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Controlling the rate of bulk data multicast to a large number of receivers is difficult due to the heterogeneity among the end-systems' capabilities and their available network bandwidth. If the data transfer rate is too high, some receivers will lose data, and retransmissions will be required. If the data transfer rate is too low, an inordinate amount of time will be required to transfer the data. In this paper, we examine an approach towards rate-controlled multicast of bulk data in which the sender uses multiple multicast groups to transmit data at different rates to different sub-groups of receivers. We present simple algorithms for determining the transmission rate associated with each multicast channel, based on static resource constraints, e.g., network bandwidth bottlenecks. Transmission rates are chosen so as to minimize the average time needed to transfer data to all receivers. Analysis and simulation are used to show that our policies for rate selection perform well for large and diverse receiver groups and make efficient use of network bandwidth. Moreover, we find that only a small number of multicast groups are needed to reap most of the possible performance benefits.

Efficient rate-controlled bulk data transfer using multiple multicast groups

This paper explores three different methods, employed separately and in combination, to improve the quality of video delivery on wireless local area networks. The approaches are: leader-driven multicast (LDM), monitoring MAC layer unicast (re)transmissions by other receivers; application-level forward error correction (FEC) using block erasure codes; negative feedback from selected receivers in the form of extra parity requests (EPR). The performance of these three methods is evaluated using both experiments on a mobile computing testbed and simulation. The results indicate that, while LDM is helpful in improving the raw packet reception rate, the combination of FEC and EPR is most effective in improving the frame delivery rate.

/pdf/comparisons-of-error-control-techniques-for-wireless-video-3xjuq8c53p.pdf

Comparisons of error control techniques for wireless video multicasting

One of the most commonly identified features which is felt to be necessary for LinuxTM to be considered "enterprise-ready" is High-Availability. High-Availability (HA) systems provide increased service availability through clustering techniques.

HA clusters minimize availability interruptions by quickly switching services over from failed systems to working systems, providing the customer with an illusion of continuous availability. As such, high-availability features, are vital to mission-critical systems. Although there are many components to a high-availability system, two of the key components are heartbeat services and cluster communication services. Heartbeat services provide notification of when nodes are working, and when they fail. In the Linux-HA project, the heartbeat program provides these services and intracluster communication services.

This paper describes the design of the heartbeat program which is part of the High-Availability Linux Project with particular emphasis on the rationales behind key design choices, and the results obtained.

Linux-HA heartbeat system design

Controlling the rate of bulk data multicast to a large number of receivers is difficult, due to the heterogeneity among the end systems' capabilities and their available network bandwidth. If the data transfer rate is too high, some receivers will lose data, and retransmissions will be required. If the data transfer rate is too slow, an inordinate amount of time will be required to transfer the data. In this paper, we examine an approach toward rate-controlled multicast of bulk data in which the sender uses multiple multicast groups to transmit data at different rates to different subgroups of receivers. We present simple algorithms for determining the transmission rate associated with each multicast channel, based on static resource constraints, e.g., network bandwidth bottlenecks. Transmission rates are chosen so as to minimize the average time needed to transfer data to all receivers. Analysis and simulation are used to show that our policies for rate selection perform well for large and diverse receiver groups and make efficient use of network bandwidth. Moreover, we find that only a small number of multicast groups are needed to reap most of the possible performance benefits.

Efficient rate-controlled bulk data transfer using multiple multicast Groups

Analyses a multiround flow control algorithm that attempts to minimize the time required to multicast a message to a group of recipients and receive responses directly from each group member. Such a flow control algorithm may be necessary because the hurry of responses to the multicast can overflow the buffer space of the process that issued the multicast. The condition that each recipient directly respond to the multicast prevents the use of reliable multicast protocols based on software combining trees or negative-acknowledgments. The flow control analysed algorithm directs the responding processes to hold their responses for some period of time, called the backoff time, before sending them to the originator. The backoff time depends on the number of recipients that respond, the originator's available buffer space and buffer service time distribution, and the number of times that the originator is willing to retransmit its message. This paper develops an approximate analysis of the service time distribution of the limited-buffer preemptive queuing process that occurs within the protocol processing layers of a multiprogrammed operating system. It then uses this model to calculate multicast backoff times. The paper reports experimental verification of the accuracy of this service time model and discusses its application to the multicast flow control problem. >

Flow control for limited buffer multicast

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Flow control for limited buffer multicast