Receiver-driven Bandwidth Adaptation for Light-Weight sessions

1. Receiver-driven Bandwidth Adaptation for Light-Weight sessions Elan Amir; Steven McCanne and Randy Katz Presented By: Monu Mathur

2. Basic Concepts: • What is Multicasting? • -A single source can send data to multiple receivers at the same time. • -Sender can send packets to a multicast group address. • What is Multicast Backbone or MBone? • -A virtual network embedded in the unicast internet that • implements IP multicasting. • What is the Light-weight Sessions Architecture? • -MBone tools multicast packets to the multicast group address. Receivers “tune-in”. • -Loosely coupled, real-time model.

3. Issues Discussed: • All sources are not of equal interest to the receivers. • Current methods allocate bandwidth in a fixed and • inflexible manner. • Users have to configure, enable and disable their • transmissions manually. • Proposal: • Media sources should adapt their transmission rates • to meet collective preference of receivers. • Accommodate and avoid network congestion by • controlling the traffic injected into the network across • all senders. • Augment existing adaptation schemes with receiver • feedback.

4. A number of schemes address the problem of adjusting the media • delivery rate at each source. However the issue of receiver feedback, that describes the receiver feedback throughout the session has not been addressed. • SCUBA • Scalable ConsensUs -based Bandwidth Allocation • New protocol that deals with trying to solve the issues discussed above. • A scalable, light-weight feedback protocol. • Reflects receiver interest back to the media services. • Employs receiver consensus to allocate session bandwidth • among resources. • Has 2 variants: • “Flat Delivery”:Receiver feedback constraints the rate chosen by sender- based adaptation algorithm.

5. “Layered delivery”: Feedback is used to control the mapping of • the source signal layers to the network channels. • Advantage of Receiver based multicast: • The burden of adaptation is moved from the source • to the receiver. • Enhanced scalability of the system. • Working of the protocol • Problem addressed • by SCUBA: • Static bandwidth • allocation-Sources • send at a fixed rate • and bandwidth is divided equally

6. The solution of the problem is given by SCUBA: Dynamic Bandwidth Allocation: Sources adjust their transmission rate dynamically and do the bandwidth allocation accordingly. Problem: How can we determine a single bandwidth partition that simultaneously satisfies all receivers? Solution: Participants reach “consensus” through voting and the bandwidth partition is done accordingly. SCUBA uses the “exit poll” principle: Source bandwidth partition is derived from a small unbiased sample of receiver population.

7. Feedback Algorithm: • Each receiver associates a weight with every active source. • The weights define the relative priority of each source with respect • to a given receiver. • Receivers periodically advertise a source-weight report containing • sources and their corresponding weights with respect to that receiver. • Scaling mechanism is employed by announce/listen control protocols • including SRM and SAP. • Each receiver announces its source weight report by multicasting it. • Each source listens for the reports and combines them into an • aggregate metric called average source weight.

8. Translation of average source weight to • sender’s rate control decision: • Case 1: Flat Delivery • Flat delivery adjustment decision maps the transmission weight • directly to the source transmission bandwidth. • The mechanism is arbitrary and can be customized depending • on the application or environment. • Allocation is done in such a way that each active source multicasts • it’s signal continuously even though at a very low rate.

9. Case 2: Layered Delivery • Overcomes the limitation of sending the date at the rate of the • slowest link. • Each source generates a layered media stream striped across • multiple network channels. • Distinguishes more important • sources from less important • ones. • Given a source weight, • the source determines it’s • signal layer mapping. The • source then transmits each • of it’s signal layers defined • by the mapping.

10. Scalability Issues • SCUBA makes decisions at each source on behalf of all receivers • in the network: Hence prone to scaling problems. • Sacrifices absolute consistency in favor of scalability through the • use of sampling. • The two factors that affect the scalability of SCUBA are: • - Control message size: Limit the number of sources for which • each receiver reports to a small constant. • - Expected source weight convergence time: Change in • receiver interest is not reflected back to the receiver • immediately. This latency is called average source weight • convergence time (ASCT).

11. Solution to the problem is provided by keeping the time taken by • the receivers to reach the consensus (ASCT) small. • The time-scale of fluctuations in receiver interest is determined by • the users. Hence the average source weights must be computed • on the time scale of seconds. • To avoid the linear time growth of ASCT, sampling is used. • The convergence time of the algorithm is decoupled from the • session size allowing scaling to large sessions.

12. Applications • SCUBA can support: • Video Conferencing • Media Gateway Control • Floor Control • Future work: • An alternative approach to Samplingin orderto enhance the scalability of the announce/listen receiver interest protocol.