arXiv subjects

Dongxiao Yu

Publications and source records attributed to Dongxiao Yu.

72 records · Page 4Linked to original sources

arXiv2022

Online Learning for Failure-aware Edge Backup of Service Function Chains with the Minimum Latency

Virtual network functions (VNFs) have been widely deployed in mobile edge computing (MEC) to flexibly and efficiently serve end users running resource-intensive applications, which can be further serialized to form service function chains (SFCs), providing customized networking services. To ensure the availability of SFCs, it turns out to be effective to place redundant SFC backups at the edge for quickly recovering from any failures. The existing research largely overlooks the influences of SFC popularity, backup completeness and failure rate on the optimal deployment of SFC backups on edge servers. In this paper, we comprehensively consider from the perspectives of both the end users and edge system to backup SFCs for providing popular services with the lowest latency. To overcome the challenges resulted from unknown SFC popularity and failure rate, as well as the known system parameter constraints, we take advantage of the online bandit learning technique to cope with the uncertainty issue. Combining the Prim-inspired method with the greedy strategy, we propose a Real-Time Selection and Deployment(RTSD) algorithm. Extensive simulation experiments are conducted to demonstrate the superiority of our proposed algorithms.

cs.NI↗

arXiv2022

Decentralized Wireless Federated Learning with Differential Privacy

This paper studies decentralized federated learning algorithms in wireless IoT networks. The traditional parameter server architecture for federated learning faces some problems such as low fault tolerance, large communication overhead and inaccessibility of private data. To solve these problems, we propose a Decentralized-Wireless-Federated-Learning algorithm called DWFL. The algorithm works in a system where the workers are organized in a peer-to-peer and server-less manner, and the workers exchange their privacy preserving data with the analog transmission scheme over wireless channels in parallel. With rigorous analysis, we show that DWFL satisfies $(ε,δ)$-differential privacy and the privacy budget per worker scales as $\mathcal{O}(\frac{1}{\sqrt{N}})$, in contrast with the constant budget in the orthogonal transmission approach. Furthermore, DWFL converges at the same rate of $\mathcal{O}(\sqrt{\frac{1}{TN}})$ as the best known centralized algorithm with a central parameter server. Extensive experiments demonstrate that our algorithm DWFL also performs well in real settings.

cs.DC↗

arXiv2022

SPDL: Blockchain-secured and Privacy-preserving Decentralized Learning

Decentralized learning involves training machine learning models over remote mobile devices, edge servers, or cloud servers while keeping data localized. Even though many studies have shown the feasibility of preserving privacy, enhancing training performance or introducing Byzantine resilience, but none of them simultaneously considers all of them. Therefore we face the following problem: \textit{how can we efficiently coordinate the decentralized learning process while simultaneously maintaining learning security and data privacy?} To address this issue, in this paper we propose SPDL, a blockchain-secured and privacy-preserving decentralized learning scheme. SPDL integrates blockchain, Byzantine Fault-Tolerant (BFT) consensus, BFT Gradients Aggregation Rule (GAR), and differential privacy seamlessly into one system, ensuring efficient machine learning while maintaining data privacy, Byzantine fault tolerance, transparency, and traceability. To validate our scheme, we provide rigorous analysis on convergence and regret in the presence of Byzantine nodes. We also build a SPDL prototype and conduct extensive experiments to demonstrate that SPDL is effective and efficient with strong security and privacy guarantees.

cs.CR↗

arXiv2022

Extending On-chain Trust to Off-chain -- Trustworthy Blockchain Data Collection using Trusted Execution Environment (TEE)

Blockchain creates a secure environment on top of strict cryptographic assumptions and rigorous security proofs. It permits on-chain interactions to achieve trustworthy properties such as traceability, transparency, and accountability. However, current blockchain trustworthiness is only confined to on-chain, creating a "trust gap" to the physical, off-chain environment. This is due to the lack of a scheme that can truthfully reflect the physical world in a real-time and consistent manner. Such an absence hinders further real-world blockchain applications, especially for security-sensitive ones. In this paper, we propose a scheme to extend blockchain trust from on-chain to off-chain, and take trustworthy vaccine transportation as an example. Our scheme consists of 1) a Trusted Execution Environment (TEE)-enabled trusted environment monitoring system built with the Arm Cortex-M33 microcontroller that continuously senses the inside of a vaccine box through trusted sensors and generates anti-forgery data; and 2) a consistency protocol to upload the environment status data from the TEE system to blockchain in a truthful, real-time consistent, continuous and fault-tolerant fashion. Our security analysis indicates that no adversary can tamper with the vaccine in any way without being captured. We carry out an experiment to record the internal status of a vaccine shipping box during transportation, and the results indicate that the proposed system incurs an average latency of 84 ms in local sensing and processing followed by an average latency of 130 ms to have the sensed data transmitted to and available in the blockchain.

cs.CR↗

arXiv2021

Asymptotic completeness for a scalar quasilinear wave equation satisfying the weak null condition

In this paper, we prove the first asymptotic completeness result for a scalar quasilinear wave equation satisfying the weak null condition. The main tool we use in the study of this equation is the geometric reduced system introduced in arXiv:2002.05355. Starting from a global solution $u$ to the quasilinear wave equation, we rigorously show that well chosen asymptotic variables solve the same reduced system with small error terms. This allows us to recover the scattering data for our system, as well as to construct a matching exact solution to the reduced system.

math.AP↗

arXiv2021

CloudChain: A Cloud Blockchain Using Shared Memory Consensus and RDMA

Blockchain technologies can enable secure computing environments among mistrusting parties. Permissioned blockchains are particularly enlightened by companies, enterprises, and government agencies due to their efficiency, customizability, and governance-friendly features. Obviously, seamlessly fusing blockchain and cloud computing can significantly benefit permissioned blockchains; nevertheless, most blockchains implemented on clouds are originally designed for loosely-coupled networks where nodes communicate asynchronously, failing to take advantages of the closely-coupled nature of cloud servers. In this paper, we propose an innovative cloud-oriented blockchain -- CloudChain, which is a modularized three-layer system composed of the network layer, consensus layer, and blockchain layer. CloudChain is based on a shared-memory model where nodes communicate synchronously by direct memory accesses. We realize the shared-memory model with the Remote Direct Memory Access technology, based on which we propose a shared-memory consensus algorithm to ensure presistence and liveness, the two crucial blockchain security properties countering Byzantine nodes. We also implement a CloudChain prototype based on a RoCEv2-based testbed to experimentally validate our design, and the results verify the feasibility and efficiency of CloudChain.

cs.DC↗

arXiv2021

Applications of Differential Privacy in Social Network Analysis: A Survey

Differential privacy is effective in sharing information and preserving privacy with a strong guarantee. As social network analysis has been extensively adopted in many applications, it opens a new arena for the application of differential privacy. In this article, we provide a comprehensive survey connecting the basic principles of differential privacy and applications in social network analysis. We present a concise review of the foundations of differential privacy and the major variants and discuss how differential privacy is applied to social network analysis, including privacy attacks in social networks, types of differential privacy in social network analysis, and a series of popular tasks, such as degree distribution analysis, subgraph counting and edge weights. We also discuss a series of challenges for future studies.

cs.SI↗

arXiv2020

Tokoin: A Coin-Based Accountable Access Control Scheme for Internet of Things

With the prevalence of Internet of Things (IoT) applications, IoT devices interact closely with our surrounding environments, bringing us unparalleled smartness and convenience. However, the development of secure IoT solutions is getting a long way lagged behind, making us exposed to common unauthorized accesses that may bring malicious attacks and unprecedented danger to our daily life. Overprivilege attack, a widely reported phenomenon in IoT that accesses unauthorized or excessive resources, is notoriously hard to prevent, trace and mitigate. To tackle this challenge, we propose Tokoin-Based Access Control (TBAC), an accountable access control model enabled by blockchain and Trusted Execution Environment (TEE) technologies, to offer fine-graininess, strong auditability, and access procedure control for IoT. TBAC materializes the virtual access power into a definite-amount and secure cryptographic coin termed "tokoin" (token+coin), and manages it using atomic and accountable state-transition functions in a blockchain. We also realize access procedure control by mandating every tokoin a fine-grained access policy defining who is allowed to do what at when in where by how. The tokoin is peer-to-peer transferable, and can be modified only by the resource owner when necessary. We fully implement TBAC with well-studied cryptographic primitives and blockchain platforms and present a readily available APP for regular users. We also present a case study to demonstrate how TBAC is employed to enable autonomous in-home cargo delivery while guaranteeing the access policy compliance and home owner's physical security by regulating the physical behaviors of the deliveryman.

cs.CR↗

arXiv2020

Modified wave operators for a scalar quasilinear wave equation satisfying the weak null condition

We prove the existence of the modified wave operators for a scalar quasilinear wave equation satisfying the weak null condition. This is accomplished in three steps. First, we derive a new reduced asymptotic system for the quasilinear wave equation by modifying Hörmander's method. Next, we construct an approximate solution, by solving our new reduced system given some scattering data at infinite time. Finally, we prove that the quasilinear wave equation has a global solution which agrees with the approximate solution at infinite time.

math.AP↗

arXiv2018

Path model for an extremal weight module over the quantized hyperbolic Kac-Moody algebra of rank 2

Let $\mathfrak{g}$ be a hyperbolic Kac-Moody algebra of rank 2, and set $λ=Λ_{1} - Λ_{2}$, where $Λ_{1}$, $Λ_{2}$ are the fundamental weights. Denote by $V(λ)$ the extremal weight module of extremal weight $λ$ with $v_λ$ the extremal weight vector, and by $\mathcal{B}(λ)$ the crystal basis of $V(λ)$ with $u_λ$ the element corresponding to $v_λ$. We prove that (i) $\mathcal{B}(λ)$ is connected, (ii) the subset $\mathcal{B}(λ)_μ$ of elements of weight $μ$ in $\mathcal{B}(λ)$ is a finite set for every integral weight $μ$, and $\mathcal{B}(λ)_λ = \{u_λ\}$, (iii) every extremal element in $\mathcal{B}(λ)$ is contained in the Weyl group orbit of $u_λ$, (iv) $V(λ)$ is irreducible. Finally, we prove that the crystal basis $\mathcal{B}(λ)$ is isomorphic, as a crystal, to the crystal $\mathbb{B}(λ)$ of Lakshmibai-Seshadri paths of shape $λ$.

math.QA↗

arXiv2017

Lakshmibai-Seshadri paths for hyperbolic Kac-Moody algebras of rank $2$

Let $\mathfrak{g}$ be a hyperbolic Kac-Moody algebra of rank $2$, and set $λ: = Λ_1 - Λ_2$, where $Λ_1, Λ_2$ are the fundamental weights for $\mathfrak{g}$; note that $λ$ is neither dominant nor antidominant. Let $\mathbb{B}(λ)$ be the crystal of all Lakshmibai-Seshadri paths of shape $λ$. We prove that (the crystal graph of) $\mathbb{B}(λ)$ is connected. Furthermore, we give an explicit description of Lakshmibai-Seshadri paths of shape $λ$.

math.QA↗

arXiv2017

Core Maintenance in Dynamic Graphs: A Parallel Approach based on Matching

The core number of a vertex is a basic index depicting cohesiveness of a graph, and has been widely used in large-scale graph analytics. In this paper, we study the update of core numbers of vertices in dynamic graphs with edge insertions/deletions, which is known as the core maintenance problem. Different from previous approaches that just focus on the case of single-edge insertion/deletion and sequentially handle the edges when multiple edges are inserted/deleted, we investigate the parallelism in the core maintenance procedure. Specifically, we show that if the inserted/deleted edges constitute a matching, the core number update with respect to each inserted/deleted edge can be handled in parallel. Based on this key observation, we propose parallel algorithms for core maintenance in both cases of edge insertions and deletions. We conduct extensive experiments to evaluate the efficiency, stability, parallelism and scalability of our algorithms on different types of real-world and synthetic graphs. Comparing with sequential approaches, our algorithms can improve the core maintenance efficiency significantly.

cs.DS↗

arXiv2016

Parallel Algorithms for Core Maintenance in Dynamic Graphs

This paper initiates the studies of parallel algorithms for core maintenance in dynamic graphs. The core number is a fundamental index reflecting the cohesiveness of a graph, which are widely used in large-scale graph analytics. The core maintenance problem requires to update the core numbers of vertices after a set of edges and vertices are inserted into or deleted from the graph. We investigate the parallelism in the core update process when multiple edges and vertices are inserted or deleted. Specifically, we discover a structure called superior edge set, the insertion or deletion of edges in which can be processed in parallel. Based on the structure of superior edge set, efficient parallel algorithms are then devised for incremental and decremental core maintenance respectively. To the best of our knowledge, the proposed algorithms are the first parallel ones for the fundamental core maintenance problem. The algorithms show a significant speedup in the processing time compared with previous results that sequentially handle edge and vertex insertions/deletions. Finally, extensive experiments are conducted on different types of real-world and synthetic datasets, and the results illustrate the efficiency, stability and scalability of the proposed algorithms.

cs.DS↗

arXiv2016

Data Dissemination in Unified Dynamic Wireless Networks

We give efficient algorithms for the fundamental problems of Broadcast and Local Broadcast in dynamic wireless networks. We propose a general model of communication which captures and includes both fading models (like SINR) and graph-based models (such as quasi unit disc graphs, bounded-independence graphs, and protocol model). The only requirement is that the nodes can be embedded in a bounded growth quasi-metric, which is the weakest condition known to ensure distributed operability. Both the nodes and the links of the network are dynamic: nodes can come and go, while the signal strength on links can go up or down. The results improve some of the known bounds even in the static setting, including an optimal algorithm for local broadcasting in the SINR model, which is additionally uniform (independent of network size). An essential component is a procedure for balancing contention, which has potentially wide applicability. The results illustrate the importance of carrier sensing, a stock feature of wireless nodes today, which we encapsulate in primitives to better explore its uses and usefulness.

cs.DC↗

arXiv2016

Leveraging Multiple Channels in Ad Hoc Networks

We examine the utility of multiple channels of communication in wireless networks under the SINR model of interference. The central question is whether the use of multiple channels can result in linear speedup, up to some fundamental limit. We answer this question affirmatively for the data aggregation problem, perhaps the most fundamental problem in sensor networks. To achieve this, we form a hierarchical structure of independent interest, and illustrate its versatility by obtaining a new algorithm with linear speedup for the node coloring problem.

cs.DC↗

arXiv2015

Uniform Information Exchange in Multi-channel Wireless Ad Hoc Networks

In the information exchange problem, k packets that are initially maintained by k nodes need to be disseminated to the whole network as quickly as possible. We consider this problem in single-hop multi- channel networks of n nodes, and propose a uniform protocol that with high probability accomplishes the dissemination in O(k/F + F \cdot log n) rounds, assuming F available channels and collision detection. This result is asymptotically optimal when k is large (k \geq F^2 \cdot log n). To our knowledge, this is the first uniform protocol for information exchange in multi-channel networks.

cs.DC↗

arXiv2013

Sybil-proof Mechanisms in Query Incentive Networks

In this paper, we study incentive mechanisms for retrieving information from networked agents. Following the model in [Kleinberg and Raghavan 2005], the agents are represented as nodes in an infinite tree, which is generated by a random branching process. A query is issued by the root, and each node possesses an answer with an independent probability $p=1/n$. Further, each node in the tree acts strategically to maximize its own payoff. In order to encourage the agents to participate in the information acquisition process, an incentive mechanism is needed to reward agents who provide the information as well as agents who help to facilitate such acquisition. We focus on designing efficient sybil-proof incentive mechanisms, i.e., which are robust to fake identity attacks. %We consider incentive mechanisms which are sybil-proof, i.e., robust to fake identity attacks. We propose a family of mechanisms, called the direct referral (DR) mechanisms, which allocate most reward to the information holder as well as its direct parent (or direct referral). We show that, when designed properly, the direct referral mechanism is sybil-proof and efficient. In particular, we show that we may achieve an expected cost of $O(h^2)$ for propagating the query down $h$ levels for any branching factor $b>1$. This result exponentially improves on previous work when requiring to find an answer with high probability. When the underlying network is a deterministic chain, our mechanism is optimal under some mild assumptions. In addition, due to its simple reward structure, the DR mechanism might have good chance to be adopted in practice.

cs.GT↗

arXiv2013

On the Complexity of Connectivity in Cognitive Radio Networks Through Spectrum Assignment

Cognitive Radio Networks (CRNs) are considered as a promising solution to the spectrum shortage problem in wireless communication. In this paper, we initiate the first systematic study on the algorithmic complexity of the connectivity problem in CRNs through spectrum assignments. We model the network of secondary users (SUs) as a potential graph, where two nodes having an edge between them are connected as long as they choose a common available channel. In the general case, where the potential graph is arbitrary and the SUs may have different number of antennae, we prove that it is NP-complete to determine whether the network is connectable even if there are only two channels. For the special case where the number of channels is constant and all the SUs have the same number of antennae, which is more than one but less than the number of channels, the problem is also NP-complete. For the special cases in which the potential graph is complete, a tree, or a graph with bounded treewidth, we prove the problem is NP-complete and fixed-parameter tractable (FPT) when parameterized by the number of channels. Exact algorithms are also derived to determine the connectability of a given cognitive radio network.

cs.DS↗