Xiangyu Ren

Topic

Cross-Layer Scheduling and Routing for Ultra Reliable and Low Latency Communication

Department of Electrical and Computer Engineering

Date & location

• Tuesday, July 23, 2024

• 3:00 P.M.

• Engineering Computer Science Building

• Room 468

Reviewers

Supervisory Committee

• Dr. Lin Cai, Department of Electrical and Computer Engineering, University of Victoria (Supervisor)

• Dr. Kin Fun Li, Department of Electrical and Computer Engineering, UVic (Member)

• Dr. Sudhakar Ganti, Department of Computer Science, UVic (Outside Member) 

External Examiner

• Dr. Qiang Ye, Department of Electrical and Software Engineering, University of Calgary 

Chair of Oral Examination

• Dr. Nikki Macdonald, School of Public Administration, UVic

   

Abstract

The success of recent communication and computing technologies has attracted growing interest from both academia and industry in developing advanced applications such as metaverse, digital twin, and intelligent transport systems, which are characterized by ultra-high reliability and low latency service requirements. However, the existing routing and scheduling solutions may not fully support these applications. We observe one major reason is the lack of collaboration between each layer in the protocol stack and inefficient handling of network information.

To bridge the gap, we leverage a novel protocol architecture SET which enables flexible protocol assembling via control function decomposition. A new concept called protocol control agent (PCA) is introduced in SET to enable in-network intelligence and enhanced adaptability. PCA leverages cross-layer network information and collaborations to support QoS requirements and improve resource efficiency. In addition, we consider the durability of network information for designing new protocols based on SET. In this context, we develop a range of scheduling and routing solutions to support ultra-reliable and low-latency communications in different networks.

We start with the problem of guaranteeing the per-packet end-to-end delay in wired data networks. To address the congestion caused by bursty traffic and poor load balancing, we implement a congestion-aware mechanism where neighboring routers exchange queue information to improve routing decisions and reduce congestion. Furthermore, a delay-guaranteed scheduling and routing (DSR) algorithm based on renewal optimization is proposed to enhance routing decisions.

Next, we investigate the scheduling problem for time-critical applications in a single-hop downlink wireless network. We consider packets with different priorities carrying different delay requirements, where high-priority packets yield high utility after successful transmission. We introduce a delay-laxity concept and an output gain function for making scheduling decisions. Due to the problem’s complexity and uncertainty of the network environment, a deep reinforcement learning framework is proposed to find the optimal scheduling decisions that maximize network utility and guarantee per-packet delay requirement.

Considering mobility in emerging applications, we extend our research to vehicular networks, where ensuring QoS is challenging due to unstable channel conditions, high mobility, and limited resources. To address these issues, we propose a hybrid control framework leveraging global and local network information and taking advantage of the time-scale difference between the change rate of network typology and channel condition to perform control at different scopes.

Based on the framework, we first focus on the routing problem in vehicular networks. A QoS-guaranteed clustering and routing protocol (QCRP) is proposed where the global information, i.e., network topology is used for clustering and route planning to ensure per-cluster connectivity and routing path initialization and the local information, i.e., channel condition and vehicle location is used for re-routing. Next, to support efficient in-network communication under the constraints of limited network resources, we propose a QoS-guaranteed medium access control (QMAC) protocol to perform resource allocation. Following the same framework, a centralized spectrum allocation combined with distributed power and error control solution is proposed.

Overall, in this thesis, we introduced a new perspective of supporting stringent QoS requirements and demonstrated the effectiveness of our solution in various network settings. Our work opens up new possibilities for research extensions and applications.