Software system based on adaptive decentration architecture and communication method thereof

Abstract

The invention relates to a software system based on a self-adaptive decentration architecture and a communication method thereof, and belongs to the technical field of computer software and communication. According to the system, an ad hoc network is adopted as a communication means, a decentralized software architecture is adopted as a core, and the task processing efficiency and the system robustness in a distributed environment are improved. Through a self-adaptive decentralized task allocation mechanism, each node can make a decision autonomously according to a network state, computing power and task requirements, so that dynamic and balanced task scheduling is realized, and the problem of single-point failure is avoided. The system adopts a multi-stage data consistency management strategy to ensure data reliability and consistency in a distributed environment. The method is widely applied to the fields of unmanned systems, emergency communication, intelligent manufacturing and the like, and the software system stability and the collaborative operation capability in a network environment are improved.

Description

Technical Field

[0001] The present invention relates to the field of distributed software systems and ad hoc network communication technology, and in particular to a software system based on an adaptive decentralized architecture. Background Art

[0002] With the rapid development of information technology, traditional centralized software systems face limitations in multi-terminal collaboration, adaptability to dynamic environments, and high reliability. Centralized architectures rely on central servers for task scheduling, data storage, and communication management. This makes the system susceptible to single points of failure, communication bottlenecks, and response delays in high-concurrency, high-dynamic, or emergency situations. This makes it difficult to meet the real-time requirements of application scenarios such as emergency rescue, military communications, unmanned system collaboration, and industrial automation.

[0003] Self-organizing networks are a decentralized communication method characterized by the ability of individual nodes to autonomously discover, form networks, and transmit data without fixed infrastructure. While self-organizing networking technology has, to a certain extent, addressed the deployment difficulties of traditional communication networks in complex environments, existing self-organizing network applications primarily focus on the communication layer and lack effective software architectures to support decentralized software operation management, task scheduling, and data processing. Consequently, distributed software still relies on a certain degree of centralized control in practical applications.

[0004] While distributed computing and blockchain technologies have explored the possibilities of decentralized architectures to a certain extent, existing solutions are mostly based on pre-set task allocation models, making it difficult to dynamically adapt to changes in computing resource distribution and task requirements in different application scenarios. Existing decentralized software systems still have room for improvement in terms of node task allocation, data synchronization, and security mechanisms. In particular, achieving efficient and adaptive task scheduling and data management in complex environments remains a technical challenge facing the industry. Therefore, a software architecture that combines ad hoc network communication with adaptive decentralized task management capabilities is urgently needed to improve the system's robustness, flexibility, and task execution efficiency, and meet the application needs of various dynamic environments. Summary of the Invention

[0005] This invention provides a decentralized software system based on ad hoc network communication. This system enables distributed task scheduling, data storage, and multi-node collaboration in an environment without fixed infrastructure. A core feature of this system is its decentralized software architecture, which enables each node to independently perform computations, execute tasks, and store data. Dynamic communication via the ad hoc network ensures high availability and robustness. Compared to traditional centralized systems, this system can maintain efficient operation even without fixed servers and in unstable networks, making it suitable for complex environments such as emergency rescue, military communications, and unmanned system collaboration.

[0006] A software system based on an adaptive decentralized architecture, characterized in that the software system uses an ad hoc network as a communication means and includes the following modules:

[0007] (1) Adaptive task allocation module, which is used to dynamically adjust the task allocation strategy according to the computing power of each node, network status and task requirements to achieve decentralized task scheduling;

[0008] (2) Data synchronization and consistency management module, which is used to ensure data consistency between nodes in a decentralized environment and synchronize data based on timestamps, priority rules or blockchain technology;

[0009] (3) A decentralized communication management module, which is used to realize end-to-end information interaction between nodes without a central server, including multiple data types such as text, voice, and video;

[0010] (4) Security and access control module, which is used to ensure the security of data transmission and access permission management based on preset security mechanisms such as identity authentication, dynamic key management, and end-to-end encryption.

[0011] Preferably, the software system is characterized in that the adaptive task allocation module is based on machine learning or a rule engine to achieve task scheduling optimization and improve task processing efficiency.

[0012] Preferably, the software system is characterized in that the data synchronization and consistency management module adopts a distributed hash table (DHT) or a consensus algorithm to improve the stability of data distribution.

[0013] Preferably, the software system is characterized in that the decentralized communication management module supports multi-hop routing and can realize remote data transmission between nodes in an environment without a public network.

[0014] Preferably, the software system is characterized in that the security and access control module adopts a dynamic access strategy to adjust access rights according to environmental changes, thereby improving the adaptability and security of the system.

[0015] A communication method based on the software system according to claims 1 to 5, characterized in that it comprises the following steps:

[0016] (1) In the pre-setting phase, each node loads the initial task rules, identity information, and encryption keys, and performs data synchronization;

[0017] (2) During the operation phase, nodes dynamically adjust task allocation based on real-time network topology and computing power to achieve adaptive task scheduling;

[0018] (3) During the communication process, data transmission adopts end-to-end encryption, and a multi-hop self-organizing network is used to ensure data accessibility in an off-network environment;

[0019] (4) When a new node joins, identity authentication is performed based on the preset security mechanism, and the network topology and task allocation strategy are dynamically adjusted;

[0020] (5) The data consistency management module regularly checks and synchronizes key mission data to ensure the information consistency of each node.

[0021] Preferably, the method described therein is characterized in that the communication method is applicable to various decentralized application scenarios such as emergency rescue, military communications, and industrial automation.

[0022] The present invention has the following beneficial effects: (1) The present invention proposes an adaptive decentralized task scheduling mechanism, which enables each node to independently determine the execution right of the task based on factors such as computing resources, energy consumption status, and link quality. Task scheduling adopts a distributed competition strategy. When each task is initiated, it will be broadcast to multiple candidate nodes. These nodes compete by evaluating their own status, and the task is finally executed by the optimal node, rather than relying on a central server for unified allocation. This mechanism greatly improves the flexibility of task allocation, while avoiding the problem of single point failure, making the system more stable and scalable. (2) The present invention adopts a distributed data storage and synchronization mechanism to ensure data consistency and availability in the system. In the absence of a central server, data is split and stored on different computing nodes, and real-time data updates are achieved through a decentralized data synchronization protocol (such as the Gossip protocol). When a node fails or loses data, other nodes can restore the data through redundant storage or neighboring data queries, thereby ensuring the integrity and availability of key data in the entire network. This mechanism effectively reduces the risk of data loss and improves the system's anti-destruction capabilities. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 : Schematic diagram of the system architecture of the present invention

[0024] Figure 2 :Decentralized task scheduling flow chart

[0025] Figure 3 :Schematic diagram of decentralized data storage and synchronization mechanism

[0026] Figure 4 :Schematic diagram of communication mode based on ad hoc network

[0027] Figure 5 : Schematic diagram of application scenario of the present invention DETAILED DESCRIPTION

[0028] This invention provides a decentralized software system based on ad hoc network communication. This system enables distributed task scheduling, data storage, and multi-node collaboration in an environment without fixed infrastructure. A core feature of this system is its decentralized software architecture, which enables each node to independently perform computations, execute tasks, and store data. Dynamic communication via the ad hoc network ensures high availability and robustness. Compared to traditional centralized systems, this system can maintain efficient operation even without fixed servers and in unstable networks, making it suitable for complex environments such as emergency rescue, military communications, and unmanned system collaboration.

[0029] A software system based on an adaptive decentralized architecture, characterized in that the software system uses an ad hoc network as a communication means and includes the following modules:

[0030] (1) Adaptive task allocation module, which is used to dynamically adjust the task allocation strategy according to the computing power of each node, network status and task requirements to achieve decentralized task scheduling;

[0031] (2) Data synchronization and consistency management module, which is used to ensure data consistency between nodes in a decentralized environment and synchronize data based on timestamps, priority rules or blockchain technology;

[0032] (3) A decentralized communication management module, which is used to realize end-to-end information interaction between nodes without a central server, including multiple data types such as text, voice, and video;

[0033] (4) Security and access control module, which is used to ensure the security of data transmission and access permission management based on preset security mechanisms such as identity authentication, dynamic key management, and end-to-end encryption.

[0034] Preferably, the software system is characterized in that the adaptive task allocation module is based on machine learning or a rule engine to achieve task scheduling optimization and improve task processing efficiency.

[0035] Preferably, the software system is characterized in that the data synchronization and consistency management module adopts a distributed hash table (DHT) or a consensus algorithm to improve the stability of data distribution.

[0036] Preferably, the software system is characterized in that the decentralized communication management module supports multi-hop routing and can realize remote data transmission between nodes in an environment without a public network.

[0037] Preferably, the software system is characterized in that the security and access control module adopts a dynamic access strategy to adjust access rights according to environmental changes, thereby improving the adaptability and security of the system.

[0038] A communication method based on the software system according to claims 1 to 5, characterized in that it comprises the following steps:

[0039] (1) In the pre-setting phase, each node loads the initial task rules, identity information, and encryption keys, and performs data synchronization;

[0040] (2) During the operation phase, nodes dynamically adjust task allocation based on real-time network topology and computing power to achieve adaptive task scheduling;

[0041] (3) During the communication process, data transmission adopts end-to-end encryption, and a multi-hop self-organizing network is used to ensure data accessibility in an off-network environment;

[0042] (4) When a new node joins, identity authentication is performed based on the preset security mechanism, and the network topology and task allocation strategy are dynamically adjusted;

[0043] (5) The data consistency management module regularly checks and synchronizes key mission data to ensure the information consistency of each node.

[0044] Preferably, the method described therein is characterized in that the communication method is applicable to various decentralized application scenarios such as emergency rescue, military communications, and industrial automation.

[0045] The present invention has the following beneficial effects: (1) The present invention proposes an adaptive decentralized task scheduling mechanism, which enables each node to independently determine the execution right of the task based on factors such as computing resources, energy consumption status, and link quality. Task scheduling adopts a distributed competition strategy. When each task is initiated, it will be broadcast to multiple candidate nodes. These nodes compete by evaluating their own status, and the task is finally executed by the optimal node, rather than relying on a central server for unified allocation. This mechanism greatly improves the flexibility of task allocation, while avoiding the problem of single point failure, making the system more stable and scalable. (2) The present invention adopts a distributed data storage and synchronization mechanism to ensure data consistency and availability in the system. In the absence of a central server, data is split and stored on different computing nodes, and real-time data updates are achieved through a decentralized data synchronization protocol (such as the Gossip protocol). When a node fails or loses data, other nodes can restore the data through redundant storage or neighboring data queries, thereby ensuring the integrity and availability of key data in the entire network. This mechanism effectively reduces the risk of data loss and improves the system's anti-destruction capabilities.

[0046] Implementation method 1: Software system based on decentralized adaptive scheduling

[0047] This embodiment provides a software system based on a decentralized architecture, in which each computing node has independent data processing and task execution capabilities. It is suitable for scenarios such as drone clusters, robot collaboration, and emergency communications, ensuring that each node can still efficiently collaborate to complete tasks without a central server.

[0048] like Figure 1 As shown, the system mainly includes:

[0049] 1. Adaptive task allocation module (100): Using a distributed task bidding method, each node decides whether to compete for a task based on its own computing power, energy consumption and network status, and collaboratively decides on the optimal execution node.

[0050] 2. Data synchronization and consistency management module (200). Responsible for data sharing between nodes, ensuring information consistency during task execution, and using decentralized data storage protocols such as Gossip protocol or blockchain technology.

[0051] 3. Decentralized communication management module (300). Each node exchanges data through an ad hoc network, supports multi-hop communication, and dynamically adjusts the data transmission path based on channel quality assessment.

[0052] 4. Security and access control module (400), based on preset security mechanisms such as identity authentication, dynamic key management, end-to-end encryption, etc., to ensure the security of data transmission and access rights management.

[0053] When executing a task, the system first broadcasts the task request to the initiator. Neighboring nodes then independently assess the task's requirements and decide whether to compete for execution. Once the execution node is selected, the task can be dynamically migrated throughout the process based on network status and computing resources, ensuring efficient completion.

[0054] Implementation 2: Adaptive Task Scheduling and Optimization Strategy

[0055] like Figure 2 As shown, in order to improve the intelligence level of the system and the efficiency of task scheduling, the present invention adopts a set of adaptive task scheduling strategies, including:

[0056] 1. Task evaluation (510): After receiving a task request, each computing node evaluates the current available resources (such as CPU load, remaining power, link quality, etc.) and decides whether to compete for the task.

[0057] 2. Task bidding (520). If multiple nodes meet the task requirements, the best executor is selected through a distributed bidding algorithm (such as Vickrey auction) to avoid uneven task execution load or resource waste.

[0058] 3. Task execution (530). During the task execution process, the system will continuously monitor the status of the execution node. If it detects that the node load is too high or the link quality is degraded, it can dynamically migrate the task to other suitable nodes.

[0059] 4. Task Migration (540). If an execution node fails or disconnects from the network, the task will automatically be transferred to an alternative node to ensure uninterrupted tasks and improve system stability.

[0060] Implementation 3: Distributed Data Storage and Synchronization Mechanism

[0061] like Figure 3 As shown, the present invention adopts a decentralized data storage and synchronization mechanism to ensure data consistency between nodes and improve the system's anti-destruction capabilities.

[0062] 1. Data fragmentation storage (610). Task-related data will not be stored in a single node, but will be stored in a distributed manner, splitting the data into multiple fragments and storing them on multiple computing nodes.

[0063] 2. Redundant backup (620). To prevent data loss, each data fragment is stored in at least multiple different nodes to ensure that the data can be restored even if some nodes fail.

[0064] 3. Data synchronization (630). The system uses the Gossip protocol or DHT (distributed hash table) technology to enable each node to regularly exchange and update stored data to ensure data consistency.

[0065] 4. Abnormal recovery (640). When a node fails, the system can automatically detect the missing data and obtain data copies from other nodes for recovery to ensure stable system operation.

[0066] Implementation 4: Dynamic communication mechanism based on ad hoc networks

[0067] like Figure 4 As shown, the software system of the present invention utilizes ad hoc networking technology to implement a decentralized communication mechanism, ensuring that each computing node can be efficiently interconnected in a complex environment.

[0068] 1. Neighbor Discovery (710): Each computing node can automatically discover other nodes around it and establish dynamic topology connections, supporting multi-hop routing.

[0069] 2. Link evaluation (720): The system dynamically evaluates link quality based on parameters such as RSSI (received signal strength) and SNR (signal-to-noise ratio) and selects the optimal data transmission path.

[0070] 3. Dynamic routing adjustment (730): When a communication link is degraded or interfered, the system will automatically find a new routing path to ensure the stability of data transmission.

[0071] 4. Multi-mode communication (740). The system supports point-to-point (P2P) transmission, broadcast (Broadcast) and multicast (Multicast) modes, and can flexibly switch communication modes according to task requirements.

[0072] Implementation 5: Security and Tamper-Proofing Mechanism

[0073] like Figure 5 As shown, in order to prevent malicious attacks and data tampering, the present invention designs a decentralized security mechanism, including:

[0074] 1. Authentication (810). Each computing node holds a unique digital signature or device authentication information based on PUF (Physically Unclonable Function) to ensure the trustworthiness of the data source.

[0075] 2. Data encryption (820). When task data is transmitted between nodes, an end-to-end encryption mechanism, such as AES or ECC encryption algorithm, is used to prevent data from being stolen or tampered with.

[0076] 3. Access Control (830). The execution permissions of different tasks are managed by a distributed access control policy to prevent unauthorized nodes from accessing sensitive data.

[0077] 4. Anomaly Detection (840). The system has security monitoring capabilities that can detect abnormal communication behaviors, such as malicious data tampering and traffic attacks, and trigger defense mechanisms.

[0078] This invention combines a decentralized software architecture, distributed task scheduling, dynamic data synchronization, and ad hoc network communication technologies to achieve an efficient, stable, and secure intelligent collaborative system. Compared to traditional centralized systems, this invention can adapt to infrastructure-free environments, improving system robustness and task execution flexibility. It is particularly suitable for application scenarios such as drone swarms, collaborative robots, autonomous vehicle networks, and emergency communications.

Claims

1. A software system based on an adaptive decentralized architecture, characterized in that: The software system uses ad hoc networking as a means of communication and includes the following modules: (1) Adaptive task allocation module, which is used to dynamically adjust the task allocation strategy according to the computing power of each node, network status and task requirements to achieve decentralized task scheduling; (2) Data synchronization and consistency management module, which is used to ensure data consistency between nodes in a decentralized environment and synchronize data based on timestamps, priority rules or blockchain technology; (3) A decentralized communication management module, which is used to realize end-to-end information interaction between nodes without a central server, including multiple data types such as text, voice, and video; (4) Security and access control module, which is used to ensure the security of data transmission and access permission management based on preset security mechanisms such as identity authentication, dynamic key management, and end-to-end encryption.

2. The software system according to claim 1, characterized in that: The adaptive task allocation module is based on machine learning or a rule engine to optimize task scheduling and improve task processing efficiency.

3. The software system according to claim 1, wherein: The data synchronization and consistency management module adopts a distributed hash table (DHT) or a consensus algorithm to improve the stability of data distribution.

4. The software system according to claim 1, wherein: The decentralized communication management module supports multi-hop routing and can realize remote data transmission between nodes in an environment without a public network.

5. The software system according to claim 1, characterized in that: The security and access control module adopts a dynamic access strategy to adjust access rights according to environmental changes, thereby improving the adaptability and security of the system.

6. A communication method based on the software system according to claims 1 to 5, characterized in that: The following steps are involved: (1) In the pre-setting phase, each node loads the initial task rules, identity information, and encryption keys, and performs data synchronization; (2) During the operation phase, nodes dynamically adjust task allocation based on real-time network topology and computing power to achieve adaptive task scheduling; (3) During the communication process, data transmission adopts end-to-end encryption, and a multi-hop self-organizing network is used to ensure data accessibility in an off-network environment; (4) When a new node joins, identity authentication is performed based on the preset security mechanism, and the network topology and task allocation strategy are dynamically adjusted; (5) The data consistency management module regularly checks and synchronizes key mission data to ensure the information consistency of each node.

7. The method according to claim 6, characterized in that The communication method is applicable to various decentralized application scenarios such as emergency rescue, military communications, and industrial automation.

Images