BITS Faculty Publications

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Subject: search.filters.subject.Game theory

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    An energy efficient data dissemination and information retrieval scheme for VANET
    (IEEE, 2016-02) Dua, Amit
    With the increasing scarcity of resources, the need for energy efficient solutions has reached its pinnacle. Vehicular ad hoc networks (VANETs) is no exception and there is a need for exclusive solutions for energy efficient data dissemination and information retrieval. The proposed scheme classifies the vehicles into different types based on their storage and computation capacity. Cluster heads (CHs) are elected for each energy zone according to type of vehicle, and act as information center. Apart from CHs, the dissemination of data and access of information in efficient and correct manner is made possible with the help of vehicles having high processing capability. The broadcast storm problem that consumes high energy in terms of bandwidth, is solved using proposed game theoretic decision model. The proposed model gives suggestion to vehicles whether to disseminate the information or not based on the current energy situation of the network. Simulation results prove that the proposed model saves energy and time by minimizing the overhead and delay. The network energy is efficiently utilized by achieving higher packet delivery ratio and lower delay than other state-of-art protocols.
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    A novel resource reservation scheme for mobile PHEVS in V2G environment using game theoretical approach
    (IEEE, 2015-09) Dua, Amit
    With the widespread penetration of plug-in hybrid electric vehicles (PHEVs), the overall demand on microgrids (MGs) may increase manifold in the near future. Unregulated power demands from PHEVs may increase the demand-supply gap at MGs. Thus, to keep MGs stabilize and cater the ever-growing energy demands, there is a requirement of an intelligent solution to regulate and manage PHEVs in vehicle-to-grid (V2G) environment. Keeping in view the given issues, this paper proposes a novel scheme that aims to regulate PHEVs' charging and discharging activities based on MGs' day-ahead load curves. These load curves are obtained by utilizing the existing load forecasting techniques such as fuzzy logic (FL) and artificial neural networks (ANNs). Efficient utilization of PHEVs according to these curves may play a vital role in flattening MG's load profile. Thus, the proposed scheme works by reserving resources such as time slots and charging points (CPs) for PHEVs during peak shaving and valley filling. Different algorithms pertaining to resource reservation for PHEVs have also been designed. These algorithms employ the concepts of game theory and the 0/1 knapsack problem for supporting peak shaving and valley filling, respectively. Moreover, PHEVs are also utilized when there are transitions from valley filling to peak shaving areas in the load curves and vice versa. PHEVs involved in this process have both charging and discharging capabilities and are referred to as dual-mode PHEVs. The proposed scheme has been tested with respect to various parameters, and its performance was found satisfactory.
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    QoS Aware Uplink Scheduling for M2M Communication in LTE/LTE-A Network: A Game Theoretic Approach
    (IEEE, 2022-04) Dua, Amit
    M2M communication in the LTE network is gaining attention with a growing number of connected devices and adaptation of new emerging technologies. Usually, the traffic generated by M2M devices is heterogeneous in terms of packet size, intensity, strict delay, and throughput requirements. The M2M traffic generally flows in the uplink direction. It imposes several challenges in designing scheduling for uplink in the LTE network. The research community proposed various solutions regarding the QoS handling in M2M communications. Allocating the resources based on the QoS of machine type communications (MTCs) has a challenge in deciding on devices’ priority. This work applies game theory to control devices’ strategic behavior claiming a false priority. In this paper, a Quality-of-Service aware uplink packet scheduling scheme is proposed using a combinatorial game. The packet scheduling problem is modeled as an Auction game that handles the scheduling in both Time-Domain and Frequency-Domain. The packet scheduler uses the QoS requirement as an allocation metric, and a power control mechanism is applied to control the devices’ strategic behavior. Simulation is performed in MATLAB R2019b. The performance of the proposed schemes is evaluated in terms of the total system utility in QoS satisfaction against standard schedulers like Round Robin and Proportional Fair schedulers and some other schedulers proposed in the literature.
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    Coalition Games for Performance Evaluation in 5G and Beyond Networks: A Survey
    (IEEE, 2022-01) Dua, Amit
    The 5G network is an emerging field of the research community. 5G is a multi-disciplinary network that aims to support a wide range of services. 5G network has an objective to support a massive number of connected devices. Game theory has an extensive role in wireless network management. Game theory is an approach to analyzing and modeling the system where multiple actors have a role in decision-making with independent objectives and actions. The game theory is an exciting methodology to control the strategic behavior of players and generate an efficient outcome. Coalition game theory can play a crucial role in ensuring cooperation among a massive number of devices. This article provides insight into the current research trends in 5G using coalition games. The work presented in the survey is divided into three categories, namely resource management, interference management, and miscellaneous. This article also provides the foundation about 5G and coalition games highlight the scope of future research.
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    UAV SECaaS: Game-Theoretic Formulation for Security as a Service in UAV Swarms
    (IEEE, 2022-12) Chamola, Vinay
    Unmanned aerial vehicles, popularly known as UAVs, have been used in many applications in the recent past. UAVs have also been recently used to provide security as a service (SECaaS). SECaaS involves technical solutions, like antivirus and antispam software, firewalls, using secure operating systems, etc. UAVs are resource-constrained entities, and thus, they avail the computational facilities of the base station (BS) to serve the users in their range. At times, several UAVs cooperatively come together to serve a given region, and such a group of UAVs is called a swarm of UAVs. Generally, a group/swarm of UAVs connect themselves to the BS through cluster head (CH) UAVs, which are intermediary nodes. In real-world scenarios, many stakeholders come together to form a UAV swarm configuration providing services to users. Each stakeholder wants to maximize gains. This work proposes a pricing Stackelberg game among the UAVs, CHs, and the BS by formulating their behavioral utilities. Using particle swarm optimization on each entity’s utility functions, we create an optimal price strategy to maximize profit.
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    A Framework for Secure Vehicular Network using Advanced Blockchain
    (IEEE, 2020) Chamola, Vinay; Chalapathi, G.S.S.
    Vehicular Ad-hoc Network (VANET) poses to be a promising technology for the future since it increases the comfort level of the drivers while also enhancing the safety measures for them. The main aim of VANETs is to enable communication among vehicles and roadside units (RSUs) using vehicle-to-vehicle (V2V) and vehicle-to-RSU (V2R) networks. VANET applications have a vast potential for growth owing to the increasing number of smart cities around the globe and advancement taking place in the technology sector. However, with all their benefits, VANETs also face several security challenges. The sensitive nature of data being transferred turns VANETs prone to malicious attacks. To overcome the security challenges, this paper proposes a distributed Directed Acyclic Graph (DAG) enabled vehicular network comprising several requesting vehicles and RSUs. The proposed model is based on advanced blockchain and therefore provides a strong level of security and data immutability. Furthermore, the interactions between the requesting vehicles and the RSUs have been modeled using an auction-based game-theoretic smart contract deployed on the blockchain.
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    BitFund: A blockchain-based crowd funding platform for future smart and connected nation
    (Elsevier, 2020-09) Chamola, Vinay
    The rapid growth in information technology and related talent has let to a competition among the investors to look for the best available talent. Additionally, the diverse range of directions in technology, gives a lot of options to the applicants to choose from. In such a scenario, it is imperative to link the most appropriate investors and developers in a secure and cost optimal way. Blockchain technology helps in creating a decentralized network of users where the transactions are recorded in an open distributed ledger. These features of blockchain enable a transparent and cost-effective platform for different applications. Based on the need to an effective crowdfunding platform for developing smart nation and the inherent features of blockchain technology, we propose a global crowdfunding platform called BitFund. Investors and developers can act as different nodes of the network. The investors can request a specific project and they can give their initial bid value in terms of time, cost and maintenance required. Different developers can bid with different values of the same parameters to get the project ownership. A smart contract is deployed between the investors and the developers to reach an optimal solution for the investors. Multiple iterations of bidding are carried out between the developers until the optimal solution or equilibrium is reached. The experimental results show that the proposed model yields better results as compared to other generic algorithms for crowdfunding.
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    Analyzing Advanced Persistent Threats Using Game Theory: A Critical Literature Review
    (Springer, 2022) Kumar, Rajesh
    Advanced persistent threats present significant security challenges due to their customized, stealthy and adaptive nature. Since no generic solution exists to combat advanced persistent threats, the recommended option is to employ information security best practices. While practitioner-oriented security guidelines have been published by the International Organization for Standardization and the U.S. National Institute of Standards and Technology, they cannot be employed in rigorous quantitative analyses required for objective decision making such as choosing countermeasures that balance security, cost and usability. In contrast, game-theoretic approaches, which express the behavior of rational agents that maximize their utility, provide appropriate models for objective decision making. This chapter conducts a critical analysis of several game-theoretic approaches for analyzing advanced persistent threats. Eleven highly-cited, peer-reviewed articles from the research literature are examined in terms of their objectives, features, game models and solutions. The models provide valuable insights into advanced persistent threat behavior, support resource-optimal decision making and can be mapped to the various risk management stages. However, they have some delicate modeling and analysis limitations. The critical analysis exposes the omissions in the literature and points to future research focused on integrating practitioner perspectives in game-theoretic approaches to advance information security risk management.