Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: In the oblivious buy-at-bulk network design problem in a graph, the task is to compute a fixed set of paths for every pair of source-destination in the graph, such that any set of demands can be routed along these paths. The demands could be aggregated at intermediate edges where the fusion-cost is specified by a canonical (non-negative concave) function f.  give a novel algorithm for planar graphs which is oblivious with respect to the demands, and is also oblivious with respect to the fusion function f. The algorithm is deterministic and computes the fixed set of paths in polynomial time, and guarantees a O(log n) approximation ratio for any set of demands and any canonical fusion function f, where n is the number of nodes. The algorithm is asymptotically optimal, since it is known that this problem cannot be approximated with better than Ω(log n) ratio. To our knowledge, this is the first tight analysis for planar graphs, and improves the approximation ratio by a factor of log n with respect to previously known results.
['Srivathsan Srinivasagopalan', 'Costas Busch', 'S. Sitharama Iyengar']
I am writing a research paper on a idea Oblivious buy-at-bulk in planar graphs
[{"from": "human", "value": "I am writing a research paper on a idea Oblivious buy-at-bulk in planar graphs"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: In the oblivious buy-at-bulk network design problem in a graph, the task is to compute a fixed set of paths for every pair of source-destination in the graph, such that any set of demands can be routed along these paths. The demands could be aggregated at intermediate edges where the fusion-cost is specified by a canonical (non-negative concave) function f.  give a novel algorithm for planar graphs which is oblivious with respect to the demands, and is also oblivious with respect to the fusion function f. The algorithm is deterministic and computes the fixed set of paths in polynomial time, and guarantees a O(log n) approximation ratio for any set of demands and any canonical fusion function f, where n is the number of nodes. The algorithm is asymptotically optimal, since it is known that this problem cannot be approximated with better than \u03a9(log n) ratio. To our knowledge, this is the first tight analysis for planar graphs, and improves the approximation ratio by a factor of log n with respect to previously known results."}]