Energy-Efficient Computing Solutions for Internet of Things with ZigBee Reconfigurable Devices

2017 ◽  
pp. 441-459
Author(s):  
Grzegorz Chmaj ◽  
Henry Selvaraj
Keyword(s):  
Internet Of Things ◽  
High Efficiency ◽  
Local Network ◽  
Energy Efficient Computing ◽  
Distributed Structure ◽  
Reconfigurable Devices ◽  
Battery Power ◽  
Iot Devices ◽  
Logic Structures ◽  
High Level

Nowadays we are witnessing a trend with significantly increasing number of networked and computing-capable devices being integrated into everyday environment. This trend is expected to continue. With computing devices available as logic structures, they might use each other's processing capabilities to achieve a given goal. In this paper, the authors propose an architectural solution to perform the processing of tasks using a distributed structure of Internet of Things devices. They also include ZigBee devices that are not connected to the Internet, but participate with the processing swarm using local network. This significantly extends the flexibility and potential of the IoT structure, while being still not a well-researched area. Unlike many high-level realizations for IoT processing, the authors present a realization operating on the communications, computing and near protocol level that achieves energy consumption efficiency. They also include the reconfigurability of IoT devices. The authors' work is suitable to be the base for higher-level realizations, especially for systems with devices operating on battery power. At the same time, the architecture presented in this paper uses minimal centralization, moving maximum responsibilities to regular devices. The proposed realizations are described using linear programming models and their high efficiency is evaluated.

Energy-Efficient Computing Solutions for Internet of Things with ZigBee Reconfigurable Devices

2016 ◽  
Vol 4 (1) ◽  
pp. 31-47 ◽  
Author(s):  
Grzegorz Chmaj ◽  
Henry Selvaraj
Keyword(s):  
Internet Of Things ◽  
High Efficiency ◽  
Local Network ◽  
Energy Efficient Computing ◽  
Distributed Structure ◽  
Reconfigurable Devices ◽  
Battery Power ◽  
Iot Devices ◽  
Logic Structures ◽  
High Level

Nowadays we are witnessing a trend with significantly increasing number of networked and computing-capable devices being integrated into everyday environment. This trend is expected to continue. With computing devices available as logic structures, they might use each other's processing capabilities to achieve a given goal. In this paper, the authors propose an architectural solution to perform the processing of tasks using a distributed structure of Internet of Things devices. They also include ZigBee devices that are not connected to the Internet, but participate with the processing swarm using local network. This significantly extends the flexibility and potential of the IoT structure, while being still not a well-researched area. Unlike many high-level realizations for IoT processing, the authors present a realization operating on the communications, computing and near protocol level that achieves energy consumption efficiency. They also include the reconfigurability of IoT devices. The authors' work is suitable to be the base for higher-level realizations, especially for systems with devices operating on battery power. At the same time, the architecture presented in this paper uses minimal centralization, moving maximum responsibilities to regular devices. The proposed realizations are described using linear programming models and their high efficiency is evaluated.

RESEARCH ON THE USE OF DECEPTION TECHNOLOGY TO PREVENT CYBERSECURITY THREATS

2020 ◽  
Vol 52 (4) ◽  
pp. 85-98
Author(s):  
MIKHAIL M PUTYATO ◽  
◽  
ALEKSANDR S. MAKARYAN ◽  
SHAMIL M. CHICH ◽  
VALENTINA K. MARKOVA ◽  
...  
Keyword(s):  
Comparative Analysis ◽  
Information Security ◽  
Internet Of Things ◽  
The Internet ◽  
Security Audit ◽  
Timely Manner ◽  
Simple Operation ◽  
Malicious Activity ◽  
Iot Devices ◽  
High Level

Internet of things (IoT) devices have become increasingly popular in recent years. IoT refers to smart refrigerators, smart locks, video nannies, and other household devices that have access to the Internet. However, the growing popularity of IoT technology is increasingly attracting the attention of hackers who are interested both in disclosing confidential enduser data and in misuse of the computing resources of the attacked devices. Unfortunately, malicious attacks often result in successful compromise of devices, with the ensuing consequences. The reasons for the high level of compromise of IoT devices are caused both by errors in the design, implementation, and relatively simple operation with the use of various information security audit tools. To identify defects in the development and implementation of devices, you need to have some idea about them, that is, to identify and eliminate them in a timely manner. This can be achieved in various ways. One of these methods is to create special traps that collect information about the activity of an attacker, called honeypot. The essence of the honeypot technology is to emulate or implement the functionality of existing devices, services, and protocols, with the accumulation of data about malicious activity of an attacker. The information obtained can be used to improve the protection of real devices, services, and protocols, as well as to develop measures to counter hackers. The article provides a comparative analysis of the existing most popular honeypot systems in order to identify the best system. The analysis identified both the weaknesses and strengths of these systems. Next, an attempt is made to adapt these same systems to function at the level of Internet of things devices.

scholarly journals E-HIP: An Energy-Efficient OpenHIP-Based Security in Internet of Things Networks

Sensors ◽  
2019 ◽  
Vol 19 (22) ◽  
pp. 4921 ◽  
Author(s):  
Peter Kaňuch ◽  
Dominik Macko
Keyword(s):  
Internet Of Things ◽  
Data Transfer ◽  
Security Protocols ◽  
Security Threats ◽  
Optimized Protocol ◽  
Host Identity ◽  
Iot Devices ◽  
High Level ◽  
Application Specific ◽  
The Internet Of Things

The rapidly growing segment of the Internet of Things (IoT) makes the security threats more prominent than ever. The research around communication security and cybersecurity in such networks is still a challenge, mainly due to the typically limited energy and computation resources of IoT devices. The strong security mechanisms require significant power and thus the energy wastage must be minimized. Optimized application-specific security protocols are commonly used to make the data transfer more efficient, while still offering a high level of security. The supported security features, such as confidentiality, integrity or authenticity, should not be affected by the optimization. Our work is focused on optimizing one of the existing security protocols for the use in the IoT area, namely the Host Identity Protocol (HIP). Based on the analysis of related works, we have identified multiple possibilities for optimization and combined some of them into the proposed E-HIP optimized protocol. For verification purpose, it has been implemented as a modification of the open-source OpenHIP library and applied on a communication between real hardware devices. The secured communication worked correctly. The resulting effect of the proposed optimization has been evaluated experimentally and it represents an increase in energy efficiency by about 20%. Compared to other HIP optimizations, the achieved results are similar; however, the proposed optimizations are unique and can be further combined with some of the existing ones to achieve even higher efficiency.

scholarly journals Cybersecurity and the Internet of Things

2016 ◽  
Vol 54 (2(108)) ◽  
pp. 22-36
Author(s):  
Christopher Biedermann
Keyword(s):  
Internet Of Things ◽  
The Internet ◽  
Security Threats ◽  
Cyber Attack ◽  
Security Issues ◽  
Risk Approach ◽  
Key Issues ◽  
Iot Devices ◽  
High Level ◽  
The Internet Of Things

PURPOSE/THESIS: The purpose of this paper is to use a recent cyber-attack to highlight the current state of readiness of Internet of Things (IoT) technologies with regard to security vulnerabilities as well as fundamental – in the author’s opinion – changes that will need to take place within these industries and technologies to mitigate the overall cybersecurity risk. APPROACH/METHODS: The analysis of the findings from numerous existing published security studies. RESULTS AND CONCLUSIONS: The following conclusions were reached: (1) in the world becoming more and more interconnected through the web enabled devices (IoT devices), new forms of security threats have been developed; (2) at present IoT devices introduce a high level of vulnerability; (3) many of these risks may be mitigated with already existing technologies; (4) however, due to the fragmented and heterogeneous nature of the IoT devices, the implementation of even basic levels of security is more challenging than in the case of traditional Internet connected devices (e.g. personal computers); (5) the industry needs to face and address three key issues that will in turn help to mitigate the unique security threats posed by IoT devices, namely: the drive towards open standards, the industry cooperation and consolidation, and the improvement of consumer awareness. ORIGINALITY/VALUE: The value of the research is to highlight the security issues related to the Internet of Things and propose solutions that must be implemented to increase the level of security awareness within the IoT environment.

A Comprehensive Study on Internet of Things Security

2019 ◽  
pp. 72-86 ◽  
Author(s):  
Manikandakumar Muthusamy ◽  
Karthikeyan Periasamy
Keyword(s):  
Internet Of Things ◽  
Smart Cities ◽  
Denial Of Service ◽  
Critical Issue ◽  
Security And Privacy ◽  
The Internet ◽  
Privacy Concerns ◽  
Major Shift ◽  
Iot Devices ◽  
High Level

Internet of things is a growing technology with many business opportunities and risks. It is strongly believed that IoT will cause a major shift in people's lives similar to how the internet transformed the way people communicate and share information. IoT is becoming popular in the various domains such as smart health, smart cities, smart transport, and smart retail. The security and privacy concerns of IoT are crucial as it connects a large number of devices. Security is a more critical issue that certainly needs to be resolved with a high level of attention, as with an increasing number of users, there would be a need to manage their requests and check authenticity on the cloud-based pattern. Recently, a series of massive distributed denial-of-service attacks have occurred in IoT organizations. Such malicious attacks have highlighted the threats resulting from not enough security in IoT devices together with their overwhelming effects on the internet. This chapter provides an overview of the security attacks with regard to IoT technologies, protocols, and applications.

Design of Polytechnic College Practice Training Base Management System Based on Internet of Things

2014 ◽  
Vol 496-500 ◽  
pp. 2224-2227
Author(s):  
Zhen Zhang ◽  
Cheng Cheng
Keyword(s):  
Internet Of Things ◽  
Management System ◽  
High Efficiency ◽  
Management Practice ◽  
Basic Research ◽  
Management Skills ◽  
Management Platform ◽  
High Level ◽  
And Training ◽  
Lab Management

Practice training base is the main place for students to practice and also the significant organizations where universities do high level basic research and basic application research. Current situation and problem of practice and training lab management in college is introduced, such as the problems of equipments managements and class arrangement. To analyze the improvement areas of existing lab management practice, design the management platform of practice and training lab basing on Internet of things, using the modern management methods to improve advanced management skills of practice and training lab in polytechnic colleges. Taking internet of things and the characteristics of college into consideration, customized architecture of internet of things is discussed. Prototype of internet of things based management system is proposed. The sensor layer, network layer, support layer and application layer are constructed. Trend of practice and training lab management system and challenges faced are also briefed. Results: Through trial run in some colleges, designed internet of things based lab management system can achieve what is desired by college of polytechnic instrumentation on lab management system and work flow. High efficiency, simple operation, and powerful functions are also proven at the same time.

scholarly journals Edge Machine Learning for AI-Enabled IoT Devices: A Review

Sensors ◽  
2020 ◽  
Vol 20 (9) ◽  
pp. 2533 ◽  
Author(s):  
Massimo Merenda ◽  
Carlo Porcaro ◽  
Demetrio Iero
Keyword(s):  
Machine Learning ◽  
Internet Of Things ◽  
Machine Learning Algorithms ◽  
The Internet ◽  
Learning Models ◽  
Iot Devices ◽  
High Level ◽  
And Behavior ◽  
The Internet Of Things ◽  
Machine Learning Models

In a few years, the world will be populated by billions of connected devices that will be placed in our homes, cities, vehicles, and industries. Devices with limited resources will interact with the surrounding environment and users. Many of these devices will be based on machine learning models to decode meaning and behavior behind sensors’ data, to implement accurate predictions and make decisions. The bottleneck will be the high level of connected things that could congest the network. Hence, the need to incorporate intelligence on end devices using machine learning algorithms. Deploying machine learning on such edge devices improves the network congestion by allowing computations to be performed close to the data sources. The aim of this work is to provide a review of the main techniques that guarantee the execution of machine learning models on hardware with low performances in the Internet of Things paradigm, paving the way to the Internet of Conscious Things. In this work, a detailed review on models, architecture, and requirements on solutions that implement edge machine learning on Internet of Things devices is presented, with the main goal to define the state of the art and envisioning development requirements. Furthermore, an example of edge machine learning implementation on a microcontroller will be provided, commonly regarded as the machine learning “Hello World”.

scholarly journals Definition of Internet of Things (IoT) Cyber Risk – Discussion on a Transformation Roadmap for Standardisation of Regulations, Risk Maturity, Strategy Design and Impact Assessment

2019 ◽  
Author(s):  
Petar Radanliev ◽  
David De Roure ◽  
Jason R.C. Nurse ◽  
Pete Burnap ◽  
Eirini Anthi ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Impact Assessment ◽  
Cyber Security ◽  
The Internet ◽  
Self Assessment ◽  
Target State ◽  
Iot Devices ◽  
High Level ◽  
Cyber Risk ◽  
The Internet Of Things

The Internet-of-Things (IoT) enables enterprises to obtain profits from data but triggers data protection questions and new types of cyber risk. Cyber risk regulations for the IoT however do not exist. The IoT risk is not included in the cyber security assessment standards, hence, often not visible to cyber security experts. This is concerning, because companies integrating IoT devices and services need to perform a self-assessment of its IoT cyber security posture. The outcome of such self-assessment needs to define a current and target state, prior to creating a transformation roadmap outlining tasks to achieve the stated target state. In this article, a comparative empirical analysis is performed of multiple cyber risk assessment approaches, to define a high-level potential target state for company integrating IoT devices and/or services. Defining a high-level potential target state represent is followed by a high-level transformation roadmap, describing how company can achieve their target state, based on their current state. The transformation roadmap is used to adapt IoT risk impact assessment with a Goal-Oriented Approach and the Internet of Things Micro Mart model.

Sensor Integration Technologies for Internet of Things

2015 ◽  
Vol 2015 (S1) ◽  
pp. S1-S34
Author(s):  
Franz Schrank
Keyword(s):  
Internet Of Things ◽  
3D Integration ◽  
Processing Power ◽  
Functional Blocks ◽  
Iot Devices ◽  
On Chip ◽  
High Level ◽  
Improve Reliability ◽  
Market Volume ◽  
Total Market

Internet of things (IoT) will influence all areas from consumer to health care to building and home automation and to observation. IoT enables direct communication between objects via internet. The main functional blocks of IoT devices are sensing, data transmitting, processing and analysis and subsequent actuation. As a result such a system will consist of sensors, actuators, wireless connection, data processing, power management, energy harvesting, memory and software. A total market volume of almost 400 Bio US$ is predicted for 2024 whereof about 12Bio US$ are expected for IoT sensors (Yole2014)). The main challenges are to reduce footprint (e.g. wearables, swarm), reduce costs of system, improve reliability and provide better performance. For example the costs of today's smart sensor systems are in the 100–1000US$ range and for 2024 an ASP in the 1US$ $ level is expected (Yole2014). To enable this, a high level of integration is needed for the next generations of IoT sensors. This will on one hand reduce costs and form factor but also enable multi sensors devices. More than Moore integration of functions offers the potential to meet both performance and cost targets for mass-market adoption. In addition to SoC (System on Chip) and SiP (System in Package) heterogeneous 3D integrations will be key enablers. 3D integration with the main technology bricks like TSV (Through Silicon Via), RDL (Redistribution Layer), D2W (Die to Wafer) and W2W (Wafer to Wafer) stacking and embedding allows to combine different technologies - different CMOS notes, MEMS, photonics, etc. At the same time expensive single die packaging can be avoided. The presentation will focus on reviewing 3D integration technologies and their potential for IoT from the perspective of a sensor solution provider.

Designing an Automated Composter for Food Waste Management with the Implementation of Internet of Things

2020 ◽  
Vol 1 (2) ◽  
Author(s):  
N. A. Fakharulrazi ◽  
◽  
F. Yakub ◽  
M. N. Baba ◽  
L. F. Zhao ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Food Waste ◽  
High Efficiency ◽  
Animal Feed ◽  
Modern Technology ◽  
Constant Attention ◽  
Whole Process ◽  
Handling Cost ◽  
Unpleasant Odor ◽  
Environmentally Friendly Method

Composting food waste is a delicate procedure that requires specific infrastructure and machinery that can gradually transform the wastes to nutrient-rich manure. Nevertheless, it also desires a constant attention by experts to achieve a quality outcome. Therefore, automatic composting machinery is a promising new idea as modern technology is taking over the world with it high efficiency. The objective of this paper is to build a fully automated composting machine that can help to reduce food waste using a more efficient and environmentally friendly method. This machine has its special features of heating, cooling and grinding which is simple and easy to use for every consumer at just one touch of a button. In addition, it uses a special filter to eliminate unpleasant odor to ensure consumer’s space of mind. The composting process uses node microcontroller (MCU) to run its operation and Internet of Things (IoT) with a developed mobile application to measure the amount of food waste, current process and its moisture content before turning the waste into high nutrient flakes at around 10% of its original volume. It will also notify the consumer when the whole process is done and the final product is ready to use. The produced flakes are good for nurturing soils, use as fertilizer, and renewable source of energy or animal feed. The benefit is to help reduce handling cost of waste at landfill. Excessive logistical energy is required to send food waste to landfill if conventional equipment is applied. This product has a high potential to penetrate the end users who usually cooks at home and also the industrial food manufacturers whether from medium to large which produces a lot of raw waste. Essentially, this machine allows food waste, through implementation of IoT to be converted to usable fertilizer.

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