Date of Award

6-2025

Document Type

Dissertation

Publisher

Santa Clara : Santa Clara University, 2025

Degree Name

Doctor of Philosophy (PhD)

Department

Computer Science and Engineering

First Advisor

Behnam Dezfouli

Abstract

The adoption of Wi-Fi (IEEE 802.11) for Internet of Things (IoT) connectivity presents energy efficiency and reliability challenges, particularly for devices operating under stringent power constraints. Although recent enhancements such as Power Save Mode (PSM) and Target Wake Time (TWT) offer mechanisms for power savings, Wi-Fi was originally designed for high-throughput, continuously connected applications, and does not natively accommodate the low duty-cycle requirements typical of many IoT scenarios. This dissertation addresses the problem of how Wi-Fi-based IoT systems can achieve energy efficient and reliable connectivity while supporting periodic data exchange.

The investigation is structured through three empirical studies. The first examines the overhead associated with the association process across heterogeneous software and hardware configurations, identifying sources of inefficiency related to probing, key generation, and IP address assignment. Optimization techniques such as application processor-based key offloading and targeted Access Point (AP) probing are proposed and evaluated. The second study focuses on the impact of listen interval configurations on beacon reception, demonstrating that while longer intervals reduce wake-up frequency, they can increase total active time and energy consumption due to channel contention and timing uncertainties. The third study explores the interaction between TWT scheduling and Transmission Control Protocol (TCP) behavior, showing that misalignment between wake-up schedules and transport-layer expectations leads to premature retransmissions and degraded throughput. A cross-layer coordination mechanism is introduced to share TWT parameters with the TCP stack, enabling improved retransmission timeout estimation and congestion control.

The results of this work provide a comprehensive understanding of power consumption in Wi-Fi IoT devices and introduce practical methods to enhance energy efficiency and protocol reliability. The proposed techniques are validated across Real-Time Operating System (RTOS) and Linux-based platforms, demonstrating their applicability to a broad range of IoT deployments.

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