Reduce Communication Complexity Research Articles

Secure Data Sharing over Vehicular Networks Based on Multi-sharding Blockchain

Internet of Vehicles (IoV) has become an indispensable technology to bridge vehicles, persons, and infrastructures and is promising to make our cities smarter and more connected. It enables vehicles to exchange vehicular data (e.g., GPS, sensors, and brakes) with different entities nearby. However, sharing these vehicular data over the air raises concerns about identity privacy leakage. Besides, the centralized architecture adopted in existing IoV systems is fragile to single point-of-failure and malicious attacks. With the emergence of blockchain technology, there is the chance to solve these problems due to its features of being tamper-proof, traceability, and decentralization. In this article, we propose a privacy-preserving vehicular data sharing framework based on blockchain. In particular, we design an anonymous and auditable data sharing scheme using Zero-Knowledge Proof (ZKP) technology so as to protect the identity privacy of vehicles while preserving the vehicular data auditability for Trusted Authorities (TAs). In response to high mobility of vehicles, we design an efficient multi-sharding protocol to decrease blockchain communication costs without compromising the blockchain security. We implement a prototype of our framework and conduct extensive experiments and simulations on it. Evaluation and analysis results indicate that our framework can not only strengthen system security and data privacy but also reduce communication complexity by \(O(\frac{n\sqrt {m}}{m^2})\) times compared to existing sharding protocols.

An Optimized Byzantine Fault Tolerance Algorithm for Medical Data Security

Medical data are an intangible asset and an important resource for the entire society. The mining and application of medical data can generate enormous value. Currently, medical data management is mostly centralized and heavily relies on central servers, which are prone to malfunctions or malicious attacks, making it difficult to form a consensus among multiple parties and achieve secure sharing. Blockchain technology offers a solution to enhance medical data security. However, in medical data security sharing schemes based on blockchain, the widely adopted Practical Byzantine Fault-Tolerant (PBFT) algorithm encounters challenges, including intricate communication, limited scalability, and the inability to dynamically add or remove nodes. These issues make it challenging to address practical requirements effectively. In this paper, we implement an efficient and scalable consensus algorithm based on the PBFT consensus algorithm, referred to as Me-PBFT, which is more suitable for the field of medical data security. First, we design a reputation evaluation model to select more trusted nodes to participate in the system consensus, which is implemented based on a sigmoid function with adjustable difficulty. Second, we implement the division of node roles to construct a dual consensus layer structure. Finally, we design a node dynamic join and exit mechanism on the overall framework of the algorithm. Analysis shows that compared to PBFT and RAFT, ME-PBFT can reduce communication complexity, improve fault tolerance, and have good scalability. It can meet the need for consensus and secure sharing of medical data among multiple parties.

A Comprehensive Review of Advancements in Communication-Efficient Distributed Optimization

Abstract: In the ever-evolving landscape of machine learning and deep neural networks, the demand for training large models on massive datasets has driven research into innovative approaches for efficient distributed optimization. These approaches aim to simultaneously improve model accuracy and generalization while mitigating the communication overhead challenges inherent to distributed training. Reduced communication complexity is highly desirable, as communication overhead often poses a performance bottleneck in distributed systems. This literature review explores the progression of communication-efficient techniques, culminating in the introduction of the Slow Momentum (SLOWMO) framework. It traces the trajectory of distributed optimization, addresses decentralization strategies, and highlights the role of Local Stochastic Gradient Descent (Local SGD) and momentum in communication-efficient algorithms. It delves into Block-Wise Model Update Filtering (BMUF) and introduces SLOWMO, a framework consistently enhancing optimization and generalization performance across various base algorithms. This review unveils the evolving field of communication-efficient distributed optimization, offering theoretical guarantees and practical insights for improving large-scale model training.

Droop-Based Distributed Secondary Control Method With Reduced Communication Complexity for Radial DC Microgrids

This paper proposes a distributed secondary control method for radial DC microgrid systems with reduced communication complexity. The proposed method utilizes the bus voltage information of the DC microgrid, which is communicated to the individual converters. The proposed method is distributed in nature as the secondary controllers are implemented locally at each converter. The proposed method does not require communication channels between individual converters. Thus, it achieves accurate current sharing and good load voltage regulation with reduced complexity compared to state-of-the-art control methods. The proposed method is robust, and its performance gracefully degrades in the event of a failure of a communication channel. Also, the addition or removal of a converter is seamless with the proposed method. The effectiveness of the proposed method is validated using circuit simulations and hardware-based experiments on different configurations of radial DC microgrid systems.

Blockchain-Based Double-Layer Byzantine Fault Tolerance for Scalability Enhancement for Building Information Modeling Information Exchange

A Practical Byzantine Fault Tolerance (PBFT) is a consensus algorithm deployed in a consortium blockchain that connects a group of related participants. This type of blockchain suits the implementation of the Building Information Modeling (BIM) information exchange with few participants. However, when much more participants are involved in the BIM information exchange, the PBFT algorithm, which inherently requires intensive communications among participating nodes, has limitations in terms of scalability and performance. The proposed solution for a multi-layer BFT hypothesizes that multi-layer BFT reduces communication complexity. However, having more layers will introduce more latency. Therefore, in this paper, Double-Layer Byzantine Fault Tolerance (DLBFT) is proposed to improve the blockchain scalability and performance of BIM information exchange. This study shows a double-layer network structure of nodes that can be built with each node on the first layer, which connects and forms a group with several nodes on the second layer. This network runs the Byzantine Fault Tolerance algorithm to reach a consensus. Instead of having one node send messages to all the nodes in the peer-to-peer network, one node only sends messages to a limited number of nodes on Layer 1 and up to three nodes in each corresponding group in Layer 2 in a hierarchical network. The DLBFT algorithm has been shown to reduce the required number of messages exchanged among nodes by 84% and the time to reach a consensus by 70%, thus improving blockchain scalability. Further research is required if more than one party is involved in multi-BIM projects.

Improved PBFT Algorithm Based on Comprehensive Evaluation Model

Blockchain technology is well known due to the advent of Bitcoin. With the development of recent years, blockchain technology has been widely used in medicine, digital currency, energy, etc. The practical Byzantine fault-tolerant (PBFT) algorithm is a consensus algorithm widely used in consortium blockchains. Aiming to address the problems of the PBFT algorithm, low consensus efficiency due to high communication complexity, and malicious behavior of the primary node leading to consensus failure, an improved PBFT algorithm based on a comprehensive evaluation model (TB-PBFT) is proposed. First, nodes are divided into several groups based on the multi-formation control strategy of an unmanned aerial vehicle (UAV) cluster, which significantly reduces the communication complexity. Second, a comprehensive evaluation model combining the entropy method, TOPSIS method, and Borda count is proposed, which uses the behavior of nodes as an evaluation index, and the comprehensive score of nodes is obtained according to the preferences of other nodes. Finally, the highest ranking node is selected as the primary node through the comprehensive evaluation model to ensure the security and stability of the blockchain network. We analyze TB-PBFT algorithms and compare them with other Byzantine fault tolerance algorithms. Theoretical analysis and simulation results show that the TB-PBFT algorithm can improve node scalability and fault tolerance and reduce communication complexity and view switching probability. We also prove that the comprehensive evaluation model can improve the consensus success rate of the algorithm, and the feasibility and effectiveness of the improved consensus algorithm are verified. Hence, it can be applied to the consortium blockchain system effectively and efficiently.

An efficient sharding consensus algorithm for consortium chains

The consensus algorithm is very critical in any blockchain system, because it directly affects the performance and security of the blockchain system. At present, the classic Practical Byzantine Fault Tolerance Algorithm (PBFT), which is mainly used in the consortium chain, will lead to system communication congestion and reduced throughput when the number of nodes increases, so the PBFT algorithm is not suitable for large-scale consortium chains. In response to the above problems, this paper proposes a new clustering-based sharding consensus algorithm (KBFT), which aims to ensure that the consortium chain takes into account decentralization, security and scalability. The KBFT algorithm first uses the K-prototype clustering algorithm to shard the nodes in the network according to mixed attributes, and second, disjoint transactions are used to reach consensus in parallel in different shards. Concurrently, the KBFT algorithm introduces a supervision mechanism and a node credit mechanism, which is used to supervise and score the behavior of the nodes and select the proxy nodes, which improves security. We discuss the choice of shard size with the help of the binomial probability distribution and analyze the probability that the system can successfully form a global block under different node failure probabilities. Finally, the proposed algorithm is evaluated through theoretical analysis and simulation experiments. Results show that the proposed algorithm achieves a marked improvement in scalability and throughput along with a marked reduction in communication complexity compared with the classic baseline algorithm PBFT in this field of study, which improves the operating efficiency of the system and simultaneously guarantees the security and robustness of the system.

Improved PBFT Algorithm Based on Vague Sets

The traditional PBFT consensus algorithm has several limitations in the consortium blockchain environment, such as unclear selection of primary node, excessive communication times, etc. To solve these limitations, an improved consensus algorithm VS-PBFT based on vague sets was proposed. VS-PBFT has three phases: node partition, primary node selection, and global consensus. Firstly, the nodes of the whole network are partitioned using the consistent hashing-like consensus algorithm, and then the local primary node is selected by the primary node selection algorithm in each partition. The local primary nodes run the four-phase PBFT consensus algorithm to complete the global consensus. The analysis of the VS-PBFT consistency algorithm shows that the algorithm can improve the fault-tolerant rate and reduce communication complexity, and the algorithm is dynamic; that is, node can join and quit adaptively.

A Derivative PBFT Blockchain Consensus Algorithm With Dual Primary Nodes Based on Separation of Powers-DPNPBFT

The Practical Byzantine Fault Tolerant (PBFT) consensus algorithm has many advantages, which makes PBFT utilized widely. Nonetheless, PBFT is not suitable for large-scale node scenarios due to its high communication complexity and it also has an apparent disadvantage of inadequate fault tolerance. The typically derived PBFT algorithms focus on reducing communication complexity at the cost of diminished system security or fault tolerance. In this paper, Dual-Primary-Node derived Practical Byzantine Fault Tolerance (DPNPBFT) is proposed to achieve the best balance of the above three performances. First, DPNPBFT selects dual master nodes based on the idea of power separation. The two master nodes check balance and supervise each other to avoid excessive centralization as a single master node system. It also reduces the communication complexity of the replica node, which only communicates with the master node. Furthermore, we designed the architecture of DPNPBFT to get a practical 49% fault tolerance rate, and it is close to the current mainstream Proof of Work and Proof of Stake algorithms. Experimental results demonstrate that DPNPBFT has O(N) level communication complexity and excellent anti-host node malicious performance. The Transactions Per Second of DPNPBFT is stable at 1700. It proves DPNPBFT has the best performance balance and excellent comprehensive performance for large-scale Internet of Things application scenarios.

No-go theorem for device-independent security in relativistic causal theories

A crucial task for secure communication networks is to determine the minimum of physical requirements to certify a cryptographic protocol. A widely accepted candidate for certification is the principle of relativistic causality which is equivalent to the disallowance of causal loops. Contrary to expectations, we demonstrate how correlations allowed by relativistic causality could be exploited to break security for a broad class of multi-party protocols (all modern protocols belong to this class). As we show, deep roots of this dramatic lack of security lies in the fact that unlike in previous (quantum or no-signaling) scenarios the new theory "decouples" the property of extremality and that of statistical independence on environment variables. Finally, we find out, that the lack of security is accompanied by some advantage: the new correlations can reduce communication complexity better than the no-signaling ones. As a tool for analysis of this advantage, we characterize relativistic causal polytope by its extremal points in the simplest multi-party scenario that goes beyond the no-signaling paradigm.

Symmetrized persistency of Bell correlations for Dicke states and GHZ-based mixtures

Quantum correlations, in particular those, which enable to violate a Bell inequality, open a way to advantage in certain communication tasks. However, the main difficulty in harnessing quantumness is its fragility to, e.g, noise or loss of particles. We study the persistency of Bell correlations of GHZ based mixtures and Dicke states. For the former, we consider quantum communication complexity reduction (QCCR) scheme, and propose new Bell inequalities (BIs), which can be used in that scheme for higher persistency in the limit of large number of particles N. In case of Dicke states, we show that persistency can reach 0.482N, significantly more than reported in previous studies.

General theory of quantum fingerprinting network

The purpose of fingerprinting is to compare long messages with low communication complexity. Compared with its classical version, the quantum fingerprinting can realize exponential reduction in communication complexity. Recently, the multi-party quantum fingerprinting is studied on whether the messages from many parties are the same. However, sometimes it is not enough just to know whether these messages are the same, we usually need to know the relationship among them. We provide a general model of quantum fingerprinting network, defining the relationship function $f^R$ and giving the corresponding decision rules. In this work, we take the four-party quantum fingerprinting protocol as an example for detailed analysis. We also choose the optimal parameters to minimize communication complexity in the case of asymmetric channels. Furthermore, we compare the multi-party quantum fingerprinting with the protocol based on the two-party quantum fingerprinting and find that the multi-party protocol has obvious advantages, especially in terms of communication time. Finally, the method of encoding more than one bit on each coherent state is used to further improve the performance of the protocol.

Blockchain for decentralized multi‐drone to combat COVID‐19 and future pandemics: Framework and proposed solutions

Currently, drones represent a promising technology for combating Coronavirus disease 2019 (COVID‐19) due to the transport of goods, medical supplies to a given target location in the quarantine areas experiencing an epidemic outbreak. Drone missions will increasingly rely on drone collaboration, which requires the drones to reduce communication complexity and be controlled in a decentralized fashion. Blockchain technology becomes a must in industrial applications because it provides decentralized data, accessibility, immutability, and irreversibility. Therefore, Blockchain makes data public for all drones and enables drones to log information concerning world states, time, location, resources, delivery data, and drone relation to all neighbors drones. This paper introduces decentralized independent multi‐drones to accomplish the task collaboratively. Improving blockchain with a consensus algorithm can improve network partitioning and scalability in order to combat COVID‐19. The multi‐drones task is to combat COVID‐19 via monitoring and detecting, social distancing, sanitization, data analysis, delivering goods and medical supplies, and announcement while avoiding collisions with one another. We discuss End to End (E2E) delivery application of combination blockchain and multi‐drone in combating COVID‐19 and beyond future pandemics. Furthermore, the challenges and opportunities of our proposed framework are highlighted.

Quantum Fingerprinting Over AWGN Channels With Power-Limited Optical Signals

Quantum fingerprinting reduces communication complexity of determination whether two $n$-bit long inputs are equal or different in the simultaneous message passing model. Here we quantify the advantage of quantum fingerprinting over classical protocols when communication is carried out using optical signals with limited power and unrestricted bandwidth propagating over additive white Gaussian noise (AWGN) channels with power spectral density (PSD) much less than one photon per unit time and unit bandwidth. We identify a noise parameter whose order of magnitude separates near-noiseless quantum fingerprinting, with signal duration effectively independent of $n$, from a regime where the impact of AWGN is significant. In the latter case the signal duration is found to scale as $O(\sqrt{n})$, analogously to classical fingerprinting. However, the dependence of the signal duration on the AWGN PSD is starkly distinct, leading to quantum advantage in the form of a reduced multiplicative factor in $O(\sqrt{n})$ scaling.

SIGEST

The SIGEST article in this issue, “Randomized Projection for Rank-Revealing Matrix Factorizations and Low-Rank Approximations,” by Jed A. Duersch and Ming Gu, concerns the use of randomization to reduce the bottleneck in a central numerical linear algebra kernel. The authors consider QR factorization, which is a key component in algorithms for constructing stable bases, for solving least-squares problems, and generally for summarizing or extracting insights from data. Column pivoting is the standard technique for dealing with cases where the target matrix is not of full rank, or where the rank is in doubt. However, for large-scale problems column pivoting requires substantial communication between different levels of computer memory, which severely limits the overall efficiency. The authors therefore propose a strategy for choosing pivots based on randomization rather than exhaustive search. This approach reduces communication complexity while increasing uncertainty in the quality of the factorization in a controlled manner. The article makes use of clear pseudocode listings in order to summarize both the original deterministic strategies and the newly developed randomized approaches; see Algorithms 1 to 6. The authors also explain how a Bayesian framework can be set up to quantify the uncertainty introduced by the use of random projections. Extensive, large-scale tests are conducted using Fortran with OpenMP, an application programming interface that supports shared-memory multiprocessing. The original article appeared in the SIAM Journal on Scientific Computing in 2017, and the main idea has subsequently proved to be effective for a number of related tasks. In creating this highlighted article for the SIGEST section, the authors have revised the introductory material, providing additional context; reorganized the document structure and added new visualizations; updated and extended the computational experiments, while making this section more compact and easier to interpret; and discussed recent developments in the field and provided references to the growing literature.

Distributed Online Voltage Control in Active Distribution Networks Considering PV Curtailment

In this paper, we propose a distributed online voltage control algorithm for distribution networks with multiple photovoltaic (PV) systems based on dual-ascent method. Conventional distributed algorithms implement voltage control only when the algorithms converge. However, our proposed algorithm is able to carry out voltage control immediately. In particular, we derive a closed-form solution for PV controllers to locally update the active and reactive power set points aiming at minimizing the total loss and maintaining bus voltages within the acceptable ranges. The optimality is guaranteed and the convergence is established analytically. Moreover, our proposed algorithm only requires the information exchange between neighboring PV systems, thus reducing communication complexity. Finally, numerical tests on IEEE 37-bus distribution system verify the effectiveness and robustness of our proposed algorithm.

Decentralizing IoT Management Systems Using Blockchain for Censorship Resistance

Blockchain technology has been increasingly used for decentralizing cloud-based Internet of Things (IoT) architectures to address limitations faced by centralized systems. While many existing efforts are successful in decentralization with multiple servers (i.e., full nodes) to handle faulty nodes, an important issue has arisen that external clients have to rely on a relay node to communicate with the full nodes in the blockchain. Compromization of such relay nodes may result in a security breach and even a blockage of IoT sensors from the network. In this article, we propose blockchain-based decentralized IoT management systems for censorship resistance, which include a “diffusion” function to deliver all messages from sensors to all full nodes and an augmented consensus protocol to check data losses, replicate processing outcome, and facilitate opportunistic outcome delivery. We also leverage public key aggregation to reduce communication complexity and signature verification. The experimental results from proof-of-concept implementation and deployment in a real distributed environment show the feasibility and effectiveness in achieving censorship resistance.

On Share Conversions for Private Information Retrieval

Beimel et al. in CCC 12’ put forward a paradigm for constructing Private Information Retrieval (PIR) schemes, capturing several previous constructions for servers. A key component in the paradigm, applicable to three-server PIR, is a share conversion scheme from corresponding linear three-party secret sharing schemes with respect to a certain type of “modified universal” relation. In a useful particular instantiation of the paradigm, they used a share conversion from -CNF over to three-additive sharing over for primes where and . The share conversion is with respect to the modified universal relation . They reduced the question of whether a suitable share conversion exists for a triple to the (in)solvability of a certain linear system over . Assuming a solution exists, they also provided a efficient (in ) construction of such a sharing scheme. They proved a suitable conversion exists for several triples of small numbers using a computer program; in particular, yielded the three-server PIR with the best communication complexity at the time. This approach quickly becomes infeasible as the resulting matrix is of size . In this work, we prove that the solvability condition holds for an infinite family of ’s, answering an open question of Beimel et al. Concretely, we prove that if and , then a conversion of the required form exists. We leave the full characterization of such triples, with potential applications to PIR complexity, to future work. Although larger (particularly with ) triples do not yield improved three-server PIR communication complexity via BIKO’s construction, a richer family of PIR protocols we obtain by plugging in our share conversions might have useful properties for other applications. Moreover, we hope that the analytic techniques for understanding the relevant matrices we developed would help to understand whether share conversion as above for , where m is a product of more than two (say three) distinct primes, exists. The general BIKO paradigm generalizes to work for such ’s. Furthermore, the linear condition in Beimel et al. generalizes to m’s, which are products of more than two primes, so our hope is somewhat justified. In case such a conversion does exist, plugging it into BIKO’s construction would lead to major improvement to the state of the art of three-server PIR communication complexity (reducing Communication Complexity (CC) in correspondence with certain matching vector families).

Distributed Elections Using Site-Push Majority Winner Monitoring

The problem of distributed election majority-winner monitoring for checkpoint-based protocols has been of interest for some time now, and the approach that most of the major algorithms take on this is to employ a center-based pull from all voting sites in conjunction with a count tracker, to continually monitor the information about the incoming voter stream. This paper presents an alternative solution to this problem, using site-based voter information push to the center, with reduced communication complexity, using a unique sampling technique. This technique is utilized to come up with a winner or an approximate winner with very high probability for Approval-based and Scoring-based rules. The site-push algorithm introduced here has been validated with correctness results, and has also been analyzed for different scenarios to see the improvement in the number of messages initiated, in comparison to the center-based pull algorithm considered for a checkpoint-based protocol. The effect of this algorithm is to reduce the communication complexity by a factor of $(1+\frac{\log {k}}{\log {\frac{n}{k}}})$ in comparison to the center-pull algorithm (where $k$ is the number of voting sites, and $n$ the number of voters), which leads to a large reduction in communication complexity in democratic election scenarios. Also, to analyze other scenarios, simulation results are presented to show how the algorithm fares under randomized voter assignment, with variations in the value of total voters, total sites and the approximation parameter $\epsilon$ .

Property Testing Lower Bounds via a Generalization of Randomized Parity Decision Trees

A few years ago, Blais, Brody, and Matulef: Comput. Complex. 21(2), 311–358 (2012) presented a methodology for proving lower bounds for property testing problems by reducing them from problems in communication complexity. Recently, Bhrushundi, Chakraborty, and Kulkarni (2014) showed that some reductions of this type can be deconstructed to two separate reductions, from communication complexity to randomized parity decision trees and from the latter to property testing. This work follows up on these ideas. We introduce a model called linear-access algorithms, which is a generalization of randomized parity decision trees, and show several methods to reduce communication complexity problems to problems for linear-access algorithms and problems for linear-access algorithms to property testing problems. This approach yields a new interpretation for several well-known reductions, since we present these reductions as a composition of two steps with fundamentally different functionalities. Furthermore, we demonstrate the potential of proving lower bounds on property testing problems by reducing them directly from problems for linear-access algorithms. In particular, we provide an alternative and simple proof for a known lower bound of Ω(k) queries on testing “k-linearity”; that is, the property of k-sparse linear functions over $\mathbb {F}_{2}$ . This alternative proof relies on a theorem by Linial and Samorodnitsky: Combinatorica 22(4), 497–522 (2002). We then extend this result to a new lower bound of Ω(s) queries for testing s-sparse degree-d polynomials over $\mathbb {F}_{2}$ , for any $d\in \mathbb {N}$ . In addition we provide a simple proof for the hardness of testing some families of linear subcodes.