AI Summary & Key Takeaways
AI InsightOurresults show an eflicient way to balance the efirects ofthe metrics in the context of many-to-many routing.
📌 3 Key Takeaways
Abstract
Diflerent metrics are usedfor measuring the goodness ofpacket routing between the source and destinationpairs in communication network. One approach is to compute the paths from the measured metric values, which arepredetermined independently according to the network resources. The combination ofsome metrics of different naturesto get composite cost function for the routing process is non-trivial. We consider two metrics, namely delay andpacket loss rate. The first one takes values from the large numbers and the secondfrom the small. We propose somemethods for constructing composite functions of these metrics without any constraints and use them for the shortestpath calculations. We give the numerical results of the proposed composite functions versus the Dijkstra ’s algorithmwith the individual metrics. We spot out the bestfunction according to our computer simulation results. Our compositefunction works for any arbitrary point-to—point networks. To the best of our knowledge, the technique is novel. Ourresults show an eflicient way to balance the efirects ofthe metrics in the context of many-to-many routing.