Yingsong Huang

Adaptive Electricity Scheduling in Microgrids

Microgrid (MG) is a promising component for future smart grid (SG) deployment. The balance of supply and demand of electric energy is one of the most important requirements of MG management. In this paper, we present a novel framework for smart energy management based on the concept of quality-of-service in electricity (QoSE). Specifically, the resident electricity demand is classified into basic usage and quality usage. The basic usage is always guaranteed by the MG, while the quality usage is controlled based on the MG state. The microgrid control center (MGCC) aims to minimize the MG operation cost and maintain the outage probability of quality usage, i.e., QoSE, below a target value, by scheduling electricity among renewable energy resources, energy storage systems, and macrogrid. The problem is formulated as a constrained stochastic programming problem. The Lyapunov optimization technique is then applied to derive an adaptive electricity scheduling algorithm by introducing the QoSE virtual queues and energy storage virtual queues. The proposed algorithm is an online algorithm. We derive several “hard” performance bounds for the proposed algorithm, and evaluate its performance with trace-driven simulations. The simulation results demonstrate the efficacy of the proposed electricity scheduling algorithm.

A Control-Theoretic Approach to Rate Control for Streaming Videos

As streaming videos are becoming increasingly popular, it is important to understand the end-to-end streaming system and to develop effective algorithms for quality control. In this paper, we address the problem of rate control for streaming videos with a control-theoretic approach. Among the various control knobs, video bit rate is one of the most effective in the sense that it has a direct impact on the interaction between the video coder and network system. While increasing rate reduces the coder-induced distortion, it may also cause congestion at a bottleneck link. The packet loss due to congestion will, then, increase the distortion of the decoded video. We model end-to-end video steaming as a feedback control system, taking into account video codec and sequence characteristics, rate control, active queue management, and receiver feedback. We then develop effective proportional (P) controllers to stabilize the received video quality as well as the bottleneck link queue, for both homogeneous and heterogeneous video systems. Simulation results are presented to demonstrate the efficacy of the P controllers and the viability of the proposed control-theoretic approach.

Adaptive electricity scheduling in microgrids

Microgrid (MG) is a promising component for future smart grid (SG) deployment. The balance of supply and demand of electric energy is one of the most important requirements of MG management. In this paper, we present a novel framework for smart energy management based on the concept of quality-of-service in electricity (QoSE). Specifically, the resident electricity demand is classified into basic usage and quality usage. The basic usage is always guaranteed by the MG, while the quality usage is controlled based on the MG state. The microgrid control center (MGCC) aims to minimize the MG operation cost and maintain the outage probability of quality usage, i.e., QoSE, below a target value, by scheduling electricity among renewable energy resources, energy storage systems, and macrogrid. The problem is formulated as a constrained stochastic programming problem. The Lyapunov optimization technique is then applied to derive an adaptive electricity scheduling algorithm by introducing the QoSE virtual queues and energy storage virtual queues. The proposed algorithm is an online algorithm. We derive several “hard” performance bounds for the proposed algorithm, and evaluate its performance with trace-driven simulations. The simulation results demonstrate the efficacy of the proposed electricity scheduling algorithm.

Downlink power control for variable bit rate videos over multicell wireless networks

We investigate the problem of downlink power control for streaming multiple variable bit rate (VBR) videos in a multicell wireless network, where downlink capacities are limited by inter-cell interference. We adopt a deterministic model for VBR traffic that considers video frame sizes and playout buffers at the mobile users. The problem is to find the optimal transmit powers for the base stations, such that VBR video data can be delivered to mobile users without causing playout buffer underflow or overflow. We formulate a nonlinear nonconvex optimization problem and prove the condition for the existence of feasible solutions. We then develop a centralized branch-and-bound algorithm incorporating the Reformulation-Linearization Technique, which can produce (1−ε)-optimal solutions. We also propose a low-complexity distributed algorithm with fast convergence. Through simulations with VBR video traces under fading channels, we find the distributed algorithm can achieve a performance very close to that of the centralized algorithm.

Experimental study of utility function selection for video over IEEE 802.22 wireless regional area networks

Cognitive Radio (CR) is a new wireless communications and networking paradigm that is enabled by the Software Defined Radio (SDR) technology and a recent change in spectrum regulation policy. As the first commercial application of CR technology, IEEE 802.22 wireless regional area networks (WRAN) aim to offer broadband wireless access by efficiently utilizing “white spaces” in the broadcast TV bands. In this paper, we evaluate the performance of an IEEE 802.22 WRAN base station (BS) cognitive engine (CE) testbed developed at Wireless@Virginia Tech on supporting video applications. We investigate the important problem of utility function selection and its impact on the received video quality. Through testbed experiments, we find that a video-specific utility function achieves significant improvements on received video quality over a general purpose utility function, indicating the efficacy of cross-layer design and more importantly, the need for adopting dynamic situation- and application-aware utility functions at the CE, rather than a predefined static one.

A distributed polling service-based MAC protocol testbed

Medium access control MAC protocols play a vital role in wireless networking. It is well-known that the high control overhead of IEEE 802.11 MAC is the limiting factor on the throughput and delay performance of wireless networks. In our prior work, three polling service-based medium access control protocols PSMACs are developed to amortize the high control overhead over multiple frame transmissions, thus achieving higher efficiency. Both analysis and simulations are conducted to validate the efficacy of the proposed protocols. In this paper, we extend this work by implementing the distributed version of PSMAC, i.e., PSMAC 2, on the GNU Radio and universal software radio peripheral GNU Radio/USRP platform. We discuss various design considerations and challenges of prototyping PSMAC 2 and carry out extensive experimental studies with the GNU Radio/USRP PSMAC testbed. Our experimental results are found to be consistent with the theoretical study reported in our prior work and validate the advantages of PSMAC under a realistic wireless channels. Copyright

Utility function selection for streaming videos with a cognitive engine testbed

Cognitive Radio (CR) is a new wireless communication and networking paradigm that is enabled by the Software Defined Radio (SDR) technology and the recent change in spectrum regulation policy. As the first commercial application of CR technology, IEEE 802.22 wireless regional area networks (WRAN) aim to offer broadband wireless access by efficiently utilizing the unoccupied TV channels. In this paper, we investigate the problem of utility function selection and its impact on streaming video quality through an IEEE 802.22 WRAN base station (BS) cognitive engine (CE) testbed developed at Wireless@Virginia Tech. We find that significant improvement on received video quality can be achieved when CE adopts a dynamic, content-aware, video-specific utility function rather than a static, predefined, general purpose utility function. This work indicates the importance of video distortion modeling and cross-layer design, and the need for employing dynamic content-aware utility functions at the CE for cognitive streaming video communication networks.

On Quality of Usage Provisioning for Electricity Scheduling in Microgrids

Microgrid is a promising component for future smart grid deployment. The balance of supply and demand of electricity is one of the most important requirements of microgrid management. In this paper, we investigate the grid stability problem from an admission control perspective, while guaranteeing the quality of usage (QoU) of local residents in a microgrid under both random electricity supply and demand. In particular, a QoU request is generated when the electricity demand exceeds the microgrid supply. The microgrid control center aims to maintain the QoU blocking probability around a target value by serving (i.e., switching to the macrogrid for extra electricity supply) or blocking QoU requests. The problem is formulated as a queue stability problem by introducing the concept of a QoU blocking virtual queue. Lyapunov optimization is then applied to derive an adaptive QoU scheduling algorithm with low complexity O(1. Furthermore, it is an online algorithm since it does not require any future knowledge of the electricity supply and demand processes. The stability of the algorithm is proven, and its performance is evaluated with trace-driven simulations under random or nonstationary QoU requests. The simulation results demonstrate the efficacy and robustness of the proposed QoU scheduling algorithm.

Downlink Power Control for Multi-User VBR Video Streaming in Cellular Networks

We investigate the problem of downlink power control for streaming multiple variable bit rate (VBR) videos in a multicell wireless network, where downlink capacities are limited by inter-cell interference. We adopt a deterministic model for VBR video traffic that considers video frame sizes and playout buffers at the mobile users. The problem is to find the optimal transmit powers for the base stations, such that VBR video data can be delivered to mobile users without causing playout buffer underflow or overflow. We formulate a nonlinear nonconvex optimization problem and prove the condition for the existence of feasible solutions. A centralized branch-and-bound algorithm is then developed, which incorporates the Reformulation-Linearization Technique and can produce (1-ε)-optimal solutions. We also propose a low-complexity distributed algorithm with fast convergence as an alternative to the centralized algorithm. Through simulations with VBR video traces under fading channels, we find the distributed algorithm can achieve a performance very close to that of the centralized algorithm.

Smooth electric power scheduling in power distribution networks

The emergence of Smart Grid (SG) brings about many fundamental changes in electric power systems. In this paper, we study the problem of smooth electric power scheduling in power distribution networks. We introduce an electricity supply/demand model that takes into account the time-varying demands and their deadlines. We formulate a constrained nonlinear programming problem and incorporate the theory of majorization to develop algorithms that can compute smoothness optimal schedules for deferrable load dominant system. An effective heuristic algorithm is also presented by extending the majorization-based algorithm for the general scenario with mixed priority loads and deferrable loads. After obtaining the smooth power schedule, a distributed user benefit maximization load control scheme is used to allocate the scheduled power to individual users, while maximizing their level of satisfaction. The simulation results demonstrate the efficacy of the proposed algorithms on smooth electric power scheduling.