Francisco José da e Silva

The Mobile Hub concept: Enabling applications for the Internet of Mobile Things

Few studies have investigated and proposed a middleware solution for the Internet of Mobile Things (IoMT), where the smart things (Smart Objects) can be moved, or else can move autonomously, and yet remain accessible and controllable remotely from any other computer over the Internet. Examples of mobile Smart Objects include vehicles of any kind, wearable devices, sensor tags, mobile robots, etc, anyhing with embedded sensors and/or actuators. In this context of general mobility of objects, mobile personal devices (smart phones, tablets, etc.) are well suited as the universal providers of Internet connectivity and location information for simpler smart objects that lack location sensors and have only short-range wireless interfaces. This paper describes Mobile Hub (M-Hub), a generic mobile middleware for IoMT, its design and prototype implementation for Android and Bluetooth. The Mobile Hub extends our previous mobile-cloud communication middleware SDDL, so that it is able to provide scalable and reliable mobile communication and data processing capabilities to mobile smart objects. Preliminary experiments have shown that our implementation of M-Hub delivers good mobility responsiveness and that the concept is suitable for IoT applications that require opportunistic discovery and connection to a variety of mobile Smart Objects.

Application execution management on the InteGrade opportunistic grid middleware

The InteGrade project is a multi-university effort to build a novel grid computing middleware based on the opportunistic use of resources belonging to user workstations. The InteGrade middleware currently enables the execution of sequential, bag-of-tasks, and parallel applications that follow the BSP or the MPI programming models. This article presents the lessons learned over the last five years of the InteGrade development and describes the solutions achieved concerning the support for robust application execution. The contributions cover the related fields of application scheduling, execution management, and fault tolerance. We present our solutions, describing their implementation principles and evaluation through the analysis of several experimental results.

Semantics-based grid resource management

Scheduling parallel and distributed applications efficiently onto grid environments is a difficult task and a great variety of scheduling heuristics have been developed aiming to address this issue. A successful grid resource allocation depends, among other things, on the quality of the available information about software artifacts and grid resources. In this paper, we propose a semantic approach to integrate selection of equivalent resources and selection of equivalent software artifacts in order to improve the schedule of resources suitable for a given set of application execution requirements. We also describe a prototype implementation of our approach based on the Integrade grid middleware and experimental results that indicate its benefits.

Developing Adaptive Distributed Applications: A Framework Overview and Experimental Results

Building self-adaptive applications is a complex and challenging task. Developers must consider several issues in addition to the implementation of the application-specific functionalities. These issues include the selection of which environment elements must be monitored for detecting when adaptations should take place, how to perform the monitoring, which software adaptations should be carried out, and when should they take place.

Adapta: a framework for dynamic reconfiguration of distributed applications

Modern computational systems are characterized by a high degree of dynamism that, along with the heterogeneity of computational devices and communication infrastructure, demand the development of a new range of applications that must be able to self-adapt dynamically and transparently according to changes in its execution environment. The Adapta framework is a reflective middleware that provides the means to develop self-adaptive component-based distributed applications, separating the business code from the code responsible for adaptation. Adapta also provides a runtime execution environment that monitors computational resources and notifies application components about the occurrence of important events that should trigger a reconfiguration mechanism. Adapta provides a XML based reconfiguration language that defines how the application must adapt in response to environmental changes. Statements of the reconfiguration language can also be applied at runtime, which allows to dynamically change the reconfiguration mechanism itself. The behavior of all framework components can also be alter dynamically through a similar approach.

MAG: a mobile agent based computational grid platform

In recent years, Grid computing has emerged as a promising alternative to the integration and sharing of multi-institutional resources. However, constructing a Grid middleware is a complex task. Developers must address several design and implementation challenges, such as: efficient management and allocation of distributed resources, dynamic task scheduling, high scalability and heterogeneity, fault tolerance, efficient mechanisms for collaborative communication among Grid nodes, and security issues. MAG (Mobile Agents for Grid Computing Environments) explores the agents paradigm as a way to overcome several of these challenges. MAG middleware executes Grid applications by dynamically loading the application code into a mobile agent. The MAG agent can be dynamically reallocated to Grid nodes though a transparent migration mechanism, as a way to provide load balancing and support for non-dedicated nodes. MAG middleware also includes mechanisms for providing fault tolerance and support for mobile clients. This paper describes MAG architecture, implementation and performance issues.

A comprehensive and scalable middleware for Ambient Assisted Living based on cloud computing and Internet of Things

Ambient Assisted Living (AAL) main goal is the development of health monitoring systems for patients with chronic diseases and elderly people through the use of body, home, and environmental sensors that increase their degree of independence and mobility. A comprehensive software infrastructure for AAL systems should be able to cover scenarios involving several patient mobility levels, locations, and physical and cognitive abilities. Cloud computing can provide to AAL systems the ability to extend the limited processing power of mobile devices, but its main role is to integrate all stakeholders through the storage and processing of health data and the orchestration of healthcare business logic. On the other hand, the Internet of Things (IoT) provides the ability to connect sensors and actuators, integrating and making them available through the Internet. This paper presents the Mobile‐Hub/Scalable Data Distribution Layer, a middleware for AAL based on cloud computing and IoT. We discuss how this middleware can handle the requirements of the main health monitoring scenarios and present results that demonstrate the ability to opportunistically discover and connect with sensors in a timely manner and the scalability necessary for handling the connection and data processing of many connected patients.

A security infrastructure for massive mobile data distribution

Many modern mobile applications have to address the challenge of enabling communication and managing a very large amount of mobile nodes. Examples of those applications include fleet management, workforce coordination, Intelligent Transportation Systems, cooperative mobile robots, rescue and emergency management, and environmental surveillance. Data distribution is an essential part of those systems, and the data traffic often contains sensitive information - thus enforcing the need of the CIA triad (confidentiality, integrity and availability). This work presents a data distribution layer based on the OMG DDS standard, developed to enforce CIA for data distribution through the usage of PKI and symmetric cryptography. This layer provides all required PKI-related functionality and symmetric key management, offering mobile devices an affordable data distribution solution.

A Middleware with Comprehensive Quality of Context Support for the Internet of Things Applications

Context aware systems are able to adapt their behavior according to the environment in which the user is. They can be integrated into an Internet of Things (IoT) infrastructure, allowing a better perception of the user’s physical environment by collecting context data from sensors embedded in devices known as smart objects. An IoT extension called the Internet of Mobile Things (IoMT) suggests new scenarios in which smart objects and IoT gateways can move autonomously or be moved easily. In a comprehensive view, Quality of Context (QoC) is a term that can express quality requirements of context aware applications. These requirements can be those related to the quality of information provided by the sensors (e.g., accuracy, resolution, age, validity time) or those referring to the quality of the data distribution service (e.g, reliability, delay, delivery time). Some functionalities of context aware applications and/or decision-making processes of these applications and their users depend on the level of quality of context available, which tend to vary over time for various reasons. Reviewing the literature, it is possible to verify that the quality of context support provided by IoT-oriented middleware systems still has limitations in relation to at least four relevant aspects: (i) quality of context provisioning; (ii) quality of context monitoring; (iii) support for heterogeneous device and technology management; (iv) support for reliable data delivery in mobility scenarios. This paper presents two main contributions: (i) a state-of-the-art survey specifically aimed at analyzing the middleware with quality of context support and; (ii) a new middleware with comprehensive quality of context support for Internet of Things Applications. The proposed middleware was evaluated and the results are presented and discussed in this article, which also shows a case study involving the development of a mobile remote patient monitoring application that was developed using the proposed middleware. This case study highlights how middleware components were used to meet the quality of context requirements of the application. In addition, the proposed middleware was compared to other solutions in the literature.

Situation-based privacy autonomous management for mobile social networks

As On-line Social Networks are nowadays largely used by mobile users and their posts potentially reveal - either explicitly or implicitly - much sensitive information about users, privacy control becomes a fundamental issue in such Mobile Social Networks (MSNs). In this paper we advocate that situational computing is the key ingredient for the development of effective mechanisms for privacy control in MSNs. We first describe an on-line survey carried out in order to understand the user’s requirements regarding privacy when using MSNs. The results suggest that users have dynamic and context-dependent privacy requirements and also pinpoints which types of context data are more relevant for the decision about the user’s willingness to share MSN content. Based on these findings, we propose SelPri, a solution developed as a proof of concept in form of an Android mobile social application that is integrated with Facebook. SelPri employs Fuzzy Logic to autonomously and dynamically adapt privacy settings of posts in MSNs according to the user’s current situation, freeing the user from the hassle of the manual configuration of the privacy settings whenever his/her situation changes. We also describe conducted evaluations of the user experience in using SelPri to assess its accuracy to identify user situations, and its usability and effectiveness in meeting the user’s dynamic and contextual privacy requirements.