Hybrid-Vehfog: A Robust Approach for Reliable Dissemination of Critical Messages in Connected Vehicles

Vehicular Ad-hoc Networks (VANET) enable efficient communication between vehicles with the aim of improving road safety. However, the growing number of vehicles in dense regions and obstacle shadowing regions like Manhattan and other downtown areas leads to frequent disconnection problems resulting in disrupted radio wave propagation between vehicles. To address this issue and to transmit critical messages between vehicles and drones deployed from service vehicles to overcome road incidents and obstacles, we proposed a hybrid technique based on fog computing called Hybrid-Vehfog to disseminate messages in obstacle shadowing regions, and multi-hop technique to disseminate messages in non-obstacle shadowing regions. Our proposed algorithm dynamically adapts to changes in an environment and benefits in efficiency with robust drone deployment capability as needed. Performance of Hybrid-Vehfog is carried out in Network Simulator (NS-2) and Simulation of Urban Mobility (SUMO) simulators. The results showed that Hybrid-Vehfog outperformed Cloud-assisted Message Downlink Dissemination Scheme (CMDS), Cross-Layer Broadcast Protocol (CLBP), PEer-to-Peer protocol for Allocated REsource (PrEPARE), Fog-Named Data Networking (NDN) with mobility, and flooding schemes at all vehicle densities and simulation times

Internet Predictions

More than a dozen leading experts give their opinions on where the Internet is headed and where it will be in the next decade in terms of technology, policy, and applications. They cover topics ranging from the Internet of Things to climate change to the digital storage of the future. A summary of the articles is available in the Web extras section

A Proposal for the Use of Wireless Technology in Healthcare

The annual healthcare cost in the United States is a staggering $2.6 trillion USD or over 17$200 billion per year. Enhancements in mobile communication devices and networks make them on par or more advanced than some of the standard instruments used in healthcare today. In addition, these devices are available at much lower costs than traditional healthcare devices. Thus, leveraging these devices and wireless networks could significantly reduce the cost of healthcare delivery and expand coverage. Wireless operators have the distribution channels and marketing capability to reach the majority of the population. Wireless operators are looking to vertical industries like healthcare for future revenue growth due to saturation in the consumer market (greater than 103% penetration). Mobile operators have networks that cover over 97% of the total US population. In addition, they have a large employee base to leverage for m-health trials. With their large employee base, mobile operators have influence over large health insurers such as United Healthcare, Wellpoint, Kaiser and others. Since healthcare insurers and the Center for Medicare and Medicaid Services influence the industry through reimbursements for services, gaining their acceptance is tantamount to success

A Flexible and Scalable Architecture for Real-Time ANT+ Sensor Data Acquisition and NoSQL Storage

Wireless Personal or Body Area Networks (WPANs or WBANs) are the main mechanisms to develop healthcare systems for an ageing society. Such systems offer monitoring, security, and caring services by measuring physiological body parameters using wearable devices. Wireless sensor networks allow inexpensive, continuous, and real-time updates of the sensor data, to the data repositories via an Internet. A great deal of research is going on with a focus on technical, managerial, economic, and social health issues. The technical obstacles, which we encounter, in general, are better methodologies, architectures, and context data storage. Sensor communication, data processing and interpretation, data interchange format, data transferal, and context data storage are sensitive phases during the whole process of body parameter acquisition until the storage. ANT+ is a proprietary (but open access) low energy protocol, which supports device interoperability by mutually agreeing upon device profile standards. We have implemented a prototype, based upon ANT+ enabled sensors for a real-time scenario. This paper presents a system architecture, with its software organization, for real-time message interpretation, event-driven based real-time bidirectional communication, and schema flexible storage. A computer user uses it to acquire and to transmit the data using a Windows service to the context server

Game-based data offloading scheme for IoT system traffic congestion problems

Internet of things (IoT) is seen as another information and industrial wave after the invention of personal computers, the Internet, and mobile communication networks. Especially, IoT/cellular network integration becomes a new service platform for the different kinds of traffic manipulation. However, due to the excessive traffic demands, it is currently facing a severe traffic overload problem. In this paper, we propose a new traffic control scheme based on the data offloading technique. By using the Vickrey-Clarke-Groves (VCG) mechanism and Rubinstein bargaining game model, our data offloading approach can effectively alleviate the IoT traffic congestion while enhancing the quality-of-service (QoS) in cellular network systems. Finally, we show the effectiveness of our proposed scheme through extensive simulations. Document type: Articl

Designing Human-Centered Collective Intelligence

Human-Centered Collective Intelligence (HCCI) is an emergent research area that seeks to bring together major research areas like machine learning, statistical modeling, information retrieval, market research, and software engineering to address challenges pertaining to deriving intelligent insights and solutions through the collaboration of several intelligent sensors, devices and data sources. An archetypal contextual CI scenario might be concerned with deriving affect-driven intelligence through multimodal emotion detection sources in a bid to determine the likability of one movie trailer over another. On the other hand, the key tenets to designing robust and evolutionary software and infrastructure architecture models to address cross-cutting quality concerns is of keen interest in the “Cloud” age of today. Some of the key quality concerns of interest in CI scenarios span the gamut of security and privacy, scalability, performance, fault-tolerance, and reliability. I present recent advances in CI system design with a focus on highlighting optimal solutions for the aforementioned cross-cutting concerns. I also describe a number of design challenges and a framework that I have determined to be critical to designing CI systems. With inspiration from machine learning, computational advertising, ubiquitous computing, and sociable robotics, this literature incorporates theories and concepts from various viewpoints to empower the collective intelligence engine, ZOEI, to discover affective state and emotional intent across multiple mediums. The discerned affective state is used in recommender systems among others to support content personalization. I dive into the design of optimal architectures that allow humans and intelligent systems to work collectively to solve complex problems. I present an evaluation of various studies that leverage the ZOEI framework to design collective intelligence

Research of the internet of things business models in Portugal

Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Information Systems and Technologies ManagementThe Internet of Things is a concept that is revolutionizing how “things” and people are interconnected nowadays. The impact it is going to create in the economy and the society is going to be immense and it will change the manner in which we do our personal and corporative daily tasks. This concept was created several years in the past when the first communication machine-to-machine was achieved and with time, the technology has been evolving to what we know as the “Internet of Things”. It is based on networks among sensors, things and people. As the IoT is so diverse, there is not a specific architecture, but several. Depends on the objective of the clients or developers, what do they want to improve or achieve by developing or implementing this technology. The main objectives are making processes as efficient as possible and gather data about several parameters such as, temperature, traffic, speed, product usage, health, machine functioning, among several others. This type of information and technology is very important for entities as it helps them positioning in the market, improve their strategy, differentiate from the competition, create more value, impact for the clients and in the decision making process. For the citizens, the IoT will help them to interact better with public services and increase their life quality, for instance. This dissertation attempts to understand what the IoT is, its architectures and the advantages and disadvantages that exist throughout its implementation. It was also investigated the impact the Internet of Things has in entities, its business models and the entities business models as well in order to understand if they remain the same or go through some changes after introducing these technologies in the entity, and the overall market and economic impact. The method used to obtain these results is based in interviews conducted to several enterprises with experience and direct contact with the IoT

Intelligent Energy Management with IoT Framework in Smart Cities Using Intelligent Analysis: An Application of Machine Learning Methods for Complex Networks and Systems

Smart buildings are increasingly using Internet of Things (IoT)-based wireless sensing systems to reduce their energy consumption and environmental impact. As a result of their compact size and ability to sense, measure, and compute all electrical properties, Internet of Things devices have become increasingly important in our society. A major contribution of this study is the development of a comprehensive IoT-based framework for smart city energy management, incorporating multiple components of IoT architecture and framework. An IoT framework for intelligent energy management applications that employ intelligent analysis is an essential system component that collects and stores information. Additionally, it serves as a platform for the development of applications by other companies. Furthermore, we have studied intelligent energy management solutions based on intelligent mechanisms. The depletion of energy resources and the increase in energy demand have led to an increase in energy consumption and building maintenance. The data collected is used to monitor, control, and enhance the efficiency of the system