Shengrong Bu

When the Smart Grid Meets Energy-Efficient Communications: Green Wireless Cellular Networks Powered by the Smart Grid

Recently, there is great interest in considering the energy efficiency aspect of cellular networks. On the other hand, the power grid infrastructure, which provides electricity to cellular networks, is experiencing a significant shift from the traditional electricity grid to the smart grid. When a cellular network is powered by the smart grid, only considering energy efficiency in the cellular network may not be enough. In this paper, we consider not only energy-efficient communications but also the dynamics of the smart grid in designing green wireless cellular networks. Specifically, the dynamic operation of cellular base stations depends on the traffic, real-time electricity price, and the pollutant level associated with electricity generation. Coordinated multipoint (CoMP) is used to ensure acceptable service quality in the cells whose base stations have been shut down. The active base stations decide on which retailers to procure electricity from and how much electricity to procure. We formulate the system as a Stackelberg game, which has two levels: a cellular network level and a smart grid level. Simulation results show that the smart grid has significant impacts on green wireless cellular networks, and our proposed scheme can significantly reduce operational expenditure and CO_2 emissions in green wireless cellular networks.

Green Cognitive Mobile Networks With Small Cells for Multimedia Communications in the Smart Grid Environment

High-data-rate mobile multimedia applications can greatly increase energy consumption, leading to an emerging trend of addressing the “energy efficiency” aspect of mobile networks. Cognitive mobile networks with small cells are important techniques for meeting the high-data-rate requirements and improving the energy efficiency of mobile multimedia communications. However, most existing works do not consider the power grid, which provides electricity to mobile networks. Currently, the power grid is experiencing a significant shift from the traditional grid to the smart grid. In the smart grid environment, only considering energy efficiency may not be sufficient since the dynamics of the smart grid will have significant impacts on mobile networks. In this paper, we study green cognitive mobile networks with small cells in the smart grid environment. Unlike most existing studies on cognitive networks, where only the radio spectrum is sensed, our cognitive networks sense not only the radio spectrum environment but also the smart grid environment, based on which power allocation and interference management for multimedia communications are performed. We formulate the problems of electricity price decision, energy-efficient power allocation, and interference management as a three-stage Stackelberg game. A homogeneous Bertrand game with asymmetric costs is used to model price decisions made by the electricity retailers. A backward induction method is used to analyze the proposed Stackelberg game. Simulation results show that our proposed scheme can significantly reduce operational expenditure and CO2 emissions in cognitive mobile networks with small cells for multimedia communications.

A Game-Theoretical Scheme in the Smart Grid With Demand-Side Management: Towards a Smart Cyber-Physical Power Infrastructure

The smart grid is becoming one of the fundamental cyber-physical systems due to the employment of information and communication technology. In the smart grid, demand-side management (DSM) based on real-time pricing is an important mechanism for improving the reliability of the grid. Electricity retailers in the smart grid can procure electricity from various supply sources, and then sell it to the customers. Therefore, it is critical for retailers to make effective procurement and price decisions. In this paper, we propose a novel game-theoretical decision-making scheme for electricity retailers in the smart grid using real-time pricing DSM. We model and analyze the interactions between the retailer and electricity customers as a four-stage Stackelberg game. In the first three stages, the electricity retailer, as the Stackelberg leader, makes decisions on which electricity sources to procure electricity from, how much electricity to procure, and the optimal retail price to offer to the customers, to maximize its profit. In the fourth stage, the customers, who are the followers in the Stackelberg game, adjust their individual electricity demand to maximize their individual utility. Simulation results show that the retailer and customers can achieve a higher profit and higher utility using our proposed decision-making scheme. We also analyze how the system parameters affect the procurement and price decisions in the proposed decision-making scheme.

Distributed Combined Authentication and Intrusion Detection With Data Fusion in High-Security Mobile Ad Hoc Networks

Multimodal biometric technology provides potential solutions for continuous user-to-device authentication in high-security mobile ad hoc networks (MANETs). This paper studies distributed combined authentication and intrusion detection with data fusion in such MANETs. Multimodal biometrics are deployed to work with intrusion detection systems (IDSs) to alleviate the shortcomings of unimodal biometric systems. Since each device in the network has measurement and estimation limitations, more than one device needs to be chosen, and observations can be fused to increase observation accuracy using Dempster-Shafer theory for data fusion. The system decides whether user authentication (or IDS input) is required and which biosensors (or IDSs) should be chosen, depending on the security posture. The decisions are made in a fully distributed manner by each authentication device and IDS. Simulation results are presented to show the effectiveness of the proposed scheme.

A game-theoretical decision-making scheme for electricity retailers in the smart grid with demand-side management

In the smart grid, demand-side management (DSM) is an important mechanism for improving the reliability of the grid by dynamically changing or shifting electricity consumption. Real-time pricing is one of the most important DSM strategies. Moreover, in an electricity market, retailers procure electricity from various electricity sources, and then sell it to customers. Therefore, it is critical for retailers to make effective procurement and price decisions. In this paper, we propose a novel game-theoretical decision-making scheme for electricity retailers in the smart grid using real-time pricing DSM. We model and analyze the interactions between the retailer and electricity customers as a four-stage Stackelberg game. Simulation results show the effectiveness of the proposed scheme and how the system parameters affect the procurement and price decisions.

Stochastic unit commitment in smart grid communications

There is growing interest in renewable energy resources and smart grid. Since most renewable sources are highly intermittent, they can induce significan fluctuation on the supply side of the power grid. On the other hand, the use of smart meters and smart appliances in the smart grid can cause significan uncertainties on the demand side as well. Unit commitment scheduling of power generation systems is an important issue in smart grid communications to coordinate energy demand and generation. In this paper, we study the stochastic unit commitment problem in smart grid communications. Hidden Markov models (HMMs) are used for renewable energy resources. The stochastic power demand loads are modeled by a Markov-modulated Poisson process (MMPP). We show that, under reasonable conditions on the smart grid, structural results can be derived for the unit commit problem, which make the solution practically useful. Simulation results are presented to show the effectiveness of the proposed schemes.

Interference-Aware Energy-Efficient Resource Allocation for OFDMA-Based Heterogeneous Networks With Incomplete Channel State Information

Heterogeneous wireless networks are considered as promising technologies to improve energy efficiency. In heterogeneous networks, interference management is very important since the interference due to spectrum sharing can significantly degrade overall performance. In the existing work, various resource allocation methods are proposed to either improve energy efficiency or mitigate interference in orthogonal frequency-division multiple access (OFDMA)-based multicell networks. To the best of our knowledge, no research on resource allocation has jointly considered improving energy efficiency and performing interference control, especially using interference power constraint strategies. Furthermore, most existing work assumes that all of the channel state information (CSI) is known completely, which might not be realistic in heterogeneous networks due to the limited capacity of the backhaul links and varied ownership of network devices. In this paper, we propose a game-theoretical scheme using energy-efficient resource allocation and interference pricing for an interference-limited environment in heterogeneous networks. We formulate the problems of resource allocation and interference management as a Stackelberg game with incomplete CSI. A backward induction method is used to analyze the proposed game. A closed-form expression of the Stackelberg equilibrium (SE) is obtained for the proposed game with various interference power constraints. Simulation results are presented to show the effectiveness of the proposed scheme.

Structural Results for Combined Continuous User Authentication and Intrusion Detection in High Security Mobile Ad-Hoc Networks

Continuous user authentication is an important prevention-based approach to protect high security mobile ad-hoc networks (MANETs). On the other hand, intrusion detection systems (IDSs) are also important in MANETs to effectively identify malicious activities. Considering these two approaches jointly is effective in optimal security design taking into account system security requirements and resource constraints in MANETs. To obtain the optimal scheme of combining continuous user authentication and IDSs in a distributed manner, we formulate the problem as a partially observable Markov decision process (POMDP) multi-armed bandit problem. We present a structural results method to solve the problem for a large network with a variety of nodes. The policies derived from structural results are easy to implement in practical MANETs. Simulation results are presented to show the effectiveness and the performance of the proposed scheme.

Dynamic pricing for demand-side management in the smart grid

Intermittent renewable energy sources and the use of smart meters introduce a significant challenge for the reliability of the smart grid. Real-time pricing is an important demand-side management mechanism for improving smart grid reliability through dynamically changing or shifting the electricity consumption of users. Presently, the dynamic real-time pricing research in the smart grid mainly focuses on the interactions between a single utility company/retailer and its users. In this paper, we consider electricity liberalization, where more than one electricity retailer can co-exist in each region, and the retailers compete or cooperate with each other to achieve the highest individual or combined revenue. Two types of electricity users are considered in this paper: traditional electricity users who pay a fixed price and opportunistic electricity users who may change the electricity demand or even turn to another electricity retailer. Two game formulations are described for the proposed real-time pricing scheme. One formulation is proposed for a totally competitive environment. Another game formulation is proposed for a cooperative environment. Some simulation results are presented to show the effectiveness of the proposed real-time pricing scheme.

Joint Cloud and Wireless Networks Operations in Mobile Cloud Computing Environments With Telecom Operator Cloud

In mobile cloud computing systems, cloud computing has a significant impact on wireless networks. Cloud computing and wireless networks have traditionally been addressed separately in the literature. In this paper, we jointly study the operations of cloud computing and wireless networks in mobile computing environments, where the objective is to improve the end-to-end performances of cloud mobile media delivered through mobile cloud computing systems. Unlike most existing studies on wireless networks, where only the spectrum efficiency is considered, we consider not only the spectrum efficiency in wireless networks but also the pricing information in the cloud, based on which power allocation and interference management in the wireless networks are performed. We formulate the problems encountered in the operations of mobile cloud computing environments, including determining the price to charge for media services, resource allocation, and interference management, as a Stackelberg game model. Moreover, we extend this game model with multiple players through network virtualization technology, and adopt the replicator dynamics method to solve the evolutionary game between the different groups of small cells. Furthermore, a backward induction method is used to analyze the proposed Stackelberg game. Simulation results are presented to show the effectiveness of the proposed techniques.