Vehicle clustering improves communication efficiency, safety, and comfort in connected vehicular networks. Cluster heads (CHs) manage critical tasks such as handoff (HO), coordination, and resource allocation. However, in overlapping regions, CH-based group HO handling is hindered by high traffic and limited channel access, causing delays, signaling overhead, and reduced bandwidth efficiency. These issues increase HO latency and risk congestion and HO failures. To address HO loading, latency in overlapping regions, and poor convergence in dynamic environments, this paper proposes an evolutionary game-theoretic framework that selects multiple HO agents (HOAs) in overlapping areas. These agents form HO clusters to distribute load and mitigate channel contention, achieving up to 72.21% lower delay compared to conventional CH-based HO. The buffering of HO data at HOAs, necessitated by the distinct variability of vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) links, is addressed through a queueing-theoretic model. This is followed by optimal resource block (RB) allocation, minimizing total waiting time to 2.063 ms at optimal RB values for two HO-clusters and enhancing network stability. At an average vehicle speed of 140 km/h, the proposed HOA-based HO achieves a total average HO delay of 0.91 ms, corresponding to an 83.8% reduction compared with direct V2I HO. Analytical proof of equilibrium and Lyapunov-based stability validation ensure robustness in dynamic environments. It is observed that, under high incentive, a 12.5% increase in vehicle velocity slows the convergence rate by approximately 60%, primarily due to increased channel variability at higher speeds.

Cluster Head (CH)-based group handoff (HO) management in VANETs faces challenges in overlapping regions, where high traffic and limited channel access exacerbate HO delays. These delays, along with loading problems, signaling overhead, and reduced bandwidth (BW) efficiency, lead to congestion and potential failures, further complicating HO management. CHs in VANETs are responsible for various essential functions beyond HO management, including coordination and communication, resource management, and data aggregation. To address the challenges of loading and delay during HO in the overlapping area and the problem of low convergence in dynamic environments, we propose an evolutionary game-theoretic (EGT) framework. This framework selects multiple handoff agents (HOAs) in overlapping regions, effectively distributing the load and reducing HO delays. Given VANETs’ dynamic topology, frequent cluster reformation can disrupt stability; however, the proposed EGT model ensures an evolutionarily stable strategy (ESS), maintaining efficient HO performance despite sudden network changes. The equilibrium point is analytically proven, and stability is further validated using the Lyapunov function, ensuring robustness against disruptions. This work offers valuable insights into achieving stable and efficient HO clustering in VANETs, especially in highly dynamic environments where traditional CH-based HO management approaches struggle. Simulation results confirm that the system quickly stabilizes, preventing failures caused by selfish user behavior.

In this study, we jointly investigate the connectivity probability and the number of required resource blocks (RBs) for load reduction during handoff (HO) decision for hybrid vehicle-to-everything (V2X) communication. Frequent HOs is a major issue in vehicular communication, causing various concerns such as loading problems in the overlapping area, signalling overhead, and decreasing the bandwidth efficiency of the network. To combat the loading problem due to HO in the overlapping area and the low convergence issues, we propose a game-theoretic approach to resolve the imbalance of resource allocation amongst the clusters at the edge of the coverage area. The proposed game-based Flexible Resource Allocation (FRA) approach optimally redistributes the resources to all clusters within a g-NodeB (g-NB). We obtain a closed-form expression of the transmit power for a cellular-vehicle-to-everything (C-V2X) standard of 5G network, besides analyzing the effects of connectivity probability and required resources for vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) during HO. We explore the implications of non-uniform speeds among the clusters and perform an analysis of time complexity. Additionally, we compare two types of cost functions. A linear cost function links a player’s cost to their action proportionally, while a nonlinear cost function shows a non-proportional relationship between a player’s cost and their action. The simulation results indicate that, with an increasing number of clusters, the linear cost case outperforms the non-linear case in both connectivity probability (which increases by 30.18%) and the number of required resources (which is reduced by 39%) in the HO region. The analytical derivation has been verified through simulation results.

In this study, we jointly investigate the connectivity probability and the number of required resource blocks (RBs) for load reduction during handoff (HO) decision for hybrid vehicle-to-everything (V2X) communication. Frequent handoffs (HOs) is a major issue in vehicular communication, causing various concerns such as loading problems in the overlapping area, signalling overhead, and decreasing the bandwidth efficiency of the network. To combat the loading problem due to HO in the overlapping area and the low convergence issues, we propose a game-theoretic approach to resolve the imbalance of resource allocation amongst the edge clusters. The proposed game-based Flexible Resource Allocation (FRA) approach optimally redistributes the resources to all clusters within a base station (BS). We obtain an approximate closed-form expression of the transmit power for a 5G network, besides analyzing the effects of connectivity probability and required resources for vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) during HO. The analytical derivation has been verified through simulation results.

Free space optical (FSO) channel provides a significantly large transmission capacity. However, in the presence of random jamming attacks, the efficacy of FSO communication channel can be affected critically. In this paper, the discrete-input continuous-output memoryless channel (DCMC) capacity of a single-input single-output FSO communication system is investigated under the random jamming effects. The ergodic channel capacity analysis is performed over additive non-Gaussian noise channel (jamming noise channel). The derived closed-form expression of DCMC capacity for the considered FSO system and also, the effects of partial-band jamming and broadband jamming over the FSO channel capacity are verified through simulation results. It is observed that the FSO channel capacity is very sensitive to the degree of jamming and the ergodic channel capacity alters crucially even for small change in jamming probability. The derived results are utilized to study the considered network in the presence of a rational jammer whose ability to jam is limited by its battery capacity. The presence of a rational jammer is addressed by modelling the interaction between the FSO transmitter and the jammer as a non-cooperative game. The closed-form expressions of the equilibrium of the proposed game are derived and verified through simulation. The game-theoretic solution provides a performance improvement of 74% in comparison to uniform power allocation.

In this paper, a cyber-physical system (CPS) is considered, whose state estimation is done by a central controller (CC) using the measurements received from a wireless powered sensor network (WPSN) over fading channels. An adversary injects false data in this system by compromising some of the idle sensor nodes (SNs) of the WPSN. Using the WPSN for transmitting supervision and control data, in the aforementioned setting, makes the CPS vulnerable to both error and false data injection (FDI). The existing techniques of launching stealthy FDI attack are not applicable to the aforementioned network due to the random nature of wireless channels, which is used for both transmitting control and false data. The objectives of the adversary and the CC to launch stealthy FDI attack and to detect the same, respectively, are found to be depending on the powers they use for transmitting data over wireless channels. The transmit powers of the CC, and the adversary that fulfill their respective objectives are derived by modeling their interaction as a Bayesian Stackelberg game. Based on their objectives, novel utility functions are defined for the CC and the adversary. Subsequently, the equilibrium of the proposed game is obtained by solving a non-convex bi-level quadratic-quadratic program. Finally, the analytical results are verified and compared with other state-of-art techniques by applying them in a realistic smart grid simulations.

In this work, the authors consider the communication network of a power substation, where multiple intelligent electronic devices (IEDs) transmit their delay sensitive control and monitoring messages to a common receiver over a wireless network; in the presence of a broadband jammer, which is capable of jamming multiple channels simultaneously. The objective of the IEDs is to successfully transmit their messages within a specified time, whereas the jammer wants to obstruct IED's transmission. A novel utility function is designed for the players, that addresses the time‐critical nature of communication. Due to the conflicting interest of the IEDs and the jammer, they model the interaction between them as a repeated Bayesian zero‐sum game, which also addresses the repeated interaction among the IEDs and the jammer, and the unavailability of exact information about the jammer. The equilibrium strategies for both the scenarios of perfect and imperfect monitoring are derived and verified through simulation results. Further, the performance of the proposed game model in various scenarios is thoroughly compared in the result section. Finally, the efficacy of the proposed defence strategies is tested in a practical communication network of a power substation under jamming, which is simulated in Optimised Network Engineering Tool (OPNET).

In this paper, an underlay based cognitive radio network (CRN) consisting of a secondary base station (SBS), a secondary receiver (SR), an energy harvesting node (EHN), and a primary transmitter-receiver (PT-PR) pair, is considered. The EHN is assumed to have a power splitter (PS) at the receiver to decode information and harvest energy simultaneously from the SBS transmission, thus reducing the secrecy capacity of SBS. Since both the SBS and the malicious EHN are selfish with conflicting interests, we model the interaction between them as a non-cooperative Stackelberg game. The objective of the SBS is to maximize the secrecy rate and minimize its interference at the PR, whereas the EHN aims at maximizing both the energy it can harvest and the information it can decode from the received SBS signal. The existence of a unique equilibrium point is proved through mathematical analysis. Further, a distributed algorithm is proposed, following which the players will attain the equilibrium of the game as predicted by analytical results. Analytical and simulation results demonstrate that both SBS and EHN can achieve their optimal utilities by adopting the equilibrium strategy.