Dynamic Network Service Allocation for Datacenter Bottlenecks
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Solution Overview
Problem
Existing network service deployment in datacenters is static and complex, leading to challenges such as hair-pinning traffic, choke points, and interdependencies among applications and tenants, making management inefficient and difficult to scale.
Innovation Solution
A system for dynamic network service allocation that maps generic services to specific resources based on application requirements and network conditions, using an orchestration engine to identify suitable resources and configure them dynamically.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If network services are deployed at fixed points in the datacenter topology, then service provisioning is simplified, but the system becomes complex and inefficient when demand increases due to hair-pinning traffic, choke points, and interdependencies
Solution Approach 1:
The patent implements dynamic service placement that automatically adjusts service locations based on real-time network conditions, workload demands, and topology changes. Instead of fixed service deployment points, the system continuously optimizes where services are instantiated, eliminating hair-pinning traffic and choke points while maintaining operational simplicity through automated orchestration.
Solution Approach 2:
The system employs self-service mechanisms where the network infrastructure automatically provisions and configures services without manual intervention. The orchestration engine monitors network conditions and autonomously determines optimal service placements, configuring resources and routing policies dynamically to prevent complexity while meeting changing demands.
2Ease of manufacture
If network services are statically provisioned to serve applications and tenants, then initial deployment is straightforward, but management becomes a mangled mess due to interdependencies across various apps and tenants
Solution Approach 1:
The patent implements feedback mechanisms where the orchestration engine continuously monitors network service performance, resource utilization, and inter-service dependencies. Based on this feedback, the system dynamically adjusts service placements and configurations to optimize performance and simplify management, automatically resolving interdependencies rather than accumulating complexity over time.
Solution Approach 2:
The system dynamically changes service placement parameters based on evolving network conditions, workload patterns, and tenant requirements. Instead of maintaining static service assignments, the orchestration engine continuously optimizes service locations and resource allocations, transforming the management approach from manual configuration to adaptive automated management.
3Device complexity
If network services are deployed in a static manner, then deployment configuration is simple, but scalability is limited and resource utilization is inefficient when demands vary
Solution Approach 1:
The patent implements dynamic service deployment that automatically scales service instances based on real-time demand metrics. The orchestration engine monitors workload patterns and resource utilization, dynamically provisioning additional service capacity when needed and deallocating resources when demand decreases, enabling the system to scale efficiently while maintaining configuration simplicity through automated orchestration.
Solution Approach 2:
The system employs universal service templates and orchestration mechanisms that can accommodate diverse service types and deployment scenarios. The same dynamic provisioning framework handles different service categories, tenant requirements, and workload patterns uniformly, enabling scalable deployment across varied conditions without increasing configuration complexity.
Data Source
AI summary
A novel method for dynamic network service allocation that maps generic services into specific configurations of service resources in a network is provided. An application that is assigned to be performed by computing resources in the network is associated with a set of generic services, and the method maps the set of generic services to the service resources based on the assignment of the application to the computing resources. The mapping of generic services is further based on a level of service that is chosen for the application, where the set of generic services are mapped to different sets of network resources according to different levels of services.