Dynamic Application Redistribution Between Vehicle and Cloud
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Solution Overview
Problem
The transfer of data between vehicles and cloud-based computing systems is constrained by bandwidth limitations, which can slow down service processing and hinder the effectiveness of cloud-based computing due to insufficient connectivity and varying communication conditions.
Innovation Solution
A system and method that dynamically determine whether to execute applications locally or remotely based on current connectivity availability, switching between local and remote processing to optimize service handling by transferring execution of applications according to connectivity conditions, ensuring efficient use of both local and remote resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Power
If cloud-based computing services are used to provide powerful computing engines, then computing power and processing speed are improved, but bandwidth limitations and data transfer constraints slow down service processing
Solution Approach 1:
The system dynamically switches between cloud-based and local execution modes based on real-time connectivity conditions. When connectivity is good, computationally intensive tasks are offloaded to the cloud; when connectivity degrades, tasks are executed locally to maintain responsiveness. This dynamic adaptation resolves the contradiction by making the computing power source flexible rather than fixed.
Solution Approach 2:
The system implements hybrid execution where different application components or tasks can be executed in different locations (cloud or local device) based on their specific requirements and current connectivity conditions. This allows critical time-sensitive operations to run locally while less time-critical heavy computations utilize cloud resources.
2Adaptability or versatility
If data is transferred between vehicle and cloud for processing, then access to powerful remote computing resources is enabled, but bandwidth limitations constrain service speed and volume
Solution Approach 1:
The system dynamically adjusts the balance between local and remote execution based on real-time bandwidth conditions. When bandwidth is sufficient, more tasks are offloaded to the cloud; when bandwidth is constrained, the system increases local execution to maintain productivity. This resolves the contradiction by making resource allocation adaptive to changing transfer conditions.
Solution Approach 2:
The system performs preliminary assessment of connectivity conditions before initiating data transfer or cloud execution. This allows proactive decision-making about whether to proceed with cloud-based processing or switch to local execution, preventing wasted transfer attempts and maintaining productivity.
3Use of energy by moving object
If applications are executed remotely on cloud servers, then local processing resources are freed, but insufficient connectivity prevents reliable remote execution
Solution Approach 1:
The system implements location-aware execution where the execution location (cloud or local) is selected based on current connectivity quality. Critical applications or time-sensitive tasks are executed locally to ensure reliability, while non-critical tasks can be offloaded to the cloud when connectivity permits. This resolves the contradiction by matching execution location to reliability requirements.
Solution Approach 2:
The system continuously monitors connectivity conditions and uses this feedback to dynamically adjust execution location. When connectivity degrades below a threshold, the system automatically switches from remote to local execution to maintain reliability. This feedback loop ensures that reliability requirements are met while still utilizing cloud resources when available.
Data Source
AI summary
A system includes a processor configured to detect an application initiation request. The processor is further configured to determine whether current vehicle connectivity availability is sufficient to support remote execution of the application. Also, the processor is configured to launch a local version of the application, responsive to determining that current vehicle connectivity is insufficient to support remote execution. The processor is further configured to request that a remote server launch an instance of the application, once current vehicle connectivity is sufficient to support remote execution.