Cache-Based Remote Data Retrieval for Isolated Application Iterations
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Solution Overview
Problem
Existing solutions for executing client application software on remote servers are network resource intensive and time-consuming due to the need to reproduce entire application environments, and they fail to efficiently manage multiple instances of client software applications, leading to network latency and interference issues.
Innovation Solution
A method and system for executing remote application iterations on a server by dynamically retrieving data objects from a computing device using a cache device or cache server, with distinct data retrieval processes for data objects and metadata, optimizing data access and reducing network overhead.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If entire application environment is reproduced at remote server, then data consistency is ensured, but network resource consumption and time increase significantly
Solution Approach 1:
The patent extracts only the necessary data objects required by the remote application iteration from the local application environment, rather than reproducing the entire environment. This selective extraction is achieved through dynamic data object retrieval mechanisms that identify and transfer only essential data, significantly reducing network bandwidth consumption while maintaining data consistency for the specific application instance being executed remotely.
Solution Approach 2:
The application environment is segmented into multiple discrete data objects that can be independently identified, selected, and transferred. The system divides the monolithic application environment into manageable units (data objects) that can be selectively retrieved based on actual application needs, enabling efficient network resource utilization while ensuring required data consistency.
2Reliability
If entire application environment is reproduced at remote server, then data consistency is ensured, but provisioning time increases significantly
Solution Approach 1:
The system performs preliminary identification and categorization of data objects before remote execution is needed. Metadata about data objects is pre-established, allowing the remote server to quickly determine which data objects are required and retrieve them efficiently during provisioning, rather than waiting to identify necessary data during the actual execution phase.
Solution Approach 2:
By extracting only the minimal set of data objects required for a specific remote application iteration, the system dramatically reduces provisioning time. The extraction process is guided by application requirements and data dependency analysis, ensuring that only essential data is transferred while maintaining consistency for the targeted application instance.
3Adaptability or versatility
If multiple remote iterations are executed, then system versatility improves, but network latency and resource interference increase
Solution Approach 1:
Each remote application iteration is associated with its own isolated application environment instance containing specific data objects. This segmentation allows multiple iterations to be executed simultaneously without network interference, as each iteration retrieves only its required data objects independently. The system manages resource allocation and network bandwidth for each iteration separately, reducing overall latency.
Solution Approach 2:
The system introduces an intermediary data retrieval mechanism that mediates between the remote applications and the local data storage. This intermediary layer manages data object identification, selection, and transfer for multiple concurrent iterations, optimizing network resource allocation and minimizing latency through coordinated data retrieval operations.
4Loss of energy
If dynamic data object retrieval is implemented, then network resource consumption decreases, but data retrieval speed may be reduced
Solution Approach 1:
The system performs preliminary analysis of application requirements and data object dependencies before initiating retrieval operations. By pre-identifying which data objects are essential and their inter-dependencies, the system can optimize retrieval sequences and parallelize operations, maintaining high retrieval speeds while consuming fewer network resources through selective data transfer.
Solution Approach 2:
The data retrieval process is dynamically adjusted based on real-time conditions including network bandwidth, data object sizes, and application requirements. The system adapts retrieval strategies dynamically, using parallel transfers, priority-based data object selection, and adaptive buffering to maintain optimal retrieval speeds while minimizing network resource consumption across multiple concurrent iterations.
Data Source
AI summary
The invention provides systems, methods and computer program products for executing remote application iteration(s) of client application software on a remote server platform, and for enabling each remote application iteration of a client application software to have access to a corresponding instance of an application software environment that has access to all data objects necessary for execution of such remote application iteration. The invention enables execution of a remote application iteration of a client software application at a remote server platform, through need-based or dynamic retrieval of data objects from an on-premise device for appropriately provisioning the remote server platform to execute the remote iteration of the client software application. The invention additionally relates to optimizing dynamic retrieval of data objects from a computing device/on-premise device through cache device(s) or cache server(s).