Service Mode Management for Wireless Connectivity Reliability
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Solution Overview
Problem
Wireless communication systems face challenges in maintaining high reliability for Machine-to-Machine (M2M) communication, leading to potential failures in critical services like industrial control and smart grid applications, due to issues with connectivity and coverage, which can result in costly manual restoration or device replacement.
Innovation Solution
A method and node for managing service modes based on estimated connectivity levels, allowing the selection of appropriate operational modes to ensure reliable communication, switching to more secure modes when connectivity is low, and optimizing efficiency when connectivity is high.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the radio access network is over-dimensioned to provide high reliability for M2M devices, then connectivity reliability is improved, but network deployment cost and complexity increase
Solution Approach 1:
The patent implements dynamic mode switching that allows the service to adapt its operational characteristics based on real-time connectivity conditions. The service can transition between different operational modes (e.g., normal mode, degraded mode, safe mode) depending on connectivity reliability, eliminating the need for static over-dimensioning of the network infrastructure.
Solution Approach 2:
The patent changes operational parameters of the service based on connectivity conditions. By adjusting service parameters dynamically rather than maintaining fixed high-reliability parameters, the system achieves reliability adaptation without requiring permanent over-dimensioned network resources.
2Reliability
If more base stations and radio link resources are deployed to ensure high reliability, then connectivity availability is improved, but deployment cost increases
Solution Approach 1:
The service dynamically adjusts its operational mode based on real-time connectivity assessment. When connectivity is poor, the service switches to modes that are more tolerant of connectivity issues, thereby achieving reliable operation without requiring additional base stations or radio resources.
Solution Approach 2:
The service autonomously monitors connectivity conditions and self-adjusts its operational parameters without requiring manual intervention or additional network infrastructure. This self-adaptation capability allows the service to maintain reliability using existing network resources.
3Reliability
If manual restoration or device replacement is performed to compensate for communication failure, then service reliability is improved, but labor costs increase significantly
Solution Approach 1:
The service pre-configures multiple operational modes and establishes fallback procedures before connectivity failures occur. When failures happen, the service can immediately switch to pre-planned alternative modes, eliminating the need for manual restoration activities.
Solution Approach 2:
The service automatically detects connectivity failures and self-restores by switching to alternative operational modes without requiring manual intervention. This autonomous failure recovery dramatically reduces labor costs associated with manual restoration.
Data Source
AI summary
A first node (110) and a method therein for managing modes of operation of a service, referred to as “service modes” are disclosed. The service is executed in the first node (110). The service is capable of communicating with a second node (120) over a wireless network (100). The first node (110) receives an estimated level of a connectivity for the service from the wireless network (100). The estimated level of the connectivity relates to likelihood of maintaining the connectivity to the second node (120). The first node (110) selects one of the service modes based on the estimated level of the connectivity. Moreover, corresponding computer programs and computer program products are disclosed.