Internet traffic load balancing using dynamic hashing with flow volume

Sending IP packets over multiple parallel links is in extensive use in today's Internet and its use is growing due to its scalability, reliability and cost-effectiveness. To maximize the efficiency of parallel links, load balancing is necessary among the links, but it may cause the problem of packet reordering. Since packet reordering impairs TCP performance, it is important to reduce the amount of reordering. Hashing offers a simple solution to keep the packet order by sending a flow over a unique link, but static hashing does not guarantee an even distribution of the traffic amount among the links, which could lead to packet loss under heavy load. Dynamic hashing offers some degree of load balancing but suffers from load fluctuations and excessive packet reordering. To overcome these shortcomings, we have enhanced the dynamic hashing algorithm to utilize the flow volume information in order to reassign only the appropriate flows. This new method, called dynamic hashing with flow volume (DHFV), eliminates unnecessary flow reassignments of small flows and achieves load balancing very quickly without load fluctuation by accurately predicting the amount of transferred load between the links. In this paper we provide the general framework of DHFV and address the challenges in implementing DHFV. We then introduce two algorithms of DHFV with different flow selection strategies and show their performances through simulation.