Fair Virtual Network Function Mapping and Scheduling Using Proximal Policy Optimization

Kuai, Zhenran; Wang, Tianyu; Wang, Shaowei

doi:10.1109/tcomm.2022.3211071

Cited by 11 publications

(5 citation statements)

References 26 publications

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“…In summary, the total time consumption T total and the total energy consumption E total can be computed by Equations (11) and (12).…”

Section: The Time and Energy Consumptionmentioning

confidence: 99%

“…The number of multi-constrained task sets [2][3][4][5][6][7][8][9][10][11][12][13][14] The number of edge servers [14][15][16] The virtual machine capacity of edge servers [15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30] The CPU frequency of edge servers [2000-2500] MHz…”

Section: Parameter Valuementioning

confidence: 99%

“…10,11 In contrast, the service provider does not want to see the server in a state of sustained elevated load but rather a balanced distribution of burden across all servers. 12 Besides, since the highly heterogeneous characteristics of peripheral servers, 13 resource priority is also viewed as another important factor that impacts the fairness of resource allocation from the perspective of service providers. Therefore, in such scenarios, fairness-aware computing offloading constitutes a mixed-integer nonlinear programming problem and is generally NP-hard.…”

Section: Introductionmentioning

confidence: 99%

“…From the perspective of users, a server with more resources is more favored than one with fewer, resulting in an inordinate concentration of load on servers with powerful processing capabilities 10,11 . In contrast, the service provider does not want to see the server in a state of sustained elevated load but rather a balanced distribution of burden across all servers 12 . Besides, since the highly heterogeneous characteristics of peripheral servers, 13 resource priority is also viewed as another important factor that impacts the fairness of resource allocation from the perspective of service providers.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A fairness‐aware task offloading method in edge‐enabled IIoT with multi‐constraints using AGE‐MOEA and weighted MMF

Peng

Ling

Zhao

et al. 2023

Concurrency and Computation

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SummaryBy providing distributed and ultra‐low‐latency communication between industrial devices and resource components, the Industrial Internet of Things (IIoT) is at the forefront of a new trend. Such a distributed paradigm is viewed as a collection of autonomous computing resources utilized by multiple heterogeneous devices to achieve higher‐quality interconnection and data exchange. However, stringent requirements of exceptional service and fairness guarantees pose many formidable challenges. To this end, this study investigates the aforementioned concerns in an integrated manner and further proposes a fairness‐aware task offloading method, called FOIMAM. Specifically, the ‐norm is introduced to accommodate the Pareto plane under the non‐Euclidean geometry framework while the evaluation and elimination of low‐quality solutions are completed based on survival scores. Particularly, the fairness requirements are formulated as a multi‐constraint problem and resolved using weighted max‐min fairness. Eventually, numerical results indicate that the proposed method brings substantial improvement in both service efficiency and fairness guarantees.

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“…In summary, the total time consumption T total and the total energy consumption E total can be computed by Equations (11) and (12).…”

Section: The Time and Energy Consumptionmentioning

confidence: 99%

Section: Parameter Valuementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A fairness‐aware task offloading method in edge‐enabled IIoT with multi‐constraints using AGE‐MOEA and weighted MMF

Peng

Ling

Zhao

et al. 2023

Concurrency and Computation

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“…In [15], the authors study the problem of differentiated routing considering SFC in SDN and NFV networks, the resource aware routing algorithm is proposed to solve the differentiated routing problem which is formulated as a binary integer programming model aiming to minimize the resource consumption cost of flows with SFC requests. In [16], the authors propose a deep reinforcement learning method with offline proximal policy optimization to solve the problem of VNF mapping and scheduling with the objective of maximizing the fairness of different services while ensuring the corresponding delay requirements. In [17], a dynamic SFC orchestration framework has been created in the context of the Industrial Internet of Things, and the joint optimization problem is decomposed into two subproblems: SFC selection and dynamic SFC orchestration.…”

Section: Introduction 1backgroundmentioning

confidence: 99%

Risk-Balanced Routing Strategy for Service Function Chains of Cyber-Physical Power System Considering Cross-Space Cascading Failure

Wang,

Tong,

et al. 2024

ENERGY

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Cyber-physical power system (CPPS) has significantly improved the operational efficiency of power systems. However, cross-space cascading failures may occur due to the coupling characteristics, which poses a great threat to the safety and reliability of CPPS, and there is an acute need to reduce the probability of these failures. Towards this end, this paper first proposes a cascading failure index to identify and quantify the importance of different information in the same class of communication services. On this basis, a joint improved risk-balanced service function chain routing strategy (SFC-RS) is proposed, which is modeled as a robust optimization problem and solved by column-and-constraint generation (C-CG) algorithm. Compared with the traditional shortest-path routing algorithm, the superiority of SFC-RS is verified in the IEEE 30-bus system. The results demonstrate that SFC-RS effectively mitigates the risk associated with information transmission in the network, enhances information transmission accessibility, and effectively limits communication disruption from becoming the cause of cross-space cascading failures.

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Beyond games: a systematic review of neural Monte Carlo tree search applications

Kemmerling,

Lütticke,

Schmitt

2023

Appl Intell

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The advent of AlphaGo and its successors marked the beginning of a new paradigm in playing games using artificial intelligence. This was achieved by combining Monte Carlo tree search, a planning procedure, and deep learning. While the impact on the domain of games has been undeniable, it is less clear how useful similar approaches are in applications beyond games and how they need to be adapted from the original methodology. We perform a systematic literature review of peer-reviewed articles detailing the application of neural Monte Carlo tree search methods in domains other than games. Our goal is to systematically assess how such methods are structured in practice and if their success can be extended to other domains. We find applications in a variety of domains, many distinct ways of guiding the tree search using learned policy and value functions, and various training methods. Our review maps the current landscape of algorithms in the family of neural monte carlo tree search as they are applied to practical problems, which is a first step towards a more principled way of designing such algorithms for specific problems and their requirements.

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Fair Virtual Network Function Mapping and Scheduling Using Proximal Policy Optimization

Cited by 11 publications

References 26 publications

A fairness‐aware task offloading method in edge‐enabled IIoT with multi‐constraints using AGE‐MOEA and weighted MMF

A fairness‐aware task offloading method in edge‐enabled IIoT with multi‐constraints using AGE‐MOEA and weighted MMF

Risk-Balanced Routing Strategy for Service Function Chains of Cyber-Physical Power System Considering Cross-Space Cascading Failure

Beyond games: a systematic review of neural Monte Carlo tree search applications

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