SDN ADC Cluster Hash Table Traffic Distribution
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional ADC clustering techniques are not optimized for cloud-computing environments, failing to provide efficient elasticity and scalability due to limitations such as uniform capacity constraints, complex configuration changes, and physical co-location requirements, leading to poor adaptability and performance issues.
Innovation Solution
A method for managing an ADC cluster in a software-defined networking (SDN)-based environment, using a central controller to create a hash table for traffic distribution among multiple virtual appliances (VAs) based on client IP addresses, dynamically adding or removing VAs, and reconfiguring the cluster to balance load and ensure high availability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If ADC devices are clustered using conventional techniques, then traffic distribution capability is improved, but adaptability to varying demand is worsened due to uniform capacity constraints
Solution Approach 1:
The patent segments the ADC cluster into multiple zones with different capacity levels (high-capacity ADCs and low-capacity ADCs). Each zone can be independently configured and scaled, allowing the system to adapt to varying demand patterns without requiring uniform capacity across all devices. This segmentation enables flexible resource allocation where high-capacity ADCs handle peak loads while low-capacity ADCs serve baseline traffic.
Solution Approach 2:
The patent implements dynamic capacity assignment where ADC devices can be added or removed from the cluster without reconfiguring the entire system. The hash table structure allows dynamic insertion and deletion of entries, enabling the cluster to adapt its capacity in real-time based on demand fluctuations. This dynamic approach eliminates the rigidity of conventional clustering where any capacity change requires complete system reconfiguration.
2Adaptability or versatility
If ADC devices are added or removed from the cluster, then scalability is improved, but configuration complexity increases due to persistence correction requirements
Solution Approach 1:
The patent performs preliminary actions by pre-configuring the hash table structure to accommodate future ADC additions or removals. The hash table is designed with sufficient buckets to handle the maximum expected number of ADCs, and the distribution algorithm is pre-established. This allows ADC devices to be added or removed without requiring complex persistence correction procedures, as the system is already prepared to handle such changes.
Solution Approach 2:
The patent uses a hash table copying mechanism where the entire hash table can be efficiently copied and redistributed among ADCs when devices are added or removed. Instead of complex individual persistence corrections, the system creates a new hash table configuration that automatically accounts for the changed cluster composition, simplifying the scalability process.
3Speed
If physical co-location is required for ADC devices, then network performance is improved, but deployment flexibility is worsened
Solution Approach 1:
The patent creates a universal hash table-based traffic distribution mechanism that works effectively regardless of the physical location of ADC devices. The hash function distributes traffic based on logical identifiers rather than physical positions, allowing ADCs to be deployed in geographically distributed data centers while maintaining optimal network performance. This universal approach eliminates the need for physical co-location constraints.
4Device complexity
If uniform capacity is enforced across all ADC devices, then system simplicity is improved, but resource utilization efficiency is worsened
Solution Approach 1:
The patent applies local quality by allowing different ADC devices to have different capacity characteristics (high-capacity vs. low-capacity) while maintaining overall system coherence through the hash table distribution mechanism. Each ADC can be optimized for its specific capacity level, and the hash table ensures fair and efficient traffic distribution tailored to each device's capabilities. This eliminates the waste of forcing uniform capacity constraints on heterogeneous hardware.
Data Source
AI summary
A method for managing an application delivery controller (ADC) cluster operable in a software defined networking (SDN)-based network and including a plurality of ADC virtual appliances (VAs). The method comprises creating, by a central controller, a hash table including a plurality of buckets allocated to active VAs out of the plurality of VAs, each bucket is assigned to a range of a source internet protocol (IP) addresses of a client; and programming by the central controller at least one ingress network element connected to the ADC cluster and receive incoming traffic from clients to perform a balanced incoming traffic distribution among the plurality of VAs, wherein the traffic distribution is based in part on the allocation of the buckets to the plurality of VAs and the SIP addresses of the clients originating the incoming traffic. The plurality of VAs are virtual ADC instances operable i the plurality of physical devices.