UWSpace

UWSpace is the University of Waterloo’s institutional repository for the free, secure, and long-term home of research produced by faculty, students, and staff.

Depositing Theses/Dissertations or Research to UWSpace

Are you a Graduate Student depositing your thesis to UWSpace? See our Thesis Deposit Help and UWSpace Thesis FAQ pages to learn more.

Are you a Faculty or Staff member depositing research to UWSpace? See our Waterloo Research Deposit Help and Self-Archiving pages to learn more.

Photo by Waterloo staff

Communities in UWSpace

Select a community to browse its collections.

Recent Submissions

  • Thumbnail Image
    Item type: Item ,
    Cross-O-DU Detection of RRC Signaling Storms in 5G O-RAN Networks
    (University of Waterloo, 2026-10-21) Saqib, Eimaan
    Open Radio Access Network (O-RAN) adopts a disaggregated Radio Access Network (RAN) architecture in which O-RAN Centralized Units (O-CUs) and Distributed Units (O-DUs) expose telemetry to operator applications. I use this architecture to detect signaling storms: deliberate or accidental surges of connection-establishment signaling that can degrade service before devices authenticate. Detection is difficult for two reasons. First, a distributed storm can produce moderately elevated evidence at several O-DUs without crossing a per-O-DU alarm threshold. Second, some random-access attempts fail inside the O-DU before their RRC request reaches the O-CU, so O-CU RRC counters alone omit part of the load. I present a tiered, unsupervised detector: one Isolation Forest per O-DU produces calibrated anomaly scores, and a cross-O-DU LSTM-autoencoder/Isolation-Forest ensemble combines the continuous scores and signaling counters. Model fitting and threshold calibration use benign operation only. I also implement a custom E2 service model that exports per-O-DU RRC counters and O-DU MAC scheduler-outcome counters. Across ten storm scenarios, the detector obtains 0.991 PR-AUC; its recall is 0.943 at a threshold calibrated to the 95th percentile of benign scores, compared with 0.972 and 0.860 for the strongest unsupervised baseline. At the 10s operating window, cross-O-DU combination raises recall on the rolling, low-intensity coordinated scenario from 0.27 to 0.81.
  • Thumbnail Image
    Item type: Item ,
    Measuring the Severity of Violations Committed by Pedestrians at Signalized Intersections
    (University of Waterloo, 2026-10-21) Kim, Jeffrey
    Pedestrian safety remains a global concern, with pedestrians accounting for a substantial proportion of road fatalities and injuries. Previous research has examined many factors that influence pedestrian safety however, pedestrian violations at signalized intersections are a major contributor to pedestrian-vehicle conflicts, yet existing traffic safety research primarily treats these behaviours as binary outcomes, either as compliant or non-compliant. This representation fails to capture the varying degrees of severity in different crossing paths, limiting a nuanced understanding of pedestrian risk and road safety. To address this gap, this thesis proposes, applies, and evaluates continuous metrics to characterize the severity of both spatial and temporal pedestrian violations at signalized intersections. Three spatial violations (SV) metrics and four temporal violation (TV) metrics were developed. To evaluate these measures, observational pilot studies were conducted at a highly active signalized intersection in Waterloo, Ontario, utilizing both drone and street-level video data. The spatial violation analysis revealed that 48% of pedestrians committed a spatial violation, with the vast majority (86.5%) engaging in corner cutting. Among the spatial metrics, SV Metric 2 (total violation area) and SV Metric 3 (time-step metric) provided the most robust and consistent severity evaluations, whereas SV Metric 1 (maximum lateral distance) tended to overestimate spatial violation severities. The temporal violation analysis found that 7.6% of pedestrians committed a temporal violation, predominantly initiating crossings during the Flashing Don’t Walk interval (86.7%). Unlike the spatial metrics, the temporal metrics yielded statistically distinct severity distributions, demonstrating that the measurement of temporal violation severities is highly sensitive to whether the selected metric prioritizes strict legal compliance or practical safety risk. Ultimately, this research recommends the use of SV Metrics 2 and 3 for spatial analysis and provides a framework for selecting appropriate TV metrics based on specific study parameters. The proposed metrics can be integrated into existing automated traffic data collection systems, supporting future research relating violation severity to conflict severity.
  • Thumbnail Image
    Item type: Item ,
    The Fence Complexity of Persistent Sets
    (Springer Nature Switzerland, 2023-09-30) Coccimiglio, Gaetano; Brown, Trevor; Ravi, Srivatsan
    We study the psync complexity of concurrent sets in the non-volatile shared memory model. Flush instructions are used in non-volatile memory to force shared state to be written back to non-volatile memory and must typically be accompanied by the use of expensive fence instructions to enforce ordering among such flushes. Collectively we refer to a flush and a fence as a psync. The safety property of strict linearizability forces crashed operations to take effect before the crash or not take effect at all; the weaker property of durable linearizability enforces this requirement only for operations that have completed prior to the crash event. We consider lock-free implementations of list-based sets and prove two lower bounds. We prove that for any durable linearizable lock-free set there must exist an execution where some process must perform at least one redundant psync as part of an update operation. We introduce an extension to strict linearizability specialized for persistent sets that we call strict limited effect (SLE) linearizability. SLE linearizability explicitly ensures that operations do not take effect after a crash which better reflects the original intentions of strict linearizability. We show that it is impossible to implement SLE linearizable lock-free sets in which read-only (or search) operations do not flush or fence. We undertake an empirical study of persistent sets that examines various algorithmic design techniques and the impact of flush instructions in practice. We present concurrent set algorithms that provide matching upper bounds and rigorously evaluate them against existing persistent sets to expose the impact of algorithmic design and safety properties on psync complexity in practice as well as the cost of recovering the data structure following a system crash.
  • Thumbnail Image
    Item type: Item ,
    Non-blocking k-ary Search Trees
    (Springer Berlin Heidelberg, 2011) Brown, Trevor; Helga, Joanna
    This paper presents the first concurrent non-blocking k-ary search tree. Our data structure generalizes the recent non-blocking binary search tree of Ellen et al. [5] to trees in which each internal node has k children. Larger values of k decrease the depth of the tree, but lead to higher contention among processes performing updates to the tree. Our Java implementation uses single-word compare-and-set operations to coordinate updates to the tree. We present experimental results from a 16-core Sun machine with 128 hardware contexts, which show that our implementation achieves higher throughput than the non-blocking skip list of the Java class library and the leading lock-based concurrent search tree of Bronson et al. [3].
  • Thumbnail Image
    Item type: Item ,
    Range Queries in Non-blocking k-ary Search Trees
    (Springer Berlin Heidelberg, 2012) Brown, Trevor; Avni, Hillel
    We present a linearizable, non-blocking k-ary search tree (k-ST) that supports fast searches and range queries. Our algorithm uses single-word compare-and-swap (CAS) operations, and tolerates any number of crash failures. Performance experiments show that, for workloads containing small range queries, our k-ST significantly outperforms other algorithms which support these operations, and rivals the performance of a leading concurrent skip-list, which provides range queries that cannot always be linearized.