Journal of Communications Software and Systems (Sep 2005)
A Model-based Scalable Reliable Multicast Transport Protocol for Satellite Networks
Abstract
In this paper, we design a new scalable reliable multicast transport protocol for satellite networks (RMT). This paper is the extensions of paper in [18]. The proposed protocoldoes not require inspection and/or interception of packets at intermediate nodes. The protocol would not require anymodification of satellites, which could be bent-pipe satellites or onboard processing satellites. The proposed protocol is divided in 2 parts: error control part and congestion control part. In error control part, we intend to solve feedback implosion and improve scalability by using a new hybrid of ARQ (Auto Repeat Request) and adaptive forward error correction (AFEC). The AFEC algorithm adapts proactive redundancy levels following the number of receivers and average packet loss rate. This leads to a number of transmissions and the number of feedback signals are virtually independent of the number of receivers. Therefore, wireless link utilization used by the proposed protocol is virtually independent of the number of multicast receivers. In congestion control part, the proposed protocol employs a new window-based congestion control scheme, which is optimized for satellite networks. To be fair to the other traffics, the congestion control mimics congestion control in the wellknown Transmission Control Protocol (TCP) which relies on “packet conservation” principle. To reduce feedback implosion, only a few receivers, ACKers, are selected to report the receiving status. In addition, in order to avoid “drop-to-zero” problem, we use a new simple wireless loss filter algorithm. This loss filter algorithm significantly reduces the probability of the congestion window size to be unnecessarily reduced because of common wireless losses. Furthermore, to improve achievable throughput, we employ slow start threshold adaptation based on estimated bandwidth. The congestion control also deals with variations in network conditions by dynamically electing ACKers.