English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

In this paper, the problem of seeking optimal distributed resource allocation(DRA) policies on cellular networks in the presence of an unknown maliciousadding-edge attacker is investigated. This problem is described as the games ofgames (GoG) model. Specifically, two subnetwork policymakers constitute a Nashgame, while the confrontation between each subnetwork policymaker and theattacker is captured by a Stackelberg game. First, we show that thecommunication resource allocation of cellular networks based on theFoschini-Miljanic (FM) algorithm can be transformed into a \emph{geometricprogram} and be efficiently solved via convex optimization. Second, the upperlimit of attack magnitude that can be tolerated by the network is calculated bythe corresponding theory, and it is proved that the above geometric programming(GP) framework is solvable within the attack bound, that is, there exists aGestalt Nash equilibrium (GNE) in our GoG. Third, a heuristic algorithm thatiteratively uses GP is proposed to identify the optimal policy profiles of bothsubnetworks, for which asymptotic convergence is also confirmed. Fourth, agreedy heuristic adding-edge strategy is developed for the attacker todetermine the set of the most vulnerable edges. Finally, simulation examplesillustrate that the proposed theoretical results are robust and can achieve theGNE. It is verified that the transmission gains and interference gains of allchannels are well tuned within a limited budget, despite the existence ofmalicious attacks.

Optimal Resource Allocation between Two Nonfully Cooperative Wireless Networks under Malicious Attacks: A Gestalt Game Perspective