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distributed load balancing algorithm considering QoS for next generation multi-RAT HetNets

COMPUTER NETWORKS 2023年第1期229卷

作者： Seyoum, Yemane Teklay Shahid, Syed Maaz Cho, Eun Seon Kwon, Sungoh Univ Ulsan Dept Elect Elect & Comp Engn Ulsan 44610 South Korea Elect & Telecommun Res Inst ETRI Daejeon 34129 South Korea

In this paper, we propose a distributed load balancing algorithm for multi-radio access technology (multi-RAT) heterogeneous networks (HetNets). The random deployment of small cells and the user mobility make the network load distribution uneven, which degrades overall network capacity and the QoS for users. Furthermore, the disparate capabilities of multiple RATs such as the different propagation delays in terrestrial and non-terrestrial RATs affect the latency requirements. To balance the network load in multi-RAT HetNets, we propose a distributed game-theoretic algorithm considering QoS for users. To that end, a cost function is defined to reflect the cell load status, required data rates, and delay constraints. In the proposed algorithm, overloaded cells iteratively minimize user cost in a distributed manner by associating a user with a less-loaded cell based on its cost. We provide analysis to show that minimizing each user cost in the game theory setting achieves a balanced load distribution among cells. We show that the proposed algorithm brings each cell load to a balanced state in a finite number of iterations. Via simulation, we show that the proposed algorithm achieves superior performance in terms of even load distribution, network throughput, and the number of users with satisfactory QoS.

关键词： Next generation cellular networks Multi-RATs HetNets Terrestrial and non-terrestrial network integration QoS distributed load balancing Game theory Wardrop equilibrium

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distributed Low-Effort load balancing in the Presence of Time-Delays 22

Distributed Low-Effort Load Balancing in the Presence of Tim...

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22nd World Congress of the International Federation of Automatic Control (IFAC)

作者： Charalambous, Themistoklis Panzieri, Stefano Oliva, Gabriele Univ Cyprus Sch Engn Dept Elect & Comp Engn Nicosia Cyprus Univ Roma Tre Via Vasca Navale 79 I-00146 Rome Italy Univ Campus Biomed Roma Dept Engn Unit Automat Control Rome Italy

ISBN: (纸本)9781713872344

In this paper, we investigate the problem of distributed load balancing under network capacity constraints, where the participating agents cooperate with the aim of jointly minimizing both the workload disparity among them as well as the overall workload transfer. Classical approaches for asymptotic convergence to the global optimum in a distributed fashion typically assume timely exchange of information between neighboring agents of a given multi-agent system. This assumption is not necessarily valid in practical settings due to non-commensurate (heterogeneous) communication and processing delays that might affect transmissions at different times. More specifically, we consider what effect multiple heterogeneous time-varying delays, among the agents can have on the distributed load balancing problem. We show that the distributed load balancing problem under bounded heterogeneous time-varying delays is globally asymptotically stable, but the rate of convergence is affected. Bounds on the convergence rate are provided with respect to an upper bound on the delays. Simulation examples are provided to show the validity and performance of our theoretical results. Copyright (c) 2023 The Authors. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0/)

关键词： distributed load balancing time-delays distributed algorithms minimum effort

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distributed load balancing for Future 5G Systems On-board High-Speed Trains 1

Distributed Load Balancing for Future 5G Systems On-board Hi...

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1st International Conference on 5G for Ubiquitous Connectivity (5GU)

作者： Goratti, Leonardo Savazzi, Stefano Parichehreh, Ali Spagnolini, Umberto NET Res Ctr CREATE Trento Italy CNR IEIIT Milan Italy Politecn Milan DEIB Milan Italy

ISBN: (纸本)9781631900556

The surge of mobile broadband Internet access has nowadays reached the critical point that traffic is projected to increase dramatically in the next years and even the 4G UMTS Long term Evolution ( LTE) cellular technology and its advanced version LTE-A might lack enough flexibility and system reconfiguration capability. For these reasons, the quest for the Fifth Generation ( 5G) of cellular technology has started. In the context of users that require high Quality of Experience ( QoE) anytime and anywhere, users on-board of fast moving vehicles such as high-speed trains represent an important market segment for both telecom operators and transportation companies. In particular, people who are moving for business everyday require low latency and high throughput Internet connectivity even when moving at hundreds of kilometers per hour. In this landscape, novel algorithms can find their space in future 5G systems to cope with fast resource ( re) allocation in the presence of large Doppler spread and high hand over frequency. Focusing on a high-speed train ( HST), in this paper we propose a simple but effective distributed load balancing algorithm to relieve service interruption caused by frequent handovers in high mobility scenarios. Our results show the effectiveness of the solution while leveraging on the concept of cell edge intelligence.

关键词： 5G mobile communication Internet Long Term Evolution cellular radio railway communication resource allocation 4G UMTS Long term Evolution 5G systems Internet connectivity LTE cellular technology distributed load balancing mobile broadband Internet access on-board high-speed trains quality of experience 3G mobile communication Artificial intelligence Handover Joining processes Quality of service Servers cellular technology Long Term Evolution Resource utilization Quality of service Local thermodynamic equilibrium cellular radio high-speed train Servers Artificial Intelligence railway communication management of resources Internets 3G mobile communication distributed loads Handover

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distributed Low-Effort load balancing in the Presence of Time-Delays

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IFAC-PapersOnLine 2023年第2期56卷 5191-5196页

作者： Themistoklis Charalambous Stefano Panzieri Gabriele Oliva Department of Electrical and Computer Engineering School of Engineering University of Cyprus Nicosia Cyprus University Roma Tre via della Vasca Navale 79 00146 Rome Italy Unit of Automatic Control Department of Engineering Università Campus Bio-Medico di Roma Rome Italy

关键词： distributed load balancing time-delays distributed algorithms minimum effort

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An Optimal distributed load balancing Algorithm for Homogeneous Work Units 14

An Optimal Distributed Load Balancing Algorithm for Homogene...

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28th ACM International Conference on Supercomputing (ICS)

作者： Langer, Akhil Univ Illinois Dept Comp Sci Champaign IL 61820 USA

ISBN: (纸本)9781450326421

Many parallel applications, for example, Adaptive Mesh Refinement [1] simulations, need dynamic load balancing during the course of their execution because of dynamic variation in the computational load. We propose a novel tree based fully distributed algorithm for load balancing homogeneous work units. The proposed algorithm achieves perfect load balance while doing minimum number of migrations of work units.

关键词： distributed load balancing adaptive mesh refinement complexity analysis scaling high performance computing

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distributed load balancing in a Multiple Server System by Shift-Invariant Protocol Sequences

Distributed Load Balancing in a Multiple Server System by Sh...

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IEEE Wireless Communications and Networking Conference (WCNC)

作者： Zhang, Yupeng Wong, Wing Shing Chinese Univ Hong Kong Dept Informat Engn Hong Kong Hong Kong Peoples R China

ISBN: (纸本)9781467359399;9781467359382

Ideally, many application systems for distributed users should be designed without requiring a centralized controller, for example cloud computing or wireless sensor networks. A fundamental challenge to developing distributed algorithms for these systems is load balancing, which is the focus of study in this paper. A common feature of these distributed algorithms is that routing decisions should be derivable without requiring much information from the system, probabilistic routing is one example coming to mind. In this paper, we propose a new routing strategy based on the idea of shift-invariant protocol sequences. We study this load balancing approach in the context of a queuing model of multi-server system. Our model and strategy can be applied to many practical systems, including wireless networks. Numerical studies were carried out to compare our strategy with other routing strategies such as probabilistic routing and random sequences routing. The results show that the proposed algorithm has better performance than these strategies.

关键词： Wireless sensor network Multiple server system distributed load balancing Shift- Invariant Protocol Sequences

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Stochastic coordination in heterogeneous load balancing systems

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distributed COMPUTING 2023年第3期36卷 253-275页

作者： Goren, Guy Vargaftik, Shay Moses, Yoram Technion Haifa Israel VMware Res Palo Alto CA USA

Current-day data centers and high-volume cloud services employ a broad set of heterogeneous servers. In such settings, client requests typically arrive at multiple entry points, and dispatching them to servers is an urgent distributed systems problem. This paper presents an efficient solution to the load balancing problem in such systems that improves on and overcomes problems of previous solutions. The load balancing problem is formulated as a stochastic optimization problem, and an efficient algorithmic solution is obtained based on a subtle mathematical analysis of the problem. Finally, extensive evaluation of the solution on simulated data shows that it outperforms previous solutions. Moreover, the resulting dispatching policy can be computed very efficiently, making the solution practically viable.

关键词： distributed load balancing Heterogeneous load balancing Stochastically coordinated dispatching Parallel server model

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Malcolm: Multi-agent Learning for Cooperative load Management at Rack Scale

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PROCEEDINGS OF THE ACM ON MEASUREMENT AND ANALYSIS OF COMPUTING SYSTEMS 2022年第3期6卷 1–25页

作者： Abyaneh, Ali Hossein Abbasi Liao, Maizi Zahedi, Seyed Majid Univ Waterloo Waterloo ON Canada

We consider the problem of balancing the load among servers in dense racks for microsecond-scale workloads. To balance the load in such settings tens of millions of scheduling decisions have to be made per second. Achieving this throughput while providing microsecond-scale latency and high availability is extremely challenging. To address this challenge, we design a fully decentralized load-balancing framework. In this framework, servers collectively balance the load in the system. We model the interactions among servers as a cooperative stochastic game. To find the game's parametric Nash equilibrium, we design and implement 59 a decentralized algorithm based on multi-agent-learning theory. We empirically show that our proposed algorithm is adaptive and scalable while outperforming state-of-the art alternatives. In homogeneous settings, Malcolm performs as well as the best alternative among other baselines. In heterogeneous settings, compared to other baselines, for lower loads, Malcolm improves tail latency by up to a factor of four. And for the same tail latency, Malcolm achieves up to 60% more throughput compared to the best alternative among other baselines.

关键词： distributed load balancing task scheduling cooperative game theory multi-agent reinforcement learning heterogeneous systems

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A model-based approach for formal verification and performance analysis of dynamic load-balancing protocols in cloud environment

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CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS 2021年第4期24卷 2977-2994页

作者： Ben Hafaiedh, Imene Ben Hamouda, Roua Robbana, Riadh Univ Tunis El Manar UTM ISI Tunis 1002 Tunisia Univ Tunis El Manar UTM Fac Sci Tunis FST Tunis 2092 Tunisia Univ Carthage UC Natl Inst Appl Sci & Technol Tunis Tunisia

Cloud computing is a new technology, providing different online resources and services to users. load balancing has become an interesting research area in this field. A few existing scheduling algorithms can maintain load balancing and provide better strategies through efficient job scheduling and resource allocation techniques as well. In order to gain maximum profits with optimized load balancing algorithms, it is necessary to guarantee a service level along dimensions such as performance, availability and reliability. In this work, we propose a Model-based approach to study and analyze centralized and distributed dynamic load balancing protocols in the Cloud. The formal verification of different properties of the studied protocols has been performed automatically and a performance analysis allowing their comparison is also provided. In this paper, we show how aspects of performance, resource consumption, and reliability of the Cloud can be formally modeled, verified and analyzed using a component-based architecture.

关键词： Formal models Cloud architecture load balancing protocols distributed load balancing Performance analysis

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PackStealLB: A scalable distributed load balancer based on work stealing and workload discretization

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JOURNAL OF PARALLEL AND distributed COMPUTING 2021年 150卷 34-45页

作者： Freitas, Vinicius Pilla, Laercio L. Santana, Alexandre de L. Castro, Marcio Cohen, Johanne Fed Univ Santa Catarina UFSC PPGCC Florianopolis SC Brazil Univ Paris Saclay CNRS LRI Orsay France

The scalability of high-performance, parallel iterative applications is directly affected by how well they use the available computing resources. These applications are subject to load imbalance due to the nature and dynamics of their computations. It is common that high performance systems employ periodic load balancing to tackle this issue. Dynamic load balancing algorithms redistribute the application's workload using heuristics to circumvent the NP-hard complexity of the problem However, scheduling heuristics must be fast to avoid hindering application performance when distributing the workload on large and distributed environments. In this work, we present a technique for low overhead, high quality scheduling decisions for parallel iterative applications. The technique relies on combined application workload information paired with distributed scheduling algorithms. An initial distributed step among scheduling agents group application tasks in packs of similar load to minimize messages among them. This information is used by our scheduling algorithm, PackStealLB, for its distributed-memory work stealing heuristic. Experimental results showed that PackStealLB is able to improve the performance of a molecular dynamics benchmark by up to 41%, outperforming other scheduling algorithms in most scenarios over almost one thousand cores. (c) 2020 Elsevier Inc. All rights reserved.

关键词： distributed load balancing Workload discretization Work stealing

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