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Distributed computing plays a vital role in computer science, enabling more efficient and scalable systems. Over the past several decades, it has evolved from basic time-sharing systems to advanced paradigms such as edge computing and distributed quantum computing (DQC). However, these emerging distributed systems introduce new challenges in resource management and optimization. This dissertation addresses key challenges and open issues in both emerging distributed quantum computing systems and edge computing environments.
In edge environments, the rapid growth of Internet of Things (IoT) applications has led to a surging demand for diverse on-demand network services, requiring efficient resource provisioning and intelligent service orchestration to meet performance and latency requirements. To support a wide range of on-demand network services for IoT applications at the edge, I have developed a series of provable approximation algorithms and an online learning framework for efficient Service Function Chain (SFC) deployment in diverse edge-centric environments. These solutions are specifically designed to address emerging challenges in edge computing, including resource limitations, device and network heterogeneity, service dependencies, and the need for rapid decision-making.
Beyond edge computing, I have also advanced an emerging DQC paradigm to address the scalability bottleneck in quantum computing. The unique quantum mechanisms, such as novel communication methods, high sensitivity to environmental noise, the non-cloning property of quantum data, and the unsplittable nature of new computing resources (i.e., qubits), introduce additional challenges in this area. To tackle these issues, I have developed innovative algorithms targeting two fundamental problems in DQC: the qubit-to-processor mapping problem, which involves distributing quantum circuits across a quantum network while minimizing communication overhead, and the network topology design problem, which focuses on efficiently connecting quantum processors to form a cohesive and scalable distributed system.