Proposal of a Multi-agent Based Flexible IoT Edge Computing Architecture Harmonizing Its Control with Cloud Computing

2017 ◽  
Author(s):  
Shinji Kitagami ◽  
Tadashi Ogino ◽  
Takuo Suganuma ◽  
Norio Shiratori
Keyword(s):  
Cloud Computing ◽  
Edge Computing ◽  
Computing Architecture ◽  
Agent Based ◽  
Multi Agent

scholarly journals A Multi-agent Based Flexible IoT Edge Computing Architecture Harmonizing Its Control with Cloud Computing

2018 ◽  
Vol 8 (2) ◽  
pp. 218-239 ◽  
Author(s):  
Tadashi Ogino ◽  
Shinji Kitagami ◽  
Takuo Suganuma ◽  
Norio Shiratori
Keyword(s):  
Cloud Computing ◽  
Edge Computing ◽  
Computing Architecture ◽  
Agent Based ◽  
Multi Agent

A Multi-agent Based Flexible IoT Edge Computing Architecture and Application to ITS

2019 ◽  
pp. 47-52 ◽  
Author(s):  
Tadashi Ogino ◽  
◽  
Shinji Kitagami ◽  
Norio Shiratori
Keyword(s):  
Edge Computing ◽  
Computing Architecture ◽  
Agent Based ◽  
Multi Agent

scholarly journals A Novel Multi-Agent-Based Collaborative Virtual Manufacturing Environment Integrated with Edge Computing Technique

Energies ◽  
2019 ◽  
Vol 12 (14) ◽  
pp. 2815
Author(s):  
Xiaohui Zhang ◽  
Shufeng Tang ◽  
Xinhua Liu ◽  
Reza Malekian ◽  
Zhixiong Li
Keyword(s):  
Virtual Manufacturing ◽  
Edge Computing ◽  
Manufacturing Environment ◽  
Computing Technique ◽  
Agent Based ◽  
System A ◽  
Multi Agent ◽  
Save Energy ◽  
Virtual Manufacturing Environment

This paper proposes a multi-agent-based collaborative virtual manufacturing environment (VME) to save energy consumption and improve efficiency in the manufacturing process. In order to achieve the high autonomy of the manufacturing system, a multi-agent system (MAS) is designed to build a collaborative VME. In this new VME environment, edge computing is embedded to strengthen the cyber resource utilization and system economy. Moreover, an efficient communication channel between networks is proposed. The subsequent cooperation and collaboration protocols among agents are designed to ensure flexible and process-oriented operations. Furthermore, the fuzzy resolution algorithm is employed to resolve the competition conflicts among function-similar MASs in the distributed manufacturing scenario. Lastly, a simulation and case study are performed to evaluate the performance of the proposed VME in Internet of Things (IoT)-based manufacturing. The analysis results have demonstrated the feasibility and effectiveness of the proposed VME system.

An Overview of Cloud and Edge Computing Architecture and Its Current Issues and Challenges

2021 ◽  
pp. 2340-2370
Author(s):  
Guru Prasad Bhandari ◽  
Ratneshwer Gupta
Keyword(s):  
Cloud Computing ◽  
Edge Computing ◽  
Network Access ◽  
Computing Systems ◽  
Computing Architecture ◽  
Resource Pooling ◽  
Cloud Architecture ◽  
On Demand ◽  
Emerging Issues ◽  
Self Service

Edge computing is a technique of optimizing cloud computing systems by performing data processing at the edge of the network, near the source of the data in the systems. And, cloud computing is a service that delivers on-demand self-service, broad network access, resource pooling, rapid elasticity or expansion, which is trending in today's technology-driven world. With the advantage of flexibility, storage, sharing, and easy accessibility, cloud is being used by major players in IT (information technology). This chapter highlights cloud/edge computing architecture and its current issues and challenges from technological and organizational aspects. A brief introduction of edge computing architecture with similar technologies along with its service models is discussed. A few counterexamples of cloud computing architecture are showed. Organizational aspects of cloud computing architecture, as well as IBM and Oracle reference cloud architecture, are briefly presented. Some emerging issues and challenges associated with cloud/edge computing on its utilization are also elaborated.

Multi-agent based dynamic resource provisioning and monitoring for cloud computing systems infrastructure

2015 ◽  
Vol 18 (2) ◽  
pp. 919-932 ◽  
Author(s):  
Mahmoud Al-Ayyoub ◽  
Yaser Jararweh ◽  
Mustafa Daraghmeh ◽  
Qutaibah Althebyan
Keyword(s):  
Cloud Computing ◽  
Resource Provisioning ◽  
Computing Systems ◽  
Agent Based ◽  
Dynamic Resource Provisioning ◽  
Multi Agent ◽  
Dynamic Resource

Opportunistic Edge Computing Architecture for Smart Healthcare Systems

2021 ◽  
pp. 289-306
Author(s):  
Nivethitha V. ◽  
Aghila G.
Keyword(s):  
Cloud Computing ◽  
Healthcare Systems ◽  
Edge Computing ◽  
Healthcare Applications ◽  
Sensitive Data ◽  
Network Resource ◽  
Computing Architecture ◽  
Healthcare Data ◽  
Smart Healthcare ◽  
Network Response Time

Some of the largest global industries that is driving smart city environments are anywhere and anytime health monitoring applications. Smart healthcare systems need to be more preventive and responsive as they deal with sensitive data. Even though cloud computing provides solutions to the smart healthcare applications, the major challenge imposed on cloud computing is how could the centralized traditional cloud computing handle voluminous data. The existing models may encounter problems related to network resource utilization, overheads in network response time, and communication latency. As a solution to these problems, edge-oriented computing has emerged as a new computing paradigm through localized computing. Edge computing expands the compute, storage, and networking capabilities to the edge of the network which will respond to the above-mentioned issues. Based on cloud computing and edge computing, in this chapter an opportunistic edge computing architecture is introduced for smart provisioning of healthcare data.

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