Abstract
Additive increase multiplicative decrease (AIMD) is the dominant algorithm for congestion avoidance and control in the Internet. The major goal of AIMD is to achieve fairness and efficiency in allocating resources. In the context of packet networks, AIMD attains its goal partially. We exploit here a property of AIMD-based data sources to share common knowledge, yet in a distributed manner; we use this as our departing point to achieve better efficiency and faster convergence to fairness. Our control model is based on the assumptions of the original AIMD algorithm; we show that both efficiency and fairness of AIMD can be improved. We call our approach AIMD with fast convergence (AIMD-FC). We present experimental results with TCP that match the expectations of our theoretical analysis.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
