Security and Privacy for Green IoT-based Agriculture: Review, Blockchain solutions, and Challenges

open access articleThis paper presents research challenges on security and privacy issues in the field of green IoT-based agriculture. We start by describing a four-tier green IoT-based agriculture architecture and summarizing the existing surveys that deal with smart agriculture. Then, we provide a classification of threat models against green IoT-based agriculture into five categories, including, attacks against privacy, authentication, confidentiality, availability, and integrity properties. Moreover, we provide a taxonomy and a side-by-side comparison of the state-of-the-art methods toward secure and privacy-preserving technologies for IoT applications and how they will be adapted for green IoT-based agriculture. In addition, we analyze the privacy-oriented blockchain-based solutions as well as consensus algorithms for IoT applications and how they will be adapted for green IoT-based agriculture. Based on the current survey, we highlight open research challenges and discuss possible future research directions in the security and privacy of green IoT-based agriculture

Middleware Technologies for Cloud of Things - a survey

The next wave of communication and applications rely on the new services provided by Internet of Things which is becoming an important aspect in human and machines future. The IoT services are a key solution for providing smart environments in homes, buildings and cities. In the era of a massive number of connected things and objects with a high grow rate, several challenges have been raised such as management, aggregation and storage for big produced data. In order to tackle some of these issues, cloud computing emerged to IoT as Cloud of Things (CoT) which provides virtually unlimited cloud services to enhance the large scale IoT platforms. There are several factors to be considered in design and implementation of a CoT platform. One of the most important and challenging problems is the heterogeneity of different objects. This problem can be addressed by deploying suitable "Middleware". Middleware sits between things and applications that make a reliable platform for communication among things with different interfaces, operating systems, and architectures. The main aim of this paper is to study the middleware technologies for CoT. Toward this end, we first present the main features and characteristics of middlewares. Next we study different architecture styles and service domains. Then we presents several middlewares that are suitable for CoT based platforms and lastly a list of current challenges and issues in design of CoT based middlewares is discussed.Comment: http://www.sciencedirect.com/science/article/pii/S2352864817301268, Digital Communications and Networks, Elsevier (2017

Middleware Technologies for Cloud of Things - a survey

The next wave of communication and applications rely on the new services provided by Internet of Things which is becoming an important aspect in human and machines future. The IoT services are a key solution for providing smart environments in homes, buildings and cities. In the era of a massive number of connected things and objects with a high grow rate, several challenges have been raised such as management, aggregation and storage for big produced data. In order to tackle some of these issues, cloud computing emerged to IoT as Cloud of Things (CoT) which provides virtually unlimited cloud services to enhance the large scale IoT platforms. There are several factors to be considered in design and implementation of a CoT platform. One of the most important and challenging problems is the heterogeneity of different objects. This problem can be addressed by deploying suitable "Middleware". Middleware sits between things and applications that make a reliable platform for communication among things with different interfaces, operating systems, and architectures. The main aim of this paper is to study the middleware technologies for CoT. Toward this end, we first present the main features and characteristics of middlewares. Next we study different architecture styles and service domains. Then we presents several middlewares that are suitable for CoT based platforms and lastly a list of current challenges and issues in design of CoT based middlewares is discussed.Comment: http://www.sciencedirect.com/science/article/pii/S2352864817301268, Digital Communications and Networks, Elsevier (2017

Learning and Management for Internet-of-Things: Accounting for Adaptivity and Scalability

Internet-of-Things (IoT) envisions an intelligent infrastructure of networked smart devices offering task-specific monitoring and control services. The unique features of IoT include extreme heterogeneity, massive number of devices, and unpredictable dynamics partially due to human interaction. These call for foundational innovations in network design and management. Ideally, it should allow efficient adaptation to changing environments, and low-cost implementation scalable to massive number of devices, subject to stringent latency constraints. To this end, the overarching goal of this paper is to outline a unified framework for online learning and management policies in IoT through joint advances in communication, networking, learning, and optimization. From the network architecture vantage point, the unified framework leverages a promising fog architecture that enables smart devices to have proximity access to cloud functionalities at the network edge, along the cloud-to-things continuum. From the algorithmic perspective, key innovations target online approaches adaptive to different degrees of nonstationarity in IoT dynamics, and their scalable model-free implementation under limited feedback that motivates blind or bandit approaches. The proposed framework aspires to offer a stepping stone that leads to systematic designs and analysis of task-specific learning and management schemes for IoT, along with a host of new research directions to build on.Comment: Submitted on June 15 to Proceeding of IEEE Special Issue on Adaptive and Scalable Communication Network

IoT@run-time: a model-based approach to support deployment and self-adaptations in IoT systems

Today, most Internet of Things (IoT) systems leverage edge and fog computing to meet increasingly restrictive requirements and improve quality of service (QoS). Although these multi-layer architectures can improve system performance, their design is challenging because the dynamic and changing IoT environment can impact the QoS and system operation. In this thesis, we propose a modeling-based approach that addresses the limitations of existing studies to support the design, deployment, and management of self-adaptive IoT systems. We have designed a domain specific language (DSL) to specify the self-adaptive IoT system, a code generator that generates YAML manifests for the deployment of the IoT system, and a framework based on the MAPE-K loop to monitor and adapt the IoT system at runtime. Finally, we have conducted several experimental studies to validate the expressiveness and usability of the DSL and to evaluate the ability and performance of our framework to address the growth of concurrent adaptations on an IoT system.Hoy en día, la mayoría de los sistemas de internet de las cosas (IoT, por su sigla en inglés) aprovechan la computación en el borde (edge computing) y la computación en la niebla (fog computing) para cumplir requisitos cada vez más restrictivos y mejorar la calidad del servicio. Aunque estas arquitecturas multicapa pueden mejorar el rendimiento del sistema, diseñarlas supone un reto debido a que el entorno de IoT dinámico y cambiante puede afectar a la calidad del servicio y al funcionamiento del sistema. En esta tesis proponemos un enfoque basado en el modelado que aborda las limitaciones de los estudios existentes para dar soporte en el diseño, el despliegue y la gestión de sistemas de IoT autoadaptables. Hemos diseñado un lenguaje de dominio específico (DSL) para modelar el sistema de IoT autoadaptable, un generador de código que produce manifiestos YAML para el despliegue del sistema de IoT y un marco basado en el bucle MAPE-K para monitorizar y adaptar el sistema de IoT en tiempo de ejecución. Por último, hemos llevado a cabo varios estudios experimentales para validar la expresividad y usabilidad del DSL y evaluar la capacidad y el rendimiento de nuestro marco para abordar el crecimiento de las adaptaciones concurrentes en un sistema de IoT.Avui dia, la majoria dels sistemes d'internet de les coses (IoT, per la sigla en anglès) aprofiten la informàtica a la perifèria (edge computing) i la informàtica a la boira (fog computing) per complir requisits cada cop més restrictius i millorar la qualitat del servei. Tot i que aquestes arquitectures multicapa poden millorar el rendiment del sistema, dissenyar-les suposa un repte perquè l'entorn d'IoT dinàmic i canviant pot afectar la qualitat del servei i el funcionament del sistema. En aquesta tesi proposem un enfocament basat en el modelatge que aborda les limitacions dels estudis existents per donar suport al disseny, el desplegament i la gestió de sistemes d'IoT autoadaptatius. Hem dissenyat un llenguatge de domini específic (DSL) per modelar el sistema d'IoT autoadaptatiu, un generador de codi que produeix manifestos YAML per al desplegament del sistema d'IoT i un marc basat en el bucle MAPE-K per monitorar i adaptar el sistema d'IoT en temps d'execució. Finalment, hem dut a terme diversos estudis experimentals per validar l'expressivitat i la usabilitat del DSL i avaluar la capacitat i el rendiment del nostre marc per abordar el creixement de les adaptacions concurrents en un sistema d'IoT.Tecnologies de la informació i de xarxe