Geoffrey; Williamson, Carey L.; Hossain, Ekram
    Traffic offloading among coexisting heterogeneous radio access technologies (RATs) (i.e., inter-RAT offloading) is considered an effective strategy for enhancing the capacity of wireless networks and reducing the power consumption of base stations (BSs) and mobile stations (MSs). To fully utilize inter-RAT offloading advantages, a mobility-aware evaluation is needed, which takes into account the combined effects of mobility and MSs/BSs spatial distributions on the performance gains. This thesis develops an analytical mobility-aware evaluation framework that accurately evaluates the performance of inter-RAT offloading while accounting for the MSs/BSs spatial distribution. This framework is then utilized to develop a novel mobility-aware inter-RAT offloading policy, which aims at associating a MS to the best RAT at any time that optimizes a predefined multi-criterion objective. Deploying a power saving mode (PSM) is also considered an effective solution for saving energy. To efficiently exploit the PSM power saving capabilities for voice over IP (VoIP) services, a quality of experience (QoE)-aware PSM performance evaluation is needed. This thesis develops an analytical evaluation framework that assesses the QoE and energy consumption achieved by a fixed PSM. Based on this framework, this thesis develops a novel QoE-aware PSM, which exploits the on-off characteristics of VoIP sessions to further improve the energy saving while accounting for the bursty losses effects on the QoE. Finally, benefits of deploying a PSM can be combined with those of utilizing inter-RAT offloading to maximize the energy saving while guaranteeing a desired level of QoE for VoIP services. This thesis develops an analytical inter-RAT offloading performance evaluation framework that assesses the QoE and energy consumption achieved by an inter-RAT traffic offloading policy taking into account the PSM being used. Based on this framework, this thesis develops a novel QoE/mobility-aware inter-RAT offloading policy that jointly utilizes the inter-RAT offloading and PSM for optimizing a predefined multi-criterion objective. The research in this thesis offers potentials for enhancing performance while reducing computational complexity. The numerical results validate the accuracy of the proposed performance evaluation frameworks and verify the efficacy of the proposed techniques in enhancing the performance compared to their counterparts.