Recent proposals in multicast overlay construction have demonstrated the importance of exploiting underlying network topology. However, these topology-aware proposals often rely on incremental and periodic refinements to improve the system performance. These approaches are therefore neither scalable, as they induce high communication cost due to refinement overhead, nor efficient because long convergence time is necessary to obtain a stabilized structure. In this paper, we propose a highly scalable locating algorithm that gradually directs newcomers to their a set of their closest nodes without inducing high overhead. On the basis of this locating process, we build a robust and scalable topology-aware clustered hierarchical overlay scheme, called LCC. We conducted both simulations and PlanetLab experiments to evaluate the performance of LCC. Results show that the locating process entails modest resources in terms of time and bandwidth. Moreover, LCC demonstrates promising performance to support large scale multicast applications.
Other tree-first'' protocols like ZigZag @cite_17 and NICE @cite_8 , are topology-aware clustering-based protocols which are designed to support wide-area size multicast for low bandwidth application. However, they do not consider individual node fan-out capability. Rather, they bound the overlay fan-out using a (global) cluster-size parameter. In particular, since both protocols only consider latency for cluster leader selection, they may experience problems if the cluster leader has insufficient fan-out. Other proposals exploit the AS-level @cite_1 or the router-level @cite_2 underlying network topology information to build efficient overlay networks. However, these approaches assume some assistance from the IP layer (routers sending ICMP messages, or BGP information access), which may be problematic. LCC does not require any extra assistance from entities that do not belong to the overlay.
@cite_2 @cite_8 @cite_1 @cite_17
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Given that the Internet does not widely support Internet protocol multicast while content-distribution-network technologies are costly, the concept of peer-to-peer could be a promising start for enabling large-scale streaming systems. In our so-called Zigzag approach, we propose a method for clustering peers into a hierarchy called the administrative organization for easy management, and a method for building the multicast tree atop this hierarchy for efficient content transmission. In Zigzag, the multicast tree has a height logarithmic with the number of clients, and a node degree bounded by a constant. This helps reduce the number of processing hops on the delivery path to a client while avoiding network bottlenecks. Consequently, the end-to-end delay is kept small. Although one could build a tree satisfying such properties easily, an efficient control protocol between the nodes must be in place to maintain the tree under the effects of network dynamics. Zigzag handles such situations gracefully, requiring a constant amortized worst-case control overhead. Especially, failure recovery is done regionally with impact on, at most, a constant number of existing clients and with mostly no burden on the server. Structured peer-to-peer overlay networks such as CAN, Chord, Pastry, and Tapestry can be used to implement Internet-scale application-level multicast. There are two general approaches to accomplishing this: tree building and flooding. This paper evaluates these two approaches using two different types of structured overlay: 1) overlays which use a form of generalized hypercube routing, e.g., Chord, Pastry and Tapestry, and 2) overlays which use a numerical distance metric to route through a Cartesian hyperspace, e.g., CAN. Pastry and CAN are chosen as the representatives of each type of overlay. To the best of our knowledge, this paper reports the first head-to-head comparison of CAN-style versus Pastry-style overlay networks, using multicast communication workloads running on an identical simulation infrastructure. The two approaches to multicast are independent of overlay network choice, and we provide a comparison of flooding versus tree-based multicast on both overlays. Results show that the tree-based approach consistently outperforms the flooding approach. Finally, for tree-based multicast, we show that Pastry provides better performance than CAN. As the size of High Performance Computing clusters grows, so does the probability of interconnect hot spots that degrade the latency and effective bandwidth the network provides. This paper presents a solution to this scalability problem for real life constant bisectional-bandwidth fat-tree topologies. It is shown that maximal bandwidth and cut-through latency can be achieved for MPI global collective traffic. To form such a congestion-free configuration, MPI programs should utilize collective communication, MPI-node-order should be topology aware, and the packet routing should match the MPI communication patterns. First, we show that MPI collectives can be classified into unidirectional and bidirectional shifts. Using this property, we propose a scheme for congestion-free routing of the global collectives in fully and partially populated fat trees running a single job. The no-contention result is then obtained for multiple jobs running on the same fat-tree by applying some job size and placement restrictions. Simulation results of the proposed routing, MPI-node-order and communication patterns show no contention which provides a 40 throughput improvement over previously published results for all-to-all collectives. Aggregate traffic loads and topology in multihop wireless networks may vary slowly, permitting MAC protocols to "learn" how to spatially coordinate and adapt contention patterns. Such an approach could reduce contention, leading to better throughput. To that end, we propose a family of MAC scheduling algorithms and demonstrate general conditions, which, if satisfied, ensure lattice rate optimality (i.e., achieving any rate-point on a uniform discrete lattice within the throughput region). This general framework enables the design of MAC protocols that meet various objectives and conditions. In this paper, as instances of such a lattice-rate-optimal family, we propose distributed, synchronous contention-based scheduling algorithms that: 1) are lattice-rate-optimal under both the signal-to-interference-plus-noise ratio (SINR)-based and graph-based interference models; 2) do not require node location information; and 3) only require three-stage RTS CTS message exchanges for contention signaling. Thus, the protocols are amenable to simple implementation and may be robust to network dynamics such as topology and load changes. Finally, we propose a heuristic, which also belongs to the proposed lattice-rate-optimal family of protocols and achieves faster convergence, leading to a better transient throughput.