An open question recently posed by Fawzi and Ferme [IEEE Transactions on Information Theory 2024], asks whether non-signaling (NS) assistance can increase the capacity of a broadcast channel (BC). We answer this question in the affirmative, by showing that for a certainK-receiver BC model, called Coordinated Multipoint broadcast (CoMP BC) that arises naturally in wireless networks, NS-assistance provides multiplicative gains in both capacity and degrees of freedom (DoF), even achievingK-fold improvements in extremal cases. Somewhat surprisingly, this is shown to be true even for 2-receiver broadcast channels that are semi-deterministic and/or degraded. In a CoMP BC,Bsingle-antenna transmitters, supported by a backhaul that allows them to share data, act as oneB-antenna transmitter, to send independent messages toKreceivers, each equipped with a single receive antenna. A fixed and globally known connectivity matrix specifies for each transmit antenna, the subset of receivers that are connected to (have a non-zero channel coefficient to) that antenna. Besides the connectivity, there is no channel state information at the transmitter. The receivers have perfect channel knowledge. We show that NS-assistance has no DoF advantage in a fully connected CoMP BC. The DoF region is fully characterized for a class of connectivity patterns associated with tree graphs, for which the classical sum-DoF value is shown to be the number of leaf nodes, while the NS-assisted sum-DoF value is the total number of all (non-root) nodes. For arbitrary connectivity patterns, the sum-capacity with NS-assistance is bounded above and below by the min-rank and triangle number of the connectivity matrix, respectively, leading to matching bounds in many cases, e.g., if min(B,K) ≤ 6. While translations to Gaussian settings are demonstrated, for simplicity most of our results are presented under noise-free, finite-field (Fq) models. Converse proofs for classical DoF are found by adapting the Aligned Images bounds to the finite field model. Converse bounds for NS-assisted DoF/capacity extend the same-marginals property to the BC with NS-assistance available to all parties. Beyond the BC setting, even stronger (unbounded) gains in capacity due to NS-assistance are established for certain ‘communication with side-information’ settings, such as the fading dirty paper channel.
Abstract: Homomorphic encryption (HE) enables secure computations on encrypted data without decryption, offering a transformative solution for privacy-preserving computation. This review presents a ten-year retrospective (2014–2024) on HE’s evolution since Gentry’s 2009 fully homomorphic encryption (FHE) scheme, which introduced the concept of performing arbitrary computations on ciphertexts. Early schemes were hindered by inefficiencies like computational overhead and noise accumulation. Over the past decade, significant advancements have addressed these barriers. Schemes such as BGV, BFV, and CKKS have been developed for efficient integer and approximate real-number computations. Algorithmic innovations like optimized bootstrapping and improved noise management have reduced complexity. Hardware acceleration using GPUs and FPGAs has enhanced performance, while integration with secure multi-party computation and zero-knowledge proofs has broadened HE’s applicability. Applications now span privacy-preserving machine learning, genomic data analysis, and financial analytics. Toolkits such as SEAL, HElib, and PALISADE have improved accessibility for developers and researchers. Despite progress, challenges remain, including balancing efficiency and security, and improving usability for non-experts. The article also explores HE’s reliance on lattice-based problems like Learning With Errors (LWE) and Ring-LWE, which provide quantum resistance. As hybrid cryptographic models emerge, HE is increasingly recognized as a key component in securing sensitive data in the postquantum era. This review highlights HE’s maturation from a theoretical concept to a practical solution, demonstrating its potential as a cornerstone for secure, privacy-preserving computing across industries.
Elham Hashemi Nezhad, Antonio Di Maio, Torsten Braun
The orchestrators’ deployment problem presents numerous challenges in 6G Network Radio Access Networks due to their large-scale, dynamic conditions, and variable user demands. Most works propose single- or hierarchical-orchestrator solutions, which offer poor resiliency, high signaling overhead, and slow adaptation to variable network dynamics. To tackle these challenges, we propose an online, data-driven, fully decentralized, Multi-Agent Reinforcement Learning (MARL)-based, self-organization orchestrator deployment system for 6G networks, which jointly optimizes the tradeoff between user throughput and fairness, based on time-varying system conditions. In the proposed approach, a flexible variable number of decentralized, cooperative, peer self-organization agents autonomously adapt their associated orchestrator’s deployment location and activity to optimize network operation, without requiring centralized coordination. Simulations show improvements of up to 77% in user throughput compared to Hierarchical and Single Orchestrator baselines in a broad range of realistic scenarios.
We present a secure and efficient federated learning protocol for autonomous vehicles that resists data leaks, redundancy, and adversarial attacks. Our system combines fast zero-knowledge proofs and compressed Bloom filters to verify updates without exposing private data. Compared to traditional approaches, our method reduces proof sizes by 90 % (under 10 KB), memory by up to 75 %, and maintains accuracy with less than 4% degradation under 30% attack rates. The entire update cycle completes in under 600 ms, making it practical for real-time use in vehicles. This work advances trustworthy AI deployment in dynamic, resource-limited networks.
Alfonso Egio, Álvaro Le Monnier, Muhammad Asad, Maxime Compastié · 5 authors
As the sixth generation of the cellular network is set to be deployed around 2030, the needs for ubiquitous connectivity and increased resource demand will press for further collaboration between different stakeholders to constitute an efficient and resilient network fabric. In practice, the deployment of multiple network slices in multiple domains is one of the promising approaches to reach this vision. However, from a privacy standpoint, this introduces additional risks for the customers, as a malicious slice may contemplate the impersonation of a legit one for exfiltrating network traffic. It is therefore necessary to proceed with slice identification and authentication to prevent any collaboration with a non-legit network domain while avoiding exchanging sensitive data before authentication. In response to this challenge, this paper presents a privacy-preserving authentication framework for inter-slice communication. The framework integrates Zero-Knowledge Proofs (ZKPs) for privacy-preserving authentication and Public Key Cryptography (PKC) for secure identity management, ensuring that no sensitive information is jeopardized before a slice can be trusted. We expose an implementation prototype and evaluate it in controlled slicing environment, demonstrating its ability to maintain performance under varying operational constraints. Quantitative results highlight the efficiency limited resource consumption of the authentication model, its scalability in distributed environments, and robustness against security threats.
Daniel Hindemburg de Miranda Marques, Dalton Cézane Gomes Valadares
5G is the most recent technology standard for cellular networks, and one of its key elements is the Radio Access Networks (RAN), which furthers the enabling of the 5G basic capabilities: enhanced Mobile Broadband (eMBB), Massive Machine-Type Communication (mMTC), and Ultra-Reliable, Low-Latency Communication (URLLC). To meet the capabilities required by 5G use cases, 5G is distributed, virtualized, and architecturally more complex than previous generations. These capabilities bring benefits but introduce risks and security challenges that must be addressed through controls designed to support and secure 5G services across any operator cloud. Therefore, this paper focuses on studying and evaluating security mechanisms used in RANs. Special attention is given to Distributed Ledger Technologies (DLTs) since they are one of the most studied topics regarding security enhancement. DLTs could bring advantages for improving network security through encryption to protect the information and automate verification and execution of transactions. For this reason, we carried out a systematic review, extracting and analyzing data from 39 papers from 2010 to 2023. Our main results list RAN-related susceptible security dimensions, vulnerabilities, and possible attacks and threats. We also show how DLTs can enhance RANs and present other considered mechanisms to increase RAN security. • The evolution of mobile communication based on openness, softwarization, and virtualization inserts new vulnerabilities into networks. • The increasing number of connected devices, especially IoT ones, is a security attention point in mobile networks. • Various security mechanisms, including Distributed ledger technologies (DLT), may enhance RAN security once these technologies can increase system resilience. • Other security approaches may also address RAN security issues.
Threshold multi-party fully homomorphic encryption (TMFHE) schemes enable efficient computation to be performed on sensitive data while maintaining privacy. These schemes allow a subset of parties to perform threshold decryption of evaluation results via a distributed protocol without the need for a trusted dealer, and provide a degree of fault tolerance against a set of corrupted parties. However, existing TMFHE schemes can only provide correctness and security against honest-but-curious parties. We construct a compact TMFHE scheme based on the Learning with Errors (LWE) problem. The scheme applies Shamir secret sharing and share resharing to support an arbitrary t-out-of-N threshold access structure, and enables non-interactive reconstruction of secret key shares using additive shares derived from the current set of online participants. Furthermore, the scheme implements commitment and non-interactive zero-knowledge (NIZK) proof techniques to verify the TMFHE operations. Finally, our experiments demonstrate that the proposed scheme achieves active security against malicious adversaries. It overcomes the limitation of existing TMFHE schemes that can only guarantee correct computation under passive semi-honest adversaries.
Yong Yu, Qian Zhang, Yannan Li, Y. Yao · 5 authors
Auctions conducted via wireless devices have promoted trade worth trillions of dollars globally. Their potential market share and crucial role in resource allocation make them an appealing research topic. However, sealed-bid auctions are usually considered high-risk behaviors for bidders due to their unequal status, dependence on auctioneers, and lack of transparency during an auction. In order to meet these requirements for confidentiality, integrity, and availability of data and reduce communication complexity between wireless devices, in this article, we propose a trustworthy sealed-bid auction protocol in wireless networks with low communication costs. Specifically, the protocol adopts cryptographic techniques such as commitment and zero-knowledge proofs to ensure the validity of bids and the credibility of auction results. Inner-product arguments of vectors and proof of aggregation are employed to reduce communication costs of the proposal. The protocol guarantees the continuous verification of submitted data throughout the process (before, during, and at the end) of an auction so as to grant admission to network resources. We show that the proposed protocol satisfies privacy protection, public verifiability, fairness, and non-repudiation of bidders and auctioneers. In addition, our construction is generic, and the protocol can be extended to ordinal-price sealed-bid auctions. The time consumption evaluated in the implementation indicates the feasibility of the protocol in real-world applications.
Forks in the Bitcoin network result from the natural competition in the blockchain's Proof-of-Work consensus protocol. Their frequency is a critical indicator for the efficiency of a distributed ledger as they can contribute to resource waste and network insecurity. We introduce a model for the estimation of natural fork rates in a network of heterogeneous miners as a function of their number, the distribution of hash rates and the block propagation time over the peer-to-peer infrastructure. Despite relatively simplistic assumptions, such as zero propagation delay within mining pools, the model predicts fork rates which are comparable with the empirical stale blocks rate. In the past decade, we observe a reduction in the number of mining pools approximately by a factor 3, and quantify its consequences for the fork rate, whilst showing the emergence of a truncated power-law distribution in hash rates, justified by a rich-get-richer effect constrained by global energy supply limits. We demonstrate, both empirically and with the aid of our quantitative model, that the ratio between the block propagation time and the mining time is a sufficiently accurate estimator of the fork rate, but also quantify its dependence on the heterogeneity of miner activities. We provide empirical and theoretical evidence that both hash rate concentration and lower block propagation time reduce fork rates in distributed ledgers. Our work introduces a robust mathematical setting for investigating power concentration and competition on a distributed network, for interpreting discrepancies in fork rates -- for example caused by selfish mining practices and asymmetric propagation times -- thus providing an effective tool for designing future and alternative scenarios for existing and new blockchain distributed mining systems.
Nischal Aryal, Fariba Ghaffari, E. Bertin, Noël Crespi
The rise of internet and data usage highlights the importance of service provisioning for Mobile Network Operators (MNOs) in expanding their operations and meeting user demands. Implementing scalable and secure authentication and access control mechanisms is crucial for enabling service utilization among eligible users and ensuring the viability of emerging business models. Conventional centralized approaches face limitations such as single-point-of-failure, low scalability, computational overhead, and privacy vulnerabilities. MNOs must explore innovative business models to augment revenue streams and address these challenges. Realizing such models involves automating user contracts with service providers and safeguarding user privacy regarding data sharing with external entities. Blockchain technology offers a transformative avenue for integration within existing MNO infrastructures, providing novel distributed authentication and access control methodologies. We propose a new business model for MNOs and service providers in which an Attribute-Based Access Control (ABAC) framework handles user access to services on top of Blockchain. Moreover, a tokenized data-sharing method facilitates selective data sharing with service providers through MNO channels based on user-defined permissions. Central to this approach are non-fungible tokens (NFTs) and the Self-Sovereign Identity (SSI) paradigm, where NFTs ensure secure, decentralized tokenization of user data, and SSI empowers users with ownership and control over their data. Assessments confirm the scalability of this solution, making it suitable for different use-case requirements.
This work presents an innovative algorithm demonstrating the effectiveness of zero-knowledge proofs (ZKPs) in network security. By integrating Advanced Encryption Standard (AES) and Rivest-Shamir-Adleman (RSA) for key generation, the algorithm showcases their applicability in enhancing security measures within 6G networks. It highlights the utility of ZKPs in bolstering data privacy and security by enabling entities to validate knowledge without compromising sensitive information. The algorithm shows its capability to ensure robust communication security through comprehensive simulations, thereby laying the groundwork for dependable next-generation communication infrastructures.
Data aggregation management is paramount in data-driven distributed systems. Conventional solutions premised on centralized networks grapple with security challenges concerning authenticity, confidentiality, integrity, and privacy. Recently, distributed ledger technology has gained popularity for its decentralized nature to facilitate overcoming these challenges. Nevertheless, insufficient identity management introduces risks like impersonation and unauthorized access. In this paper, we propose Degator, a data aggregation management framework that leverages self-sovereign identity and functions in decentralized networks to address security concerns and mitigate identity-related risks. We formulate fully decentralized aggregation protocols for data persistence and acquisition in Degator. Degator is compatible with existing data persistence methods, and supports cost-effective data acquisition minimizing dependency on distributed ledgers. We also conduct a formal analysis to elucidate the mechanism of Degator to tackle current security challenges in conventional data aggregation management. Furthermore, we showcase the applicability of Degator through its application in the management of decentralized neuroscience data aggregation and demonstrate its scalability via performance evaluation.
Blockchain transactions can be made more scalable using Payment Channel Networks (PCNs), which do not require significant modifications to the distributed ledger algorithm. On the other hand, an onion protocol for anonymity and a locking mechanism to prevent race conditions are needed when routing a payment via several channels in a PCN. This method can be abused by adversaries to launch wormhole attacks. Prior research concentrated on source routing, which is unlikely to continue to be an effective routing strategy as these networks expand. We investigate the impact of attacks in PCNs that employ local knowledge-based routing algorithms. In these scenarios, malicious nodes can steal the benefits of interacting nodes by exchanging confidential information among themselves. We have analyzed the impact of wormhole attacks in the Swift algorithm, Speedy Murmurs, and Silent Whispers. Our experiments introduced an attack that uses a depth measure to arrange malicious nodes in various locations. We used attack gain, attack cost, and attack transaction ratio metrics to assess the attack's impact on routing algorithms. Our simulation-driven analysis demonstrates that placing a malicious node subsequent to a landmark node will raise the likelihood of an attack but at a higher cost. With high transaction volume, attack gain in Silent Whisper will decrease compared to Speedy Murmurs and Swift due to congestion. With 9.6% malicious nodes located at different locations, the average attack transaction ratio for all distributive routing algorithms is 41 %.
Federated Learning (FL) addresses the challenges posed by data silos, which arise from privacy, security regulations, and ownership concerns. Despite these barriers, FL enables these isolated data repositories to participate in collaborative learning without compromising privacy or security. Concurrently, the advancement of blockchain technology and decentralized applications (DApps) within Web 3.0 heralds a new era of transformative possibilities in web development. As such, incorporating FL into Web 3.0 paves the path for overcoming the limitations of data silos through collaborative learning. However, given the transaction speed constraints of core blockchains such as Ethereum (ETH) and the latency in smart contracts, employing one-shot FL, which minimizes client-server interactions in traditional FL to a single exchange, is considered more apt for Web 3.0 environments. This paper presents a practical one-shot FL system for Web 3.0, termed OFL-W3. OFL-W3 capitalizes on blockchain technology by utilizing smart contracts for managing transactions. Meanwhile, OFL-W3 utilizes the Inter-Planetary File System (IPFS) coupled with Flask communication, to facilitate backend server operations to use existing one-shot FL algorithms. With the integration of the incentive mechanism, OFL-W3 showcases an effective implementation of one-shot FL on Web 3.0, offering valuable insights and future directions for AI combined with Web 3.0 studies.
Sung-Min Choi, Zhuochen Xie, Tat Woo Tan, Yifan Liu · 6 authors
In the context of the telecom network trending towards centralization, the relatively decentralized and citizen-centric, non-profit network architecture known as Wireless Community Network (WCN) has emerged. However, WCN faces challenges related to unintentional shifts towards centralization, the lack of automation and verifiability to handle increasing volumes of information, and the absence of real-time and more flexible incentive mechanisms to incentivize a diverse range of contributors based on the quality of their contributions. As the network expands, maintenance becomes more challenging for small volunteer teams, potentially compromising network performance, reliability, and overall trustworthiness. With the development of the decentralized physical infrastructure network (DePIN), this paper proposes a methodology for designing a decentralized wireless community network (DeWCN) system. This methodology includes the design of a consensus layer, a trust and reputation management layer, and presents incentive-driven oracle design methodologies for verifiable common resource pools. This is the first work in the DePIN domain discussing the design of DeWCNs. Unlike projects like Helium [1], we eliminate the need for specialized devices and mining-based token systems.
Distributed ledger technology, with its multitude of advantages including immutability, transparency, decentralization, and security, has excellent potential to promote and even revolutionize future 6G mobile networks. Large-scale distributed ledger deployment within or for mobile networks relies on distributed ledger-focused standards to facilitate and ensure interoperability. The European Telecommunications Standards (ETSI) Industry Specification Group (ISG) on Permissioned Distributed Ledger (PDL) develops PDL-related standards, targeting various application verticals, especially within the Information and Communications Technology (ICT) domain. This article aims to give an overview of ETSI ISG PDL and describes selected PDL standards, which have synergies with future 6G mobile networks.
Krishna Murthy Kattiyan Ramamoorthy, Wei Wang, K. Sohraby, Yanxiao Zhao
In Non-Orthogonal Multiple Access (NOMA) wireless networks, it can be beneficial to allow closer users to relay the cache data to farther users. However, motivating short-distance NOMA users to participate in the relaying requires an appropriate incentive. In this paper, we propose a new crypto token - NOMAToken on the Ethereum blockchain leveraging the Proof of Quality of Experience (QoE) consensus mechanism. NOMAToken serves as a payment token that facilitates all monetary transactions within a NOMA network. As an Ethereum-based token, it can be held or traded against reserve tokens, establishing its own price. The optimal price for retransmission services is determined using the Vickery-Clarke-Groves (VCG) second price auction technique. We discuss the Proof-of-QoE driven consensus model and a Prospect Theory inspired scoring model to regulate the token. The consensus model is designed to ensure that the relay provides the highest possible QoE for its users, while the scoring mechanism serves as a paradigm to allow users to mint new NOMAToken and introduce liquidity.
The InterPlanetary File System (IPFS) has emerged in 2015 as a promising peerto-peer (P2P) distributed file-sharing system poised to become the backbone of Web3.However, its BitSwap protocol, responsible for block exchange, encounters redundancy issues when multiple peers respond with duplicate blocks.To address this limitation, we propose CodedBitSwap, an innovative network coding-based data exchange protocol that integrates Random Linear Network Coding (RLNC) into BitSwap.Considering that RLNC operations incur additional computational overhead, the RLNC-based protocol is designed with careful attention to its computational complexity that is investigated through trial experiments guiding the selection of coding parameters and structures.To assess the feasibility and performance of CodedBitSwap, an experimental evaluation that compares it with BitSwap was conducted in different scenarios xv using a controlled testbed environment consisting of 11 nodes exchanging three files of different sizes.During file exchange, the amount of data transmitted, download time, and encoding and decoding times were measured for each node.The evaluation results demonstrate that CodedBitSwap effectively eliminates redundancy at a relatively low cost of increased download time.The introduced RLNC computational complexity was optimized by the generation-based design strategy that minimizes it, ensuring that the cost of the reduced redundancy remains relatively low.The undertaken design methodology of CodedBitSwap offers a practical approach for future systems, which balances the overhead of RLNC coding with the benefits it brings.This work contributes to the advancement of network coding in P2P networks and demonstrates its potential to improve the efficiency of IPFS, opening up avenues for future research.
Tooba Faisal, Damiano Di Francesco Maesa, Nishanth Sastry, Simone Mangiante
For the viability of future “mission-critical” applications such as remote surgery and connected cars, the customers must trust the network connection and operators must adhere to the Service Level Agreement (SLA). The key to enabling trust between the customer and the operator is the transparency and accountability of the SLA. That is, the operators ensure the transparent and appropriate execution of SLA clauses (e.g., Quality of Service (QoS) and compensations if the SLA is violated). In this work, we argue that today’s network is highly volatile. Therefore, it is convenient for the operators to provide service guarantees for short-term rather than traditional long-term methods. Consequently, we advocate short-term and dynamic service contracts considering spatial and temporal characteristics rather than typical long-term contracts. We propose a Distributed Ledger Technology (DLT)-focused end-to-end transparent, accountable and automated resource provisioning system architecture in which are installed as smart contracts. In our architecture, resources can be requested and allocated dynamically and automatically with Quality-of-Service (QoS) monitoring. Our architecture is scalable through a side-channel based QoS monitoring protocol that guarantees data integrity and minimises the Permissioned Distributed Ledgers (PDL) updates. To measure the viability of our proposal, we first evaluate resource provisioning in the context of network slicing. Then we assess the DLT performance for smart contract execution, in both permissioned and permission-less settings. In the end, we evaluate the monitoring tools and compare and contrast sketches and bloomfilters, and justify our choice of bloomfilters.
Summary Small cell networks can fulfill the increasing demandfor the high data rate of wireless applications. Energy efficiency is an important design parameter of the ultra dense small cell network (UDSCN). The sleeping strategy of small base stations (s‐BSs) is used to enhance the network's energy efficiency. An efficient sleeping strategy of s‐BSs is required while preserving users' quality of service (QoS). The idle s‐BSs can be switched to sleep mode. This paper proposes a blockchain‐enabled solution for the sleeping strategy of s‐BSs. Here, a blockchain‐enabled small cell network is created between the s‐BSs. The network is decentralized, which eliminates the workload of the macro base station (MBS). The proposed network architecture is enabled as a decentralized network through blockchain. The blockchain provides distributed control over the s‐BS operations through a smart contract. Here, smart contracts act as distributed self organizing network features to handle self‐transactions among small cells for switching off s‐BSs in the network. All the software logic required to perform s‐BS operations is written in a smart contract using Ethereum. The proposed solution improves energy efficiency and enables the ultra dense small cell network to be decentralized.
Xueqiang Yan, Xueli An, Wenxuan Ye, Mingyu Zhao · 6 authors
In conventional mobile communications systems, network services are designed to serve a huge amount of subscribers simultaneously, which is normally called a network-centric design approach. In comparison, this paper aims to investigate the user-centric design approach, which refers to sys-tems that are designed to be user-defined, user-configurable and user-controllable. The user-centric approach allows for dedicated network services to be provided at the granularity of the user. A novel User-Centric Network (UCN) architecture is proposed in this work, which includes key design principles, corresponding network elements as well as procedures. It is envisioned that UCN is distributed in nature by leveraging enabling technologies like Distributed Ledger Technology (DLT) and Distributed Hash Table (DHT). In this way, UCN not only provides extreme customization by offering fine-grained services, but also enables autonomous and trusted data control and privacy protection. A simulation platform is developed to verify the feasibility of the architecture, and to preliminarily evaluate its performance by numerical results in terms of hop count, bandwidth consumption, latency, success ratio and scalability.
Named-Data Networking (NDN) is a novel network that secures network communication by fetching semantically named and secured data. All data packets in NDN are signed by producers and verified by data consumers. Therefore, it is vital to have producers' certificates available all the time. In this paper, we describe the design of CLedger, a secure distributed certificate ledger, to ensure certificate availability in NDN. CLedger logs certificate records in an immutable Directed Acyclic Graph (DAG) structure and replicates the DAG among a set of distributed loggers. We implemented CLedger using NDN's pub/sub API, and evaluated our design through an emulated deployment setting. Our initial evaluation results show that CLedger is effective, efficient, and resilient to failures.
Relay Mining presents a scalable solution employing probabilistic mechanisms, crypto-economic incentives, and new cryptographic primitives to estimate and prove the volume of Remote Procedure Calls (RPCs) made from a client to a server. Distributed ledgers are designed to secure permissionless state transitions (writes), highlighting a gap for incentivizing full non-validating nodes to service non-transactional (read) RPCs. This leads applications to have a dependency on altruistic or centralized off-chain Node RPC Providers. We present a solution that enables multiple RPC providers to service requests from independent applications on a permissionless network. We leverage digital signatures, commit-and-reveal schemes, and Sparse Merkle Sum Tries (SMSTs) to prove the amount of work done. This is enabled through the introduction of a novel ClosestMerkleProof proof-of-inclusion scheme. A native cryptocurrency on a distributed ledger is used to rate limit applications and disincentivize over-usage. Building upon established research in token bucket algorithms and distributed rate-limiting penalty models, our approach harnesses a feedback loop control mechanism to adjust the difficulty of mining relay rewards, dynamically scaling with network usage growth. By leveraging crypto-economic incentives, we reduce coordination overhead costs and introduce a mechanism for providing RPC services that are both geopolitically and geographically distributed. We use common formulations from rate limiting research to demonstrate how this solution in the Web3 ecosystem translates to distributed verifiable multi-tenant rate limiting in Web2.
Lorena Chinchilla-Romero, Jonathan Prados-Garzon, Pablo Muñoz, Pablo Ameigeiras · 5 authors
Multi-Wireless Access Technology (WAT) Radio Access Networks (RANs) are becoming a key enabler in 5G and beyond networks due to the public spectrum scarcity, the level of signal confinement and security offered by some wireless technologies (e.g., Light Fidelity (Li-Fi)), and the reduction of the deployment and operational costs. For instance, Wireless Fidelity (Wi-Fi) technology is cheaper and easier to manage than 5G, and leveraging their already deployed infrastructures contributes to capital expenditures saving. Developing autonomous radio resource provisioning (RRP) solutions is fundamental to cost-effectively achieve the zero-touch management in private 5G networks while fulfilling the service requirements. However, modelling the Key Performance Indicators of the radio interface in 5G and beyond is a complex task that requires high-domain knowledge. Furthermore, the resulting models, as well as solving the respective RRP optimization problem using exact methods usually offer a high computational complexity, especially in multi-WAT scenarios. In order to cope with these issues, in this work, we propose an initial design of a Deep Reinforcement Learning-assisted solution for the RRP in a multi-WAT private 5G network. Furthermore, we contex-tualize the solution in the Open RAN architecture framework. A simulation-based proof-of-concept validates the proposal’s proper design and operation considering a realistic private 5G network scenario.