An Application Layer Protocol to Support Cooperative Navigation of Multiple UAVs Systems

Applications involving multiple UAVs have gained increasing relevance in recent years, due to the benefits that cooperative systems tend to provide to their applications. In addition to performing several simultaneous tasks, the time spent to perform a certain task is reduced. In this article, an architecture for sharing navigation information is demonstrated to support applications composed of systems with multiple UAVs

MODELO DE APLICABILIDADE DE SISTEMA RFID PARA RASTREABILIDADE NA INDÚSTRIA ALIMENTÍCIA

The production traceability presents a number of benefits both in the industry logistics as in terms of product quality control. However, in this particular, different types of industry present specific issues that have to be addressed so that a convenient traceability solution can be provided. This paper presents the development of a traceability model based on RFID technology for application in food companies’ system. The model demonstrates the benefits generated from the use of traceability technologies to support the food industry control. The validation of the model uses a simulation with Rifidi Toolkit.A rastreabilidade de produtos durante o processo de produção apresenta uma série de benefícios tanto do ponto de vista logístico quanto de controle de qualidade. Entretanto, nesse contexto, diferentes tipos de indústrias apresentam particularidades que devem ser endereçadas na composição de uma solução conveniente para a rastreabilidade. Este artigo apresenta o desenvolvimento de um modelo de sistema de rastreabilidade de produção baseado na tecnologia RFID para aplicação em empresas do ramo alimentício. O modelo tem, como objetivo, demonstrar os benefícios gerados com o uso de tecnologias automatizadas de rastreabilidade, para apoiar o controle dos produtos da indústria alimentícia. A prova de conceito do modelo foi realizada por meio de uma simulação utilizando-se o Rifidi Toolkit

STFANET : SDN-Based Topology Management for Flying Ad Hoc Network

In recent years, with the growth in the use of Unmanned Aerial Vehicles (UAVs), UAV-based systems have become popular in both military and civil applications. The lack of reliable communication infrastructure in these scenarios has motivated the use of UAVs to establish a network as flying nodes, also known as Flying Ad Hoc Networks (FANETs). However, the high mobility degree of flying and terrestrial users may be responsible for constant changes in the network topology, which makes more challenging to guarantee their communication during the operational time. In this context, this article presents a Software-defined networking (SDN) based Topology management for FANETs - called of STFANET -, which is a coordination protocol that englobes both an efficient SDN-based UAV communication and a set of topology management algorithms. The goal is to establish and maintain a FANET topology in order to provide a constant and reliable communication link among independent nodes - which are performing individual or collaborative missions - through relays units. Simulation results show the efficiency of the proposed protocol in order to provide communication in a dynamic scenario. Considering its use in a military setting, STFANET managed to achieve 25% of packet loss in transmitting data packets, 1.5ms of latency and 71% of connectivity on average

Coordinating Aerial Robots and Unattended Ground Sensors for Intelligent Surveillance Systems

Sensor networks are being used to implement different types of sophisticated emerging applications, such as those aimed at supporting ambient intelligence and surveillance systems. This usage is enhanced by employing sensors with different characteristics in terms of sensing, computing and mobility capabilities, working cooperatively in the network. However, the design and deployment of these heterogeneous systems present several issues that have to be handled in order to meet the user expectations. The main problems are related to the nodes‘ interoperability and the overall resource allocation, both inter and intra nodes. The first problem requires a common platform that abstracts the nodes’ heterogeneity and provides a smooth communication, while the second is handled by cooperation mechanisms supported by the platform. Moreover, as the nodes are supposed to be heterogeneous, a customizable platform is required to support both resource rich and poorer nodes. This paper analyses surveillance systems based on a heterogeneous sensor network, which is composed by lowend ground sensor nodes and autonomous aerial robots, i.e. Unmanned Aerial Vehicles (UAVs), carrying different kinds of sensors. The approach proposed in this work tackles the two above mentioned problems by using a customizable hardware platform and a middleware to support interoperability. Experimental results are also provided

SMART: An Application Framework for Real Time Big Data Analysis on Heterogeneous Cloud Environments

International audienceThe amount of data that human activities generate poses a challenge to current computer systems. Big data processing techniques are evolving to address this challenge, with analysis increasingly being performed using cloud-based systems. Emerging services, however, require additional enhancements in order to ensure their applicability to highly dynamic and heterogeneous environments and facilitate their use by Small & Medium-sized Enterprises (SMEs). Observing this landscape in emerging computing system development, this work presents Small & Medium-sized Enterprise Data Analytic in Real Time (SMART) for addressing some of the issues in providing compute service solutions for SMEs. SMART offers a framework for efficient development of Big Data analysis services suitable to small and medium-sized organizations, considering very heterogeneous data sources, from wireless sensor networks to data warehouses, focusing on service composability for a number of domains. This paper presents the basis of this proposal and preliminary results on exploring application deployment on hybrid infrastructure

Boosting big data streaming applications in clouds with burstFlow

The rapid growth of stream applications in financial markets, health care, education, social media, and sensor networks represents a remarkable milestone for data processing and analytic in recent years, leading to new challenges to handle Big Data in real-time. Traditionally, a single cloud infrastructure often holds the deployment of Stream Processing applications because it has extensive and adaptative virtual computing resources. Hence, data sources send data from distant and different locations of the cloud infrastructure, increasing the application latency. The cloud infrastructure may be geographically distributed and it requires to run a set of frameworks to handle communication. These frameworks often comprise a Message Queue System and a Stream Processing Framework. The frameworks explore Multi-Cloud deploying each service in a different cloud and communication via high latency network links. This creates challenges to meet real-time application requirements because the data streams have different and unpredictable latencies forcing cloud providers' communication systems to adjust to the environment changes continually. Previous works explore static micro-batch demonstrating its potential to overcome communication issues. This paper introduces BurstFlow, a tool for enhancing communication across data sources located at the edges of the Internet and Big Data Stream Processing applications located in cloud infrastructures. BurstFlow introduces a strategy for adjusting the micro-batch sizes dynamically according to the time required for communication and computation. BurstFlow also presents an adaptive data partition policy for distributing incoming streams across available machines by considering memory and CPU capacities. The experiments use a real-world multi-cloud deployment showing that BurstFlow can reduce the execution time up to 77% when compared to the state-of-the-art solutions, improving CPU efficiency by up to 49%

A review and comparison of ontology-based approaches to robot autonomy

Within the next decades, robots will need to be able to execute a large variety of tasks autonomously in a large variety of environments. To relax the resulting programming effort, a knowledge-enabled approach to robot programming can be adopted to organize information in re-usable knowledge pieces. However, for the ease of reuse, there needs to be an agreement on the meaning of terms. A common approach is to represent these terms using ontology languages that conceptualize the respective domain. In this work, we will review projects that use ontologies to support robot autonomy. We will systematically search for projects that fulfill a set of inclusion criteria and compare them with each other with respect to the scope of their ontology, what types of cognitive capabilities are supported by the use of ontologies, and which is their application domain.Peer ReviewedPostprint (author's final draft

A survey on adaptable middleware for wireless sensor networks

The use of sensor networks in different kinds of sophisticated applications is emerging due to several advances in sensor technologies and embedded systems and the increased demand from users. These systems run in highly dynamic and heterogeneous environments, in which changes occur very frequently, creating the need for adaptation support to environment changes and changes imposed by the users. An approach to allow the use of sensor networks in such complex and sophisticated applications is the use of middleware, especially adaptable middleware, which provides efficient response to the environment changes, adapting the middleware behaviour according to new requirements. In this survey we present a study of the state of the art in adaptable middleware for sensor networks, in which we analyse the main trends represented by important projects in the area, analysing their main features and providing a comparison among them