The invention discloses a mMulti-QoS constraint-based task scheduling ant colony optimization algorithm for a wide area information management system
A technology of wide-area information management and ant colony optimization algorithm, which is applied in the field of civil aviation special information system network, and can solve the problems of considering the execution time span of tasks to be executed.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Publication Date
- 2019-04-12
- Estimated Expiration
- Not applicable · inactive patent
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Abstract
Description
technical field
[0001] The invention relates to a civil aviation special information system network technology, especially for the task scheduling of the wide-area information management system, which can better meet the multi-QoS requirements of users and improve the system operation performance. Background technique
[0002] The basic idea of the Wide Area Information Management System (System Wide Information Management, SWIM) is to maximize the sharing of the latest information by all participants in air traffic management through SWIM, integrate distributed and heterogeneous information resources, and realize dynamic, multi- Coordinate resource sharing in the virtual organization of the management mechanism to ensure that the relevant information of air traffic control departments, airlines, aviation airports and other relevant civil aviation units can be shared and exchanged in an effective and timely manner, so that timely and accurate collaborative decision-making c...
Examples
Embodiment Construction
[0027] A preferred embodiment of a method for evaluating the survivability of a BP neural network-based wide-area information management system according to the present invention will be described in detail below in conjunction with the accompanying drawings.
[0028] Figure 1 to Figure 2 Specific implementation methods of the present invention are shown: SWIM survivability PDRRDR model, BP neural network-based SWIM survivability evaluation model and SWIM survivability evaluation index system.
[0029] The present invention comprises the following steps:
[0030] 1. SWIM task scheduling model
[0031] SWIM task scheduling focuses on the following three QoS constraints:
[0032] (1) Time: The acceptable execution time limit for each task.
[0033] (2) Security: The security level available on SWIM nodes.
[0034] (3) Reliability: The probability that the task can be successfully executed.
[0035] SWIM is mainly composed of three parts, namely:
[0036] (1) SWIM shared d...