Internet of Things Service Provisioning Platform for Cross-Application Cooperation

2016 ◽  
Vol 13 (1) ◽  
pp. 1-22 ◽  
Author(s):  
Shuai Zhao ◽  
Bo Cheng ◽  
Le Yu ◽  
Shou-lu Hou ◽  
Yang Zhang ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Large Scale ◽  
Physical Space ◽  
Service Provisioning ◽  
Problem Domain ◽  
Tight Coupling ◽  
User Requirement ◽  
Loosely Coupled ◽  
Heterogeneous Devices ◽  
On Demand

With the development of Internet of Things (IoT), large-scale of resources and applications atop them emerge. However, most of existing efforts are “silo” solutions, there is a tight-coupling between the device and the application. The paradigm for IoT and its corresponding infrastructure are required to move away from isolated solutions towards cooperative models. Recent works have focused on applying Service Oriented Architecture (SOA) to IoT service provisioning. Other than the traditional services of cyberspace which are oriented to a two-tuple problem domain, IoT services are faced with a three-tuple problem domain of user requirement, cyberspace and physical space. One challenge of existing works is lacking of efficient mechanism to on-demand provisioning the sensing information in a loosely-coupled, decentralized way and then dynamically coordinate the relevant services to rapidly respond to changes in the physical world. Another challenge is how to systematically and effectively access (plug) the heterogeneous devices without intrusive changing. This paper proposes a service provisioning platform which enables to access heterogeneous devices and expose device capabilities as light-weighted service, and presents an event-based message interaction mode to facilitate the asynchronous, on-demand sharing of sensing information in distributed, loosely-coupled IoT environment. It provides the basic infrastructure for IoT application pattern: inner-domain high-degree autonomy and inter-domain dynamic coordination. The practicability of platform is validated by experimental evaluations and a District Heating Control and Information System (DHCIS).

Internet of Things Service Provisioning Platform for Cross-Application Cooperation

2020 ◽  
pp. 655-678
Author(s):  
Shuai Zhao ◽  
Bo Cheng ◽  
Le Yu ◽  
Shou-lu Hou ◽  
Yang Zhang ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Large Scale ◽  
Service Provisioning ◽  
Problem Domain ◽  
Tight Coupling ◽  
User Requirement ◽  
Loosely Coupled ◽  
Heterogeneous Devices ◽  
On Demand ◽  
Basic Infrastructure

With the development of Internet of Things (IoT), large-scale of resources and applications atop them emerge. However, most of existing efforts are “silo” solutions, there is a tight-coupling between the device and the application. The paradigm for IoT and its corresponding infrastructure are required to move away from isolated solutions towards cooperative models. Recent works have focused on applying Service Oriented Architecture (SOA) to IoT service provisioning. Other than the traditional services of cyberspace which are oriented to a two-tuple problem domain, IoT services are faced with a three-tuple problem domain of user requirement, cyberspace and physical space. One challenge of existing works is lacking of efficient mechanism to on-demand provisioning the sensing information in a loosely-coupled, decentralized way and then dynamically coordinate the relevant services to rapidly respond to changes in the physical world. Another challenge is how to systematically and effectively access (plug) the heterogeneous devices without intrusive changing. This paper proposes a service provisioning platform which enables to access heterogeneous devices and expose device capabilities as light-weighted service, and presents an event-based message interaction mode to facilitate the asynchronous, on-demand sharing of sensing information in distributed, loosely-coupled IoT environment. It provides the basic infrastructure for IoT application pattern: inner-domain high-degree autonomy and inter-domain dynamic coordination. The practicability of platform is validated by experimental evaluations and a District Heating Control and Information System (DHCIS).

scholarly journals Efficient Byzantine Consensus Mechanism Based on Reputation in IoT Blockchain

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Xu Yuan ◽  
Fang Luo ◽  
Muhammad Zeeshan Haider ◽  
Zhikui Chen ◽  
Yucheng Li
Keyword(s):  
Internet Of Things ◽  
Large Scale ◽  
Consensus Algorithm ◽  
Consensus Algorithms ◽  
Heterogeneous Devices ◽  
Blockchain Technology ◽  
Critical Problems ◽  
Iot Devices ◽  
Reliability And Robustness ◽  
The Internet Of Things

Blockchain technology has advanced rapidly in recent years and is now widely used in a variety of fields. Blockchain appears to be one of the best solutions for managing massive heterogeneous devices while achieving advanced data security and data reputation, particularly in the field of large-scale IoT (Internet of Things) networks. Despite the numerous advantages, there are still challenges while deploying IoT applications on blockchain systems due to the limited storage, power, and computing capability of IoT devices, and some of these problems are caused by the consensus algorithm, which plays a significant role in blockchain systems by ensuring overall system reliability and robustness. Nonetheless, most existing consensus algorithms are prone to poor node reliability, low transaction per second (TPS) rates, and scalability issues. Aiming at some critical problems in the existing consensus algorithms, this paper proposes the Efficient Byzantine Reputation-based Consensus (EBRC) mechanism to resolve the issues raised above. In comparison to traditional algorithms, we reinvented ways to evaluate node reliability and robustness and manage active nodes. Our experiments show that the EBRC algorithm has lower consensus delay, higher throughput, improved security, and lower verification costs. It offers new reference ideas for solving the Internet of Things+blockchain+Internet court construction problem.

scholarly journals An Overview of Public Cloud Security Issues

2014 ◽  
Vol 3 (2) ◽  
pp. 440-445
Author(s):  
Atefeh Heydari ◽  
Mohammad Ali Tavakoli ◽  
Mohammad Riazi
Keyword(s):  
Cloud Computing ◽  
Large Scale ◽  
Physical Space ◽  
Public Cloud ◽  
Huge Number ◽  
Security Issues ◽  
On Demand ◽  
Computing Services ◽  
Cloud Computing Services ◽  
Computing Platforms

Traditionally, computational needs of organizations were alleviated by purchasing, updating and maintaining required equipments. Beside expensive devices, physical space to hold them, technical staffs to maintain them and many other side costs were essential prerequisites of this matter. Nowadays with the development of cloud computing services, a huge number of peoples and organizations are served in terms of computational needs by large scale computing platforms. Offering enormous amounts of economical compute resources on-demand motivates organizations to outsource their computational needs incrementally. Public cloud computing vendors offer their infrastructure to the customers via the internet. It means that the control of customers’ data is not in their hands anymore. Unfortunately various security issues are emerged from this subject. In this paper the security issues of public cloud computing are overviewed. More destructive security issues are highlighted in order to be used by organizations in making better decisions for moving to cloud.

Convergence of Manufacturing Cloud and Industrial IoT

2019 ◽  
pp. 49-78
Author(s):  
Manoj Himmatrao Devare
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Large Scale ◽  
Manufacturing Industry ◽  
Business Environment ◽  
On Demand ◽  
Industrial Internet ◽  
Industrial Iot ◽  
Key Technologies ◽  
Manufacturing Resources

The manufacturing cloud (CMfg) covers the use of three key technologies including cloud computing, the industrial internet of things (IIoT), and collaborative engineering for achieving the productivity and quality challenges in the big manufacturing, which is enabled due to the communication, mobile, and broadcasting network. It is necessary to establish a flexible and adaptive infrastructure for manufacturing industry to share and use various manufacturing resources and services on-demand under the dynamic, complicated, and large-scale business environment. The CMfg makes the industry more agile, responsive, and reconfigurable for exposure to the industry as a global manufacturing enterprise. The chapter considers the CMfg facets and IIoT, use cases in the manufacturing industry, and explains IIoT and CMfg as a complementary technology.

scholarly journals On the Root Causes of the Fukushima Daiichi Disaster from the Perspective of High Complexity and Tight Coupling in Large-Scale Systems

Symmetry ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 414
Author(s):  
Atsuo Murata ◽  
Waldemar Karwowski
Keyword(s):  
Nuclear Power ◽  
Power Plants ◽  
Large Scale ◽  
High Complexity ◽  
Tight Coupling ◽  
Large Scale Systems ◽  
Safety Issues ◽  
Loss Of Coolant ◽  
Station Blackout ◽  
Fukushima Daiichi

This study explores the root causes of the Fukushima Daiichi disaster and discusses how the complexity and tight coupling in large-scale systems should be reduced under emergencies such as station blackout (SBO) to prevent future disasters. First, on the basis of a summary of the published literature on the Fukushima Daiichi disaster, we found that the direct causes (i.e., malfunctions and problems) included overlooking the loss of coolant and the nuclear reactor’s failure to cool down. Second, we verified that two characteristics proposed in “normal accident” theory—high complexity and tight coupling—underlay each of the direct causes. These two characteristics were found to have made emergency management more challenging. We discuss how such disasters in large-scale systems with high complexity and tight coupling could be prevented through an organizational and managerial approach that can remove asymmetry of authority and information and foster a climate of openly discussing critical safety issues in nuclear power plants.

scholarly journals A Survey on Edge Performance Benchmarking

2021 ◽  
Vol 54 (3) ◽  
pp. 1-33
Author(s):  
Blesson Varghese ◽  
Nan Wang ◽  
David Bermbach ◽  
Cheol-Ho Hong ◽  
Eyal De Lara ◽  
...  
Keyword(s):  
Large Scale ◽  
Future Internet ◽  
Coupled Systems ◽  
Operational Conditions ◽  
Loosely Coupled ◽  
Performance Benchmarking ◽  
The Past ◽  
Geographically Dispersed ◽  
Tightly Coupled ◽  
History Of

Edge computing is the next Internet frontier that will leverage computing resources located near users, sensors, and data stores to provide more responsive services. Therefore, it is envisioned that a large-scale, geographically dispersed, and resource-rich distributed system will emerge and play a key role in the future Internet. However, given the loosely coupled nature of such complex systems, their operational conditions are expected to change significantly over time. In this context, the performance characteristics of such systems will need to be captured rapidly, which is referred to as performance benchmarking, for application deployment, resource orchestration, and adaptive decision-making. Edge performance benchmarking is a nascent research avenue that has started gaining momentum over the past five years. This article first reviews articles published over the past three decades to trace the history of performance benchmarking from tightly coupled to loosely coupled systems. It then systematically classifies previous research to identify the system under test, techniques analyzed, and benchmark runtime in edge performance benchmarking.

Sign in / Sign up

Export Citation Format

Share Document