CN113032484A - Block chain-based data system congestion management method and system - Google Patents
Block chain-based data system congestion management method and system Download PDFInfo
- Publication number
- CN113032484A CN113032484A CN202110282012.8A CN202110282012A CN113032484A CN 113032484 A CN113032484 A CN 113032484A CN 202110282012 A CN202110282012 A CN 202110282012A CN 113032484 A CN113032484 A CN 113032484A
- Authority
- CN
- China
- Prior art keywords
- node
- transaction
- neighbor node
- block chain
- rate
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000007726 management method Methods 0.000 title claims abstract description 12
- 238000000034 method Methods 0.000 claims description 16
- 238000005516 engineering process Methods 0.000 claims description 5
- 230000007774 longterm Effects 0.000 abstract description 3
- 230000005540 biological transmission Effects 0.000 abstract description 2
- RTZKZFJDLAIYFH-UHFFFAOYSA-N Diethyl ether Chemical compound CCOCC RTZKZFJDLAIYFH-UHFFFAOYSA-N 0.000 description 4
- 239000000306 component Substances 0.000 description 2
- 239000008358 core component Substances 0.000 description 2
- 230000007246 mechanism Effects 0.000 description 2
- 125000002015 acyclic group Chemical group 0.000 description 1
- 230000002457 bidirectional effect Effects 0.000 description 1
- 230000001934 delay Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000008569 process Effects 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 230000010076 replication Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/27—Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/07—Responding to the occurrence of a fault, e.g. fault tolerance
- G06F11/14—Error detection or correction of the data by redundancy in operation
- G06F11/1402—Saving, restoring, recovering or retrying
- G06F11/1446—Point-in-time backing up or restoration of persistent data
- G06F11/1448—Management of the data involved in backup or backup restore
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/25—Integrating or interfacing systems involving database management systems
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L47/00—Traffic control in data switching networks
- H04L47/10—Flow control; Congestion control
- H04L47/12—Avoiding congestion; Recovering from congestion
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/10—Protocols in which an application is distributed across nodes in the network
- H04L67/104—Peer-to-peer [P2P] networks
Abstract
The invention discloses a block chain-based data system congestion management method and a block chain-based data system congestion management system, wherein the block chain-based data system congestion management method comprises the following steps: each node generates a basic guaranteed rate according to the obtained reputation; when a node issues a transaction, the node interacts with the neighbor nodes to obtain the allowed rate of each neighbor node, and sends the transaction to the neighbor nodes with the allowed rate not lower than the basic guaranteed rate until each node in the block chain adds the transaction to the local ledger copy. The invention controls and optimizes the limited system resources through the credit value which is a parameter, eliminates the data transmission congestion caused by the fact that the nodes occupy extra resources beyond the processing capacity of the nodes in the system, simultaneously considers the characteristics of fairness, transparency and long-term consistency of data of the block chain system, and provides fairness and safety which are basically equal to the actual requirements.
Description
Technical Field
The invention relates to the field of internet, in particular to a block chain-based data system congestion management method and system.
Background
Distributed ledger technology (distributed ledger Technologies) DLT architecture is a trust-free point-to-point (P2P) network in which nodes store local copies of databases called ledgers. One basic characteristic of DLT is that nodes must agree on the status of the general ledger without the aid of a central entity. Here, untrusted means that the node does not need to trust any other node, but only the system as a whole is trusted to operate normally. The first generation of DLTs is a pure token type public block chain represented by bitcoin and ether house, but these DLTs are not suitable for general application scenarios. In particular, ledgers in a blockchain are stored in blocks, each block being cryptographically linked to the previous one. The longest chain contains the correct block and a new block should be added to this chain. However, due to network delays, if several tiles are created simultaneously, multiple forks will be created, but only one can be part of the system data tile chain, whereby in a conventional tile chain system, a tile should be created only once and the generation time between generating each tile should be large enough, at least larger than the network delay. This process is too slow and inefficient. In addition, due to the contention mechanism, no matter how many nodes the whole system has, only a specific single node meeting the conditions can create a block chain in a unit time, which is certainly not suitable for a large-scale network interaction scenario with high concurrency.
Distributed systems based on Directed Acyclic Graphs (DAGs) are increasingly being proposed as efficient and trusted distributed systems for use in a variety of areas, where transactions are stored individually rather than in blocks into the system. Each new transaction is linked to two or more existing transactions in a keyed manner. Multiple nodes can write transactions simultaneously, so there is no serial processing restriction corresponding to a blockchain. However, DAG-based DLT requires congestion control because the resources of the nodes are limited. In particular, network resources must be allocated to nodes based on their own cryptographic verifiable resources. In blockchains, such as bitcoin and ether house, this resource represents computational power. In addition, the allocable resources of each node are also distinguished according to the related indexes.
In DAG-based DLTs, each node must validate each transaction, add it to the ledger, and then run some reconciliation algorithm, we call the bottleneck. The details of writing a DLT implementation may vary from DLT implementation to DLT implementation and may even vary from node to node. For example, in some DLTs, some nodes may perform the most computationally intensive tasks, while other limited nodes perform lighter tasks when written. If there is no congestion control, stale transactions may accumulate.
Minimizing latency and meeting the following requirements while seeking a maximum throughput-write bottleneck:
consistency if a transaction is written by one correct node, it should be written by all correct nodes within a certain delay bound.
Fairness-all nodes should get a fair share of bandwidth and the resources each node can own are allocated according to its reputation value.
Security-a malicious node should not be able to interfere with any of the above requirements.
Disclosure of Invention
Aiming at a DLT system needing to manage transaction throughput, the invention provides a block chain-based data system congestion management method, which solves the problem of system congestion through embedding and evaluating credit degree parameters.
The technical content of the invention comprises:
a block chain-based data system congestion management method comprises the following steps:
1) each node in the block chain acquires respective reputation, and generates a basic guaranteed rate according to the reputation;
2) when a node P in the block chainmWhen issuing transaction, with neighbor node
Interacting and acquiring each neighbor node
According to the node PmAt a basic guaranteed rate λmSending the transaction to the allowable rate not lower than the basic guaranteed rate lambdamNeighbor node of (2)
3) Each neighbor node
Writing the transaction into a local ledger copy and corresponding neighbor node
Interacting to obtain each corresponding neighbor node
Where i ≧ 1, and according to each neighbor node
Basic guaranteed rate of
Sending transaction transactions to an allowed rate not lower than a basic guaranteed rate
Of the corresponding neighbor node
Until each node in the blockchain adds the transaction to a local ledger copy.
Further, the reputation comprises: connecting directly to the reputation of the node wealth or to the reputation in a delegated form.
Further, network resources are fairly allocated to each node in the block chain.
Further, the neighbor node
Does not send the transaction to node Pm。
Further, each neighbor node
Sending transaction transactions to neighboring nodes
The method comprises the following steps: and (4) a flooding method.
Further, each node maintains an inbox buffer.
Further, each node filters the transaction in the inbox buffer before adding the transaction to the local ledger copy.
Further, each node generates the speed of writing the transaction into the local ledger copy according to the reputation and the resource vacancy of the node.
Further, the method for writing in the local ledger copy is determined according to the structure of the underlying ledger and the implementation details of the distributed ledger technology.
A block chain based data system congestion management system comprising:
the plurality of nodes are used for acquiring respective reputations and generating basic guaranteed rates according to the reputations;
wherein, when a node P in the block chainmWhen issuing transaction, with neighbor node
Interacting and acquiring each neighbor node
According to the node PmAt a basic guaranteed rate λmSending the transaction to the allowable rate not lower than the basic guaranteed rate lambdamNeighbor node of (2)
Each neighbor node
Writing the transaction into a local ledger copy and corresponding neighbor node
Interacting to obtain each corresponding neighbor node
Where i ≧ 1, and according to the neighbor node
Basic guaranteed rate of
Sending transaction transactions to an allowed rate not lower than a basic guaranteed rate
Neighbor node of (2)
Until each node in the blockchain adds the transaction to a local ledger copy.
Compared with the prior art, the method has the following advantages:
1) limited system resources are controlled and optimized through the credit value parameter, data transmission congestion caused by the fact that nodes occupy extra resources exceeding the processing capacity of the nodes in the system is eliminated, and meanwhile, the block chain system is fair and transparent and has the characteristics of long-term consistency of data;
2) the block chain technology has the characteristics of being a decentralization (multi-decentration) fair management environment, ensuring that the data of the distributed system keeps long-term consistency, but improving the performance inevitably causes the reduction of the efficiency of the other two sides according to the performance, decentralization and safety triangle which cannot be theorem, so that the invention considers the fairness (decentralization) and the safety on the premise of improving the system performance by a main target, and puts forward the fairness and the safety which are basically equal to the actual requirement.
Drawings
FIG. 1 is a system framework diagram of the present invention.
Detailed Description
In order to make the purpose and technical solution of the present invention more apparent, embodiments of the present invention will be described in detail below with reference to the accompanying drawings.
The main work of the invention is as follows: 1) a node model is provided for capturing the main bottleneck of write transactions. 2) A DLT system congestion control algorithm based on DAG is provided, and is suitable for any distributed database replication architecture. The algorithm has two core components, namely a scheduling algorithm, which ensures that all nodes can fairly obtain the reputation which the nodes should obtain; a rate setting algorithm is used to solve the bottleneck write problem by setting the relative rate while preventing latency.
Node and network model: the set of all nodes participating in the network is denoted as M. Each node M belongs to M and has a group of neighbors
They communicate directly over a secure bidirectional channel. The data shared by the nodes is referred to as a transaction and may include signature updates of account balances or other data. When a transaction occurs in all ledgers, it is called propagation. Those transactions that have been created but not yet distributed are defined as undistributed transactions. The transaction propagation rate for node i is denoted DiThe propagation rate of all transactions is denoted d. The propagation rate may be a measure of network throughput in dlt. Transaction propagation rate in the long run
Is bounded because the node has a write bottleneck, which will be the primary indicator used to evaluate the performance of the congestion control algorithm, and n is the number of nodes in the node set M. Examples of reputation systems suitable for the model include reputations, delegations directly connected to the wealth of the nodeA reputation of a form. The reputation of node m is denoted repmAnd all nodes know the reputation distribution of the other nodes. Because the system is a decentralized common decision making mechanism, each node has decision making right, and the decision making basis is that each node knows the reputation state of other nodes.
1) Issuing a transaction: a transaction is issued by a node and cryptographically signed, linking the transaction to the issuer. This means that the receiving node can identify the node that generated any transaction. Each node has a lowest score, proportional to their reputation. In other words, node m has a basic guaranteed rate λm. Receive and forward transactions: the nodes receive transactions from their neighbors and forward the transactions to their neighbors, each node maintaining an Inbox buffer, denoted InboxmIt contains transactions received from neighbors and issued by themselves. Transactions are filtered before being added to the inbox to prevent spam. By using Inboxm(i) Representing the set of transactions that node i issues in node m's inbox buffer. Flooding is used here to forward the transaction, which means that all new information is forwarded to all neighbors (except the source node), regardless of whether the neighbor already owns it. The size of each buffer is limited and each node M should ensure Inbox at other nodes i e Mi(m) does not become too large because this would result in excessive queuing delay. Thus, the transaction flow from m to i consists of transactions issued by all nodes (except the transaction sent from i itself). We call the sequence of transactions issued by node i the flow of i.
2) Writing transaction: when a node is notified of a new transaction, a series of actions must be taken to add the transaction to the node's local ledger copy. The local ledger copy refers to data backup performed by the node in the equipment system of the node, is irrelevant to other nodes, and is mainly used for storing data of the node and data related to the node received by other systems. These steps are referred to as writes, and the details required to write a transaction will depend on the underlying ledger structure, as well as details specific to the DLT implementation.
And (3) a congestion control algorithm: congestion control algorithms strive to utilize resources to the maximum extent while ensuring that consistency, fairness, and security requirements are met. Two core components of the solution are the scheduling algorithm and the rate setting algorithm:
1) scheduling and allocating: the goal of this component is to schedule transactions, per rep, by each node i ∈ MiThe rate of (2) is issued. In other words, weighted ceiling fairness is achieved over the write rate of the publishing node. For a node m, it can use the appropriate rate of issuing transactions with respect to its reputation, while the following requirements will be met:
a) m's transactions will not be backlogged at any node, so the consistency of m's transactions will be ensured;
b) network resources are distributed to m fairly, malicious nodes with sending rate exceeding the allowed rate will not interrupt the propagation rate of m, and the safety requirement is met.
2) Rate setting: and the rate setting component carries out random distribution according to the credit degree and the resource vacancy degree.
The test network of the invention consists of 15 nodes and is arranged in a random 4-degree regular graph, namely, each node has 4 random neighbors. The channel delay is random between 50ms and 150ms and does not vary with time. Consider first a set of 5 nodes at each non-malicious mode of operation. The nodes are identified by letters representing the mode of operation of the node and numbers representing the reputation of the node.
The rate of content nodes converges to their guaranteed problem rate and, since each group has the same reputation, best effort nodes converge to twice their guaranteed rate, consuming unused resources left by inactive nodes.
Undistributed transactions exhibit consistency, the protocol does not discard any transactions, and the number of undistributed transactions is still limited. Also, while transactions must pass through each node, and different transactions have different start and end points, the average delay is bounded.
The above examples are provided only for the purpose of describing the present invention, and are not intended to limit the scope of the present invention. The scope of the invention is defined by the appended claims. Various equivalent substitutions and modifications can be made without departing from the spirit and principles of the invention, and are intended to be within the scope of the invention.
Claims (10)
1. A block chain-based data system congestion management method comprises the following steps:
1) each node in the block chain acquires respective reputation, and generates a basic guaranteed rate according to the reputation;
2) when a node P in the block chainmWhen issuing transaction, with neighbor node
Interacting and acquiring each neighbor node
According to the node PmAt a basic guaranteed rate λmSending the transaction to the allowable rate not lower than the basic guaranteed rate lambdamNeighbor node of (2)
3) Each neighbor node
Writing the transaction into a local ledger copy and corresponding neighbor node
Interacting to obtain each corresponding neighbor node
Where i ≧ 1, and according to each neighbor node
Basic guaranteed rate of
Sending transaction transactions to an allowed rate not lower than a basic guaranteed rate
Of the corresponding neighbor node
Until each node in the blockchain adds the transaction to a local ledger copy.
2. The method of claim 1, wherein the reputation comprises: connecting directly to the reputation of the node wealth or to the reputation in a delegated form.
3. The method of claim 1, wherein network resources are allocated fairly to nodes in a block chain.
4. The method of claim 1, wherein a neighbor node
Does not send the transaction to node Pm。
5. The method of claim 1, wherein each neighbor node
Sending transaction transactions to neighboring nodes
The method comprises the following steps: and (4) a flooding method.
6. The method of claim 1 wherein each node maintains an inbox buffer.
7. The method of claim 6, wherein each node filters the transaction in an inbox buffer before adding the transaction to a local ledger copy.
8. The method of claim 1, wherein each node generates a rate at which the transaction is written to a local ledger copy based on the reputation and resource idleness of the node.
9. The method of claim 1, wherein the method of writing to the local ledger copy is determined based on underlying ledger structures and distributed ledger technology implementation details.
10. A block chain based data system congestion management system comprising:
the plurality of nodes are used for acquiring respective reputations and generating basic guaranteed rates according to the reputations;
wherein, when a node P in the block chainmWhen issuing transaction, with neighbor node
Interacting and acquiring each neighbor node
According to the node PmAt a basic guaranteed rate λmSending the transaction to the allowable rate not lower than the basic guaranteed rate lambdamNeighbor node of (2)
Each neighbor node
Writing the transaction into a local ledger copy and corresponding neighbor node
Interacting to obtain each corresponding neighbor node
Where i ≧ 1, and according to the neighbor node
Basic guaranteed rate of
Sending transaction transactions to an allowed rate not lower than a basic guaranteed rate
Neighbor node of (2)
Until each node in the blockchain adds the transaction to a local ledger copy.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110282012.8A CN113032484B (en) | 2021-03-16 | 2021-03-16 | Block chain-based data system congestion management method and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110282012.8A CN113032484B (en) | 2021-03-16 | 2021-03-16 | Block chain-based data system congestion management method and system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113032484A true CN113032484A (en) | 2021-06-25 |
| CN113032484B CN113032484B (en) | 2024-01-02 |
Family
ID=76471059
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110282012.8A Active CN113032484B (en) | 2021-03-16 | 2021-03-16 | Block chain-based data system congestion management method and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113032484B (en) |
Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109462631A (en) * | 2018-08-31 | 2019-03-12 | 腾讯科技（深圳）有限公司 | Data processing method, device, storage medium and electronic device |
| CN109949033A (en) * | 2018-11-15 | 2019-06-28 | 陕西医链区块链集团有限公司 | A kind of affaris safety trade system and method based on block chain |
| CN110362272A (en) * | 2019-06-03 | 2019-10-22 | 阿里巴巴集团控股有限公司 | A kind of block chain date storage method and device |
| WO2020000708A1 (en) * | 2018-06-29 | 2020-01-02 | 北京金山安全软件有限公司 | Blockchain node synchronization method and device using trust mechanism |
| CN110998631A (en) * | 2017-07-17 | 2020-04-10 | Dlt基数公司 | Distributed account book technology |
| CN110992177A (en) * | 2019-10-31 | 2020-04-10 | 中国科学院计算技术研究所 | Block chain flux improving method and system based on off-chain channel route evaluation mechanism |
| CN111127013A (en) * | 2019-12-24 | 2020-05-08 | 深圳大学 | Decentralized data transaction method, device, equipment and medium based on block chain |
| CN111837101A (en) * | 2019-09-12 | 2020-10-27 | 创新先进技术有限公司 | Log structure storage system |
| US20200348662A1 (en) * | 2016-05-09 | 2020-11-05 | Strong Force Iot Portfolio 2016, Llc | Platform for facilitating development of intelligence in an industrial internet of things system |
| CN112149181A (en) * | 2020-09-29 | 2020-12-29 | 合肥城市云数据中心股份有限公司 | Hybrid cloud data center data transmission method with credit value analysis function |
| CN112381542A (en) * | 2020-11-18 | 2021-02-19 | 深圳源中瑞科技有限公司 | Transaction payment method, device, equipment and storage medium based on block chain |
-
2021
- 2021-03-16 CN CN202110282012.8A patent/CN113032484B/en active Active
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20200348662A1 (en) * | 2016-05-09 | 2020-11-05 | Strong Force Iot Portfolio 2016, Llc | Platform for facilitating development of intelligence in an industrial internet of things system |
| CN110998631A (en) * | 2017-07-17 | 2020-04-10 | Dlt基数公司 | Distributed account book technology |
| WO2020000708A1 (en) * | 2018-06-29 | 2020-01-02 | 北京金山安全软件有限公司 | Blockchain node synchronization method and device using trust mechanism |
| CN109462631A (en) * | 2018-08-31 | 2019-03-12 | 腾讯科技（深圳）有限公司 | Data processing method, device, storage medium and electronic device |
| CN109949033A (en) * | 2018-11-15 | 2019-06-28 | 陕西医链区块链集团有限公司 | A kind of affaris safety trade system and method based on block chain |
| CN110362272A (en) * | 2019-06-03 | 2019-10-22 | 阿里巴巴集团控股有限公司 | A kind of block chain date storage method and device |
| CN111837101A (en) * | 2019-09-12 | 2020-10-27 | 创新先进技术有限公司 | Log structure storage system |
| CN110992177A (en) * | 2019-10-31 | 2020-04-10 | 中国科学院计算技术研究所 | Block chain flux improving method and system based on off-chain channel route evaluation mechanism |
| CN111127013A (en) * | 2019-12-24 | 2020-05-08 | 深圳大学 | Decentralized data transaction method, device, equipment and medium based on block chain |
| CN112149181A (en) * | 2020-09-29 | 2020-12-29 | 合肥城市云数据中心股份有限公司 | Hybrid cloud data center data transmission method with credit value analysis function |
| CN112381542A (en) * | 2020-11-18 | 2021-02-19 | 深圳源中瑞科技有限公司 | Transaction payment method, device, equipment and storage medium based on block chain |
Non-Patent Citations (5)
| Title |
|---|
| ANDREW CULLEN等: "On Congestion Control for Distributed Ledgers in Adversarial IoT Networks", HTTPS://ARXIV.ORG/PDF/2005.07778V1.PDF, pages 1 - 7 * |
| ERIC KE WANG等: "PoRX: A reputation incentive scheme for blockchain consensus of IIoT", FUTURE GENERATION COMPUTER SYSTEMS, vol. 102, pages 140 - 151 * |
| JOANA PEREIRA等: "Blockchain-based platforms: Decentralized infrastructures and its boundary conditions", TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE, pages 94 - 102 * |
| 江航: "DAG链上的共识机制与均衡", 中国优秀硕士学位论文全文数据库 (信息科技辑), no. 2, pages 138 - 1012 * |
| 符纯浩: "基于分布式账本的去中心化存储系统框架", 中国优秀硕士学位论文全文数据库 (信息科技辑), pages 137 - 72 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113032484B (en) | 2024-01-02 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| JP7362654B2 (en) | Maintenance and management of blockchain blocks in a divided blockchain network | |
| CN109508982B (en) | Random parallel Byzantine fault-tolerant consensus method of block chain main chain and parallel multiple sub-chains | |
| Cui et al. | A decentralized and trusted edge computing platform for Internet of Things | |
| Wang et al. | Performance characterization and bottleneck analysis of hyperledger fabric | |
| JP2022136219A (en) | System and method for parallel verification of blockchain transaction | |
| CN111371905B (en) | Block chain layering consensus proving system and method based on cloud computing | |
| Wang et al. | Beh-Raft-Chain: a behavior-based fast blockchain protocol for complex networks | |
| CN111711526B (en) | Method and system for consensus of block chain nodes | |
| CN112769580A (en) | Block chain layered excitation consensus algorithm | |
| CN112189328A (en) | System and method for propagating data packets in a network of nodes | |
| Liu et al. | Parallel and asynchronous smart contract execution | |
| CN113626875A (en) | Knowledge graph file storage method for block chain fragment enabling | |
| KR20200081533A (en) | Blockchain Consensus Method based Improved Dynamic Blind Voting for Internet of Things Environment | |
| He et al. | Chameleon: A scalable and adaptive permissioned blockchain architecture | |
| Chen et al. | Optimizing network transfers for data analytic jobs across geo-distributed datacenters | |
| CN110493323A (en) | Fairness document distribution method, system and storage medium based on block chain | |
| Müller et al. | Stability of local tip pool sizes | |
| Chen et al. | MSig-BFT: A witness-based consensus algorithm for private blockchains | |
| CN113269543A (en) | Multilayer mixed transaction capacity expansion system and method for block chain | |
| Wu et al. | Dynamic behavior analysis of an internet flow interaction model under cascading failures | |
| KR20220082074A (en) | Decentralized network with consensus mechanism | |
| CN113032484A (en) | Block chain-based data system congestion management method and system | |
| Grybniak et al. | Waterfall: a scalable distributed ledger technology | |
| Chen et al. | Barrier-aware max-min fair bandwidth sharing and path selection in datacenter networks | |
| CN115796261A (en) | Block chain-based lightweight group consensus federated learning method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |