scholarly journals Swinging Door Trending Compression Algorithm for IoT Environments

2019 ◽  
Author(s):  
Juan David Arias Correa ◽  
Alex Sandro Roschildt Pinto ◽  
Carlos Montez ◽  
Erico Leão
Keyword(s):  
Data Compression ◽  
Communication Channel ◽  
Small Contribution ◽  
Essential Components ◽  
Major Parameter ◽  
Application Data ◽  
Iot Devices ◽  
And Storage ◽  
The Internet Of Things ◽  
Calibration Step

The transmission and storage of data collected by the devices are essential components of the Internet of Things (IoT). When devices send unnecessary or redundant information, it spends more energy, unnecessarily using the communication channel, besides processing at the destination, data that make a small contribution to the application. Data compression is a possible solution for the significant quantity of information generated by IoT devices. Data compression is the process of reducing the quantity of data necessary to represent some volume of data. This paper proposes the use of Swinging Door Trending (SDT) into an IoT environment and a new calibration step to select its major parameter: the compression deviation. A prototype was built, and experimental results show the effectivity of the proposal.

IoT Data Compression and Optimization Techniques in Cloud Storage

2019 ◽  
Vol 9 (2) ◽  
pp. 43-59 ◽  
Author(s):  
Kaium Hossain ◽  
Mizanur Rahman ◽  
Shanto Roy
Keyword(s):  
Data Compression ◽  
Cloud Storage ◽  
Smart Home ◽  
Optimization Techniques ◽  
Future Perspectives ◽  
Future Directions ◽  
Storage Optimization ◽  
Iot Devices ◽  
And Storage ◽  
The Internet Of Things

This article presents a detailed survey on different data compression and storage optimization techniques in the cloud, their implications, and discussion over future directions. The development of the smart city or smart home systems lies in the development of the Internet of Things (IoT). With the increasing number of IoT devices, the tremendous volume of data is being generated every single day. Therefore, it is necessary to optimize the system's performance by managing, compressing and mining IoT data for smart decision support systems. In this article, the authors surveyed recent approaches with up-to-date outcomes and findings related to the management, mining, compression, and optimization of IoT data. The authors then discuss the scopes and limitations of present works and finally, this article presents the future perspectives of IoT data management on basis of cloud, fog, and mobile edge computing.

scholarly journals Transparent CoAP Services to IoT Endpoints through ICN Operator Networks

Sensors ◽  
2019 ◽  
Vol 19 (6) ◽  
pp. 1339 ◽  
Author(s):  
Hasan Islam ◽  
Dmitrij Lagutin ◽  
Antti Ylä-Jääski ◽  
Nikos Fotiou ◽  
Andrei Gurtov
Keyword(s):  
Storage Capacity ◽  
Communication Overhead ◽  
Full Potential ◽  
Core Network ◽  
Computation Complexity ◽  
State Management ◽  
Iot Devices ◽  
Novel Applications ◽  
And Storage ◽  
The Internet Of Things

The Constrained Application Protocol (CoAP) is a specialized web transfer protocol which is intended to be used for constrained networks and devices. CoAP and its extensions (e.g., CoAP observe and group communication) provide the potential for developing novel applications in the Internet-of-Things (IoT). However, a full-fledged CoAP-based application may require significant computing capability, power, and storage capacity in IoT devices. To address these challenges, we present the design, implementation, and experimentation with the CoAP handler which provides transparent CoAP services through the ICN core network. In addition, we demonstrate how the CoAP traffic over an ICN network can unleash the full potential of the CoAP, shifting both overhead and complexity from the (constrained) endpoints to the ICN network. The experiments prove that the CoAP Handler helps to decrease the required computation complexity, communication overhead, and state management of the CoAP server.

scholarly journals A Conceptual Architecture in Decentralizing Computing, Storage, and Networking Aspect of IoT Infrastructure

IoT ◽  
2021 ◽  
Vol 2 (2) ◽  
pp. 205-221
Author(s):  
Yustus Eko Oktian ◽  
Elizabeth Nathania Witanto ◽  
Sang-Gon Lee
Keyword(s):  
Overlay Networks ◽  
Distributed Storage ◽  
Internet Service ◽  
Computing Platform ◽  
Smart Contract ◽  
Secure Computing ◽  
Storage Network ◽  
Application Data ◽  
Iot Devices ◽  
The Internet Of Things

Since the inception of the Internet of Things (IoT), we have adopted centralized architecture for decades. With the vastly growing number of IoT devices and gateways, this architecture struggles to cope with the high demands of state-of-the-art IoT services, which require scalable and responsive infrastructure. In response, decentralization becomes a considerable interest among IoT adopters. Following a similar trajectory, this paper introduces an IoT architecture re-work that enables three spheres of IoT workflows (i.e., computing, storage, and networking) to be run in a distributed manner. In particular, we employ the blockchain and smart contract to provide a secure computing platform. The distributed storage network maintains the saving of IoT raw data and application data. The software-defined networking (SDN) controllers and SDN switches exist in the architecture to provide connectivity across multiple IoT domains. We envision all of those services in the form of separate yet integrated peer-to-peer (P2P) overlay networks, which IoT actors such as IoT domain owners, IoT users, Internet Service Provider (ISP), and government can cultivate. We also present several IoT workflow examples showing how IoT developers can adapt to this new proposed architecture. Based on the presented workflows, the IoT computing can be performed in a trusted and privacy-preserving manner, the IoT storage can be made robust and verifiable, and finally, we can react to the network events automatically and quickly. Our discussions in this paper can be beneficial for many people ranging from academia, industries, and investors that are interested in the future of IoT in general.

scholarly journals S×C4IoT: A Security-by-contract Framework for Dynamic Evolving IoT Devices

2022 ◽  
Vol 18 (1) ◽  
pp. 1-51
Author(s):  
Alberto Giaretta ◽  
Nicola Dragoni ◽  
Fabio Massacci
Keyword(s):  
Fog Computing ◽  
Life Cycles ◽  
Information Flows ◽  
Storage Space ◽  
Proof Of Concept ◽  
Human Beings ◽  
The Past ◽  
Iot Devices ◽  
And Storage ◽  
The Internet Of Things

The Internet of Things (IoT) revolutionised the way devices, and human beings, cooperate and interact. The interconnectivity and mobility brought by IoT devices led to extremely variable networks, as well as unpredictable information flows. In turn, security proved to be a serious issue for the IoT, far more serious than it has been in the past for other technologies. We claim that IoT devices need detailed descriptions of their behaviour to achieve secure default configurations, sufficient security configurability, and self-configurability. In this article, we propose S×C4IoT, a framework that addresses these issues by combining two paradigms: Security by Contract (S×C) and Fog computing. First, we summarise the necessary background such as the basic S×C definitions. Then, we describe how devices interact within S×C4IoT and how our framework manages the dynamic evolution that naturally result from IoT devices life-cycles. Furthermore, we show that S×C4IoT can allow legacy S×C-noncompliant devices to participate with an S×C network, we illustrate two different integration approaches, and we show how they fit into S×C4IoT. Last, we implement the framework as a proof-of-concept. We show the feasibility of S×C4IoT and we run different experiments to evaluate its impact in terms of communication and storage space overhead.

scholarly journals QoS-aware CR-BM-based hybrid framework to improve the fault tolerance of fog devices

2021 ◽  
Vol 19 (1) ◽  
pp. 66-76
Author(s):  
P. Sharma ◽  
P. K. Gupta
Keyword(s):  
Fault Tolerance ◽  
Performance Metrics ◽  
Fault Tolerant ◽  
Optimal Placement ◽  
Smart Devices ◽  
Computation Cost ◽  
Hybrid Framework ◽  
Iot Devices ◽  
And Storage ◽  
The Internet Of Things

With the evolution of the Internet of Things (IoT), the use of smart devices has completely changed the day-to-day life of the human being. IoT devices are of flexible use which is implemented to sense the environment and data efficiently. However, these devices have some constrained capabilities concerning fault tolerance, computation cost, and storage. This requires an improved framework and algorithms for performing effective operations. In this paper, a hybrid framework is proposed, which incorporates the various IoT devices in fog environments to enhance fault tolerance. The proposed framework implements a novel QoS-aware technique based on the combination of checkpoints and replication (CR) for diagnosing faults and the bee-mutation (BM) algorithm for optimal placement of service. A fog service monitor is established to observe the performance of fog nodes. Both the CR module and BM module access the service monitor to ensure that the proposed hybrid framework is fault-tolerant. Furthermore, the proposed CR-BM-based hybrid framework has been evaluated for its performance by using various performance metrics. In the comparative analysis, it is observed that the proposed hybrid framework outperforms the existing genetic algorithm-based framework.

Blockchain Technology Integration in IoT and Applications

2020 ◽  
pp. 231-263
Author(s):  
Bhanu Chander
Keyword(s):  
Measured Data ◽  
The Internet ◽  
Future Directions ◽  
Security Issues ◽  
Blockchain Technology ◽  
Comprehensive Knowledge ◽  
Current Scenario ◽  
Iot Devices ◽  
And Storage ◽  
The Internet Of Things

The Internet of Things (IoT) pictures an entire connected world, where things or devices are proficient to exchange a few measured data words and interrelate with additional things. This turns for a feasible digital demonstration of the existent world. Nonetheless, nearly all IoT things are simple to mistreat or compromise. Moreover, IoT devices are restricted in computation, power, and storage, so they are more vulnerable to bugs and attacks than endpoint devices like smartphones, tablets, and computers. Blockchain has remarkable interest from academics and industry because of its salient features including reduced dependencies on third parties, cryptographic security, immutability, decentralized nature, distributed nature, and anonymity. In the current scenario, blockchain with its features provides an anonymous framework for IoT. This chapter produces comprehensive knowledge of IoTs, Blockchain knowledge, security issues, Blockchain integration with IoT (BIoT), consensus, mining, message validation mechanisms, challenges, a solution, and future directions.

CYBER SECURITY AND INTERNET OF THINGS

2018 ◽  
Vol 7 (1) ◽  
Author(s):  
Muhammad Saad ◽  
Tariq Rahim Soomro
Keyword(s):  
Internet Of Things ◽  
Cyber Security ◽  
The Internet ◽  
Vital Part ◽  
Privacy Threats ◽  
Security Challenges ◽  
Standard Solution ◽  
Iot Devices ◽  
And Storage ◽  
The Internet Of Things

Internet has become a vital part of our lives. The number of Internet connected devices are increasing every day and approximate there will be 34 billion IoT devices by 2020. It is observed that security is very weak in these devices and can be easily compromised by hackers as some manufactures failed to implement basic security. Current devices use standards that are easy to implement and works for most forms of communications and storage. There is no such standard solution that will work on every device within the Internet of Things, because of the varied constraints between different devices; resulting in classifications within the Internet of Things. This study addresses security challenges in the Internet of Things (IoT); first will discuss the IoT evolution, architecture and its applications in industries. Further, classify and examine privacy threats, including survey, and pointing out the challenges that need to be overcome to ensure that the Internet of Things becomes a reality.

Agricultural Application of Web of Things Architecture

Impact ◽  
2019 ◽  
Vol 2019 (10) ◽  
pp. 61-63 ◽  
Author(s):  
Akihiro Fujii
Keyword(s):  
Internet Of Things ◽  
Agricultural Sector ◽  
Electronic Device ◽  
Specific Work ◽  
Science And Engineering ◽  
Unique Identifier ◽  
Agricultural Application ◽  
Iot Devices ◽  
The Internet Of Things ◽  
Type Pressure

The Internet of Things (IoT) is a term that describes a system of computing devices, digital machines, objects, animals or people that are interrelated. Each of the interrelated 'things' are given a unique identifier and the ability to transfer data over a network that does not require human-to-human or human-to-computer interaction. Examples of IoT in practice include a human with a heart monitor implant, an animal with a biochip transponder (an electronic device inserted under the skin that gives the animal a unique identification number) and a car that has built-in sensors which can alert the driver about any problems, such as when the type pressure is low. The concept of a network of devices was established as early as 1982, although the term 'Internet of Things' was almost certainly first coined by Kevin Ashton in 1999. Since then, IoT devices have become ubiquitous, certainly in some parts of the world. Although there have been significant developments in the technology associated with IoT, the concept is far from being fully realised. Indeed, the potential for the reach of IoT extends to areas which some would find surprising. Researchers at the Faculty of Science and Engineering, Hosei University in Japan, are exploring using IoT in the agricultural sector, with some specific work on the production of melons. For the advancement of IoT in agriculture, difficult and important issues are implementation of subtle activities into computers procedure. The researchers challenges are going on.

scholarly journals A novel approach for IoT tasks offloading in edge-cloud environments

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Jaber Almutairi ◽  
Mohammad Aldossary
Keyword(s):  
Service Time ◽  
Edge Computing ◽  
Cloud System ◽  
Novel Approach ◽  
Delay Sensitivity ◽  
Cloud Environments ◽  
Application Characteristics ◽  
Iot Devices ◽  
Computational Resources ◽  
And Storage

AbstractRecently, the number of Internet of Things (IoT) devices connected to the Internet has increased dramatically as well as the data produced by these devices. This would require offloading IoT tasks to release heavy computation and storage to the resource-rich nodes such as Edge Computing and Cloud Computing. Although Edge Computing is a promising enabler for latency-sensitive related issues, its deployment produces new challenges. Besides, different service architectures and offloading strategies have a different impact on the service time performance of IoT applications. Therefore, this paper presents a novel approach for task offloading in an Edge-Cloud system in order to minimize the overall service time for latency-sensitive applications. This approach adopts fuzzy logic algorithms, considering application characteristics (e.g., CPU demand, network demand and delay sensitivity) as well as resource utilization and resource heterogeneity. A number of simulation experiments are conducted to evaluate the proposed approach with other related approaches, where it was found to improve the overall service time for latency-sensitive applications and utilize the edge-cloud resources effectively. Also, the results show that different offloading decisions within the Edge-Cloud system can lead to various service time due to the computational resources and communications types.

scholarly journals IoT Traffic: Modeling and Measurement Experiments

IoT ◽  
2021 ◽  
Vol 2 (1) ◽  
pp. 140-162
Author(s):  
Hung Nguyen-An ◽  
Thomas Silverston ◽  
Taku Yamazaki ◽  
Takumi Miyoshi
Keyword(s):  
Smart Home ◽  
Large Scale ◽  
Traffic Modeling ◽  
The Novel ◽  
Network Behavior ◽  
Performance Accuracy ◽  
Traffic Generator ◽  
Multiple Devices ◽  
Iot Devices ◽  
The Internet Of Things

We now use the Internet of things (IoT) in our everyday lives. The novel IoT devices collect cyber–physical data and provide information on the environment. Hence, IoT traffic will count for a major part of Internet traffic; however, its impact on the network is still widely unknown. IoT devices are prone to cyberattacks because of constrained resources or misconfigurations. It is essential to characterize IoT traffic and identify each device to monitor the IoT network and discriminate among legitimate and anomalous IoT traffic. In this study, we deployed a smart-home testbed comprising several IoT devices to study IoT traffic. We performed extensive measurement experiments using a novel IoT traffic generator tool called IoTTGen. This tool can generate traffic from multiple devices, emulating large-scale scenarios with different devices under different network conditions. We analyzed the IoT traffic properties by computing the entropy value of traffic parameters and visually observing the traffic on behavior shape graphs. We propose a new method for identifying traffic entropy-based devices, computing the entropy values of traffic features. The method relies on machine learning to classify the traffic. The proposed method succeeded in identifying devices with a performance accuracy up to 94% and is robust with unpredictable network behavior with traffic anomalies spreading in the network.

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