Dynamic Scheduling and Optimal Reconfiguration of UPF Placement in 5G Networks

Leyva-Pupo, Irian; Cervelló-Pastor, Cristina; Anagnostopoulos, Christos; Pezaros, Dimitrios P.

doi:10.1145/3416010.3423221

Cited by 17 publications

(8 citation statements)

References 14 publications

(36 reference statements)

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“…The leaves (level 0) are the datacenters colocated with the PoAs (antennas). Similarly to [8], [9], [12], the higher levels 5, 4, 3, 2, 1 recursively partition the simulated area. In both Luxembourg and Monaco, if no PoAs exist in a particular rectangle, the respective datacenters are pruned from the tree.…”

Section: A Simulation Settingsmentioning

confidence: 99%

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Asynchronous Distributed Protocol for Service Provisioning in the Edge-Cloud Continuum

Cohen¹,

Chiasserini²,

Giaccone³

2023

Preprint

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<p> In the edge-cloud continuum, datacenters provide microservices (MSs) to mobile users, with each MS having specific latency constraints and computational requirements. Deploying such a variety of MSs matching their requirements with the available computing resources is challenging. In addition, time-critical MSs may have to be migrated as the users move, to keep meeting their latency constraints. Unlike previous work relying on a central orchestrator with an always-updated global view of the available resources and of the users’ locations, this work envisions a distributed solution to the above issues. In particular, we propose a distributed asynchronous protocol for MS deployment in the cloud-edge continuum that (i) dramatically reduces the system overhead compared to a centralized approach, and (ii) increases the system stability by avoiding having a single point of failure as in the case of a central orchestrator. Our solution ensures cost-efficient feasible placement of MSs, while using negligible bandwidth. </p>

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Section: A Simulation Settingsmentioning

confidence: 99%

“…State-of-the-art solutions to the PMP [2], [8], [9], [25]. assume a centralized orchestrator that possesses a fresh, accurate information about the locations, trajectories, and computational demands of all users, and the available resources at all the datacenters.…”

Section: Related Workmentioning

confidence: 99%

Asynchronous Distributed Protocol for Service Provisioning in the Edge-Cloud Continuum

Cohen¹,

Chiasserini²,

Giaccone³

2023

Preprint

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show abstract

“…Xincai et al [23] derived the requested instances with adaptive processing capacities and called two other algorithms for new instance assignment and service chain rerouting, respectively, while achieving good competitive ratios. The problem of dynamic placement reconfiguration of 5G User Plane Functions (UPFs) in a MEC ecosystem was studied in [24], a scheduling technique based on Optimal Stopping Theory (OST) was proposed to adapt to changes in user locations while ensuring QoS and network operator expenditures reduction. The authors in [25] studied the joint SFC deployment and resource management problem (JSDRM) in heterogeneous edge environments to minimize the total system latency and proposed a scheme based on a game model to jointly deploy SFCs and manage resources.…”

Section: Related Workmentioning

confidence: 99%

Deterministic Latency/Jitter-Aware Service Function Chaining Over Beyond 5G Edge Fabric

Taleb

Zhang

2022

IEEE Trans. Netw. Serv. Manage.

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Deterministic network (DetNet) recently attracts much attention which aims at studying the deterministic bounded latency and low latency variation for time-sensitive applications (e.g., industrial automation). To improve the quality of service (QoS) guarantee and make the network management efficient, it is desirable for Internet Service Provider (ISP) to obtain an optimal service function chain (SFC) provision strategy while providing deterministic service performance for the time-sensitive applications. In this paper, we will study the deterministic SFC lifetime management problem in beyond 5G edge fabric with the objective of maximizing the overall profits and ensuring the deterministic latency and jitter of SFC requests. We first formulate this problem as a mathematical model with the maximal profits for ISP. Then, the novel Deterministic SFC Deployment algorithm (Det-SFCD) and SFC Adjustment algorithm (Det-SFCA) due to traffic load variation have been proposed to efficiently solve the SFC lifetime management problem. Extensive simulation results show that our proposed algorithms can achieve the higher performance in terms of SFC request acceptance rates, overall profits and latency variation compared with the benchmark algorithm.

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“…Other works formulate the migration problem as an ILP [4], [14], MILP [9], or Mixed-Integer Quadratic Program [16], but none of them guarantees to find a feasible solution (possibly using more resources). In particular, these solutions usually handle requests in parallel (the ILP/MIQP solvers), or in an arbitrary order, e.g., based on the request time [12].…”

Section: Related Workmentioning

confidence: 99%

“…[43] considers multiple simultaneous migration requests, and focuses on scheduling the migrations and determining the bandwidth allocated to each migration process to minimize the total migration time and the service level objective violation. [14] uses the optimal stopping theory to optimize the length of the decision period between subsequent runs of the migration algorithm. Some of the optimizations mentioned above are orthogonal to our work, and hence could be incorporated into our solution to boost performance.…”

Section: Related Workmentioning

confidence: 99%

Dynamic Service Provisioning in the Edge-cloud Continuum with Provable Guarantees

Cohen¹,

Chiasserini²,

Giaccone³

et al. 2022

Preprint

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We consider a hierarchical edge-cloud architecture in which services are provided to mobile users as chains of virtual network functions. Each service has specific computation requirements and target delay performance, which require placing the corresponding chain properly and allocating a suitable amount of computing resources. Furthermore, chain migration may be necessary to meet the services' target delay, or convenient to keep the service provisioning cost low. We tackle such issues by formalizing the problem of optimal chain placement and resource allocation in the edge-cloud continuum, taking into account migration, bandwidth, and computation costs. Specifically, we first envision an algorithm that, leveraging resource augmentation, addresses the above problem and provides an upper bound to the amount of resources required to find a feasible solution. We use this algorithm as a building block to devise an efficient approach targeting the minimum-cost solution, while minimizing the required resource augmentation. Our results, obtained through trace-driven, large-scale simulations, show that our solution can provide a feasible solution by using half the amount of resources required by state-of-the-art alternatives.

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Dynamic Scheduling and Optimal Reconfiguration of UPF Placement in 5G Networks

Cited by 17 publications

References 14 publications

Asynchronous Distributed Protocol for Service Provisioning in the Edge-Cloud Continuum

Asynchronous Distributed Protocol for Service Provisioning in the Edge-Cloud Continuum

Deterministic Latency/Jitter-Aware Service Function Chaining Over Beyond 5G Edge Fabric

Dynamic Service Provisioning in the Edge-cloud Continuum with Provable Guarantees

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