Internet-enabled things and devices operating in the physical world are increasingly integrated in modern distributed systems, supporting functionalities that require assurances that certain critical requirements are satisfied by the overall system. We focus here on spatially-distributed Internet-of-Things systems such as smart environments, where the dynamics of spatial distribution of entities in the system is crucial to requirements satisfaction. Analysis techniques need to be in place while systems operate to ensure that requirements are fulfilled. This may be achieved by keeping a model of the system at runtime, monitoring events that lead to changes in the spatial environment, and performing analysis. This computationally-intensive runtime assurance method cannot be supported by resource-constrained devices that populate the space and must be offloaded to the cloud. However, challenges arise regarding resource allocation and cost, especially when the workload is unknown at the system's design time. As such, it may be difficult or even impossible to guarantee application service level agreements, e.g., on response times. To this end, we instantiate spatial verification processes, integrating them to the service layer of an IoT-cloud architecture based on microservices. We propose several cloud deployments for such an architecture for assurance of spatial requirements -- based on virtual machines, containers, and the recent Functions-as-a-Service paradigm. Then, we assess deployments' tradeoffs in terms of elasticity, performance and cost by using a workload scenario from a known dataset of taxis roaming in Beijing. We argue that the approach can be replicated in the design process of similar kinds of spatially distributed Internet-of-Things systems.
As technology proceeds and the number of smart devices continues to grow substantially, need for ubiquitous context-aware platforms that support interconnected, heterogeneous, and distributed network of devices has given rise to what is referred today as Internet-of-Things. However, paving the path for achieving aforementioned objectives and making the IoT paradigm more tangible requires integration and convergence of different knowledge and research domains, covering aspects from identification and communication to resource discovery and service integration. Through this chapter, we aim to hi…
We will offer a method to improve energy efficient consumption for processing queries on the Internet of Things. We focused on an energy efficient hierarchical clustering index tree such that we can facilitate time-correlated region queries in the I.O.T (Internet of Things). We try to improve clustering and make a change on its proposed index tree. We try to do this by optimizing the query processing. We improve clustering to increase the accuracy of the Internet of Things and prevent the network from disconnecting. In the article that we have chosen, there is a heterogeneous cluster which mea…
The chapter presents foundations of computing paradigms for realizing emerging IoT applications, especially fog and edge computing, their background, characteristics, architectures and open challenges.
The use of virtualization technologies in different contexts - such as Cloud Environments, Internet of Things (IoT), Software Defined Networking (SDN) - has rapidly increased during the last years. Among these technologies, container-based solutions own characteristics for deploying distributed and lightweight applications. This paper presents a performance evaluation of container technologies on constrained devices, in this case, on Raspberry Pi. The study shows that, overall, the overhead added by containers is negligible.
In this age of heterogeneous systems, diverse technologies are integrated to create application-specific solutions. The recent upsurge in acceptance of technologies such as cloud computing and ubiquitous Internet has cleared the path for Internet of Things (IoT). Moreover, the increasing Internet penetration with the rising use of mobile devices has inspired an era of technology that allows interfacing of physical objects and connecting them to Internet for developing applications serving a wide range of purposes. Recent developments in the area of wearable devices has led to the creation of a…
Advances in ICT are bringing into reality the vision of a large number of uniquely identifiable, interconnected objects and things that gather information from diverse physical environments and deliver the information to a variety of innovative applications and services. These sensing objects and things form the Internet of Things (IoT) that can improve energy and cost efficiency and automation in many different industry fields such as transportation and logistics, health care and manufacturing, and facilitate our everyday lives as well. IoT applications rely on real-time context data and allo…
Federated Learning (FL) has received a significant amount of attention in the industry and research community due to its capability of keeping data on local devices. To aggregate the gradients of local models to train the global model, existing works require that the global model and the local models are the same. However, Internet of Things (IoT) devices are inherently diverse regarding computation speed and onboard memory. In this paper, we propose an FL framework targeting the heterogeneity of IoT devices. Specifically, local models are compressed from the global model, and the gradients of…
Since the term first coined in 1999 by Kevin Ashton, the Internet of Things (IoT) has gained significant momentum as a technology to connect physical objects to the Internet and to facilitate machine-to-human and machine-to-machine communications. Over the past two decades, IoT has been an active area of research and development endeavours by many technical and commercial communities. Yet, IoT technology is still not mature and many issues need to be addressed. In this paper, we identify 10 key research topics and discuss the research problems and opportunities within these topics.
With the increase in Internet of Things devices and more decentralized architectures we see a new type of application gain importance, a type where local interactions between individual entities lead to a global emergent behavior, Emergent-based IoT (EBI) Systems. In this position paper we explore techniques to evaluate this emergent behavior in IoT applications. Because of the required scale and diversity this is not an easy task. Therefore, we mainly focus on a distributed simulation approach and provide an overview of possible techniques that could optimize the overall simulation performanc…
The growth in the number of devices connected to the Internet of Things (IoT) poses major challenges in security. The integrity and trustworthiness of data and data analytics are increasingly important concerns in IoT applications. These are compounded by the highly distributed nature of IoT devices, making it infeasible to prevent attacks and intrusions on all data sources. Adversaries may hijack devices and compromise their data. As a result, reactive countermeasures, such as intrusion detection and resilient analytics, become vital components of security. This paper overviews algorithms for…
This paper presents a fog-resident controller architecture for synchronizing the operations of large collections of Internet of Things (IoT) such as drones, Internet of Vehicles, etc. Synchronization in IoT is grouped into different classes, use cases identified and multi-point synchronous scheduling algorithms are developed to schedule tasks with varying timing requirements; strict (synchronous) and relaxed (asynchronous and local) onto a bunch of worker nodes that are coordinated by a fog resident controller in the presence of disconnections and worker failures. The algorithms use time-based…
In this paper, we propose a Mobile Edge Internet of Things (MEIoT) architecture by leveraging the fiber-wireless access technology, the cloudlet concept, and the software defined networking framework. The MEIoT architecture brings computing and storage resources close to Internet of Things (IoT) devices in order to speed up IoT data sharing and analytics. Specifically, the IoT devices (belonging to the same user) are associated to a specific proxy Virtual Machine (VM) in the nearby cloudlet. The proxy VM stores and analyzes the IoT data (generated by its IoT devices) in real-time. Moreover, we…
Smart Farming has brought a major transformation in the agriculture process by using the Internet of Things (IoT) devices, emerging technologies such as cloud computing, fog computing, and data analytics. It allows farmers to have real-time awareness of the farm and help them make smart and informed decisions. In this paper, we propose a distributed data flow (DDF) based model for the smart farming application that is composed of interdependent modules. We evaluate the proposed application model using two deployment strategies: cloud-based, and fog-based where the application modules are deplo…
With recent advances in radio-frequency identification (RFID), wireless sensor networks, and Web services, physical things are becoming an integral part of the emerging ubiquitous Web. Finding correlations of ubiquitous things is a crucial prerequisite for many important applications such as things search, discovery, classification, recommendation, and composition. This article presents DisCor-T, a novel graph-based method for discovering underlying connections of things via mining the rich content embodied in human-thing interactions in terms of user, temporal and spatial information. We mode…
As the population grows, the need for a quality level of medical services grows correspondingly, so does the demand for information technology in medicine. The concept of "Smart Healthcare" offers many approaches aimed at solving the acute problems faced by modern healthcare. In this paper, we review the main problems of modern healthcare, analyze existing approaches and technologies in the areas of digital twins, the Internet of Things and mobile medicine, determine their effectiveness in solving the set problems, consider the technologies that are used to monitor and treat patients and propo…
Internet of Things (IoT) is the major research filed in the recent trends. IoT has the ability to create communication with any object. IoT produces big amount of raw data at the time of data gathering. Therefore, there is a need of efficient mechanism to address the issue of IoT. This paper presents the localized MapReduce Framework for IoT. This frame work processes the data at the local nodes without transferring the data to the cloud or high end servers. The mobile agents have the ability to migrate from one node to another node for data processing, Mapper and Reducer are used for agent du…
Within the rapidly developing Internet of Things (IoT), numerous and diverse physical devices, Edge devices, Cloud infrastructure, and their quality of service requirements (QoS), need to be represented within a unified specification in order to enable rapid IoT application development, monitoring, and dynamic reconfiguration. But heterogeneities among different configuration knowledge representation models pose limitations for acquisition, discovery and curation of configuration knowledge for coordinated IoT applications. This paper proposes a unified data model to represent IoT resource conf…
Security incidents such as targeted distributed denial of service (DDoS) attacks on power grids and hacking of factory industrial control systems (ICS) are on the increase. This paper unpacks where emerging security risks lie for the industrial internet of things, drawing on both technical and regulatory perspectives. Legal changes are being ushered by the European Union (EU) Network and Information Security (NIS) Directive 2016 and the General Data Protection Regulation 2016 (GDPR) (both to be enforced from May 2018). We use the case study of the emergent smart energy supply chain to frame, s…
