Description
A* search algorithm is a path finding algorithm that finds the single-pair shortest path between the start node(source) and the target node(destination) of a weighted graph. The algorithm not only considers the actual cost from the start node to the current node(g) but also tries to estimate the cost will take from the current node to the target node using heuristics (h). Then it selects the node that has the lowest f-value(f=g+h) to be the next node to move until it hits the target node. Dijkstra’s algorithm is a special case of A* algorithm where heuristic is 0 for all nodes.
Key Features
- Heuristic-Driven Efficiency: Uses informed estimates to guide the search, significantly reducing the number of nodes explored compared to uninformed algorithms.
- Optimal and Complete: Guarantees finding the shortest path if the heuristic is admissible (never overestimates the true cost).
- Dynamic Adaptability: Easily recalculates routes in response to network topology changes or varying traffic loads, ideal for real-time cloud environments.
- Flexible Heuristic Design: Allows customization of heuristic functions to suit specific metrics like latency, bandwidth, or cost in cloud infrastructure.
Use Case
A* algorithm is particularly well-suited for routing and resource allocation in cloud platforms such as OpenStack and GCP. It ensures:
- Fast and efficient VM placement by quickly finding the shortest path between compute nodes and user endpoints.
- Optimized network routing that reduces latency and bandwidth consumption in large, dynamic cloud topologies.
- Real-time adaptation to changing network conditions, supporting dynamic workloads and multi-tenant environments.
Implementation
Below is the implimentation of A* algorithm.
A* Implementation in JavaReferences
- Medium: https://yuminlee2.medium.com/a-search-algorithm-42c1a13fcf9f#5ca4
- Wikipedia: https://en.wikipedia.org/wiki/A*_search_algorithm
- Visulization: https://see-algorithms.com/graph/TopSort
- Youtube: https://www.youtube.com/watch?v=g024lzsknDo