Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  describes an algorithm that achieves an approximately optimal assignment of forward error correction to progressive data within the unequal loss protection framework. It first finds the optimal assignment under convex hull and fractional bit allocation assumptions. It then relaxes those constraints to find an assignment that approximates the global optimum. The algorithm has a running time of O(hNlogN) where h is the number of points on the convex hull of the source's utility-cost curve and N is the number of packets transmitted.
['Alexander E. Mohr', 'Richard E. Ladner', 'Eve A. Riskin']
I am writing a research paper on a idea Approximately optimal assignment for unequal loss protection
[{"from": "human", "value": "I am writing a research paper on a idea Approximately optimal assignment for unequal loss protection"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  describes an algorithm that achieves an approximately optimal assignment of forward error correction to progressive data within the unequal loss protection framework. It first finds the optimal assignment under convex hull and fractional bit allocation assumptions. It then relaxes those constraints to find an assignment that approximates the global optimum. The algorithm has a running time of O(hNlogN) where h is the number of points on the convex hull of the source's utility-cost curve and N is the number of packets transmitted."}]