Dedicated Channels as an Optimal Network Support for Effective Transfer of Massive Data

Gorinsky, Sergey; Rao, Nageswara S. V.

doi:10.1109/infocom.2006.20

Cited by 21 publications

(23 citation statements)

References 20 publications

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“…Ganguly et al generalize the problems of finding an optimal path in a graph with varying bandwidth to minimize the total transfer time in [12]. In [13], Gorinsky et al propose a Virtual Finish Time First algorithm to schedule incoming files in a preemptive manner to minimize total TET on a given dedicated channel. Most of the aforementioned work is primarily focused on instant scheduling of bandwidths provisioned by dedicated networks.…”

Section: B Related Workmentioning

confidence: 99%

Path Computation with Variable Bandwidth for Bulk Data Transfer in High-Performance Networks

Lin

2009

IEEE INFOCOM Workshops 2009

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Abstract-There are an increasing number of highperformance networks that provision dedicated channels through circuit-switching or MPLS/GMPLS techniques to support bulk data transfer in large-scale science or ecommerce applications. These dedicated links are typically shared by multiple users through advance reservations, resulting in varying bandwidth availability in future time periods. Therefore, efficient advance bandwidth reservation algorithms are needed to improve the utilization of network resources and meet the transport requirements of application users. We investigate the bandwidth-oriented path computation problem for two types of data transfer: (i) fixed path with variable bandwidth and (ii) variable path with variable bandwidth to minimize the transfer end time of a given data size. We prove that both problems are NP-complete and propose a heuristic algorithm for each of them. Extensive simulation results illustrate the performance superiority of the proposed heuristics over methods based on greedy strategies.

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Section: B Related Workmentioning

confidence: 99%

Path Computation with Variable Bandwidth for Bulk Data Transfer in High-Performance Networks

Lin

2009

IEEE INFOCOM Workshops 2009

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“…For example, to complete more tasks before their deadlines, sharing instantaneous bandwidth fairly among all active flows may not be optimal [5]. In some cases, it is beneficial to allow a connection with larger pending volume and earlier deadline to grab more bandwidth, similar to the case of Earliest Deadline First scheduling in real-time systems [6].…”

Section: A Motivationsmentioning

confidence: 99%

Scheduling deadline-constrained bulk data transfers to minimize network congestion

Chen

Primet

2007

Seventh IEEE International Symposium on Cluster Computing and the Grid (CCGrid '07)

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Tight coordination of resource allocation among end points in Grid networks often requires a data mover service to transfer a voluminous dataset from one site to another in a specified time interval. With flexibility at its best, the transfer can start from any time after its arrival, use any and even time variant bandwidth value, as long as it is completed before its deadline. Given a set of such tasks, we study the Bulk Data Transfer Scheduling (BDTS) problem, which searches for the optimal bandwidth allocation profile for each task to minimize the overall network congestion. We show that the multi-interval scheduling, which divides the active window of a task into multiple intervals and assigns bandwidth value independently in each of them, is both sufficient and necessary to attain the optimality in BDTS. Specifically, we show that BDTS can be solved in polynomial time as a Maximum Concurrent Flow Problem. The optimal solution attained is in the form of multi-interval scheduling with the number of intervals upper-bounded. Simulations are conducted over several representative topologies to demonstrate the significant advantage of optimal solutions.

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“…The same authors have proposed algorithms for computing the quickest paths, with a minimum end-toend delay, to transfer a message of a given size from its source to a destination when bandwidth and delay constraints on the links are specified [21]. The Virtual Finish (ViFi) [14] heuristic schedules file transfer over a shared path, depending on the earliest finish time for each file determined from a fair sharing scheme. A VaryingBandwidth List Scheduling (VBLS) heuristic to compute varying bandwidth levels for different time ranges for a circuit over a lambda grid was studied in [25].…”

Section: Introductionmentioning

confidence: 99%

Algorithms for Integrated Routing and Scheduling for Aggregating Data from Distributed Resources on a Lambda Grid

Banerjee

Feng

Ghosal

et al. 2008

IEEE Trans. Parallel Distrib. Syst.

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Abstract-In many e-science applications, there exists an important need to aggregate information from data repositories distributed around the world. In an effort to better link these resources in a unified manner, many lambda-grid networks, which provide end-to-end dedicated optical-circuit-switched connections, have been investigated. In this context, we consider the problem of aggregating files from distributed databases at a (grid) computing node over a lambda grid. The challenge is 1) to identify routes (that is, circuits) in the lambda-grid network, along which files should be transmitted, and 2) to schedule the transfers of these files over their respective circuits. To address this challenge, we propose a hybrid approach that combines offline and online scheduling. We define the TimePath Scheduling Problem (TPSP) for offline scheduling. We prove that TPSP is NP-complete, develop a Mixed Integer Linear Program (MILP) formulation for TPSP, and then propose a greedy approach to solve TPSP because the MILP does not scale well. We compare the performance of the greedy approach on a few representative lambda-grid network topologies. One key input to the offline schedule is the file transfer time. Due to dynamics at the receiving end host, which is hard to model precisely, the actual file transfer time may vary. We first propose a model for estimating the file transfer time. Then, we propose online reconfiguration algorithms so that as files are transferred, the offline schedule may be modified online, depending on the amount of time that it actually took to transfer the file. This helps in reducing the total time to transfer all the files, which is an important metric. To demonstrate the effectiveness of our approach, we present results on an emulated lambda-grid network testbed.

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Dedicated Channels as an Optimal Network Support for Effective Transfer of Massive Data

Cited by 21 publications

References 20 publications

Path Computation with Variable Bandwidth for Bulk Data Transfer in High-Performance Networks

Path Computation with Variable Bandwidth for Bulk Data Transfer in High-Performance Networks

Scheduling deadline-constrained bulk data transfers to minimize network congestion

Algorithms for Integrated Routing and Scheduling for Aggregating Data from Distributed Resources on a Lambda Grid

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