Anubis Graciela de Moraes Rossetto

Situation awareness and computational intelligence in opportunistic networks to support the data transmission of urban sensing applications

Abstract Smart cities can be seen as large-scale Cyber-Physical Systems with sensors monitoring cyber and physical indicators and with actuators dynamically changing the complex urban environment in some way. In this context, urban sensing is a new paradigm that exploits human-carried or vehicle-mounted sensors to ubiquitously collect data to provide a holistic view of the city. A challenge in this scenario is the transmission of sensed data in situations where the networking infrastructure is intermittent or unavailable. This paper outlines our research into an engine that uses opportunistic networks to support the data transmission of urban sensing applications. It applies situation awareness and computational intelligence approaches to perform routing, adaptation, and decision-making procedures. We carried out simulations within a simulated environment that showed our engine had 12% less overhead than other compared approaches.

A failure detector that gives information on the degree of confidence in the system

This work proposes a new and flexible unreliable failure detector, denoted Impact Failure Detector (FD), whose output gives the trust level of a set of processes. By expressing the relevance of each node by an impact factor value as well as an acceptable margin of failure in the system, the Impact FD enables the user to tune the failure detection configuration in accordance with the requirements of the application: in some scenarios, the failure of low impact or redundant nodes does not jeopardize the confidence in the system, while the crash resulting from a high impact factor may seriously affect it. Either a softer or stricter monitoring is thus possible. Performance evaluation results using real PlanetLab [1] traces confirm the degree of flexibility of our failure detector and that, due to the margin of failure, the number of false responses may be reduced when it is compared with traditional unreliable failure detectors.

An Architecture for Resilient Ubiquitous Systems

With the perspective of ubiquitous computing becoming more common form of technology in our everyday lives, our increasing dependency on these systems will require them to be always available, failure-free, fully operational and safe. They will also enable more activities to be carried out and provide new opportunities for solving problems. In view of the potential offered by ubiquitous computing and the challenges it raises, this work proposes a self-healing architecture to support ubiquitous applications aimed at healthcare The goal is to continuously provide reliable services to meet their requirements despite changes in the environment. We outline the application scenario and proposed architecture, as well as giving a detailed account of its main modules with particular emphasis on the fault detector.

An adaptive fault tolerance approach to enhance the execution of applications on multi-cluster grid configurations from mobile grid interfaces in wireless networks

Mobile grid environments can be broadly divided into two different types of configurations. In the first case, devices are used as grid interfaces. In the second configuration, mobile devices are considered to be grid resources. However, the interaction between mobile devices and wired networks still has to overcome several difficulties before it can produce an operational mobile grid infrastructure, in either type of configuration. Examples of these challenges include the submission of distributed applications to execute tasks in a coordinated manner, frequent disconnections, restrictions on power consumption and the selection of suitable grid resources for application executions. In this paper, a research study is conducted involving an adaptive fault tolerance approach for grid interfaces in wireless networks to enhance the submission and execution of distributed applications. The approach examines submission, monitoring and management functions through the use of fault tolerance and workflow mechanisms, especially when disconnections occur and the mobile devices are executing an application. The empirical results show that the proposed approach can achieve a satisfactory level to support grid interfaces in a wireless network, and provide a more robust environment for application executions with less power.

An ubiquitous service-oriented architecture for urban sensing

In the transformation from traditional to smart cities, there is an increasing trend around the world towards intelligent dynamic infrastructures that provide citizens with new services that can improve their quality of life and fulfill the criteria of energy efficiency and sustainability. In the light of this, an important challenge is how to enable citizens and cities to promote the sensing of data with regard to a number of different factors. This paper outlines the early stages of our research which is concerned with an ubiquitous service-oriented architecture for urban sensing called UrboSenti. The proposed approach differs from other sensing platforms since it provides a set of services to collect data from several sources and assists in the development of new sensing applications. In addition, our model encompasses all the sensing activities, ranging from the collection of data to the generation of reports about events in the city.

MultiS: A Context-Server for Pervasive Computing

Context-aware applications are capable of recognizing environmental changes and adapting their behavior to the new context. This process can be divided into three stages: monitoring, context recognition and adaptation. On the monitoring layer, raw information about the environment is collected from sensors. The context recognition layer processes the data acquired from the context and transforms it into information which can be useful for the adaptation process. With this information, the adaptation system can determine what behavior is correct for the application in each different context. This paper proposes a context server called MultiS, which has the goal of solving the problems arising from the context recognition layer, and which includes the following advantages: a) the production of new context data based on the information of several sensors and an ability to react to changes in the environment; b) definition of a composed language for the context data called CD-XML; c) support for mobility.

Implementing a Flexible Failure Detector That Expresses the Confidence in the System

Traditional unreliable failure detectors are per process oracles that provide a list of nodes suspected of having failed. In [Rossetto et al., 2015], we introduced the Impact failure detector that outputs a trust level value which is the degree of confidence in the system. An impact factor is assigned to each node and an input threshold parameter defines an impact factor limit value, over which the confidence degree on the system is ensured. The impact factor indicates the relative importance of the process in the set S, while the threshold offers a degree of flexibility for failures and false suspicions. We propose in this article two different algorithms, based on query-response message rounds, that implement the Impact FD whose conceptions were tailored to satisfy the Impact FDs flexibility. The first one exploits the time-free message pattern approach while the second one considers a set of bounded timely responses. We also introduced the concept that a process can be PS-accessible (or PS-accessible) which guarantees that the system S will always (or eventually always) be trusted by this process as well as two properties, PR(ITsp*) and PR(ITsp*), that characterize the stability conditions which ensure the confidence (or eventual confidence) of process p on S. In both implementations, if the process that monitors S is PS-accessible or PS-accessible, at every query round, it only waits (or eventually only waits) for a set of responses that satisfy the threshold. A crucial facet of this set of processes is that it is not fixed, i.e., the set of processes can change at each round, which is in accordance with the flexibility feature of the Impact FD.

A novel engine to underlie the data transmission of social urban sensing applications

Social urban sensing is a new paradigm which exploits human-carried or vehicle-mounted sensors to ubiquitously collect data for large-scale urban sensing. A challenge of such scenario is how to transmit sensed data in situations where the networking infrastructure is intermittent or unavailable. In this context, this paper outlines our researches of a novel engine that uses Opportunistic Networks paradigm to underlie the data transmission of social urban sensing applications. It applies Situation awareness, Fuzzy logic and Machine Learning approaches to perform routing and decision-making process. As we know, this is the first paper to use such approaches in Smart Cities area with focus on social sensing application. As well as being original, the results from our simulations signals the way that further research can be carried out in this area.

Towards a Novel Engine to Underlie the Data Transmission of Social Urban Sensing Applications

Social urban sensing is a new paradigm which exploits human-carried or vehicle-mounted sensors to ubiquitously collect data for large-scale urban sensing. A challenge of such scenario is how to transmit sensed data in situations where the networking infrastructure is intermittent or unavailable. In this context, this paper outlines the early stages of our research which is concerned with a novel engine that uses Opportunistic Networks paradigm to underlie the data transmission of social urban sensing applications. It applies Situation awareness, Neural Networks and Fuzzy Logic for routing and decision-making process. As we know, this is the first paper to use such approaches in Smart Cities area with focus on social sensing application. As well as being original, the preliminary results from our simulations signals the way that further research can be carried out in this area.