Delay-Guaranteed Cross-Layer Scheduling in Multi-Hop Wireless Networks

In this paper, we propose a cross-layer scheduling algorithm that achieves a throughput "epsilon-close" to the optimal throughput in multi-hop wireless networks with a tradeoff of O(1/epsilon) in delay guarantees. The algorithm aims to solve a joint congestion control, routing, and scheduling problem in a multi-hop wireless network while satisfying per-flow average end-to-end delay guarantees and minimum data rate requirements. This problem has been solved for both backlogged as well as arbitrary arrival rate systems. Moreover, we discuss the design of a class of low-complexity suboptimal algorithms, the effects of delayed feedback on the optimal algorithm, and the extensions of the proposed algorithm to different interference models with arbitrary link capacities

Cross-Layer Control for Worse Case Delay Guarantees in Heterogeneous Powered Wireless Sensor Network via Lyapunov Optimization

The delay guarantee is a challenge in wireless sensor networks (WSNs), where energy constraints must be considered. The coexistence of renewable energy and electricity grid is expected as a promising energy supply manner for WSNs to remain function for a potentially infinite lifetime. In this paper, we address cross-layer control to guarantee worse case delay for Heterogeneous Powered (HP) WSNs. We design a novel virtual delay queue structure, and apply the Lyapunov optimization technique to develop cross-layer control algorithm only requiring knowledge of the instantaneous system state, which provides efficient throughput-utility, and guarantees bounded worst-case delay. We analyze the performance of the proposed algorithm and verify the theoretic claims through the simulation results. Compared to the existing work, the algorithm presented in this paper achieves much higher optimal objective value with ultralow data drop due to the proposed novel virtual queue structure

Cross-Layer Scheduling for OFDMA-based Cognitive Radio Systems with Delay and Security Constraints

This paper considers the resource allocation problem in an Orthogonal Frequency Division Multiple Access (OFDMA) based cognitive radio (CR) network, where the CR base station adopts full overlay scheme to transmit both private and open information to multiple users with average delay and power constraints. A stochastic optimization problem is formulated to develop flow control and radio resource allocation in order to maximize the long-term system throughput of open and private information in CR system and ensure the stability of primary system. The corresponding optimal condition for employing full overlay is derived in the context of concurrent transmission of open and private information. An online resource allocation scheme is designed to adapt the transmission of open and private information based on monitoring the status of primary system as well as the channel and queue states in the CR network. The scheme is proven to be asymptotically optimal in solving the stochastic optimization problem without knowing any statistical information. Simulations are provided to verify the analytical results and efficiency of the scheme