Broadcasting on Large Scale Heterogeneous Platforms under the Bounded Multi-Port Model (original) (raw)

Optimizing the steady-state throughput of Broadcasts on heterogeneous platforms

2003

In this paper, we consider the communications involved by the execution of a complex application, deployed on a heterogeneous "grid" platform. Such applications extensively use macrocommunication schemes, for example to broadcast data items. Rather than aiming at minimizing the execution time of a single broadcast, we focus on the steady-state operation. We assume that there is a large number of messages to be broadcast in pipeline fashion, and we aim at maximizing the throughput, i.e. the (rational) number of messages which can be broadcast every time-step. We target heterogeneous platforms, modeled by a graph where resources have different communication and computation speeds. Achieving the best throughput may well require that the target platform is used in totality: we show that neither spanning trees nor DAGs are as powerful as general graphs.

Scalable and efficient broadcasting algorithms for very large internetworks

Computer Communications, 1998

Broadcast is a special case of routing in which a packet is to be delivered to a set that includes all the network nodes. While dynamic and distributed broadcast techniques have been proposed and used in the Internet, unfortunately they suffer from scalability problems, i.e. they are not efficient with respect to the tremendous size of today's networks. Moreover, it has been observed that the cost of routing and the broadcast time are two conflicting performance measures as far as optimization is concerned, especially in large networks. Also, many of the current techniques are not robust enough and give low performance under events of link failure. First, we show that in order to achieve universal reachability, intemets have naturally acquired a multi-level hierarchical structure. Second, utilizing this existing hierarchy, we propose scalable broadcasting protocols which achieve near-optimal cost and time measures. Because of the hierarchy, our proposed algorithm only maintains information of links connected to direct neighbors, thereby making it scalable to future growth in size of the network. We show that time-optimal broadcast in point-to-point networks can be achieved by formulating the problem as finding maximum marching in bipartite graphs. Several heuris&s based on matchings are presented. Performance bounds are derived along with numerical and simulation results obtained that prove the validity and feasibility of the scheme. 0 1998 Elsevier Science B.V.

Optimal distributed P2P streaming under node degree bounds

Network Protocols (ICNP), 2010 …, 2010

We study the problem of maximizing the broadcast rate in peer-to-peer (P2P) systems under node degree bounds, i.e., the number of neighbors a node can simultaneously connect to is upper-bounded. The problem is critical for supporting highquality video streaming in P2P systems, and is challenging due to its combinatorial nature. In this paper, we address this problem by providing the first distributed solution that achieves nearoptimal broadcast rate under arbitrary node degree bounds, and over arbitrary overlay graph. It runs on individual nodes and utilizes only the measurement from their one-hop neighbors, making the solution easy to implement and adaptable to peer churn and network dynamics. Our solution consists of two distributed algorithms proposed in this paper that can be of independent interests: a network-coding based broadcasting algorithm that optimizes the broadcast rate given a topology, and a Markov-chain guided topology hopping algorithm that optimizes the topology. Our distributed broadcasting algorithm achieves the optimal broadcast rate over arbitrary P2P topology, while previously proposed distributed algorithms obtain optimality only for P2P complete graphs. We prove the optimality of our solution and its convergence to a neighborhood around the optimal equilibrium under noisy measurements or without timescale separation assumptions. We demonstrate the effectiveness of our solution in simulations using uplink bandwidth statistics of Internet hosts. • We propose a distributed broadcasting algorithm that achieves the optimal broadcast rate over arbitrary overlay graph. Previous distributed P2P broadcasting algorithms

Broadcasting multiple messages in the 1-in port model in optimal time

Journal of Combinatorial Optimization, 2018

In the 1-in port model, every vertex of a synchronous network can receive at most one message in each time unit. We consider simultaneous broadcasting of multiple messages from the same source or from distinct sources in such networks with an additional restriction that every received message can be sent out to neighbors only in the next time unit and never to already informed vertex. We use a general concept of level-disjoint partitions developed for this scenario. Here we introduce a subgraph extension technique for efficient spreading information within this concept. Surprisingly, this approach with so called biwheels leads to simultaneous broadcasting of optimal number of messages on a wide class of graphs in optimal time. In particular, we provide tight results for bipartite tori, meshes, hypercubes, Knödel graphs, circulant graphs. We also propose several open problems and conjectures.

Multiple message broadcasting in communication networks

Networks, 1995

Broadcasting refers to the process of dissemination of a set of messages originating from one node to all other nodes in a communication network. We assume that, at any given time, a node can transmit a message along at most one incident link and simultaneously receive a message along at most one incident link. We first present an algorithm for determining the amount of time needed to broadcast k messages in an arbitrary tree. Second, we show that, for every n, There exists a graph with n nodes whose k-message broadcast time matches the trivial lower bound ⌈ log n⌉ + k − 1 by designing a broadcast scheme for complete graphs. We call those graphs minimal broadcast graphs. Finally, we construct an n node minimal broadcast graph with fewer than (⌈log n⌉ + 1)2⌈ log n⌉ −1 edges.

Dynamic broadcasting in parallel computing

IEEE Transactions on Parallel and Distributed Systems, 1995

We consider the problem where broadcast requests are generated at random time instants at each node of a multiprocessor network. In particular, in our model packets arrive at each node of a network according to a Poisson process, and each packet has to be broadcast to all the other nodes. We propose an on-line decentralized routing scheme to execute the broadcasts in this dynamic environment. A related, although static, communication task is the partial multinode broadcast task, where M < N arbitrary nodes of an N-processor network broadcast a packet to all the other nodes. The results that we obtain for the dynamic broadcasting scheme apply to any topology, regular or not, for which partial multinode broadcast algorithms with certain properties can be found. For the dynamic scheme we find an upper bound on the average delay required to serve a broadcast request, and we evaluate its stability region. As an application we give a near-optimal partial multinode broadcast algorithm for the hypercube network. The stability region of the corresponding hypercube dynamic scheme tends to the maximum possible as the number of nodes of the hypercube tends to infinity. Furthermore, for any fixed load in the stability region, the average delay is of the order of the diameter of the hypercube.

Throughput-Optimal Multi-hop Broadcast Algorithms

In this paper we design throughput-optimal dynamic broadcast algorithms for multi-hop networks with arbitrary topolo-gies. Most of the previous broadcast algorithms route packets along spanning trees, rooted at the source node. For large dynamic networks, computing and maintaining a set of spanning trees is not efficient, as the network-topology may change frequently. In this paper we design a class of dynamic algorithms which makes packet-by-packet scheduling and routing decisions and thus obviates the need for maintaining any global topological structures, such as spanning trees. Our algorithms may be conveniently understood as a non-trivial generalization of the familiar back-pressure algorithm which makes unicast packet routing and scheduling decisions, based on queue-length information, without maintaining end-to-end paths. However, in the broadcast problem, it is hard to define queuing structures due to absence of a work-conservation principle which results from packet duplications. We design and prove the optimality of a virtual-queue based algorithm, where a virtual-queue is defined for subsets of vertices. We then propose a multi-class broadcast policy which combines the above scheduling algorithm with a class-based in-order packet delivery constraint, resulting in significant reduction in complexity. Finally, we evaluate performance of the proposed algorithms via extensive numerical simulations.

Complexity Results for Collective Communications on Heterogeneous Platforms

International Journal of High Performance Computing Applications, 2006

In this paper, we consider the communications involved in the execution of a complex application, deployed on a heterogeneous platform. Such applications extensively use macro-communication schemes, for example to broadcast data items, either to all resources (broadcast) or to a restricted set of targets (multicast). Rather than aiming at minimizing the execution time of a single collective communication, we focus on the steady-state operation. We assume that there is a large number of messages to be broadcast or multicast in pipelined fashion, and we aim at maximizing the throughput, i.e. the (rational) number of messages which can be broadcast or multicast every timestep. We target heterogeneous platforms, modeled by a graph where resources have different communication and computation speeds. Achieving the best throughput may well require that the target platform is used in totality: different messages may need to be transferred along different paths.

Complexity results and heuristics for pipelined multicast operations on heterogeneous platforms

International Conference on Parallel Processing, 2004. ICPP 2004., 2004

In this paper, we consider the communications involved by the execution of a complex application deployed on a heterogeneous platform. Such applications extensively use macro-communication schemes, for example to broadcast data items to several targets, known as the multicast operation. Rather than seeking to minimize the execution time of a single multicast, we focus on steady-state performance. We target heterogeneous platforms, modeled by a graph where resources have different communication speeds. We show that the problem of computing the best throughput for a multicast operation is NP-hard, whereas the best throughput to broadcast a message to every node in a graph can be computed in polynomial time. Thus we introduce several heuristics to deal with this problem; most of them are based on linear programming. We prove that some of these heuristics are approximation algorithms. We perform simulations to test these heuristics and show that their results are close to a theoretical upper bound on the throughput that we obtain with the linear programming approach.

Distributed Network Formation for n-Way Broadcast Applications

2010

In an n-way broadcast application, each one of n overlay nodes wants to push its own distinct large data file to all other n À 1 destinations as well as download their respective data files. BitTorrent-like swarming protocols are ideal choices for handling such massive data volume transfers. The original BitTorrent targets one-to-many broadcasts of a single file to a very large number of receivers, and thus, by necessity, employs a suboptimized overlay topology. n-way broadcast applications, on the other hand, owing to their inherent complexity, are realizable only in small to medium scale networks. In this paper, we show that we can leverage this scale constraint to construct optimized overlay topologies that take into consideration the end-to-end characteristics of the network and as a consequence deliver far superior performance compared to random and myopic (greedy) approaches. We present the Max-Min and Max-Sum peer-selection policies used by individual nodes to select their neighbors. The first one strives to maximize the available bandwidth to the slowest destination, while the second maximizes the aggregate output rate. We design a swarming protocol suitable for n-way broadcast and operate it on top of overlay graphs formed by nodes that employ Max-Min or Max-Sum policies. Using measurements from a PlanetLab prototype implementation and trace-driven simulations, we demonstrate that the performance of swarming protocols on top of our constructed topologies is far superior to the performance of random and myopic overlays.