惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

D
Docker
F
Fortinet All Blogs
爱范儿
爱范儿
博客园 - Franky
MyScale Blog
MyScale Blog
罗磊的独立博客
博客园 - 三生石上(FineUI控件)
B
Blog
P
Proofpoint News Feed
IT之家
IT之家
宝玉的分享
宝玉的分享
D
DataBreaches.Net
S
SegmentFault 最新的问题
Microsoft Azure Blog
Microsoft Azure Blog
GbyAI
GbyAI
M
MIT News - Artificial intelligence
L
LangChain Blog
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
月光博客
月光博客
雷峰网
雷峰网
Stack Overflow Blog
Stack Overflow Blog
量子位
V
V2EX
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻

cs.IT updates on arXiv.org

Theoretical Limits of Language Model Alignment $f$-Divergence Regularized RLHF: Two Tales of Sampling and Unified Analyses A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models When Can Voting Help, Hurt, or Change Course? Exact Structure of Binary Test-Time Aggregation When Semantic Communication Meets Queueing: Cross-Layer Latency and Task Fidelity Optimization Convexity in Disguise: A Theoretical Framework for Nonconvex Low-Rank Matrix Estimation Conditional Diffusion Under Linear Constraints: Langevin Mixing and Information-Theoretic Guarantees Sharp Capacity Thresholds in Linear Associative Memory: From Winner-Take-All to Listwise Retrieval Expert Routing for Communication-Efficient MoE via Finite Expert Banks Contextual Memory-Enhanced Source Coding for Low-SNR Communications Realizable Bayes-Consistency for General Metric Losses Leveraging Code Automorphisms for Improved Syndrome-Based Neural Decoding A Hierarchical Sampling Framework for bounding the Generalization Error of Federated Learning Dueling DDQN-Based Adaptive Multi-Objective Handover Optimization for LEO Satellite Networks The Causal Description Gap: Information-Theoretic Separations Across Pearl's Hierarchy Optimization of CV-QKD Under Practical Constraints Benchmarking Wireless Representations: High-Dimensional vs. Compressed Embeddings for Efficiency and Robustness Real-Time Text Transmission via LLM-Based Entropy Coding over Fixed-Rate Channels SwiftChannel: Algorithm-Hardware Co-Design for Deep Learning-Based 5G Channel Estimation Evolving Token Communication with Parametric Memory Network Remote Action Generation: Remote Control with Minimal Communication The (Marginal) Value of a Search Ad: An Online Causal Framework for Repeated Second-price Auctions Stabilizing Private LASSO under Heterogeneous Covariates via Anisotropic Objective Perturbation Linear-Readout Floors and Threshold Recovery in Computation in Superposition Soft Graph Diffusion Transformer for MIMO Detection Hierarchical Federated Learning for Networked AI: From Communication Saving to Architecture-Aware Design Exponential families from a single KL identity MIFair: A Mutual-Information Framework for Intersectionality and Multiclass Fairness Diffusion-OAMP for Joint Image Compression and Wireless Transmission Decoupled Descent: Exact Test Error Tracking Via Approximate Message Passing
On Edge Caching in the Presence of Malicious Users
Frederic Gabry, Valerio Bioglio, Ingmar Land · 2016-05-24 · via cs.IT updates on arXiv.org

In this paper we investigate the problem of optimal cache placement in the presence of malicious mobile users in heterogeneous networks, where small-cell base stations are equipped with caches in order to reduce the overall backhaul load. In particular the malicious users aim at maximizing the congestion of files at the backhaul, i.e., at maximizing the average backhaul rate. For that adversarial model, we derive the achievable average backhaul rate of the heterogeneous network. Moreover, we study the system performance from a game-theoretic perspective, by naturally considering a zero-sum Stackelberg game between the macro-cell base station and the malicious users. We then thoroughly investigate the system performance in the presence of adversaries and we analyze the influence of the system parameters, such as the network topology and the capabilities of the small-cell base stations, on the overall performance of edge caching at the Stackelberg equilibrium. Our results highlight the impact of the malicious users on the overall caching performance of the network and they furthermore show the importance of an adversary-aware content placement at the small-cell base stations.