On Controlling Spectrum Fragility via Resource Pricing in 5G Wireless Networks

Vamvakas, Panagiotis; Tsiropoulou, Eirini Eleni; Papavassiliou, Symeon

doi:10.1109/lnet.2019.2921425

Cited by 39 publications

(28 citation statements)

References 13 publications

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“…In addition, the level of the users' satisfaction and dissatisfaction is evaluated with respect to a reference point, which is considered as the ground truth of the examined system. Recently, several efforts have appeared in the literature, where Prospect Theory has been adopted in various environments and application domains, including dynamic resource management in 5G wireless networks [18,25], public safety networks [19], anti-jamming communications in cognitive radio networks [20], users' transmission power management and anti-jamming techniques in UAV-assisted networks [5], and Quality of Experience in cyber-physical social systems [21].…”

Section: Users Prospect-theoretic Utility Function In Uav-assisted Mementioning

confidence: 99%

Data Offloading in UAV-Assisted Multi-Access Edge Computing Systems: A Resource-Based Pricing and User Risk-Awareness Approach

Mitsis

Tsiropoulou

Papavassiliou

2020

Sensors

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Unmanned Aerial Vehicle (UAV)-assisted Multi-access Edge Computing (MEC) systems have emerged recently as a flexible and dynamic computing environment, providing task offloading service to the users. In order for such a paradigm to be viable, the operator of a UAV-mounted MEC server should enjoy some form of profit by offering its computing capabilities to the end users. To deal with this issue in this paper, we apply a usage-based pricing policy for allowing the exploitation of the servers’ computing resources. The proposed pricing mechanism implicitly introduces a more social behavior to the users with respect to competing for the UAV-mounted MEC servers’ computation resources. In order to properly model the users’ risk-aware behavior within the overall data offloading decision-making process the principles of Prospect Theory are adopted, while the exploitation of the available computation resources is considered based on the theory of the Tragedy of the Commons. Initially, the user’s prospect-theoretic utility function is formulated by quantifying the user’s risk seeking and loss aversion behavior, while taking into account the pricing mechanism. Accordingly, the users’ pricing and risk-aware data offloading problem is formulated as a distributed maximization problem of each user’s expected prospect-theoretic utility function and addressed as a non-cooperative game among the users. The existence of a Pure Nash Equilibrium (PNE) for the formulated non-cooperative game is shown based on the theory of submodular games. An iterative and distributed algorithm is introduced which converges to the PNE, following the learning rule of the best response dynamics. The performance evaluation of the proposed approach is achieved via modeling and simulation, and detailed numerical results are presented highlighting its key operation features and benefits.

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Section: Users Prospect-theoretic Utility Function In Uav-assisted Mementioning

confidence: 99%

Data Offloading in UAV-Assisted Multi-Access Edge Computing Systems: A Resource-Based Pricing and User Risk-Awareness Approach

Mitsis

Tsiropoulou

Papavassiliou

2020

Sensors

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“…The individual entities of a system, i.e., cognitive IoT devices, make distributed and autonomous decisions under risk and uncertainty of the associated payoff of their decisions, which is determined in a probabilistic manner, while they may demonstrate systematic deviations from the expected utility theory, where all the individuals are assumed as risk neutral with respect to their choices. Prospect Theory has already been applied in various applications, including cyber-physical social systems [33], dynamic resource management in 5G wireless networks [34], [35], UAV-assisted communications in public safety networks [36], [37], and anti-jamming communications in cognitive radio networks [38]. To the best of our knowledge, the proposed framework constitutes the first effort towards modeling and realizing the user risk-based data offloading behavior and decision making, in a MEC IoT environment under uncertainty, thus offering a holistic, cognitive and risk-aware approach.…”

Section: B Contributions and Outlinementioning

confidence: 99%

Cognitive Data Offloading in Mobile Edge Computing for Internet of Things

2020

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Data offloading to Mobile Edge Computing (MEC) servers is an attractive choice for resource-constrained Internet of Things (IoT) devices, towards reducing their computational effort. In this paper, we investigate the potential of partial data offloading to MEC servers, under the perspective of users' cognitive IoT devices presenting loss averse and gain seeking behavior. Due to the sharing nature of the access environment and the MEC server's computational characteristics, we treat the MEC server option as a common pool of resources with uncertain payoff returned to the users, while the local computation capability is treated as a safe option for each user. Following the properties of Prospect Theory, users' prospect-theoretic utilities are formulated exploiting the local computing and offloading overhead options under probabilistic uncertainty. Such a modeling allows for the infusion of human awareness, inherent cognitive biases and behavioral characteristics into the devices' operation, their data offloading decisions and the edge computing environment that the devices are interacting with. Accordingly, each user's optimal offloaded data to the MEC server is obtained as the outcome of a non-cooperative game, with users attempting to maximize their own utilities. The existence and uniqueness of a Pure Nash Equilibrium (PNE) are proven under the probabilistic nature of the respective payoff functions, while a distributed algorithm that convergences to the PNE is designed. Numerical results are provided that demonstrate the operation and superiority of the proposed framework under different IoT scenarios and behaviors, considering both homogeneous and heterogeneous users. INDEX TERMS Intelligent data offloading, mobile edge computing, Internet of Things, risk-based behavior modeling, cognitive decision making, probabilistic uncertainty.

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“…The latter consideration enables to determine the users' optimal transmission power allocation in the two available communication alternatives, that is UAV-based and MBS-based communication, towards improving its utility, while capitalizing on this to devise a sophisticated intrusion detection and ejection process. Towards capturing normal and malicious users' behavior in a more pragmatic manner, prospect theory (PT) is adopted [32,33]. Prospect theory, introduced by Kahneman and Tversky [34], has emerged as a dominant behavioral model in formulating decision making under probabilistic uncertainty.…”

Section: Contributionsmentioning

confidence: 99%

Exploiting prospect theory and risk-awareness to protect UAV-assisted network operation

Vamvakas

Tsiropoulou

Papavassiliou

2019

J Wireless Com Network

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In this paper, a novel resource management framework is introduced and exploited to ensure the efficient and smooth operation of a wireless network, assisted by an unmanned aerial vehicle (UAV), operating under the non-orthogonal multiple access (NOMA) scheme and consisting of both normal and malicious risk-aware users. User devices are assumed capable of splitting their transmission power in two different communication alternatives, established via either the UAV or the macro base station (MBS). The bandwidth offered by the UAV is accessible by everyone, delivers potentially higher rate of return taking into account the enhanced communication channel gains owing to its proximity to the serving users, but is prone to failure due to its potential over-exploitation. Accordingly, the UAV's bandwidth is considered as common pool of resources (CPR). In contrast, the MBS's bandwidth is considered as a safe resource offering to the users a more limited but guaranteed level of service, due to the fact that though it has less available bandwidth it operates under a more controlled access scheme. The theory of the tragedy of the commons is used to capture the probability of failure of the CPR, while the prospect theory is adopted to study the normal and malicious users' risk-aware behavior in the UAV-assisted network. A non-cooperative power control game among the users is formulated and solved, in order to determine the users' power investment to the dual communication environment. The existence and uniqueness of a Pure Nash Equilibrium point is shown and a distributed algorithm is introduced to converge to the PNE point. This overall resource allocation framework is intelligently exploited as the vehicle to detect malicious user behavior and therefore protect the network from the undesired effects of such behaviors. The performance and inherent attributes of the proposed user-centric risk-aware operation framework, in terms of its capability to effectively utilize the available system and user resources (i.e., bandwidth and power), while succeeding in identifying potential abnormal or malicious user behaviors is assessed via modeling and simulation, under different operation scenarios.

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On Controlling Spectrum Fragility via Resource Pricing in 5G Wireless Networks

Cited by 39 publications

References 13 publications

Data Offloading in UAV-Assisted Multi-Access Edge Computing Systems: A Resource-Based Pricing and User Risk-Awareness Approach

Data Offloading in UAV-Assisted Multi-Access Edge Computing Systems: A Resource-Based Pricing and User Risk-Awareness Approach

Cognitive Data Offloading in Mobile Edge Computing for Internet of Things

Exploiting prospect theory and risk-awareness to protect UAV-assisted network operation

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