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We consider routing in reconfigurable networks, which is also known as coflow scheduling in the literature. The algorithmic literature generally (perhaps implicitly) assumes that the amount of data to be transferred is large. Thus the…

Data Structures and Algorithms · Computer Science 2026-03-17 Alexander Lindermayr , Kirk Pruhs , Andréa W. Richa , Tegan Wilson

This paper establishes performance guarantees for online algorithms that schedule stochastic, nonpreemptive jobs on unrelated machines to minimize the expected total weighted completion time. Prior work on unrelated machine scheduling with…

Data Structures and Algorithms · Computer Science 2020-05-14 Varun Gupta , Benjamin Moseley , Marc Uetz , Qiaomin Xie

Collective communication (CC) is critical for scaling distributed machine learning (DML). The predictable traffic patterns of DML present a great opportunity for applying optical network technologies. Optical networks with reconfigurable…

Networking and Internet Architecture · Computer Science 2026-05-01 Changbo Wu , Zhuolong Yu , Gongming Zhao , Hongli Xu

An intensive use of reconfigurable hardware is expected in future embedded systems. This means that the system has to decide which tasks are more suitable for hardware execution. In order to make an efficient use of the FPGA it is…

Hardware Architecture · Computer Science 2013-01-16 Marcos Sanchez-Elez , Sara Roman

Modern manufacturing systems must meet hard delivery deadlines while coping with stochastic task durations caused by process noise, equipment variability, and human intervention. Traditional deterministic schedules break down when reality…

Artificial Intelligence · Computer Science 2025-10-21 Ioan Hedea

We study dynamic network flows with uncertain input data under a robust optimization perspective. In the dynamic maximum flow problem, the goal is to maximize the flow reaching the sink within a given time horizon $T$, while flow requires a…

Discrete Mathematics · Computer Science 2018-05-07 Corinna Gottschalk , Arie M. C. A. Koster , Frauke Liers , Britta Peis , Daniel Schmand , Andreas Wierz

Control of multihop Wireless networks in a distributed manner while providing end-to-end delay requirements for different flows, is a challenging problem. Using the notions of Draining Time and Discrete Review from the theory of fluid…

Networking and Internet Architecture · Computer Science 2017-04-20 Ashok Krishnan K. S. , Vinod Sharma

We analyze the problem of scheduling in wireless networks to meet end-to-end service guarantees. Using network slicing to decouple the queueing dynamics between flows, we show that the network's ability to meet hard throughput and deadline…

Networking and Internet Architecture · Computer Science 2024-09-17 Nicholas Jones , Eytan Modiano

Scheduling is an important task allowing parallel systems to perform efficiently and reliably. For modern computation systems, divisible load is a special type of data which can be divided into arbitrary sizes and independently processed in…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-02-07 Fei Wu , Yang Cao , Thomas Robertazzi

Recently, low-complexity and distributed Carrier Sense Multiple Access (CSMA)-based scheduling algorithms have attracted extensive interest due to their throughput-optimal characteristics in general network topologies. However, these…

Networking and Internet Architecture · Computer Science 2014-05-06 Bin Li , Atilla Eryilmaz

The emergence of bandwidth-intensive latency-critical traffic in 5G Networks, such as Virtual Reality, has motivated interest in wireless resource allocation problems for flows with hard-deadlines. Attempting to solve this problem brings…

Networking and Internet Architecture · Computer Science 2020-02-18 Sherif ElAzzouni , Eylem Ekici , Ness Shroff

We propose a new approach to competitive analysis in online scheduling by introducing the novel concept of competitive-ratio approximation schemes. Such a scheme algorithmically constructs an online algorithm with a competitive ratio…

Data Structures and Algorithms · Computer Science 2012-11-01 Elisabeth Günther , Olaf Maurer , Nicole Megow , Andreas Wiese

Most practical scheduling applications involve some uncertainty about the arriving times and lengths of the jobs. Stochastic online scheduling is a well-established model capturing this. Here the arrivals occur online, while the processing…

Data Structures and Algorithms · Computer Science 2022-12-20 Sven Jäger

This paper considers the fundamental convergence time for opportunistic scheduling over time-varying channels. The channel state probabilities are unknown and algorithms must perform some type of estimation and learning while they make…

Optimization and Control · Mathematics 2017-10-05 Michael J. Neely

Modern data centers face new scheduling challenges in optimizing job-level performance objectives, where a significant challenge is the scheduling of highly parallel data flows with a common performance goal (e.g., the shuffle operations in…

Networking and Internet Architecture · Computer Science 2016-03-28 Zhen Qiu , Cliff Stein , Yuan Zhong

Load balancing plays a critical role in efficiently dispatching jobs in parallel-server systems such as cloud networks and data centers. A fundamental challenge in the design of load balancing algorithms is to achieve an optimal trade-off…

Performance · Computer Science 2020-12-16 Mark van der Boor , Sem Borst , Johan van Leeuwaarden

Coflow has emerged as a fundamental application-layer abstraction in distributed systems, representing communication dependencies and enabling collaborative management of related flows to enhance job completion efficiency. To meet the…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-04-30 Xin Wang , Hong Shen , Hui Tian , Ye Tao

Communication networks are time-varying and hence, fair sharing of network resources among the users in such a dynamic environment is a challenging task. In this context, a time-varying network model is designed and the shortest user's…

Networking and Internet Architecture · Computer Science 2019-05-10 Suchi Kumari , Anurag Singh

The artificial segmentation of an investment management process into a workflow with silos of offline human operators can restrict silos from collectively and adaptively pursuing a unified optimal investment goal. To meet the investor's…

Portfolio Management · Quantitative Finance 2020-09-08 Andrew Paskaramoorthy , Terence van Zyl , Tim Gebbie

Motivated by modern parallel computing applications, we consider the problem of scheduling parallel-task jobs with heterogeneous resource requirements in a cluster of machines. Each job consists of a set of tasks that can be processed in…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-04-03 Mehrnoosh Shafiee , Javad Ghaderi