Convex Optimization for Distributed Network Bandwidth Allocation
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Solution Overview
Problem
Existing network management systems struggle to optimize bandwidth allocation in distributed systems with frequent and large uploads from multiple endpoints to a central server, especially when endpoints are scattered across a wide area network, as they lack centralized control and efficient bandwidth management strategies.
Innovation Solution
A computer-implemented method that determines a logical network topology based on measurements, solves a convex optimization problem to allocate bandwidth, and controls consumption by throttling endpoints, using techniques like reverse breadth-first search to achieve max-min fairness and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If each endpoint independently determines whether to throttle its own uploading, then endpoints can autonomously manage their bandwidth, but overall bandwidth usage is suboptimal and congestion is not effectively managed
Solution Approach 1:
The patent implements a feedback mechanism where the central server receives congestion information from endpoints and sends back bandwidth allocation decisions. The server monitors network conditions and dynamically adjusts bandwidth allocation for each endpoint based on real-time feedback about network congestion and endpoint needs, resolving the contradiction between autonomous operation and optimal utilization.
Solution Approach 2:
The central server acts as an intermediary between endpoints and the network infrastructure. It receives requests from endpoints, makes centralized bandwidth allocation decisions based on global network state, and controls bandwidth consumption by regulating data flows, thereby optimizing overall bandwidth utilization while maintaining endpoint autonomy.
2Productivity
If multiple endpoints upload data simultaneously to a central server over a WAN, then data transfer speed increases, but network congestion occurs and bandwidth management becomes complex
Solution Approach 1:
The system uses feedback loops where the central server continuously monitors network congestion levels and adjusts bandwidth allocation dynamically. When congestion is detected, the server reduces bandwidth allocation for affected endpoints; when network conditions improve, allocation is increased. This feedback mechanism enables high-speed simultaneous uploads while automatically preventing congestion.
Solution Approach 2:
The bandwidth allocation scheme is dynamic rather than static. The central server continuously adapts bandwidth allocation based on changing network conditions, endpoint priorities, and data transfer requirements. This dynamic adjustment allows the system to maintain high productivity during varying load conditions while simplifying management through automated adaptation.
3Productivity
If centralized bandwidth management is implemented, then overall bandwidth utilization is optimized, but system complexity increases
Solution Approach 1:
The central server serves as an intermediary that centralizes bandwidth management intelligence while keeping endpoint devices simple. All complex optimization logic resides in the server, which makes allocation decisions based on global network state. Endpoints simply request bandwidth and receive allocation decisions, maintaining low endpoint complexity while achieving high overall utilization through centralized intelligence.
Data Source
AI summary
Techniques are disclosed herein for managing network bandwidth in a distributed system having multiple endpoints that upload data to a central server or server cluster. One embodiment provides a computer-implemented method that includes receiving a logical topology of the network that is determined based on network measurements. The method further includes resolving a convex optimization problem over the logical topology to determine a bandwidth allocation scheme for the endpoints uploading data. In addition, the method includes controlling bandwidth consumption by the endpoints based on the determined bandwidth allocation scheme.