Several organizations have built multiple datacenters connected via dedicated wide area networks over which large inter-datacenter transfers take place. This includes tremendous volumes of bulk multicast traffic generated as a result of data and content replication. Although one can perform these transfers using a single multicast forwarding tree, that can lead to poor performance as the slowest receiver on each tree dictates the completion time for all receivers. Using multiple trees per transfer each connected to a subset of receivers alleviates this concern. The choice of multicast trees also determines the total bandwidth usage. To further improve the performance, bandwidth over dedicated inter-datacenter networks can be carved for different multicast trees over specific time periods to avoid congestion and minimize the average receiver completion times. In this paper, we break this problem into the three sub-problems of partitioning, tree selection, and rate allocation. We present an algorithm called QuickCast which is computationally fast and allows us to significantly speed up multiple receivers per bulk multicast transfer with control over extra bandwidth consumption. We evaluate QuickCast against a variety of synthetic and real traffic patterns as well as real WAN topologies. Compared to performing bulk multicast transfers as separate unicast transfers, QuickCast achieves up to @math reduction in mean completion times while at the same time using @math the bandwidth. Also, QuickCast allows the top @math of receivers to complete between @math to @math faster on average compared with when a single forwarding multicast tree is used for data delivery.
A large body of general multicasting approaches have been proposed where receivers can join multicast groups anytime to receive required data and multicast trees are incrementally built and pruned as nodes join or leave a multicast session such as IP multicasting @cite_44 , TCP-SMO @cite_58 and NORM @cite_19 . These solutions focus on building and maintaining multicast trees, and do not consider link capacity and other ongoing multicast flows while building the trees.
@cite_44 @cite_19 @cite_58
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Scalable reliable multicast protocols have been the focus of recent research, tackling the problem of efficient reliable data delivery to an arbitrarily large number of receivers. Yet, the common applications of multicast, such as multi-point file delivery, or video streaming from a media server, typically only involve a moderate number of receivers, such as a thousand or fewer. Moreover, because of the limited deployment of these specialized multicast protocols, it is common, when feasible, for applications to use multiple TCP connections instead, one for each receiver, to implement multi-point delivery, causing a significant demand on the transmission server and the downstream links. We describe a multicast extension to TCP, called single-source multicast optimization (SMO), that optimizes this case of multipoint delivery, providing the benefits of multicast together with the familiar features and API of TCP. Our results from experiments based on a Linux implementation and performed on a testbed show that TCP-SMO requires just a modest extension to the TCP implementation and provides scalable performance of multicast up to over a thousand receivers, thereby satisfying the common case requirements. In addition, used with TCP-RTM (real-time mode), TCP-SMO also supports real-time multimedia multicast applications well. Continuously enriched distributed systems in data centers generate much network traffic in push-style one-to-many group mode, raising new requirements for multicast transport in terms of efficiency and robustness. Existing reliable multicast solutions, which suffer from low robustness and inefficiency in either host-side protocols or multicast routing, are not suitable for data centers. In order to address the problems of inefficiency and low robustness, we present a sender-initiated, efficient, congestion-aware and robust reliable multicast solution mainly for small groups in SDN-based data centers, called MCTCP. The main idea behind MCTCP is to manage the multicast groups in a centralized manner, and reactively schedule multicast flows to active and low-utilized links, by extending TCP as the host-side protocol and managing multicast groups in the SDN-controller. The multicast spanning trees are calculated and adjusted according to the network status to perform a better allocation of resources. Our experiments show that, MCTCP can dynamically bypass the congested and failing links, achieving high efficiency and robustness. As a result, MCTCP outperforms the state-of-the-art reliable multicast schemes. Moreover, MCTCP improves the performance of data replication in HDFS compared with the original and TCP-SMO based ones, e.g., achieves 101 and 50 improvements in terms of bandwidth, respectively. We describe a new scalable application-layer multicast protocol, specifically designed for low-bandwidth, data streaming applications with large receiver sets. Our scheme is based upon a hierarchical clustering of the application-layer multicast peers and can support a number of different data delivery trees with desirable properties.We present extensive simulations of both our protocol and the Narada application-layer multicast protocol over Internet-like topologies. Our results show that for groups of size 32 or more, our protocol has lower link stress (by about 25 ), improved or similar end-to-end latencies and similar failure recovery properties. More importantly, it is able to achieve these results by using orders of magnitude lower control traffic.Finally, we present results from our wide-area testbed in which we experimented with 32-100 member groups distributed over 8 different sites. In our experiments, average group members established and maintained low-latency paths and incurred a maximum packet loss rate of less than 1 as members randomly joined and left the multicast group. The average control overhead during our experiments was less than 1 Kbps for groups of size 100. In this paper, we investigate the problem of Multicast Routing in Sparse Splitting Networks (MR-SSN). Given a network topology with the multicast capable nodes distributed uniformly throughout the network, and a multicast session, the MR-SSN problem is to find a route from the source node of the multicast session to all destinations of the multicast session such that the total number of fibers used in establishing the session is minimized. In this paper, we develop a rerouting algorithm for a given Steiner tree, which makes it feasible to route a multicast session using a tree-based solution in sparse light splitting optical networks. In addition, we present a heuristic based on Tabu Search (TS) that requires only one transmitter for the source node and one wavelength for each multicast session. To evaluate the performance of heuristics, we formulate the MR-SSP problem as an integer linear program (ILP), and optimally solve small instances using the commercially available linear solver, CPLEX. We test our heuristic on a wide range of network topologies. Our experimental results show that: (1) The difference between our solution and ILP optimal solution, in terms of the number of fibers used for establishing a multicast session, is within 10 in almost all the instances and within 5 in about half of the instances. (2) The average delay, taken over all destination nodes, falls within three times the optimal value. (3) A sparse light splitting all-optical network with 30 of multicast capable cross-connects has an acceptable low cost and relatively good performance. (4) The improvement achieved by TS heuristic increases considerably when the session size is large, the number of Splitter-and-Delivery cross-connects is small, and the network connectivity is dense.