scholarly journals Timed protocol analysis of interconnected mobile IoT devices

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Georgios Bouloukakis ◽  
Nikolaos Georgantas ◽  
Ajay Kattepur ◽  
Valerie Issarny
Keyword(s):  
Data Exchange ◽  
Response Times ◽  
Timed Automata ◽  
Data Availability ◽  
Success Rates ◽  
Intermittent Connectivity ◽  
Time Semantics ◽  
Application Programming ◽  
Iot Devices ◽  
Application Developers

AbstractWith the emergence of the Internet of Things (IoT), application developers can rely on a variety of protocols and Application Programming Interfaces (APIs) to support data exchange between IoT devices. However, this may result in highly heterogeneous IoT interactions in terms of both functional and non-functional semantics. To map between heterogeneous functional semantics, middleware connectors can be utilized to interconnect IoT devices via bridging mechanisms. In this paper, we make use of the Data eXchange (DeX) connector model that enables interoperability among heterogeneous IoT devices. DeX interactions, including synchronous, asynchronous and streaming, rely on generic post and get primitives to represent IoT device behaviors with varying space/time coupling. Nevertheless, non-functional time semantics of IoT interactions such as data availability/validity, intermittent connectivity and application processing time, can severely affect response times and success rates of DeX interactions. We introduce timing parameters for time semantics to enhance the DeX API. The new DeX API enables the mapping of both functional and time semantics of DeX interactions. By precisely studying these timing parameters using timed automata models, we verify conditions for successful interactions with DeX connectors. Furthermore, we statistically analyze through simulations the effect of varying timing parameters to ensure higher probabilities of successful interactions. Simulation experiments are compared with experiments run on the DeX Mediators (DeXM) framework to evaluate the accuracy of the results. This work can provide application developers with precise design time information when setting these timing parameters in order to ensure accurate runtime behavior.

scholarly journals Predictive Maintenance in Building Facilities: A Machine Learning-Based Approach

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1044
Author(s):  
Yassine Bouabdallaoui ◽  
Zoubeir Lafhaj ◽  
Pascal Yim ◽  
Laure Ducoulombier ◽  
Belkacem Bennadji
Keyword(s):  
Machine Learning ◽  
Model Development ◽  
Predictive Maintenance ◽  
Data Availability ◽  
Machine Learning Techniques ◽  
Automation System ◽  
Building Maintenance ◽  
Collection Data ◽  
Iot Devices

The operation and maintenance of buildings has seen several advances in recent years. Multiple information and communication technology (ICT) solutions have been introduced to better manage building maintenance. However, maintenance practices in buildings remain less efficient and lead to significant energy waste. In this paper, a predictive maintenance framework based on machine learning techniques is proposed. This framework aims to provide guidelines to implement predictive maintenance for building installations. The framework is organised into five steps: data collection, data processing, model development, fault notification and model improvement. A sport facility was selected as a case study in this work to demonstrate the framework. Data were collected from different heating ventilation and air conditioning (HVAC) installations using Internet of Things (IoT) devices and a building automation system (BAS). Then, a deep learning model was used to predict failures. The case study showed the potential of this framework to predict failures. However, multiple obstacles and barriers were observed related to data availability and feedback collection. The overall results of this paper can help to provide guidelines for scientists and practitioners to implement predictive maintenance approaches in buildings.

A Collaborative Replication Approach for Mobile-P2P Networks

2012 ◽  
pp. 160-182
Author(s):  
Anirban Mondal ◽  
Sanjay Kumar Madria ◽  
Masaru Kitsuregawa
Keyword(s):  
Ad Hoc ◽  
Response Times ◽  
Data Availability ◽  
P2p Networks ◽  
Allocation Mechanism ◽  
Memory Space ◽  
Mobile Hosts ◽  
Dynamic Replication ◽  
Replica Allocation ◽  
Communication Traffic

This paper proposes CADRE (Collaborative Allocation and De-allocation of Replicas with Efficiency), which is a dynamic replication scheme for improving the typically low data availability in dedicated and cooperative mobile ad-hoc peer-to-peer (M-P2P) networks. In particular, replica allocation and de-allocation are collaboratively performed in tandem to facilitate effective replication. Such collaboration is facilitated by a hybrid super-peer architecture in which some of the mobile hosts act as the ‘gateway nodes’ (GNs) in a given region. GNs facilitate both search and replication. The main contributions of CADRE are as follows. First, it facilitates the prevention of ‘thrashing’ conditions due to its collaborative replica allocation and de-allocation mechanism. Second, it considers the replication of images at different resolutions to optimize the usage of the generally limited memory space of the mobile hosts (MHs). Third, it addresses fair replica allocation across the MHs. Fourth, it facilitates the optimization of the limited energy resources of MHs during replication. The authors’ performance evaluation demonstrates that CADRE is indeed effective in improving data availability in M-P2P networks with significant reduction in query response times and low communication traffic during replication as compared to a recent existing scheme as well as a baseline approach, which does not consider any replication.

scholarly journals Cryptographic Keys Generating and Renewing System for IoT Network Nodes—A Concept

Sensors ◽  
2020 ◽  
Vol 20 (17) ◽  
pp. 5012
Author(s):  
Janusz Furtak
Keyword(s):  
Data Exchange ◽  
Security And Privacy ◽  
Critical Element ◽  
Certification Authority ◽  
Trusted Platform Module ◽  
Network Nodes ◽  
Cryptographic Keys ◽  
Iot Devices ◽  
System Nodes ◽  
Trusted Platform

Designers and users of the Internet of Things (IoT) are devoting more and more attention to the issues of security and privacy as well as the integration of data coming from various areas. A critical element of cooperation is building mutual trust and secure data exchange. Because IoT devices usually have small memory resources, limited computing power, and limited energy resources, it is often impossible to effectively use a well-known solution based on the Certification Authority. This article describes the concept of the system for a cryptographic Key Generating and Renewing system (KGR). The concept of the solution is based on the use of the hardware Trusted Platform Module (TPM) v2.0 to support the procedures of creating trust structures, generating keys, protecting stored data, and securing data exchange between system nodes. The main tasks of the system are the secure distribution of a new symmetric key and renewal of an expired key for data exchange parties. The KGR system is especially designed for clusters of the IoT nodes but can also be used by other systems. A service based on the Message Queuing Telemetry Transport (MQTT) protocol will be used to exchange data between nodes of the KGR system.

Data Innovations for Transboundary Freshwater Resources Management: Are Obligations Related to Information Exchange Still Needed?

2020 ◽  
Vol 4 (4) ◽  
pp. 3-78 ◽  
Author(s):  
Christina Leb
Keyword(s):  
Spatial Data ◽  
Information Exchange ◽  
Data Exchange ◽  
Data Availability ◽  
Water Law ◽  
Space Technology ◽  
Time Data ◽  
Related Data ◽  
International Water Law ◽  
International Water

AbstractCross-border data and information exchange is one of the most challenging issues for transboundary water management. While the regular exchange of data and information has been identified as one of the general principles of international water law, only a minority of treaties include direct obligations related to mutual data exchange. Technological innovations related to real-time data availability, space technology and earth observation have led to an increase in quality and availability of hydrological, meteorological and geo-spatial data. These innovations open new avenues for access to water related data and transform data and information exchange globally. This monograph is an exploratory assessment of the potential impacts of these disruptive technologies on data and information exchange obligations in international water law.

scholarly journals DM-MQTT: An Efficient MQTT Based on SDN Multicast for Massive IoT Communications

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 3071 ◽  
Author(s):  
Jun-Hong Park ◽  
Hyeong-Su Kim ◽  
Won-Tae Kim
Keyword(s):  
Cloud Computing ◽  
Traffic Congestion ◽  
Data Exchange ◽  
Data Transfer ◽  
Edge Computing ◽  
Computing Paradigm ◽  
Transfer Delay ◽  
Network Usage ◽  
Iot Devices ◽  
Edge Networks

Edge computing is proposed to solve the problem of centralized cloud computing caused by a large number of IoT (Internet of Things) devices. The IoT protocols need to be modified according to the edge computing paradigm, where the edge computing devices for analyzing IoT data are distributed to the edge networks. The MQTT (Message Queuing Telemetry Transport) protocol, as a data distribution protocol widely adopted in many international IoT standards, is suitable for cloud computing because it uses a centralized broker to effectively collect and transmit data. However, the standard MQTT may suffer from serious traffic congestion problem on the broker, causing long transfer delays if there are massive IoT devices connected to the broker. In addition, the big data exchange between the IoT devices and the broker decreases network capability of the edge networks. The authors in this paper propose a novel MQTT with a multicast mechanism to minimize data transfer delay and network usage for the massive IoT communications. The proposed MQTT reduces data transfer delays by establishing bidirectional SDN (Software Defined Networking) multicast trees between the publishers and the subscribers by means of bypassing the centralized broker. As a result, it can reduce transmission delay by 65% and network usage by 58% compared with the standard MQTT.

scholarly journals Fine-Grained Isolation to Protect Data against In-Process Attacks on AArch64

Electronics ◽  
2020 ◽  
Vol 9 (2) ◽  
pp. 236
Author(s):  
Yeongpil Cho
Keyword(s):  
Application Programming Interface ◽  
Sensitive Data ◽  
Fine Grained ◽  
New Class ◽  
Application Programming ◽  
Application Developers ◽  
Data Isolation ◽  
Programming Interface

In-process attacks are a new class of attacks that circumvent protection schemes centered around inter-process isolation. Against these attacks, researchers have proposed fine-grained data isolation schemes that can protect sensitive data from malicious accesses even during the same process. Their proposals based on salient hardware features, such as ARM® processor architecture’s domain protection, are quite successful, but it cannot be applied to a specific architecture, namely AArch64, as this does not provide the same hardware features. In this paper, therefore, we present Sealer, a fine-grained data isolation scheme applicable in AArch64. Sealer achieves its objective by brilliantly harmonizing two hardware features of AArch64: The eXecute-no-Read and the cryptographic extension. Sealer provides application developers with a set of application programming interface (API) so that the developers can enjoy the fine-grained data isolation in their own way.

scholarly journals Node-Node Data Exchange in IoT Devices Using Twofish and DHE

2021 ◽  
Vol 6 (2) ◽  
pp. 622-628
Author(s):  
Bismark Tei Asare ◽  
Kester Quist-Aphetsi ◽  
Laurent Nana
Keyword(s):  
Data Exchange ◽  
Iot Devices

scholarly journals Serverless Computing: An Investigation of Deployment Environments for Web APIs

Computers ◽  
2019 ◽  
Vol 8 (2) ◽  
pp. 50
Author(s):  
Ivan ◽  
Vasile ◽  
Dadarlat
Keyword(s):  
Web Application ◽  
Web Applications ◽  
Virtual Machines ◽  
Response Times ◽  
Application Programming Interface ◽  
Resource Provisioning ◽  
Dynamic Scaling ◽  
Application Programming ◽  
Test Scenarios ◽  
Additional Labor

Cloud vendors offer a variety of serverless technologies promising high availability and dynamic scaling while reducing operational and maintenance costs. One such technology, serverless computing, or function-as-a-service (FaaS), is advertised as a good candidate for web applications, data-processing, or backend services, where you only pay for usage. Unlike virtual machines (VMs), they come with automatic resource provisioning and allocation, providing elastic and automatic scaling. We present the results from our investigation of a specific serverless candidate, Web Application Programming Interface or Web API, deployed on virtual machines and as function(s)-as-a-service. We contrast these deployments by varying the number of concurrent users for measuring response times and costs. We found no significant response time differences between deployments when VMs are configured for the expected load, and test scenarios are within the FaaS hardware limitations. Higher numbers of concurrent users or unexpected user growths are effortlessly handled by FaaS, whereas additional labor must be invested in VMs for equivalent results. We identified that despite the advantages serverless computing brings, there is no clear choice between serverless or virtual machines for a Web API application because one needs to carefully measure costs and factor-in all components that are included with FaaS.

scholarly journals Research on Data Mining of Permission-Induced Risk for Android IoT Devices

2019 ◽  
Vol 9 (2) ◽  
pp. 277 ◽  
Author(s):  
Rajesh Kumar ◽  
Xiaosong Zhang ◽  
Riaz Khan ◽  
Abubakar Sharif
Keyword(s):  
Data Exchange ◽  
Malware Detection ◽  
The Internet ◽  
Static And Dynamic Analysis ◽  
Android Apps ◽  
Novel Approach ◽  
Android Applications ◽  
Iot Devices ◽  
Android Permission ◽  
The Internet Of Things

With the growing era of the Internet of Things (IoT), more and more devices are connecting with the Internet using android applications to provide various services. The IoT devices are used for sensing, controlling and monitoring of different processes. Most of IoT devices use Android applications for communication and data exchange. Therefore, a secure Android permission privileged mechanism is required to increase the security of apps. According to a recent study, a malicious Android application is developed almost every 10 s. To resist this serious malware campaign, we need effective malware detection approaches to identify malware applications effectively and efficiently. Most of the studies focused on detecting malware based on static and dynamic analysis of the applications. However, to analyse the risky permission at runtime is a challenging task. In this study, first, we proposed a novel approach to distinguish between malware and benign applications based on permission ranking, similarity-based permission feature selection, and association rule for permission mining. Secondly, the proposed methodology also includes the enhancement of the random forest algorithm to improve the accuracy for malware detection. The experimental outcomes demonstrate high proficiency of the accuracy for malware detection, which is pivotal for android apps aiming for secure data exchange between IoT devices.

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