arXiv subjects

Joberto Martins

Publications and source records attributed to Joberto Martins.

4 recordsLinked to original sources

arXiv2018

On Computational Infraestruture Requirements to Smart and Autonomic Cities Framework

Smart cities are an actual trend being pursued by research that, fundamentally, tries to improve city's management on behalf of a better human quality of live. This paper proposes a new autonomic complementary approach for smart cities management. It is argued that smart city management systems with autonomic characteristics will improve and facilitate management functionalities in general. A framework is also presented as use case considering specific application scenarios like smart-health, smart-grid, smart-environment and smart-streets.

cs.NI↗

arXiv2018

A Publish/Subscribe QoS-aware Framework for Massive IoT Traffic Orchestration

Internet of Things (IoT) application deployment requires the allocation of resources such as virtual machines, storage, and network elements that must be deployed over distinct infrastructures such as cloud computing, Cloud of Things (CoT), datacenters and backbone networks. For massive IoT data acquisition, a gateway-based data aggregation approach is commonly used featuring sensor/ actuator seamless access and providing cache/ buffering and preprocessing functionality. In this perspective , gateways acting as producers need to allocate network resources to send IoT data to consumers. In this paper, it is proposed a Publish/-Subscribe (PubSub) quality of service (QoS) aware framework (PSIoT-Orch) that orchestrates IoT traffic and allocates network resources between aggregates and consumers for massive IoT traffic. PSIoT-Orch schedules IoT data flows based on its configured QoS requirements. Additionally , the framework allocates network resources (LSP/ bandwidth) over a controlled backbone network with limited and constrained resources between IoT data users and consumers. Network resources are allocated using a Bandwidth Allocation Model (BAM) to achieve efficient network resource allocation for scheduled IoT data streams. PSIoT-Orch adopts an ICN (Information-Centric Network) PubSub architecture approach to handle IoT data transfers requests among framework components. The proposed framework aims at gathering the inherent advantages of an ICN-centric approach using a PubSub message scheme while allocating resources efficiently keeping QoS awareness and handling restricted network resources (bandwidth) for massive IoT traffic.

cs.NI↗

arXiv2018

A SDN-based Flexible System for On-the-Fly Monitoring and Treatment of Security Events

The Software Defined Networking (SDN) paradigm decouples control and data planes, offering high programmability and a global view of the network. However, it is a challenge not only provide security in these next generation networks as well as allow that network attacks could be subjected to an incident and forensic treatment procedure. This paper proposes the implementation of flexible mechanisms of monitoring and treatment of security events categorized per type of attack and associated with whitelist and blacklist resources by means of the SDN controller programmability. The resources to perform intrusion and attack analysis are validated by means of a real SDN/OpenFlow testbed.

cs.CR↗

arXiv2018

Evaluating CBR Similarity Functions for BAM Switching in Networks with Dynamic Traffic Profile

In an increasingly complex scenario for network management, a solution that allows configuration in more autonomous way with less intervention of the network manager is expected. This paper presents an evaluation of similarity functions that are necessary in the context of using a learning strategy for finding solutions. The learning approach considered is based on Case-Based Reasoning (CBR) and is applied to a network scenario where different Bandwidth Allocation Models (BAMs) behaviors are used and must be eventually switched looking for the best possible network operation. In this context, it is required to identify and configure an adequate similarity function that will be used in the learning process to recover similar solutions previously considered. This paper introduces the similarity functions, explains the relevant aspects of the learning process in which the similarity function plays a role and, finally, presents a proof of concept for a specific similarity function adopted. Results show that the similarity function was capable to get similar results from the existing use case database. As such, the use of similarity functions with CBR technique has proved to be potentially satisfactory for supporting BAM switching decisions mostly driven by the dynamics of input traffic profile.

cs.NI↗