Container-Based Elastic Scaling for Carrier-Grade Telecom
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Solution Overview
Problem
Carrier-grade telecommunications systems face challenges in elastic scaling due to stringent service availability and geographical redundancy requirements, which are difficult to achieve with traditional hardware-based solutions, leading to overprovisioning and lengthy deployment cycles.
Innovation Solution
A container technology-based platform that uses a layered approach for service orchestration and automates virtual machine and container manifestation, enabling elastic scalability, fault tolerance, and agile deployment on cloud infrastructure, decoupling infrastructure and service deployment considerations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional hardware-based components are used with fixed service packages, then service availability and geographical redundancy can be supported, but system scalability and deployment speed are significantly reduced
Solution Approach 1:
The patent segments telecommunication services into independent virtualized service components that can be deployed as separate container instances. Each service function is virtualized and can be instantiated independently, allowing rapid deployment while maintaining reliability through modular architecture. This enables services to be broken down into manageable units that can be scaled and deployed autonomously.
Solution Approach 2:
The system dynamically changes operational parameters by adjusting the number of container instances based on service demand. Virtualized service components can be rapidly instantiated or terminated by modifying instance count parameters, enabling elastic scaling without hardware changes. This allows the system to adapt capacity quickly while maintaining service availability through automated orchestration.
2Reliability
If hardware components are overprovisioned to accommodate unexpected growth, then service continuity is maintained, but hardware cost and resource utilization efficiency deteriorate
Solution Approach 1:
The patent implements dynamic resource allocation where virtualized service components can be rapidly instantiated on available hardware resources. The system dynamically adjusts service capacity by creating or terminating container instances based on actual demand, eliminating the need for static overprovisioning. This dynamic approach maintains service continuity while optimizing hardware utilization through automated scaling.
Solution Approach 2:
The system creates virtual copies of service components as container instances that can be rapidly deployed on existing hardware. Instead of provisioning additional physical hardware for capacity expansion, the system creates software-based copies of service functions that run on shared infrastructure, reducing hardware resource requirements while maintaining service continuity.
3Ease of manufacture
If multiple service components are packaged together on specific hardware, then hardware cost is optimized, but system adaptability and testing complexity increase
Solution Approach 1:
The patent extracts service components from fixed hardware packages and virtualizes them into independent container instances. Each service function is separated and can be independently deployed, tested, and managed. This extraction allows services to be taken out of rigid hardware configurations and placed into flexible virtualized environments, enhancing adaptability while maintaining cost efficiency through shared infrastructure.
Solution Approach 2:
The system creates universal virtualized service components that can run on any compatible hardware platform through standard container orchestration. The same service package can be deployed across different hardware configurations and cloud environments, providing multi-functionality and platform independence. This universality enhances service adaptability while optimizing hardware utilization through consolidation.
4Reliability
If new service development follows traditional telecommunication deployment cycles, then service reliability is ensured, but development time and time-to-market increase
Solution Approach 1:
The patent implements preliminary action through automated service templates and pre-configured container images that encapsulate service logic and dependencies. Services are prepared in advance as reusable artifacts that can be rapidly instantiated through automated orchestration. This preliminary packaging of service components enables quick deployment while maintaining reliability through consistent, pre-tested service configurations.
Solution Approach 2:
The system enables self-service deployment through automated service orchestration that handles service instantiation, configuration, and management without manual intervention. Service components are self-contained with embedded configuration and can be automatically deployed, scaled, and managed by the orchestration system. This self-service capability accelerates deployment cycles while maintaining reliability through automated consistency enforcement.
Data Source
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AI summary
An embodiment method includes triggering, by a service orchestrator, creation of one or more container instances for a first service cluster. The method further includes creating, by a container manager, the one or more container instances and mapping the one or more container instances of the first service cluster to one or more first virtual machines belonging to a first virtual machine server group in accordance with a platform profile of the first virtual machine server group and the first service provided by the first service cluster. The method further includes mapping, by a virtual machine manager, the one or more first virtual machines to one or more first host virtual machines of a cloud network in accordance with the platform profile of the first virtual machine server group.