arXiv subjects

Joberto S. B. Martins

Publications and source records attributed to Joberto S. B. Martins.

30 records · Page 2Linked to original sources

arXiv2020

Managing IEC 61850 Message Exchange for SDN-Controlled Cognitive Communication Resource Allocation in the Smart Grid

The IEC 61850 standard is being largely used in the Smart Grid (SG) context mainly due to its ability to address communication, interoperability and migration issues. IEC 61850 currently aims at internal substation communication. Nevertheless, there is a demand to generalize its use for distributed SG systems like Home Energy Management Systems (HEMS) and Advanced Monitoring Infrastructure (AMI) Communication which potentially involves distributed substations or distributed SG components. IEC 61850- based systems require constrained timing requirements for communication and the common approach is to allocate static link bandwidth resources leading in some cases to over dimensioning. This paper presents the Substation Cognitive Communication Resource Management (IC2RM), that aims the management of bandwidth allocation for IEC messages using a cognitive approach for its provisioning and the SDN/OpenFlow for its deployment. By dynamically deploying bandwidth for IEC messages, IC2RM optimizes links between SG substations and systems and potentially reduces the operational costs (OPEX).

cs.NI↗

arXiv2019

A Pub/Sub SDN-Integrated Framework for IoT Traffic Orchestration

The Internet of Things (IoT) is advancing and the adoption of internet-connected devices in everyday use is constantly growing. This increase not only affects the traffic from other sources in the network, but also the communication quality requirements, like Quality of Service (QoS), for the IoT devices and applications. With the rise of dynamic network management and dynamic network programming technologies like Software-Defined Networking (SDN), traffic management and communication quality requirements can be tailored to fit niche use cases and characteristics. We propose a publish/subscribe QoS-aware framework (PSIoT-SDN) that orchestrates IoT traffic and mediates the allocation of network resources between IoT data aggregators and pub/sub consumers. The PSIoT framework allows edge-level QoS control using the features of publish/ subscribe orchestrator at IoT aggregators and, in addition, allows network-level QoS control by incorporating SDN features coupled with a bandwidth allocation model for networkwide IoT traffic management. The integration of the framework with SDN allows it to dynamically react to bandwidth sharing enabled by the SDN controller, resulting in better bandwidth distribution and higher link utilization for IoT traffic.

cs.NI↗

arXiv2019

A Electric Network Reconfiguration Strategy with Case-Based Reasoning for the Smart Grid

The complexity, heterogeneity and scale of electrical networks have grown far beyond the limits of exclusively human-based management at the Smart Grid (SG). Likewise, researchers cogitate the use of artificial intelligence and heuristics techniques to create cognitive and autonomic management tools that aim better assist and enhance SG management processes like in the grid reconfiguration. The development of self-healing management approaches towards a cognitive and autonomic distribution power network reconfiguration is a scenario in which the scalability and on-the-fly computation are issues. This paper proposes the use of Case-Based Reasoning (CBR) coupled with the HATSGA algorithm for the fast reconfiguration of large distribution power networks. The suitability and the scalability of the CBR-based reconfiguration strategy using HATSGA algorithm are evaluated. The evaluation indicates that the adopted HATSGA algorithm computes new reconfiguration topologies with a feasible computational time for large networks. The CBR strategy looks for managerial acceptable reconfiguration solutions at the CBR database and, as such, contributes to reduce the required number of reconfiguration computation using HATSGA. This suggests CBR can be applied with a fast reconfiguration algorithm resulting in more efficient, dynamic and cognitive grid recovery strategy.

cs.AI↗

arXiv2019

Evaluating the Applicability of Bandwidth Allocation Models for EON Slot Allocation

Bandwidth Allocation Models (BAMs) configure and handle resource allocation (bandwidth, LSPs, fiber, slots) in networks in general (IP/MPLS/DS-TE, optical domain, other). In this paper, BAMs are considered for elastic optical networks slot allocation targeting an improvement in resource utilization. The paper focuses initially on proposing a BAM basic configuration parameter mapping suitable for elastic optical circuits. Following that, MAM, RDM and ATCS BAMs are applied for elastic optical networks resource allocation and the overall network resource utilization is evaluated. A set of simulation results and BAM behaviors are presented as a proof of concept to evaluate BAM applicability for elastic optical network slot allocation. Authors argue that a slot allocation model for EON based on BAMs may improve utilization by dynamically managing the aggregated traffic profile.

cs.NI↗

arXiv2019

AllocTC-Sharing: A New Bandwidth Allocation Model for DS-TE Networks

DiffServ-aware MPLS-TE (DS-TE) allows bandwidth reservation for Traffic Classes (TCs) in MPLS-based engineered networks and, as such, improves the basic MPLS-TE model. In DS-TE networks, per-Class quality of service guarantees are provided while being possible to achieve improved network utilization. DS-TE requires the use of a Bandwidth Allocation Model (BAM) that establishes the amount of bandwidth per-Class and any eventual sharing among them. This paper proposes a new bandwidth allocation model (AllocTC-Sharing) in which the higher priority traffic classes are allowed to use non allocated resources of lower priority traffic classes and vice versa. By adopting this dual sense allocation strategy for dynamic bandwidth allocation, it is shown that AllocTC-Sharing model preserves bandwidth constraints for traffic classes and improves overall link utilization.

cs.NI↗

arXiv2019

Cognitive Management of Bandwidth Allocation Models with Case-Based Reasoning -- Evidences Towards Dynamic BAM Reconfiguration

Management is a complex task in today's heterogeneous and large scale networks like Cloud, IoT, vehicular and MPLS networks. Likewise, researchers and developers envision the use of artificial intelligence techniques to create cognitive and autonomic management tools that aim better assist and enhance the management process cycle. Bandwidth allocation models (BAMs) are a resource allocation solution for networks that need to share and optimize limited resources like bandwidth, fiber or optical slots in a flexible and dynamic way. This paper proposes and evaluates the use of Case-Based Reasoning (CBR) for the cognitive management of BAM reconfiguration in MPLS networks. The results suggest that CBR learns about bandwidth request profiles (LSPs requests) associated with the current network state and is able to dynamically define or assist in BAM reconfiguration. The BAM reconfiguration approach adopted is based on switching among available BAM implementations (MAM, RDM and ATCS). The cognitive management proposed allows BAMs self-configuration and results in optimizing the utilization of network resources.

cs.NI↗

arXiv2019

A Blockchain-based Educational Record Repository

The Blockchain technology was initially adopted to implement various cryptocurrencies. Currently, Blockchain is foreseen as a general purpose technology with a huge potential in many areas. Blockchain-based applications have inherent characteristics like authenticity, immutability and consensus. Beyond that, records stored on Blockchain ledger can be accessed any time and from any location. Blockchain has a great potential for managing and maintaining educational records. This paper presents a Blockchain-based Educational Record Repository (BcER2) that manages and distributes educational assets for academic and industry professionals. The BcER2 system allows educational records like e-diplomas and e-certificates to be securely and seamless transferred, shared and distributed by parties.

cs.OH↗

arXiv2018

Towards Smart City Innovation Under the Perspective of Software-Defined Networking, Artificial Intelligence and Big Data

Smart city projects address many of the current problems afflicting high populated areas and cities and, as such, are a target for government, institutions and private organizations that plan to explore its foreseen advantages. In technical terms, smart city projects present a complex set of requirements including a large number users with highly different and heterogeneous requirements. In this scenario, this paper proposes and analyses the impact and perspectives on adopting software-defined networking and artificial intelligence as innovative approaches for smart city project development and deployment. Big data is also considered as an inherent element of most smart city project that must be tackled. A framework layered view is proposed with a discussion about software-defined networking and machine learning impacts on innovation followed by a use case that demonstrates the potential benefits of cognitive learning for smart cities. It is argued that the complexity of smart city projects do require new innovative approaches that potentially result in more efficient and intelligent systems.

cs.NI↗

arXiv2018

Distribution Power Network Reconfiguration in the Smart Grid

The power network reconfiguration algorithm with an "R" modeling approach evaluates its behavior in computing new reconfiguration topologies for the power grid in the context of the Smart Grid. The power distribution network modelling with the R language is used to represent the network and support computation of different algorithm configurations for the evaluation of new reconfiguration topologies. This work presents a reconfiguration solution of distribution networks, with a construction of an algorithm that receiving the network configuration data and the nodal measurements and from these data build a radial network, after this and using a branch exchange algorithm And verifying the best configuration of the network through artificial intelligence, so that there are no unnecessary changes during the operation, and applied an algorithm that analyses the load levels, to suggest changes in the network.

eess.SP↗

arXiv2018

G-BAM: A Generalized Bandwidth Allocation Model for IP/MPLS/DS-TE Networks

Bandwidth Allocation Models (BAMs) configure and handle resource allocation (bandwidth, LSPs, fiber) in networks in general (IP/MPLS/DS-TE, optical domain, other). BAMs currently available for IP/MPLS/DS-TE networks (MAM, RDM, G-RDM and AllocTC-Sharing) basically define resource restrictions (bandwidth) by class (traffic class, application class, user class or other grouping criteria) and allocate on demand this resource. There is a BAM allocation policy inherent for each existing model which behaves differently under distinct network state, such as heavy traffic loads and dynamic traffic and/or application scenarios. A generalized Bandwidth Allocation Model (G-BAM) is proposed in this paper. G-BAM, firstly, incorporates the inherent behavior of currently used BAMs such as MAM, RDM, G-RDM and AllocTC-Sharing in IP/MPLS/DS-TE context. G-BAM, secondly, proposes a new policy/ behavior allocation in addition to existing ones in which additional private resources are incorporated. G-BAM, thirdly, allows a smoother BAM policy transition among existing policy alternatives resulting from MAM, RDM and AllocTC-Sharing adoption independently. The paper focuses on the first characteristics of G-BAM which is to reproduce MAM, RDM and AllocTC-Sharing behaviors. As such, the required configuration to achieve MAM, RDM and AllocTC-Sharing behaviors is presented followed by a proof of concept. Authors argue that the G-BAM reproducibility characteristics may improve overall network resource utilization under distinct traffic profiles.

cs.NI↗

arXiv2018

Applying Autonomy with Bandwidth Allocation Models

Bandwidth Allocation Models (BAMs) are resource allocation methods used for networks in general. BAMs are currently applied for handling resources such as bandwidth allocation in MPLS DS-TE networks (LSP setup). In general, BAMs defines resource restrictions by class and allocate the available resources on demand. This is frequently necessary to manage large and complex systems like routing networks. GBAM is a new generalized BAM that, by configuration, incorporates the behavior of existing BAMs (MAM, RDM, G-RDM and AllocTC-Sharing). In effect, any current available BAM behavior is reproduced by G-BAM by simply adjusting its configuration parameters. This paper focuses on investigating the applicability of using autonomy together with Bandwidth Allocation Models (BAMs) for improve performance and facilitating the management of MPLS DS-TE networks. It is investigated the applicability of BAM switching using a framework with autonomic characteristics. In brief, it is investigated the switching among BAM behaviors and BAM reconfiguration with distinct network traffic scenarios by using GBAM. Simulation results suggest that the autonomic switching of BAM behaviors based on high-level management rules (SLAs, QoS or other police) may result in improving overall network management and operational parameters such as link utilization and preemption.

cs.NI↗

arXiv2014

TARVOS - an Event-Based Simulator for Performance Analysis, Supporting MPLS, RSVP-TE, and Fast Recovery

This paper presents a new discrete event-based network simulator named TARVOS - Computer Networks Simulator, being designed as part of the first Author's Masters research and will provide support to simulating MPLS architecture, several RSVP-TE protocol functionalities and fast recovery in case of link failure. The tool is used in a case study, where the impact of a link failure on a VoIP application, within an MPLS domain network, is analyzed. The paper displays a preliminary research of six already available simulators and reasons why they were not adopted as tools for the Masters research. Then, it follows to describe the basics of TARVOS implementation and exhibits the case study simulated by this new tool.

cs.NI↗