Vincent W. S. Wong

Autonomous Demand-Side Management Based on Game-Theoretic Energy Consumption Scheduling for the Future Smart Grid

Most of the existing demand-side management programs focus primarily on the interactions between a utility company and its customers/users. In this paper, we present an autonomous and distributed demand-side energy management system among users that takes advantage of a two-way digital communication infrastructure which is envisioned in the future smart grid. We use game theory and formulate an energy consumption scheduling game, where the players are the users and their strategies are the daily schedules of their household appliances and loads. It is assumed that the utility company can adopt adequate pricing tariffs that differentiate the energy usage in time and level. We show that for a common scenario, with a single utility company serving multiple customers, the global optimal performance in terms of minimizing the energy costs is achieved at the Nash equilibrium of the formulated energy consumption scheduling game. The proposed distributed demand-side energy management strategy requires each user to simply apply its best response strategy to the current total load and tariffs in the power distribution system. The users can maintain privacy and do not need to reveal the details on their energy consumption schedules to other users. We also show that users will have the incentives to participate in the energy consumption scheduling game and subscribing to such services. Simulation results confirm that the proposed approach can reduce the peak-to-average ratio of the total energy demand, the total energy costs, as well as each users individual daily electricity charges.

Optimal and autonomous incentive-based energy consumption scheduling algorithm for smart grid

In this paper, we consider deployment of energy consumption scheduling (ECS) devices in smart meters for autonomous demand side management within a neighborhood, where several buildings share an energy source. The ECS devices are assumed to be built inside smart meters and to be connected to not only the power grid, but also to a local area network which is essential for handling two-way communications in a smart grid infrastructure. They interact automatically by running a distributed algorithm to find the optimal energy consumption schedule for each subscriber, with an aim at reducing the total energy cost as well as the peak-to-average-ratio (PAR) in load demand in the system. Incentives are also provided for the subscribers to actually use the ECS devices via a novel pricing model, derived from a game-theoretic analysis. Simulation results confirm that our proposed distributed algorithm significantly reduces the PAR and the total cost in the system.

Comparison between Vertical Handoff Decision Algorithms for Heterogeneous Wireless Networks

The next generation wireless networks will support the vertical handoff mechanism in which users can maintain the connections when they switch from one network to another (e.g., from IEEE 802.11b to CDMA 1timesRTT network, and vice versa). Although various vertical handoff decision algorithms have been proposed in the literature recently, there is a lack of performance comparisons between different schemes. In this paper, we compare the performance between four vertical handoff decision algorithms, namely, MEW (multiplicative exponent weighting), SAW (simple additive weighting), TOPSIS (technique for order preference by similarity to ideal solution), and GRA (grey relational analysis). All four algorithms allow different attributes (e.g., bandwidth, delay, packet loss rate, cost) to be included for vertical handoff decision. Results show that MEW, SAW, and TOPSIS provide similar performance to all four traffic classes. GRA provides a slightly higher bandwidth and lower delay for interactive and background traffic classes

Advanced Demand Side Management for the Future Smart Grid Using Mechanism Design

In the future smart grid, both users and power companies can potentially benefit from the economical and environmental advantages of smart pricing methods to more effectively reflect the fluctuations of the wholesale price into the customer side. In addition, smart pricing can be used to seek social benefits and to implement social objectives. To achieve social objectives, the utility company may need to collect various information about users and their energy consumption behavior, which can be challenging. In this paper, we propose an efficient pricing method to tackle this problem. We assume that each user is equipped with an energy consumption controller (ECC) as part of its smart meter. All smart meters are connected to not only the power grid but also a communication infrastructure. This allows two-way communication among smart meters and the utility company. We analytically model each users preferences and energy consumption patterns in form of a utility function. Based on this model, we propose a Vickrey-Clarke-Groves (VCG) mechanism which aims to maximize the social welfare, i.e., the aggregate utility functions of all users minus the total energy cost. Our design requires that each user provides some information about its energy demand. In return, the energy provider will determine each users electricity bill payment. Finally, we verify some important properties of our proposed VCG mechanism for demand side management such as efficiency, user truthfulness, and nonnegative transfer. Simulation results confirm that the proposed pricing method can benefit both users and utility companies.

An MDP-Based Vertical Handoff Decision Algorithm for Heterogeneous Wireless Networks

The architecture for the Beyond 3rd Generation (B3G) or 4th Generation (4G) wireless networks aims at integrating various heterogeneous wireless access networks. One of the major design issues is the support of vertical handoff. Vertical handoff occurs when a mobile terminal switches from one network to another (e.g., from wireless local area network to code-division multiple-access 1x radio transmission technology). The objective of this paper is to determine the conditions under which vertical handoff should be performed. The problem is formulated as a Markov decision process with the objective of maximizing the total expected reward per connection. The network resources that are utilized by the connection are captured by a link reward function. A signaling cost is used to model the signaling and processing load incurred on the network when vertical handoff is performed. The value iteration algorithm is used to compute a stationary deterministic policy. For performance evaluation, voice and data applications are considered. The numerical results show that our proposed scheme performs better than other vertical handoff decision algorithms, namely, simple additive weighting, the technique for order preference by similarity to ideal solution, and Grey relational analysis.

Location management for next-generation personal communications networks

This article presents a survey on location management algorithms for next-generation personal communications networks. We first describe different static and dynamic location update algorithms. Then we discuss various selective paging strategies. We also present various modeling techniques that have been used for the performance analysis of location update and terminal paging. We conclude by stating a number of open problems that need to be addressed for the deployment of next-generation PCNs.

WSN01-1: Frame Aggregation and Optimal Frame Size Adaptation for IEEE 802.11n WLANs

The IEEE 802.11a/b/g have been widely accepted as the de facto standards for wireless local area networks (WLANs). The recent IEEE 802.11n proposals aim at providing a physical layer transmission rate of up to 600 Mbps. However, to fully utilize this high data rate, the current IEEE 802.11 medium access control (MAC) needs to be enhanced. In this paper, we investigate the performance improvement of the MAC protocol by using the two frame aggregation techniques, namely A-MPDU (MAC Protocol Data Unit Aggregation) and A-MSDU (MAC Service Data Unit Aggregation). We first propose an analytical model to study the performance under uni-directional and bi-directional data transfer. Our proposed model incorporates packet loss either from collisions or channel errors. Comparison with simulation results show that the model is accurate in predicting the network throughput. We also propose an optimal frame size adaptation algorithm with A-MSDU under error-prone channels. Simulation results show that the network throughput performance is significant improved when compared with both randomized and fixed frame aggregation algorithms.

An energy-efficient multipath routing protocol for wireless sensor networks

The energy consumption is a key design criterion for the routing protocols in wireless sensor networks. Some of the conventional single path routing schemes may not be optimal to maximize the network lifetime and connectivity. In this paper, we propose a distributed, scalable and localized multipath search protocol to discover multiple node-disjoint paths between the sink and source nodes. We also propose a load balancing algorithm to distribute the traffic over the multiple paths discovered. We compare our proposed scheme with the directed diffusion, directed transmission, and the energy-aware routing protocols. Simulation results show that our proposed scheme has a higher node energy efficiency, lower average delay and control overhead than those protocols.

Vehicular telematics over heterogeneous wireless networks: A survey

This article presents a survey on vehicular telematics over heterogeneous wireless networks. An advanced heterogeneous vehicular network (AHVN) architecture is outlined which uses multiple access technologies and multiple radios in a collaborative manner. The challenges in designing the essential functional components of AHVN and the corresponding protocols (for radio link control, routing, congestion control, security and privacy, and application development) are discussed and the related work in the literature are reviewed. The open research challenges and several avenues for future research on vehicular telematics over heterogeneous wireless access networks are outlined.

Joint logical topology design, interface assignment, channel allocation, and routing for multi-channel wireless mesh networks

A multi-channel wireless mesh network (MC-WMN) consists of a number of stationary wireless routers, where each router is equipped with multiple network interface cards (NICs). Each NIC operates on a distinct frequency channel. Two neighboring routers establish a logical link if each one has an NIC operating on a common channel. Given the physical topology of the routers and other constraints, four important issues should be addressed in MC-WMNs: logical topology formation, interface assignment, channel allocation, and routing. Logical topology determines the set of logical links. Interface assignment decides how the logical links should be assigned to the NICs in each wireless router. Channel allocation selects the operating channel for each logical link. Finally, routing determines through which logical links the packets should be forwarded. In this paper, we mathematically formulate the logical topology design, interface assignment, channel allocation, and routing as a joint linear optimization problem. Our proposed MC-WMN architecture is called TiMesh. Extensive ns-2 simulation experiments are conducted to evaluate the performance of TiMesh and compare it with two other MC-WMN architectures Hyacinth [1] and CLICA [2]. Simulation results show that TiMesh achieves higher aggregated network throughput and lower end-to-end delay than Hyacinth and CLICA for both TCP and UDP traffic. It also provides better fairness among different flows.