CN-121985052-A - Multi-protocol switching method for mobile zero-carbon digital house mode management

CN121985052ACN 121985052 ACN121985052 ACN 121985052ACN-121985052-A

Abstract

The invention provides a multi-protocol switching method for mobile zero-carbon digital house mode management, which is characterized in that multi-dimensional feature vectors of subsystems such as energy, environment, convenience service and the like are collected and hashed fingerprint extraction is carried out, protocol adaptation strength modeling and dynamic preference patterns are established, trusted protocol configuration meeting the requirements of no deadlock, no resource competition and delay upper bound is generated by combining formal verification, and the trusted protocol configuration is compiled, deployed and containerized on an ARM architecture communication coprocessor, the link performance is monitored in real time in the operation period, the protocol adaptation preference is dynamically adjusted according to the service quality, and a closed-loop self-adaptive protocol management system is formed.

Inventors

LIN YUCHEN
Xie Bingshen
WU GUISEN
HUANG SHUIXING

Assignees

漳州寰球创新科技研发中心有限公司

Dates

Publication Date: 20260505
Application Date: 20260313

Claims (10)

1. A multi-protocol switching method for mobile zero-carbon digital house mode management is characterized by comprising the following steps: S1, non-invasive acquisition is carried out on key data interfaces of a multi-source heterogeneous subsystem, and a multi-dimensional semantic feature vector is obtained; S2, compressing the multi-dimensional semantic feature vector into a code with a fixed length to generate a subsystem semantic fingerprint code; S3, constructing a subsystem protocol preference map according to the subsystem semantic fingerprint code and the key performance index after the history protocol is switched; s4, based on the subsystem protocol preference map, decoupling protocol selection logic into a triplet structure to generate a meta-protocol instruction triplet set; S5, performing formal verification on the meta-protocol instruction triplet set to generate a trusted protocol configuration context; S6, converting the trusted protocol configuration context into executable byte codes, loading the executable byte codes into a communication coprocessor firmware area and generating edge executable protocol byte codes; s7, operating the edge executable protocol byte codes, isolating and loading a protocol state machine, an encryption context and a service quality parameter register in a containerized microkernel mode, and establishing a dynamic communication protocol link; and S8, monitoring the operation performance of the dynamic communication protocol link, returning to a default protocol if the service quality does not reach the standard, otherwise, updating the edge weight of the rolling window preference map in the recent rolling window in the subsystem protocol preference map.
2. The multi-protocol switching method for mobile zero-carbon digital house mode management according to claim 1, wherein the multi-source heterogeneous subsystem comprises an optical storage direct-drive energy subsystem, a multi-mode convenience service subsystem and a climate adaptive environment subsystem, and the multi-dimensional semantic feature vector comprises a service intention vector, an energy state transition mode, an environment response delay spectrum and a data timeliness attenuation law.
3. The method for multi-protocol switching of mobile zero-carbon digital house mode management according to claim 1, wherein the step S3 specifically comprises: carrying out hash index processing on the sub-system semantic fingerprint codes, establishing a unique mapping relation between the fingerprint codes and the sub-system identifiers, and obtaining a sub-system identifier set; Based on the subsystem identification set, extracting a historical protocol switching record from a rolling window log, calculating a key performance index, and obtaining a multi-dimensional performance evaluation vector; Performing weighted fusion operation on the multidimensional performance evaluation vector, converting the key performance index into a dimensionless protocol adaptation strength value, and obtaining an edge weight value; based on the subsystem identification set and the edge weight value, performing directed graph topology construction operation to generate a subsystem protocol preference map; and carrying out time attenuation verification on the subsystem protocol preference map, removing the weight data of the expiration edge, updating and outputting a final subsystem protocol preference map.
4. A multi-protocol switching method for mobile zero-carbon digital house mode management according to claim 3, wherein the key performance indicators comprise quality of service achievement rate, single switching energy consumption increment and service interruption duration.
5. A multi-protocol switching method for mobile zero-carbon digital house mode management according to claim 3, wherein subsystem identification is used as a node in the subsystem protocol preference map, and protocol adaptation strength value is used as a property of a connection edge.
6. The method for multi-protocol switching of mobile zero-carbon digital house mode management according to claim 1, wherein the step S4 specifically comprises: Analyzing the edge weight data and the node state information in the subsystem protocol preference map, extracting protocol path characteristics of high-adaptation-strength weights, and generating an initial decision context vector; Mapping and transforming the energy state transition mode and the threshold interval of the service intention vector based on the initial decision context vector to generate a multidimensional conditional predicate set; according to the triggering result of the multidimensional conditional predicate set, a predefined protocol primitive library is called to carry out instantiation configuration on a communication frame structure, a retransmission mechanism and encryption algorithm parameters, and an action atomic instruction sequence is generated; Aiming at the action atomic instruction sequence, the end-to-end delay upper limit, the memory occupation peak value and the energy consumption budget range of the system real-time resource constraint boundary are combined for carrying out quantization definition, and a hard constraint assertion rule set is generated; And carrying out structured packaging on the multidimensional conditional predicate set, the action atomic instruction sequence and the hard constraint assertion rule set to obtain a standardized meta-protocol instruction triplet set.
7. The method of claim 6, wherein the initial decision context vector comprises a matching of a current network environment situation to subsystem service requirements.
8. The method for multi-protocol switching of mobile zero-carbon digital house mode management according to claim 1, wherein the step S5 specifically comprises: resolving conditional predicates and action atoms in a meta-protocol instruction triplet set, extracting a mutual exclusion lock identifier, a message queue pointer and a timer register address related to a communication coprocessor firmware area, constructing a protocol state transition diagram based on finite state machine theory, and generating a formalized state space model; defining deadlock-free attribute assertion based on the formalized state space model, traversing all closed loop paths in a state transition diagram to detect whether waiting state circulation which cannot be exited exists, marking a corresponding action atom sequence if a potential deadlock loop is detected, and outputting a state subset containing a deadlock risk tag; analyzing access time sequences of the multiple concurrent protocol modules to the shared memory resources and the interrupt vectors for the state subsets and the original formalized state space model, identifying resource competition conflict points among different threads caused by uncertain preemption sequences, and generating a resource competition conflict matrix and a corresponding critical area constraint rule; Based on the resource competition conflict matrix and constraint assertion in the meta-protocol instruction triplex, calculating maximum clock period consumption of each action atom on an ARM architecture pipeline, combining a mathematical boundary of end-to-end delay of a transmission delay upper bound of a physical layer of a communication link, verifying whether an actual delay track is always within a delay upper bound range defined by the constraint assertion, and outputting a delay compliance verification report; And carrying out logic conjunctive operation on the delayed compliance verification report and the deadlock-free attribute assertion detection result, screening a meta-protocol instruction subset, packaging the meta-protocol instruction subset into a structured data block, and generating a final trusted protocol configuration context.
9. The method of claim 8, wherein the subset of meta-protocol instructions satisfies three hard constraints of deadlock free, resource free contention, and delay upper bound provability simultaneously.
10. The method for multi-protocol switching for mobile zero-carbon digital house mode management according to claim 1, wherein the step S7 further comprises: and performing memory layout repositioning processing on the generated edge executable protocol byte codes, dividing independent isolation sandbox spaces in a communication coprocessor firmware region by utilizing a containerized microkernel loader, respectively mapping a protocol state machine variable, an encryption context key and a service quality parameter register to a protected memory page, and generating a protocol runtime instance with resource access boundary control.

Description

Multi-protocol switching method for mobile zero-carbon digital house mode management Technical Field The invention relates to the technical field of edge intelligent communication and multi-protocol self-adaptive switching, in particular to a multi-protocol switching method for mobile zero-carbon digital house mode management. Background With the rapid development of scenes such as zero-carbon digital post, mobile convenience service and new energy micro-grid, the mobile edge intelligent communication system often needs to be connected with multiple types of subsystems simultaneously in the actual deployment process, and the heterogeneous subsystems respectively have different service characteristics and communication requirements, such as real-time requirements, bandwidth allocation, packet loss tolerance, energy consumption sensitivity and the like, so that the selection and switching of communication protocols become key technical points for influencing the system efficiency, reliability and service quality; The mainstream multi-protocol communication optimization method at present mostly adopts a general switching strategy, and usually, a protocol selection decision is made based on a preset rule base, a central chemistry model or a static protocol adaptation table. The general communication strategy tends to focus on the average response efficiency of the whole system, but is difficult to accurately sense and adapt to the differentiated communication characteristics of each heterogeneous subsystem, so that problems such as protocol switching delay, service interruption, energy consumption surge and the like occur in practical application, and the defects are more remarkable particularly in the scenes of off-network operation of a zero-carbon digital post, limited calculation force and high reliability requirements; Existing multi-protocol adaptive switching technologies generally include implementations based on AI model prediction, protocol feature library table lookup matching, dynamic protocol converters, and the like. Related technologies such as multi-layer protocol abstraction and policy networking methods utilize historical communication data and pre-trained models for protocol optimization and handoff control. There are also statistical learning algorithms such as wolf's search, bayesian consensus, DPPS algorithm, Q-learning, etc. to implement automatic protocol selection. The model driving or rule base methods have the following limitations that firstly, the method relies on a large amount of historical data and centralized training, is complex in deployment and high in calculation power consumption, is not suitable for mobile, off-grid and autonomous intelligent control scenes, secondly, the method is difficult to fine-tune a protocol strategy by utilizing semantic features generated by each subsystem in operation, and lacks effective fine-granularity personalized strategy generation capability, thirdly, the protocol switching process cannot realize high-speed instant assembly according to a specific state of the subsystem, so that response delay and service interruption risk are aggravated. The protocol adaptation of the public literature and the existing industry scheme to the heterogeneous subsystem is basically processed in an average optimal or fixed configuration mode, and intelligent generation of protocol strategies according to real-time states and dynamic compiling and deployment cannot be achieved. Disclosure of Invention The invention aims to solve the technical problems and provides a multi-protocol switching method for mobile zero-carbon digital house mode management. The technical scheme of the invention is realized in such a way that the multi-protocol switching method for the mode management of the mobile zero-carbon digital house comprises the following steps: S1, non-invasive acquisition is carried out on a digital base API gateway layer, an energy management bus register, an environment sensor time sequence buffer zone and a service call log stream of an optical storage direct drive energy subsystem, a multi-mode convenience service subsystem and a climate self-adaptive environment subsystem to obtain a multi-dimensional semantic feature vector comprising a service intention vector, an energy state transition mode, an environment response delay spectrum and a data timeliness attenuation law; S2, based on the multi-dimensional semantic feature vector, compressing four-dimensional features into a code with a fixed length by using a deterministic hash mapping algorithm, and generating a subsystem semantic fingerprint code for identifying a subsystem runtime state; S3, constructing a subsystem protocol preference map with nodes as subsystem identifiers and edges as protocol adaptation intensity weights according to the subsystem semantic fingerprint codes and by combining the service quality standard reaching rate, single switching energy consumption increment and service inte