Cristyan Manta-Caro

The Internet of Things is a novel and promising paradigm already being part of some of our daily activities. At the end of this year, the Internet will connect about 7 billion smart things. They are part of solutions ranging from Smart Cities to telemetry collection for Industrial applications generating a colossal amount of real-time streaming data. Cloud-based services have also being evolved from pure IaaS providing Virtual Machines to sophisticated PaaS, SaaS, and FaaS designed explicitly for Big Data, Analytics and IoT, they all exhibiting serverless architectures. Moreover, Information Retrieval (IR) is becoming a crucial application layer on top of IoT application for searching and retrieving relevant data on the real-time streaming collections, on sensors, or things. In the last years, a significant set of approaches have been explored IoT, Big Data, and IoT Search Engines. However, the cybersecurity has not been meticulously researched. Neither for IoT nor IR, as a critical component at searching on the IoT. In this paper, we present an approach to consider cybersecurity as an IR dimension for cloud-based edge-powered searching over IoT from a theoretical perspective, we compare through a compact survey the related works and finalise with a multi-perspective discussion to embrace cybersecurity in the IoT/IoTSE architectures.

Internet and Web technologies have changed our lives in ways we are not yet fully aware of. In the near future, Internet will interconnect more than 50 billion things in the real world, nodes will sense billions of features and properties of interest, and things will be represented by web-based, bi-directional services with highly dynamic content and real-time data. This is the new era of the Internet and the Web of Things . Since the emergence of such paradigms implies the evolution and integration of the systems with which they interact, it is essential to develop abstract models for representing and simulating the Web of Things in order to establish new approaches. This article describes a Web of Things model based on a structured XML representation. We also present a simulator whose ultimate goal is to encapsulate the expected dynamics of the Web of Things for the future development of information retrieval (IR) systems. The simulator generates a real-time collection of XML documents containing spatio-temporal contexts and textual and sensed information of highly dynamic dimensions. The simulator is characterized by its flexibility and versatility for representing real-world scenarios and offers a unique perspective for information retrieval. In this article, we evaluate and test the simulator in terms of its performance variables for computing resource consumption and present our experimentation with the simulator on three real scenarios by considering the generation variables for the IR document collection.

Real-time indexing is a core component in retrieval systems and search services of any type in complex domains ranging from analytics to the Web of Things. As greatest challenges, the efficiency, scalability, and performance are central factors to consider at any level when designing or building an index. The multidimensional characteristics of data exposed by smart things interacting with the World concerning volume, velocity, variety, and volatility (4V) leverage advances and research in models and techniques for the indexing process. We present a state-of-the-art regarding them focusing on the Web of Things and related research areas such as Big data. Furthermore, we propose a methodology for comparing them and some guidelines for designing real-time indexes for the Web of Things. Our novel approach brings together the recent advances in traditional domains and adjusts models and techniques for the emerging Web of Things.

The Cloud age, characterized by a revolution of Data center infrastructures with powerful resources, has leveraged the "as-a-service" paradigms. Nowadays, the Web of Things (WoT) proposes the abstraction of real world entities in a virtual Web avatar, to acquire, process and present real-time information with the ability to connect with the real-world, and to control real things. A new generation of services can arise from these complementary paradigms. One of them is crucial for a daily basis interaction with this new smart world, Information Retrieval (IR), mostly in the form of search engines can also evolve into more powerful tools. Based on that, a new architecture of this kind of services has to be defined by the synergy and challenges that WoT imposes. We propose an IR as a service IRaaS architecture for the new era of the Web of Things. It considers the high dynamics in WoT which leverages a significant amount of changes in the IR collection to merge efficiently conventional IR concepts and the cloud power. Our IRaaS approach takes into account the big-data characteristics of WoT concerning velocity, volume, volatility, and the variety of data. The architecture has two main pillars: the indexing and analysis block, and the querying and retrieval block. We propose building it driven in three dimensions: search scope, resources, and data type. From these perspectives, we show and compare the related works and researches.

Simulators are an essential tool for researching and developing new systems, architectures or protocols. They have played a key role in the history of the Internet and the Web. This paper highlights the view that the simulation-based research will continue to take part in the evolution of paradigms associated with the Internet and the Web of Things. In this work, we present a simulator whose ultimate goal is to encapsulate the model and the expected dynamics of the Web of Things, for the development of Information Retrieval systems given the new evolutionary challenges to face. The simulation model is based on the automatic generation of a collection of XML documents, which contain spatio-temporal contexts and extensive textual information with highly dynamic dimensions. The simulator is characterized among other proposals for its flexibility and versatility to represent different real-world scenarios, constructed from entities with generic qualities and a unique perspective from information retrieval.