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About 10,000 papers for “Bandwidth (computing)”

Passive bandwidth estimation for fog computing

Knut Omang, Carsten Griwodz, Frank T. Johnsen · Norsk IKT-konferanse for forskning og utdanning · 2025

This paper investigates passive bandwidth estimation as ameans to improve scheduling in Kubernetes-based fog computing environments.In contrast to active probing techniques, passive methodsrely on observing existing traffic patterns to infer available bandwidth(ABW), offering a non-intrusive alternative suitable for dynamicand distributed systems. The study focuses on wired infrastructure networkswithin the cloud–fog–edge continuum. We develop and present an approach based on a modified version ofthe probe gap model, evaluated in an emulated network testbed. Tenexperiments were conducted under varying traffic conditions, packet lossrates, and link capacities. Timestamping artifacts and data filtering wereaddressed to ensure measurement integrity. The approach demonstratesreliable ABW estimation across all scenarios, confirming the viability ofpassive methods for bandwidth-aware scheduling in Kubernetes.

Cited by 0Open access

Adaptive bandwidth reservation for multimedia computing

Luca Abeni, Giorgio Buttazzo · 2003

In this paper we present a framework for dynamically allocating the CPU resource to tasks whose execution times are not known a priori. Tasks are partitioned in three classes: the ones that require a uniform execution but do not impose any temporal constraint, periodic tasks that operate on continuous media, and event driven tasks that respond to external interrupts. For the last two classes, we show how to adjust the fraction of the CPU bandwidth assigned to each task using a feedback mechanism.

Cited by 71

Overcoming Bandwidth Limitations in Visual Computing

Robert Strzodka, Mohammed Shaheen, Max Planck et al. · 2012

Abstract—Because visual computations are very data intensive they are often limited by the bandwidth of the system rather than its peak computational performance. The trend towards many-core architectures exacerbates the problem because the parallel cores let the compute capability grow exponentially while the system bandwidth increases only linearly. At the core of the bandwidth problem in visual computing are iterative loops over discrete local operators. A typical representative is a stencil computation with constants weights or a sparse matrix vector product in case of variable weights. This computations are bandwidth limited because of their low arithmetic intensity. We have developed techniques that accelerate these loops beyond the peak bandwidth limit. While different cache friendly approaches have been tried in the past, they have never been so successful. For example our quad-core Xeon X5482 3.2GHz system reaches 22.3 GFLOPS in double precision on a stencil computation in registers. On a large 3D domain of 504 3 doubles and 100 iterations a handvectorized single-threaded naive stencil implementation achieves 1.6 GFLOPS and there is no improvement in the multi-threaded version because the system memory bandwidth limits the performance. A state-of-art automatic loop transformation framework Pluto [?] achieves 1.9 GFLOPS for this stencil computation with four threads. In comparison, our scheme performs already at 5.3 GFLOPS with a single thread and soars to 13.0 GFLOPS with four threads. I.

Cited by 0

Computing the Bandwidth of Interval Graphs

Daniel J. Kleitman, Rakesh Vohra · SIAM Journal on Discrete Mathematics · 1990

In this note, an $O ( | V |k )$ algorithm is described for determining whether an interval graph on $| V |$ vertices has a bandwidth less than or equal to a given integer k. While the algorithm is not the first to resolve this problem, it does admit a shorter proof of its correctness than a previous algorithm of the same complexity due to Kratsch (Information and Computation, 74 (1987), pp. 140–158).

Cited by 66

Improving Bandwidth Efficiency and fairness in cloud computing

Xiang Sun, Nirwan Ansari · 2013

Bandwidth is a key resource in cloud networks. Every tenant wants to be assigned the bandwidth which is proportional to the price they have paid. At the cloud vender side, the link bandwidth utilization could be enhanced to support more clients. In this paper, we show that the traditional PS-N (Proportional Sharing at Network level) bandwidth allocation algorithm cannot achieve the network proportionality fairness when the network is over-subscribed. PPSN (Persistence Proportional Sharing at Network level) is proposed to solve the unfairness issue. However, the bandwidth utilization of both algorithms is not good enough to meet venders' demands. BEPPS-N (Bandwidth Efficiency Persistence Proportional Sharing at Network level) is thus proposed to enhance the bandwidth utilization by assigning more bandwidth to the communication pairs that are not passing through bottleneck links, and at the same time, keep proportionality fairness per different tenant. Finally, simulations and performance analysis have been conducted to substantiate the viability of our proposed approach.

Cited by 7

Bandwidth‐aware divisible task scheduling for cloud computing

Weiwei Lin, Liang Chen, James Z. Wang et al. · Software Practice and Experience · 2012

SUMMARY Task scheduling is a fundamental issue in achieving high efficiency in cloud computing. However, it is a big challenge for efficient scheduling algorithm design and implementation (as general scheduling problem is NP‐complete). Most existing task‐scheduling methods of cloud computing only consider task resource requirements for CPU and memory, without considering bandwidth requirements. In order to obtain better performance, in this paper, we propose a bandwidth‐aware algorithm for divisible task scheduling in cloud‐computing environments. A nonlinear programming model for the divisible task‐scheduling problem under the bounded multi‐port model is presented. By solving this model, the optimized allocation scheme that determines proper number of tasks assigned to each virtual resource node is obtained. On the basis of the optimized allocation scheme, a heuristic algorithm for divisible load scheduling, called bandwidth‐aware task‐scheduling (BATS) algorithm, is proposed. The performance of algorithm is evaluated using CloudSim toolkit. Experimental result shows that, compared with the fair‐based task‐scheduling algorithm, the bandwidth‐only task‐scheduling algorithm, and the computation‐only task‐scheduling algorithm, the proposed algorithm (BATS) has better performance. Copyright © 2012 John Wiley & Sons, Ltd.

Cited by 141

A nanopore interface for high bandwidth DNA computing

Karen Zhang, Yuan-Jyue Chen, Kathryn J Doroschak et al. · bioRxiv (Cold Spring Harbor Laboratory) · 2021

Abstract DNA has emerged as a powerful substrate for programming information processing machines at the nanoscale. Among the DNA computing primitives used today, DNA strand displacement (DSD) is arguably the most popular, with DSD-based circuit applications ranging from disease diagnostics to molecular artificial neural networks. The outputs of DSD circuits are generally read using fluorescence spectroscopy. However, due to the spectral overlap of typical small-molecule fluorescent reporters, the number of unique outputs that can be detected in parallel is limited, requiring complex optical setups or spatial isolation of reactions to make output bandwidths scalable. Here, we present a multiplexable sequencing-free readout method that enables real-time, kinetic measurement of DSD circuit activity through highly parallel, direct detection of barcoded output strands using nanopore sensor array technology (Oxford Nanopore Technologies’ MinION device). We show that engineered reporter probes can be detected and classified with high accuracy at the single-molecule level directly from raw nanopore signals using deep learning. We then demonstrate this method’s utility in multiplexed detection of clinically relevant microRNA sequences. These results increase DSD output bandwidth by an order of magnitude over what is possible with fluorescence spectroscopy, laying the foundations for a new paradigm in DNA circuit readout and programmable multiplexed molecular diagnostics using portable nanopore devices.

Cited by 1Open access

A nanopore interface for higher bandwidth DNA computing

Karen Zhang, Yuan-Jyue Chen, Delaney Wilde et al. · Nature Communications · 2022

DNA has emerged as a powerful substrate for programming information processing machines at the nanoscale. Among the DNA computing primitives used today, DNA strand displacement (DSD) is arguably the most popular, with DSD-based circuit applications ranging from disease diagnostics to molecular artificial neural networks. The outputs of DSD circuits are generally read using fluorescence spectroscopy. However, due to the spectral overlap of typical small-molecule fluorescent reporters, the number of unique outputs that can be detected in parallel is limited, requiring complex optical setups or spatial isolation of reactions to make output bandwidths scalable. Here, we present a multiplexable sequencing-free readout method that enables real-time, kinetic measurement of DSD circuit activity through highly parallel, direct detection of barcoded output strands using nanopore sensor array technology (Oxford Nanopore Technologies' MinION device). These results increase DSD output bandwidth by an order of magnitude over what is currently feasible with fluorescence spectroscopy.

Cited by 21Open access

Cheating-Resilient Bandwidth Distribution in Mobile Cloud Computing

Snigdha Das, Manas Khatua, Sudip Misra · IEEE Transactions on Cloud Computing · 2016

In mobile cloud computing (MCC), optimal utilization of resources (e.g., bandwidth), while maintaining the required level of quality-of-services (QoS), is essential. A user participating in the resource allocation process can provide untruthful information for acquiring undue advantages with respect to the allocated resource amount, and the cost incurred. In this paper, we identify, formulate, and address the problem of such misbehaviour. We formulate the bandwidth distribution as a constrained convex utility maximization problem, and solve it using the proposed cheating-resilient bandwidth distribution (CRAB) scheme. Numerical analysis shows that, in CRAB, the misbehaving user is impelled to behave normally as the misbehaviour increases its own cost while the other users including the cloud service provider (CSP) get benefit in terms of revenue. We investigate the existence of Nash Equilibrium (NE) of the proposed scheme. Both the problem and the solution are extensively analysed theoretically. The maximum and minimum selling prices of bandwidth, and the optimal solution for individual user are computed using the method of Lagrange multiplier.

Cited by 1

Bandwidth Allocation In Cloud Environment

Akshay Badve, Bhushan Bhujbal, Akash Gavali et al. · 2015

Cloud Computing is nothing but a use of computing properties that is distributed as a service over a network. Distribution of the data in the cloud depends on the network structure of the data centers. Allocation of bandwidth shows a important role in sharing the resources on the way to the data centers. Performance of the server is the major issue in cloud computing. When lots of users send a request for the same server at a same time then the performance of the server is significantly decreased. So we are defining a new method of rearranging the bandwidth from inactive users to active users using bandwidth delay technique using delay allocation. Keywords—OpenStack,Devstack,Cloud Computing,Performance analysis,Bandwidth delay technique,IaaS,Delay Allocation.

Cited by 0

Computing actuator bandwidth limits for model reference adaptive control

Benjamin C. Gruenwald, Daniel Wagner, Tansel Yucelen et al. · International Journal of Control · 2016

Although model reference adaptive control theory has been used in numerous applications to achieve system performance without excessive reliance on dynamical system models, the presence of actuator dynamics can seriously limit the stability and the achievable performance of adaptive controllers. In this paper, a linear matrix inequalities-based hedging approach is developed and evaluated for model reference adaptive control of uncertain dynamical systems in the presence of actuator dynamics. The hedging method modifies the ideal reference model dynamics in order to allow correct adaptation that is not affected by the presence of actuator dynamics. Specifically, we first generalise the hedging approach to cover a variety of cases in which actuator output and the control effectiveness matrix of the uncertain dynamical system are known and unknown. We then show the stability of the closed-loop dynamical system using Lyapunov-based stability analysis tools and propose a linear matrix inequality-based framework for the computation of the minimum allowable actuator bandwidth limits such that the closed-loop dynamical system remains stable. Finally, an illustrative numerical example is provided to demonstrate the efficacy of the proposed approach.

Cited by 57

CoMan: Managing Bandwidth Across Computing Frameworks in Multiplexed Datacenters

Wenxin Li, Deke Guo, Alex X. Liu et al. · IEEE Transactions on Parallel and Distributed Systems · 2017

Inefficient bandwidth sharing in a datacenter network, between different application frameworks, e.g., MapReduce and Spark, can lead to inelastic and skewed usage of link bandwidth and increased completion times for the applications. Existing work, however, either solely focuses on managing computation and storage resources or controlling only sending/receiving rate at hosts. In this paper, we present CoMan, a solution that provides global in-network bandwidth management in multiplexed data centers, with two goals: improving bandwidth utilization and reducing application completion time. CoMan first designs a novel abstraction of virtual link groups (VLGs) to establish a shared bandwidth resource pool. Based on this pool, CoMan implements a three-level bandwidth allocation model, which enables elastic bandwidth sharing among computing frameworks as well as guarantees network performance for the applications. CoMan further improves the bandwidth utilization by devising a VLG dependency graph and solves an optimization problem to guide the path selection using a 32-approximation algorithm. We conduct comprehensive trace-driven simulations as well as small-scale testbed experiments to evaluate the performance of CoMan. Extensive simulation results show that CoMan improves the bandwidth utilization and speeds up the application completion time by up to 2.83× and 6.68×, respectively, compared to the ECMP + ElasticSwitch solution. Our implementation also verifies that CoMan can realistically speed up the application completion times by 2.32× on average.

Cited by 13