Ponències/Comunicacions de congressos
http://hdl.handle.net/2117/3889
2024-03-29T10:12:09Z
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A reinforcement learning approach for placement of stateful Virtualized Network Functions
http://hdl.handle.net/2117/365486
A reinforcement learning approach for placement of stateful Virtualized Network Functions
Kibalya, Godfrey Mirondo; Serrat Fernández, Juan; Gorricho Moreno, Juan Luis; Gift Bujjingo, Doreen; Sseregunda, Jonathan; Zhang, Peiying
Network softwarization increases network flexibility by supporting the implementation of network functions such as firewalls as software modules. However, this creates new concerns on service reliability due to failures at both software and hardware level. The survivability of critical applications is commonly assured by deploying stand-by Virtual Network Functions (VNFs) to which the service is migrated upon failure of the primary VNFs. However, it is challenging to identify the optimal Data Centers (DCs) for hosting the active and stand-by VNF instances, not only to minimize their placement cost, but also the cost of a continuous state transfer between active and stand-by instances, since a number of VNFs are stateful. This paper proposes a reinforcement learning (RL) approach for the placement of stateful VNFs that considers a joint reservation of primary and backup resources with the objective of minimizing the overall placement cost. Simulation results show that the proposed algorithm is optimized in terms of both acceptance ratio and cost, resulting in up to 27% and 30% improvements in terms of accepted requests and placement cost compared to a state-of-the art algorithm.
2022-04-07T11:16:12Z
Kibalya, Godfrey Mirondo
Serrat Fernández, Juan
Gorricho Moreno, Juan Luis
Gift Bujjingo, Doreen
Sseregunda, Jonathan
Zhang, Peiying
Network softwarization increases network flexibility by supporting the implementation of network functions such as firewalls as software modules. However, this creates new concerns on service reliability due to failures at both software and hardware level. The survivability of critical applications is commonly assured by deploying stand-by Virtual Network Functions (VNFs) to which the service is migrated upon failure of the primary VNFs. However, it is challenging to identify the optimal Data Centers (DCs) for hosting the active and stand-by VNF instances, not only to minimize their placement cost, but also the cost of a continuous state transfer between active and stand-by instances, since a number of VNFs are stateful. This paper proposes a reinforcement learning (RL) approach for the placement of stateful VNFs that considers a joint reservation of primary and backup resources with the objective of minimizing the overall placement cost. Simulation results show that the proposed algorithm is optimized in terms of both acceptance ratio and cost, resulting in up to 27% and 30% improvements in terms of accepted requests and placement cost compared to a state-of-the art algorithm.
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End-to-end KPI analysis in converged fixed-mobile networks
http://hdl.handle.net/2117/330607
End-to-end KPI analysis in converged fixed-mobile networks
Ruiz Ramírez, Marc; Richart Gutiérrez, Matías Mario; Castro Casales, Alberto; Velasco Esteban, Luis Domingo
The independent operation of mobile and fixed network segments is one of the main barriers that prevents improving network performance while reducing capital expenditures coming from overprovisioning. In particular, a coordinated dynamic network operation of both network segments is essential to guarantee end-to-end Key Performance Indicators (KPI), on which new network services rely on. To achieve such dynamic operation, accurate estimation of end-to-end KPIs is needed to trigger network reconfiguration before performance degrades. In this paper, we present a methodology to achieve an accurate, scalable, and predictive estimation of end-to-end KPIs with sub-second granularity near real-time in converged fixed-mobile networks. Specifically, we extend our CURSA-SQ methodology for mobile network traffic analysis, to enable converged fixed-mobile network operation. CURSA-SQ combines simulation and machine learning fueled with real network monitoring data. Numerical results validate the accuracy, robustness, and usability of the proposed CURSA-SQ methodology for converged fixed-mobile network scenarios.
©2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
2020-10-22T07:24:57Z
Ruiz Ramírez, Marc
Richart Gutiérrez, Matías Mario
Castro Casales, Alberto
Velasco Esteban, Luis Domingo
The independent operation of mobile and fixed network segments is one of the main barriers that prevents improving network performance while reducing capital expenditures coming from overprovisioning. In particular, a coordinated dynamic network operation of both network segments is essential to guarantee end-to-end Key Performance Indicators (KPI), on which new network services rely on. To achieve such dynamic operation, accurate estimation of end-to-end KPIs is needed to trigger network reconfiguration before performance degrades. In this paper, we present a methodology to achieve an accurate, scalable, and predictive estimation of end-to-end KPIs with sub-second granularity near real-time in converged fixed-mobile networks. Specifically, we extend our CURSA-SQ methodology for mobile network traffic analysis, to enable converged fixed-mobile network operation. CURSA-SQ combines simulation and machine learning fueled with real network monitoring data. Numerical results validate the accuracy, robustness, and usability of the proposed CURSA-SQ methodology for converged fixed-mobile network scenarios.
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Resource allocation and management techniques for network slicing in WiFi networks
http://hdl.handle.net/2117/192941
Resource allocation and management techniques for network slicing in WiFi networks
Richart Gutiérrez, Matías Mario; Baliosian, Javier; Serrat Fernández, Juan; Gorricho Moreno, Juan Luis
Network slicing has recently been proposed as one of the main enablers for 5G networks; it is bound to cope with the increasing and heterogeneous performance requirements of these systems. To "slice" a network is to partition a shared physical network into several self-contained logical pieces (slices) that can be tailored to offer different functional or performance requirements. Moreover, a defining characteristic of the slicing paradigm is to provide resource isolation as well as efficient use of resources. In this context, the thesis described in this paper contributes to the problem of slicing WiFi networks by proposing a solution to the problem of enforcing and controlling slices in WiFi Access Points. The focus of the research is on a variant of network slicing called QoS Slicing, in which slices have specific performance requirements. In this document, we describe the two main contributions of our research, a resource allocation mechanism to assign resources to slices, and a solution to enforce and control slices with performance requirements in WiFi Access Points.
© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
2020-07-14T15:35:46Z
Richart Gutiérrez, Matías Mario
Baliosian, Javier
Serrat Fernández, Juan
Gorricho Moreno, Juan Luis
Network slicing has recently been proposed as one of the main enablers for 5G networks; it is bound to cope with the increasing and heterogeneous performance requirements of these systems. To "slice" a network is to partition a shared physical network into several self-contained logical pieces (slices) that can be tailored to offer different functional or performance requirements. Moreover, a defining characteristic of the slicing paradigm is to provide resource isolation as well as efficient use of resources. In this context, the thesis described in this paper contributes to the problem of slicing WiFi networks by proposing a solution to the problem of enforcing and controlling slices in WiFi Access Points. The focus of the research is on a variant of network slicing called QoS Slicing, in which slices have specific performance requirements. In this document, we describe the two main contributions of our research, a resource allocation mechanism to assign resources to slices, and a solution to enforce and control slices with performance requirements in WiFi Access Points.
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Inferring cloud-network slice’s requirements from non-structured service description
http://hdl.handle.net/2117/191918
Inferring cloud-network slice’s requirements from non-structured service description
Pasquini, Rafael; Baliosian, Javier Ernesto; Serrat Fernández, Juan; Gorricho Moreno, Juan Luis; Neto, Augusto; Verdi, Fábio
To support future 5G computing and communication scenarios, cloud-network management tools should deploy cloud-network services adopting uncomplicated ways, reducing not only the time to market but also broadening the community capable of deploying new services. In this paper, we present the support of NECOS Platform, an EU-Brazil jointly funded project, towards slice-as-a-service creation from non-structured service description. We describe how NECOS architecture allows such functionality during the slice creation loop, and we present the initial efforts we took for structuring such a mechanism.
© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
2020-06-29T14:26:28Z
Pasquini, Rafael
Baliosian, Javier Ernesto
Serrat Fernández, Juan
Gorricho Moreno, Juan Luis
Neto, Augusto
Verdi, Fábio
To support future 5G computing and communication scenarios, cloud-network management tools should deploy cloud-network services adopting uncomplicated ways, reducing not only the time to market but also broadening the community capable of deploying new services. In this paper, we present the support of NECOS Platform, an EU-Brazil jointly funded project, towards slice-as-a-service creation from non-structured service description. We describe how NECOS architecture allows such functionality during the slice creation loop, and we present the initial efforts we took for structuring such a mechanism.
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Computing at the edge: but, what edge?
http://hdl.handle.net/2117/191912
Computing at the edge: but, what edge?
Contreras Murillo, Luis Miguel; Baliosian De Lazzari, Javier Ernesto; Martínez-Julia, Pedro; Serrat Fernández, Juan
The traditional telecommunications business is evolving towards offering a richer set of services beyond basic connectivity, leveraging on network programmability and virtualization. A versatile execution environment is required, capable of running different workloads in different locations in the network. Cloud computing is the key paradigm that allows fostering this trending change. One interesting question to solve is to what extent those computing environments have to move towards the network edge. Some services can be enabled by environments with increased capillarity, while others can be implemented in environments with more relaxed constraints (e.g., in terms of latency). This paper explores this topic by differentiating service edge from physical network edge and proposing an architecture based on the ALTO server for assisting orchestration systems in discriminating the suitable environments for each service. We present a network-flow strategy for assigning services to infrastructure elements following those precepts, together with an initial scalability evaluation of the proposed assignment solution to show its feasibility.
© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
2020-06-29T13:43:19Z
Contreras Murillo, Luis Miguel
Baliosian De Lazzari, Javier Ernesto
Martínez-Julia, Pedro
Serrat Fernández, Juan
The traditional telecommunications business is evolving towards offering a richer set of services beyond basic connectivity, leveraging on network programmability and virtualization. A versatile execution environment is required, capable of running different workloads in different locations in the network. Cloud computing is the key paradigm that allows fostering this trending change. One interesting question to solve is to what extent those computing environments have to move towards the network edge. Some services can be enabled by environments with increased capillarity, while others can be implemented in environments with more relaxed constraints (e.g., in terms of latency). This paper explores this topic by differentiating service edge from physical network edge and proposing an architecture based on the ALTO server for assisting orchestration systems in discriminating the suitable environments for each service. We present a network-flow strategy for assigning services to infrastructure elements following those precepts, together with an initial scalability evaluation of the proposed assignment solution to show its feasibility.
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Guaranteed bit rate slicing in WiFi networks
http://hdl.handle.net/2117/172669
Guaranteed bit rate slicing in WiFi networks
Richart Gutiérrez, Matías Mario; Baliosian De Lazzari, Javier Ernesto; Serrat Fernández, Juan; Gorricho Moreno, Juan Luis; Agüero Calvo, Ramón
In forthcoming 5G networks, slicing has been proposed as a means to partition a shared physical network infrastructure into different self-contained logical parts (slices), which are set up to satisfy certain requirements. Although the topic has been thoroughly investigated by the scientific community and the industry, there are not many works addressing the challenges that appear when trying to exploit slicing techniques over WiFi networks. In this paper, we propose a novel method of allocating resources for WiFi networks to satisfy minimum bit rate requirements. We formulate an optimization problem, and we propose a solution based on the theory of Lyapunov drift optimization. The validity of the proposed solution is assessed by means of a simulation-based evaluation in Matlab.
2019-11-18T19:02:49Z
Richart Gutiérrez, Matías Mario
Baliosian De Lazzari, Javier Ernesto
Serrat Fernández, Juan
Gorricho Moreno, Juan Luis
Agüero Calvo, Ramón
In forthcoming 5G networks, slicing has been proposed as a means to partition a shared physical network infrastructure into different self-contained logical parts (slices), which are set up to satisfy certain requirements. Although the topic has been thoroughly investigated by the scientific community and the industry, there are not many works addressing the challenges that appear when trying to exploit slicing techniques over WiFi networks. In this paper, we propose a novel method of allocating resources for WiFi networks to satisfy minimum bit rate requirements. We formulate an optimization problem, and we propose a solution based on the theory of Lyapunov drift optimization. The validity of the proposed solution is assessed by means of a simulation-based evaluation in Matlab.
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NECOS Project: towards lightweight slicing of cloud federated infrastructures
http://hdl.handle.net/2117/123199
NECOS Project: towards lightweight slicing of cloud federated infrastructures
Dantas Silva, Felipe S.; Lemos, Maricilio O.O.; Medeiros, Alisson; Venancio Neto, Augusto; Pasquini, Rafael; Rothenberg, Christian; Mamatas, Lefteris; Correa, Sand Luz; Cardoso, Kleber Vieira; Marcondes, Cesar; Abelem, Antonio; Nascimiento, Marcelo; Galis, Alex; Contreras, Luis Miguel; Serrat Fernández, Juan; Papadimitriou, Panagiotis
The Novel Enablers for Cloud Slicing (NECOS) project addresses the limitations of current cloud computing infrastructures to respond to the demand for new services, as presented in two use-cases, that will drive the whole execution of the project. The first use-case is focused on Telco service provider and is oriented towards the adoption of cloud computing in their large networks. The second use-case is targeting the use of edge clouds to support devices with low computation and storage capacity. The envisaged solution is based on a new concept, the Lightweight Slice Defined Cloud (LSDC), as an approach that extends the virtualization to all the resources in the involved networks and data centers and provides uniform management with a high-level of orchestration. In this position paper, we discuss the motivation, objectives, architecture, research challenges (and how to overcome them) and initial efforts for the NECOS project.
2018-10-29T19:41:07Z
Dantas Silva, Felipe S.
Lemos, Maricilio O.O.
Medeiros, Alisson
Venancio Neto, Augusto
Pasquini, Rafael
Rothenberg, Christian
Mamatas, Lefteris
Correa, Sand Luz
Cardoso, Kleber Vieira
Marcondes, Cesar
Abelem, Antonio
Nascimiento, Marcelo
Galis, Alex
Contreras, Luis Miguel
Serrat Fernández, Juan
Papadimitriou, Panagiotis
The Novel Enablers for Cloud Slicing (NECOS) project addresses the limitations of current cloud computing infrastructures to respond to the demand for new services, as presented in two use-cases, that will drive the whole execution of the project. The first use-case is focused on Telco service provider and is oriented towards the adoption of cloud computing in their large networks. The second use-case is targeting the use of edge clouds to support devices with low computation and storage capacity. The envisaged solution is based on a new concept, the Lightweight Slice Defined Cloud (LSDC), as an approach that extends the virtualization to all the resources in the involved networks and data centers and provides uniform management with a high-level of orchestration. In this position paper, we discuss the motivation, objectives, architecture, research challenges (and how to overcome them) and initial efforts for the NECOS project.
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Resource allocation for network slicing in WiFi access points
http://hdl.handle.net/2117/116406
Resource allocation for network slicing in WiFi access points
Richart Gutiérrez, Matías Mario; Baliosian, Javier; Serrat Fernández, Juan; Gorricho Moreno, Juan Luis; Agüero Calvo, Ramón; Agoulmine, Nazim
Network slicing has recently appeared as one of the
most important features that will be provided by 5G networks and
is attracting considerable interest from industry and academia. At
the wireless edge of these networks, most of the contributions in
this area are related to cellular technologies leaving behind WiFi
networks. In this work, we present a resource allocation mechanism
based on airtime assignment to achieve infrastructure sharing and
slicing in WiFi Access Points. The approach is simple and has the
potential to be straightforwardly used within scenarios of wireless
access infrastructure sharing.
2018-04-17T15:17:06Z
Richart Gutiérrez, Matías Mario
Baliosian, Javier
Serrat Fernández, Juan
Gorricho Moreno, Juan Luis
Agüero Calvo, Ramón
Agoulmine, Nazim
Network slicing has recently appeared as one of the
most important features that will be provided by 5G networks and
is attracting considerable interest from industry and academia. At
the wireless edge of these networks, most of the contributions in
this area are related to cellular technologies leaving behind WiFi
networks. In this work, we present a resource allocation mechanism
based on airtime assignment to achieve infrastructure sharing and
slicing in WiFi Access Points. The approach is simple and has the
potential to be straightforwardly used within scenarios of wireless
access infrastructure sharing.
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Mathematical models to evaluate the memory interference in multimicrocomputer systems
http://hdl.handle.net/2117/110485
Mathematical models to evaluate the memory interference in multimicrocomputer systems
Valero Cortés, Mateo; Alegre de Miguel, Ignasi; Sanvicente Gargallo, Emilio
In the last decade we have witnessed great advances in the integrated circuits technology. Those advances make it possible nowadays for the manufacturing, at reasonable prices of MOS technology memories that are faster than the microprocessors. These memories allow, thus several accesses in each microprocessor cycle. Therefore it seems reasonable to use the to reduce the memory interference in multimicroprocessor systems.
In this paper we present two mathematical models useful in the approximate evaluation of the memory interference. The results for both model concide. We also compare the with experimental valuesobtained by simulation.
2017-11-13T13:17:29Z
Valero Cortés, Mateo
Alegre de Miguel, Ignasi
Sanvicente Gargallo, Emilio
In the last decade we have witnessed great advances in the integrated circuits technology. Those advances make it possible nowadays for the manufacturing, at reasonable prices of MOS technology memories that are faster than the microprocessors. These memories allow, thus several accesses in each microprocessor cycle. Therefore it seems reasonable to use the to reduce the memory interference in multimicroprocessor systems.
In this paper we present two mathematical models useful in the approximate evaluation of the memory interference. The results for both model concide. We also compare the with experimental valuesobtained by simulation.
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Simulador de propagacion ionosferica para señales en banda de base
http://hdl.handle.net/2117/105986
Simulador de propagacion ionosferica para señales en banda de base
Serrat Fernández, Juan
2017-06-29T11:19:36Z
Serrat Fernández, Juan