scholarly journals Large-Scale Software-Defined IoT Platform for Provisioning IoT Services on Demand

2020 ◽  
Vol 1 (1) ◽  
pp. 1-23
Author(s):  
Chau Thi Minh Nguyen ◽  
Doan B. Hoang
Keyword(s):  
Resource Sharing ◽  
Large Scale ◽  
Virtual Sensors ◽  
On Demand ◽  
Iot Platform ◽  
Proposed Model ◽  
Geographically Distributed ◽  
Iot Platforms ◽  
End To End ◽  
Iot Devices

Internet of things (IoT) has developed into an interconnected platform infrastructure for providing everyday services. Emerging end-to-end IoT services are being developed for local and multiple distributed regions. To realize the on-demand services in a timely and economically beneficial way, programmability and reusability are crucial for provisioning and reusing IoT resources. Existing IoT platforms are rigid and cannot be easily adapted to accommodate new services. This paper proposes a programmable large-scale software-defined IoT model for provisioning IoT services on demand with two levels of management and orchestration. One orchestrates services over geographically distributed clusters and the other orchestrates services over IoT devices within a cluster. The model entails the design of IoT-specific controllers, software-defined virtual sensors, and a new protocol for managing resource-constrained but enriched devices. The model allows provisioning and resource-sharing of end-to-end IoT services on demand. Implementation results demonstrate the feasibility and efficiency of the proposed model.

scholarly journals Distributed Meta-Brokering P2P Overlay for Scheduling in Cloud Federation

Electronics ◽  
2019 ◽  
Vol 8 (8) ◽  
pp. 852 ◽  
Author(s):  
Sajid Latif ◽  
Syed Mushhad Gilani ◽  
Rana Liaqat Ali ◽  
Misbah Liaqat ◽  
Kwang-Man Ko
Keyword(s):  
Resource Management ◽  
Service Provision ◽  
Large Scale ◽  
Service Providers ◽  
Service Level Agreement ◽  
Service Level ◽  
Distributed Resources ◽  
Proposed Model ◽  
Geographically Distributed ◽  
Application Programming

The interconnected cloud (Intercloud) federation is an emerging paradigm that revolutionizes the scalable service provision of geographically distributed resources. Large-scale distributed resources require well-coordinated and automated frameworks to facilitate service provision in a seamless and systematic manner. Unquestionably, standalone service providers must communicate and federate their cloud sites with other vendors to enable the infinite pooling of resources. The pooling of these resources provides uninterpretable services to increasingly growing cloud users more efficiently, and ensures an improved Service Level Agreement (SLA). However, the research of Intercloud resource management is in its infancy. Therefore, standard interfaces, protocols, and uniform architectural components need to be developed for seamless interaction among federated clouds. In this study, we propose a distributed meta-brokering-enabled scheduling framework for provision of user application services in the federated cloud environment. Modularized architecture of the proposed system with uniform configuration in participating resource sites orchestrate the critical operations of resource management effectively, and form the federation schema. Overlaid meta-brokering instances are implemented on the top of local resource brokers to keep the global functionality isolated. These instances in overlay topology communicate in a P2P manner to maintain decentralization, high scalability, and load manageability. The proposed framework has been implemented and evaluated by extending the Java-based CloudSim 3.0.3 simulation application programming interfaces (APIs). The presented results validate the proposed model and its efficiency to facilitate user application execution with the desired QoS parameters.

Interconnection of geographically distributed wireless mesh testbeds: Resource sharing on a large scale

2011 ◽  
Vol 9 (8) ◽  
pp. 1389-1403 ◽  
Author(s):  
Giovanni Di Stasi ◽  
Roberto Bifulco ◽  
Stefano Avallone ◽  
Roberto Canonico ◽  
Apostolos Apostolaras ◽  
...  
Keyword(s):  
Resource Sharing ◽  
Large Scale ◽  
Wireless Mesh ◽  
Geographically Distributed

scholarly journals Building an IoT Platform Based on Service Containerisation

Sensors ◽  
2021 ◽  
Vol 21 (19) ◽  
pp. 6688
Author(s):  
Mário Antunes ◽  
Ana Rita Santiago ◽  
Sérgio Manso ◽  
Diogo Regateiro ◽  
João Paulo Barraca ◽  
...  
Keyword(s):  
Large Scale ◽  
Heterogeneous Data ◽  
Large Set ◽  
Smart Services ◽  
Real Time Processing ◽  
Iot Platform ◽  
Storage Solutions ◽  
Iot Platforms ◽  
And Storage

IoT platforms have become quite complex from a technical viewpoint, becoming the cornerstone for information sharing, storing, and indexing given the unprecedented scale of smart services being available by massive deployments of a large set of data-enabled devices. These platforms rely on structured formats that exploit standard technologies to deal with the gathered data, thus creating the need for carefully designed customised systems that can handle thousands of heterogeneous data sensors/actuators, multiple processing frameworks, and storage solutions. We present the SCoT2.0 platform, a generic-purpose IoT Platform that can acquire, process, and visualise data using methods adequate for both real-time processing and long-term Machine Learning (ML)-based analysis. Our goal is to develop a large-scale system that can be applied to multiple real-world scenarios and is potentially deployable on private clouds for multiple verticals. Our approach relies on extensive service containerisation, and we present the different design choices, technical challenges, and solutions found while building our own IoT platform. We validate this platform supporting two very distinct IoT projects (750 physical devices), and we analyse scaling issues within the platform components.

scholarly journals IoT Platform for Seafood Farmers and Consumers

Sensors ◽  
2020 ◽  
Vol 20 (15) ◽  
pp. 4230
Author(s):  
Bjørn Jæger ◽  
Alok Mishra
Keyword(s):  
Sustainable Operations ◽  
Information Transparency ◽  
Value Network ◽  
Iot Platform ◽  
Global Standards ◽  
Seafood Industry ◽  
Demand Information ◽  
Enterprise Level ◽  
Iot Platforms ◽  
Iot Devices

There has been a strong growth in aquatic products supported by the global seafood industry. Consumers demand information transparency to support informed decisions and to verify nutrition, food safety, and sustainable operations. Supporting these needs rests on the existence of interoperable Internet of Things (IoT) platforms for traceability that goes beyond the minimum “one up, one down” scheme required by regulators. Seafood farmers, being the source of both food and food-information, are critical to achieving the needed transparency. Traditionally, seafood farmers carry the costs of providing information, while downstream actors reap the benefits, causing limited provision of information. Now, global standards for labelling, data from IoT devices, and the reciprocity of utility from collecting data while sharing them represent great potential for farmers to generate value from traceability systems. To enable this, farmers need an IoT platform integrated with other IoT platforms in the value network. This paper presents a case study of an enterprise-level IoT platform for seafood farmers that satisfies consumers’ end-to-end traceability needs while extracting data from requests for information from downstream actors.

scholarly journals Design and Implementation of an Interworking IoT Platform and Marketplace in Cloud of Things

2019 ◽  
Vol 11 (21) ◽  
pp. 5952 ◽  
Author(s):  
Faisal Mehmood ◽  
Shabir Ahmad ◽  
DoHyeun Kim
Keyword(s):  
Value Chain ◽  
Virtual Objects ◽  
Iot Applications ◽  
Iot Platform ◽  
Vital Component ◽  
Iot Platforms ◽  
Iot Devices ◽  
User Friendly ◽  
Software Services

An internet of things (IoT) platform is a multi-layer technology that enables automation of connected devices within IoT. IoT platforms serve as a middle-ware solution and act as supporting software that is able to connect different hardware devices, access points, and networks to other parts of the value chain. Virtual objects have become a vital component in every IoT platform. Virtual objects are the digital representation of a physical entity. In this paper, we design and implement a cloud-centric IoT platform that serves a purpose for registration and initialization of virtual objects so that technology tinkerers can consume them via the IoT marketplace and integrate them to build IoT applications. The proposed IoT platform differs from existing IoT platforms in the sense that they provide hardware and software services on the same platform that users can plug and play. The proposed IoT platform is separate from the IoT marketplace where users can consume virtual objects to build IoT applications. Experiments are conducted for IoT platform and interworking IoT marketplace based on virtual objects in CoT. The proposed IoT platform provides a user-friendly interface and is secure and reliable. An IoT testbed is developed and a case study is performed for a domestic environment to reuse virtual objects on the IoT marketplace. It also provides the discovery and sharing of virtual objects. IoT devices can be monitored and controlled via virtual objects. We have conducted a comparative analysis of the proposed IoT platform with FIWARE. Results conclude that the proposed system performs marginally better than FIWARE.

scholarly journals Short-Term PM2.5 Forecasting Using Exponential Smoothing Method: A Comparative Analysis

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3223 ◽  
Author(s):  
Sachit Mahajan ◽  
Ling-Jyh Chen ◽  
Tzu-Chieh Tsai
Keyword(s):  
Large Scale ◽  
Fine Particulate Matter ◽  
Computation Time ◽  
Exponential Smoothing ◽  
Proposed Model ◽  
Forecasting Method ◽  
Monitoring And Forecasting ◽  
Iot Devices ◽  
Exponential Smoothing Method ◽  
Monitoring Stations

Air pollution is a global problem and can be perceived as a modern-day curse. One way of dealing with it is by finding economical ways to monitor and forecast air quality. Accurately monitoring and forecasting fine particulate matter (PM2.5) concentrations is a challenging prediction task but Internet of Things (IoT) can help in developing economical and agile ways to design such systems. In this paper, we use a historical data-based approach to perform PM2.5 forecasting. A forecasting method is developed which uses exponential smoothing with drift. Experiments and evaluation were performed using the real-time PM2.5 data obtained from large scale deployment of IoT devices in Taichung region in Taiwan. We used the data from 132 monitoring stations to evaluate our model’s performance. A comparison of prediction accuracy and computation time between the proposed model and three widely used forecasting models was done. The results suggest that our method can perform PM2.5 forecast for 132 monitoring stations with error as low as 0.16 μ g/ m 3 and also with an acceptable computation time of 30 s. Further evaluation was done by forecasting PM2.5 for next 3 h. The results show that 90 % of the monitoring stations have error under 1.5 μ g/ m 3 which is significantly low.

scholarly journals Performance Evaluation of Cryptographic Algorithms over IoT Platforms and Operating Systems

2017 ◽  
Vol 2017 ◽  
pp. 1-16 ◽  
Author(s):  
Geovandro C. C. F. Pereira ◽  
Renan C. A. Alves ◽  
Felipe L. da Silva ◽  
Roberto M. Azevedo ◽  
Bruno C. Albertini ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Operating Systems ◽  
Symmetric Cryptography ◽  
Significant Progress ◽  
Security Services ◽  
Iot Platform ◽  
Iot Platforms ◽  
Iot Devices ◽  
Time And Energy

The deployment of security services over Wireless Sensor Networks (WSN) and IoT devices brings significant processing and energy consumption overheads. These overheads are mainly determined by algorithmic efficiency, quality of implementation, and operating system. Benchmarks of symmetric primitives exist in the literature for WSN platforms but they are mostly focused on single platforms or single operating systems. Moreover, they are not up to date with respect to implementations and/or operating systems versions which had significant progress. Herein, we provide time and energy benchmarks of reference implementations for different platforms and operating systems and analyze their impact. Moreover, we not only give the first benchmark results of symmetric cryptography for the Intel Edison IoT platform but also describe a methodology of how to measure energy consumption on that platform.

Model and Method for Contributor’s Quality Assessment in Community Image Tagging Systems

2018 ◽  
pp. 45-51
Author(s):  
A. V. Ponomarev
Keyword(s):  
Large Scale ◽  
Wide Spectrum ◽  
Preference Relation ◽  
Pairwise Comparison ◽  
Ground Truth ◽  
Comparison Method ◽  
Characteristic Matrix ◽  
Image Tagging ◽  
Proposed Model

Introduction: Large-scale human-computer systems involving people of various skills and motivation into the information processing process are currently used in a wide spectrum of applications. An acute problem in such systems is assessing the expected quality of each contributor; for example, in order to penalize incompetent or inaccurate ones and to promote diligent ones.Purpose: To develop a method of assessing the expected contributor’s quality in community tagging systems. This method should only use generally unreliable and incomplete information provided by contributors (with ground truth tags unknown).Results:A mathematical model is proposed for community image tagging (including the model of a contributor), along with a method of assessing the expected contributor’s quality. The method is based on comparing tag sets provided by different contributors for the same images, being a modification of pairwise comparison method with preference relation replaced by a special domination characteristic. Expected contributors’ quality is evaluated as a positive eigenvector of a pairwise domination characteristic matrix. Community tagging simulation has confirmed that the proposed method allows you to adequately estimate the expected quality of community tagging system contributors (provided that the contributors' behavior fits the proposed model).Practical relevance: The obtained results can be used in the development of systems based on coordinated efforts of community (primarily, community tagging systems). 

Phoneme-to-Grapheme Conversion Based Large-Scale Pre-Training for End-to-End Automatic Speech Recognition

2020 ◽  
Author(s):  
Ryo Masumura ◽  
Naoki Makishima ◽  
Mana Ihori ◽  
Akihiko Takashima ◽  
Tomohiro Tanaka ◽  
...  
Keyword(s):  
Speech Recognition ◽  
Automatic Speech Recognition ◽  
Large Scale ◽  
End To End
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