Books by Sabita Maharjan
Economic Approaches in Cognitive Radio Networks
Papers by Sabita Maharjan
IEEE Transactions on Smart Grid, 2015
Demand Response Management (DRM) is a key component in the smart grid to effectively reduce power... more Demand Response Management (DRM) is a key component in the smart grid to effectively reduce power generation costs and user bills. However, it has been an open issue to address the DRM problem in a network of multiple utility companies and consumers where every entity is concerned about maximizing its own benefit. In this paper, we propose a Stackelberg game between utility companies and end-users to maximize the revenue of each utility company and the payoff of each user. We derive analytical results for the Stackelberg equilibrium of the game and prove that a unique solution exists. We develop a distributed algorithm which converges to the equilibrium with only local information available for both utility companies and end-users. Though DRM helps to facilitate the reliability of power supply, the smart grid can be succeptible to privacy and security issues because of communication links between the utility companies and the consumers. We study the impact of an attacker who can manipulate the price information from the utility companies. We also propose a scheme based on the concept of shared reserve power to improve the grid reliability and ensure its dependability.
IEEE Transactions on Smart Grid, 2000
Demand Response Management (DRM) is a key component in the smart grid to effectively reduce power... more Demand Response Management (DRM) is a key component in the smart grid to effectively reduce power generation costs and user bills. However, it has been an open issue to address the DRM problem in a network of multiple utility companies and consumers where every entity is concerned about maximizing its own benefit. In this paper, we propose a Stackelberg game between utility companies and end-users to maximize the revenue of each utility company and the payoff of each user. We derive analytical results for the Stackelberg equilibrium of the game and prove that a unique solution exists. We develop a distributed algorithm which converges to the equilibrium with only local information available for both utility companies and end-users. Though DRM helps to facilitate the reliability of power supply, the smart grid can be succeptible to privacy and security issues because of communication links between the utility companies and the consumers. We study the impact of an attacker who can manipulate the price information from the utility companies. We also propose a scheme based on the concept of shared reserve power to improve the grid reliability and ensure its dependability.
In this paper, we introduce a hierarchical system model that captures the decision making process... more In this paper, we introduce a hierarchical system model that captures the decision making processes involved in a network of multiple providers and a large number of consumers in the smart grid, incorporating multiple processes from power generation to market activities and to power consumption. We establish a Stackelberg game between providers and end users, where the providers behave as leaders maximizing their profit and end users act as the followers maximizing their individual welfare. We obtain closed-form expressions for the Stackelberg equilibrium of the game and prove that a unique equilibrium solution exists. In the large population regime, we show that a higher number of providers help to improve profits for the providers. This is inline with the goal of facilitating multiple distributed power generation units, one of the main design considerations in the smart grid. We further prove that there exist a unique number of providers that maximize their profits, and develop an iterative and distributed algorithm to obtain it. Finally, we provide numerical examples to illustrate the solutions and to corroborate the results.
to appear in IEEE Transactions on Emerging Topics in Computing
The smart grid is the next generation power grid with bidirectional communications between the el... more The smart grid is the next generation power grid with bidirectional communications between the electricity users and the providers. Demand Response Management is vital in the smart grid to reduce power generation costs as well as to lower the users' electricity bills. In this paper, we introduce multiple fossil-fuel and multiple renewable energy sources based utility companies on the supply side, and propose an end-user oriented utility company selection scheme to minimize user costs. We formulate the problem as a game, incorporating the uncertainty associated with the power supply of the renewable sources, and prove that there exists a Nash equilibrium for the game. To further reduce users' costs, we develop a joint scheme by integrating shiftable load scheduling with utility company selection. We model the joint scheme also as a game, and prove the existence of a Nash equilibrium for the game. For both schemes, we propose distributed algorithms for the users to find the equilibrium of the game using only local information. We evaluate our schemes and compare their performances to two other approaches. The results show that our joint utility company selection and shiftable load scheduling scheme incurs the least cost to the users.
Toward Secure Energy Harvesting Cooperative Networks
The concept of energy harvesting cooperative networks is an emerging technology that has very hig... more The concept of energy harvesting cooperative networks is an emerging technology that has very high potential for a large variety of applications. However, energy transfer capability may lead to unprecedented security challenges. In this article, we study energy security issues and the solutions in energy harvesting networks. We first identify typical energy related attacks and then propose defense solutions against these attacks. We also carry out security analysis and performance analysis to evaluate our proposed solutions. Simulation results have shown that the proposed defense solutions are effective and efficient.
Mobile cloud computing is a key enabling technology in the era of Internet-of-Things. Geo-distrib... more Mobile cloud computing is a key enabling technology in the era of Internet-of-Things. Geo-distributed mobile cloud computing (GMCC) is a new scenario that adds geography consideration in mobile cloud computing. In GMCC, users are able to access cloud resources that are geographically close to their mobile devices. This is expected to reduce communications delay and service providers’ cost compared to the traditional centralized approach. In this paper, we focus on resources sharing through cooperation among service providers in geo-distributed mobile cloud computing. Then, we propose two different strategies for efficient resource cooperation in geographically distributed data centers. Further, we present a coalition game theoretical approach to deal with the competition and cooperation among service providers. Utility functions have been specifically considered to incorporate the cost related to virtual machine migration and resource utilization. Illustrative results indicate
that our proposed schemes are able to efficiently utilize limited resources with Quality-of-Service (QoS) considerations.
It is expected that the Internet of Things (IoT) provides the foundational infrastructure for sma... more It is expected that the Internet of Things (IoT) provides the foundational infrastructure for smart cities, and making ICT an enabling technology to meet major challenges associated with climate change, energy efficiency, mobility and future services. On the other hand a smart city with these requirements is usually evolving through incremental automation and integration of new components, that are digital or physical components or smart devices. To handle the growing scale and complexity of a system, an adaptive modelling method is needed for dynamic analysis and verification and/or validation, and
integration. In this paper, we consider the case study of a Demand Response (DR) Programme that is to be realized by the deployment of a network of smart meters. Through this case study, we propose a component-based modelling approach and demonstrate how it deals with the growing complex architecture.
IEEE Transactions on Smart Grid, Vol. 4, Issue 1, pp. 120-132, March 2013., Mar 2013
Demand Response Management (DRM) is a key component in the smart grid to effectively reduce power... more Demand Response Management (DRM) is a key component in the smart grid to effectively reduce power generation costs and user bills. However, it has been an open issue to address the DRM problem in a network of multiple utility companies and consumers where every entity is concerned about maximizing its own benefit. In this paper, we propose a Stackelberg game between utility companies and end-users to maximize the revenue of each utility company and the payoff of each user. We derive analytical results for the Stackelberg equilibrium of the game and prove that a unique solution exists. We develop a distributed algorithm which converges to the equilibrium with only local information available for both utility companies and end-users. Though DRM helps to facilitate the reliability of power supply, the smart grid can be succeptible to privacy and security issues because of communication links between the utility companies and the consumers. We study the impact of an attacker who can manipulate the price information from the utility companies. We also propose a scheme based on the concept of shared reserve power to improve the grid reliability and ensure its dependability.
Sensing-Delay Tradeoff for Communication in Cognitive Radio enabled Smart Grid
Cooperative spectrum sensing improves reliability and the detection performance of sensing. Howev... more Cooperative spectrum sensing improves reliability and the detection performance of sensing. However, the fully cooperative scenario may not be realistic to assume in many cases. We consider a cognitive radio network with heavy traffic users and light traffic users and analyze their behavior towards sensing using the concept of mixed strategy Nash equilibrium. Further, we design a distributed game using evolutionary game theory such that as long as light traffic users are present, they share the sensing responsibility while heavy traffic users get a free ride. Finally, the evolution dynamics is shown to converge to the evolutionarily stable strategy for the case of multiple users.
"Efficient resource allocation is one of the key concerns of implementing cognitive radio network... more "Efficient resource allocation is one of the key concerns of implementing cognitive radio networks. Game theory has been extensively used to study the strategic interactions between primary and secondary users for effective resource allocation. The concept of spectrum trading has introduced a new direction for the coexistence of primary and secondary users through economic benefits to primary users. The use of price theory and market theory from economics has played a vital role to facilitate
economic models for spectrum trading. So, it is important to understand the feasibility of using economic approaches as well as to realize the technical challenges associated with them for implementation of cognitive radio networks. With this motivation, we present an extensive summary of the related work that use economic approaches such as game theory and/or price theory/market theory to model the behavior of primary and secondary users for spectrum sharing and discuss the associated issues. We also propose some open directions for future research on economic aspects of spectrum sharing in cognitive radio networks."
Personal Indoor and …
"Real time traffic such as voice and video have strict requirements on the acceptable end-to-end ... more "Real time traffic such as voice and video have strict requirements on the acceptable end-to-end packet delay. When
there are different types of traffic with different requirements on tolerable latency, priority based packet scheduling schemes are normally used in order to reduce the queuing delay for real time services. However, in cognitive radio networks, the time that the system spends on spectrum sensing adds further delay to the packet transmission. In this paper, we propose a new scheme to significantly reduce the overall packet delay, including the delay due to sensing for real time services in cognitive radio networks. We derive the expression for average packet delay for the proposed scheme and the simulation results match well with the analytical results. The numerical results show that the priority based scheduling scheme combined with our scheme substantially reduces the packet delay for real time applications."
B-17-6 Influence of Quantization on Detection Performance of Cognitive Radio Receiver
… 学会ソサイエティ大会講演論文集, Jan 1, 2008
Practical Detection Issues of Spectrum Sensing for Cognitive Radio System
Spectrum sensing demonstration system for energy and cyclostationary detectors
IEICE Technical Report (SR), IEICE Technical Report (SR), 電子情報通信学会, Vol. 108, no. 172, pp. 113-118 (SR2008-35), Aug 2008
Development of Spectrum Sensing Evaluation System
電子情報通信学会技術研究報告. SR, …, Jan 1, 2007
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Books by Sabita Maharjan
Papers by Sabita Maharjan
that our proposed schemes are able to efficiently utilize limited resources with Quality-of-Service (QoS) considerations.
integration. In this paper, we consider the case study of a Demand Response (DR) Programme that is to be realized by the deployment of a network of smart meters. Through this case study, we propose a component-based modelling approach and demonstrate how it deals with the growing complex architecture.
economic models for spectrum trading. So, it is important to understand the feasibility of using economic approaches as well as to realize the technical challenges associated with them for implementation of cognitive radio networks. With this motivation, we present an extensive summary of the related work that use economic approaches such as game theory and/or price theory/market theory to model the behavior of primary and secondary users for spectrum sharing and discuss the associated issues. We also propose some open directions for future research on economic aspects of spectrum sharing in cognitive radio networks."
there are different types of traffic with different requirements on tolerable latency, priority based packet scheduling schemes are normally used in order to reduce the queuing delay for real time services. However, in cognitive radio networks, the time that the system spends on spectrum sensing adds further delay to the packet transmission. In this paper, we propose a new scheme to significantly reduce the overall packet delay, including the delay due to sensing for real time services in cognitive radio networks. We derive the expression for average packet delay for the proposed scheme and the simulation results match well with the analytical results. The numerical results show that the priority based scheduling scheme combined with our scheme substantially reduces the packet delay for real time applications."
that our proposed schemes are able to efficiently utilize limited resources with Quality-of-Service (QoS) considerations.
integration. In this paper, we consider the case study of a Demand Response (DR) Programme that is to be realized by the deployment of a network of smart meters. Through this case study, we propose a component-based modelling approach and demonstrate how it deals with the growing complex architecture.
economic models for spectrum trading. So, it is important to understand the feasibility of using economic approaches as well as to realize the technical challenges associated with them for implementation of cognitive radio networks. With this motivation, we present an extensive summary of the related work that use economic approaches such as game theory and/or price theory/market theory to model the behavior of primary and secondary users for spectrum sharing and discuss the associated issues. We also propose some open directions for future research on economic aspects of spectrum sharing in cognitive radio networks."
there are different types of traffic with different requirements on tolerable latency, priority based packet scheduling schemes are normally used in order to reduce the queuing delay for real time services. However, in cognitive radio networks, the time that the system spends on spectrum sensing adds further delay to the packet transmission. In this paper, we propose a new scheme to significantly reduce the overall packet delay, including the delay due to sensing for real time services in cognitive radio networks. We derive the expression for average packet delay for the proposed scheme and the simulation results match well with the analytical results. The numerical results show that the priority based scheduling scheme combined with our scheme substantially reduces the packet delay for real time applications."