Toward Agent-Based Grid Computing

2011 ◽  
pp. 173-188
Author(s):  
Lizhe Wang
Keyword(s):  
Grid Computing ◽  
Research Trends ◽  
Future Research ◽  
Research Issues ◽  
Agent Based ◽  
Computing Paradigm ◽  
Natural Choice ◽  
Key Technologies ◽  
Computing Grid ◽  
Multi Agent

This chapter discusses research issues related to agent-based Grid computing. Grid computing now becomes an innovative computing paradigm and helps build non-traditional computing infrastructures and applications. Multiple-agent systems and algorithms, on the other hand, mainly focus on solving corporative problems among multiple participants, mainly from theoretical aspects. It is thus a natural choice to combine these two key technologies together and benefit both research communities. This chapter first reviews background for multi-agent system, agent-based computing, and Grid computing. Research challenges and issues are characterized and identified together with possible solutions. After the investigation of current research efforts of agent-based Grid computing, future research trends are presented and studied.

Enabling Key Technologies and Emerging Research Challenges Ahead of 5G Networks: An Extensive Survey

2018 ◽  
Vol 2 (3) ◽  
pp. 133 ◽  
Author(s):  
C. Amali ◽  
B. Ramachandran
Keyword(s):  
Cellular Networks ◽  
Network Capacity ◽  
Network Function Virtualization ◽  
Smart Devices ◽  
Future Research ◽  
Technical Solution ◽  
5G Networks ◽  
Modulation Formats ◽  
Research Issues ◽  
Key Technologies

The evolution towards 5G networks is expected to slake the growing thirst of internet traffic with improved Quality of Service (QoS) and reduced energy consumption and cost. The increased penetration of smart devices and induction of arising multimedia applications, together with high quality video services are already crafting a milestone on existing cellular networks. These surging demands dictate that radical enhancements need to be made in cellular architecture to drift towards ultra-dense networks. The 5G system is envisioned to achieve improved data rate, increased capacity, decreased latency, and enhanced spectral efficiency in order to provide technical solution for the challenges behind the cellular networks. Thus, the 5G era is emerging to quench the increasing demand for network capacity, to manage explosive growth of traffic patterns and to face the challenges caused by the proliferation of versatile applications and high-end devices. In this paper, we make a broad survey on 5G cellular network architecture and some of the promising key technologies such as cloud RAN (Radio Access Network), Software-Defined Networking (SDN), Network Function Virtualization (NFV) and modulation formats. Finally, this ground-breaking survey highlights major existing research issues and possible future research directions in the next new era of mobile wireless networks.

Human-Based Models for Ambient Intelligence Environments

2011 ◽  
pp. 98-112
Author(s):  
Giovanni Acampora ◽  
Vicenzo Loia ◽  
Michele Nappi ◽  
Stefano Ricciardi
Keyword(s):  
Spatial Distribution ◽  
Ambient Intelligence ◽  
Contextual Information ◽  
Agent Based ◽  
Key Technologies ◽  
Concurrent Computation ◽  
Critical Issues ◽  
Multi Agent ◽  
User Friendly ◽  
Biometric Features

Ambient intelligence gathers best results from three key technologies, ubiquitous computing, ubiquitous communication, and intelligent user friendly interfaces. The functional and spatial distribution of tasks is a natural thrust to employ multi-agent paradigm to design and implement AmI environments. Two critical issues, common in most of applications, are (1) how to detect in a general and efficient way context from sensors and (2) how to process contextual information in order to improve the functionality of services. Here we describe an agent-based ambient intelligence architecture able to deliver services on the basis of physical and emotional user status captured from a set of biometric features. Abstract representation and management is achieved thanks to two markup languages, H2ML and FML, able to model behavioral as well as fuzzy control activities and to exploit distribution and concurrent computation in order to gain real-time performances.

Architecture and Key Technologies of Cloud Computing

2013 ◽  
Vol 756-759 ◽  
pp. 1953-1956
Author(s):  
Li Yuan Xiao ◽  
Zheng Wang ◽  
Rui Wang ◽  
Hai Ning Wang
Keyword(s):  
Cloud Computing ◽  
Parallel Computing ◽  
Distributed Computing ◽  
Grid Computing ◽  
The Internet ◽  
Key Technologies ◽  
The Future ◽  
Computing Grid

The Internet has changed the computing world in a drastic way from the advent of the Internet in 1990. The concepts of distributed computing, parallel computing, grid computing and cloud computing have been proposed successively. Although cloud computing is generally recognized as a technology which will has a significant impact on IT in the future. But cloud computing is still in its infancy. In this paper we will discuss the architecture and the key technologies of the cloud computing.

scholarly journals Recent Advances in Collaborative Scheduling of Computing Tasks in an Edge Computing Paradigm

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 779
Author(s):  
Shichao Chen ◽  
Qijie Li ◽  
Mengchu Zhou ◽  
Abdullah Abusorrah
Keyword(s):  
Problem Formulation ◽  
Computing System ◽  
High Energy ◽  
Edge Computing ◽  
Computation Offloading ◽  
Future Research ◽  
Research Issues ◽  
Computing Paradigm ◽  
Collaborative Scheduling ◽  
And Storage

In edge computing, edge devices can offload their overloaded computing tasks to an edge server. This can give full play to an edge server’s advantages in computing and storage, and efficiently execute computing tasks. However, if they together offload all the overloaded computing tasks to an edge server, it can be overloaded, thereby resulting in the high processing delay of many computing tasks and unexpectedly high energy consumption. On the other hand, the resources in idle edge devices may be wasted and resource-rich cloud centers may be underutilized. Therefore, it is essential to explore a computing task collaborative scheduling mechanism with an edge server, a cloud center and edge devices according to task characteristics, optimization objectives and system status. It can help one realize efficient collaborative scheduling and precise execution of all computing tasks. This work analyzes and summarizes the edge computing scenarios in an edge computing paradigm. It then classifies the computing tasks in edge computing scenarios. Next, it formulates the optimization problem of computation offloading for an edge computing system. According to the problem formulation, the collaborative scheduling methods of computing tasks are then reviewed. Finally, future research issues for advanced collaborative scheduling in the context of edge computing are indicated.

scholarly journals Roles and Research Trends of Artificial Intelligence in Mathematics Education: A Bibliometric Mapping Analysis and Systematic Review

Mathematics ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 584 ◽  
Author(s):  
Gwo-Jen Hwang ◽  
Yun-Fang Tu
Keyword(s):  
Artificial Intelligence ◽  
Systematic Review ◽  
Education Research ◽  
Mathematics Education ◽  
Research Trends ◽  
Mathematics Education Research ◽  
Future Research ◽  
Research Issues ◽  
Bibliometric Mapping ◽  
Mapping Analysis

Learning mathematics has been considered as a great challenge for many students. The advancement of computer technologies, in particular, artificial intelligence (AI), provides an opportunity to cope with this problem by diagnosing individual students’ learning problems and providing personalized supports to maximize their learning performances in mathematics courses. However, there is a lack of reviews from diverse perspectives to help researchers, especially novices, gain a whole picture of the research of AI in mathematics education. To this end, this research aims to conduct a bibliometric mapping analysis and systematic review to explore the role and research trends of AI in mathematics education by searching for the relevant articles published in the quality journals indexed by the Social Sciences Citation Index (SSCI) from the Web of Science (WOS) database. Moreover, by referring to the technology-based learning model, several dimensions of AI in mathematics education research, such as the application domains, participants, research methods, adopted technologies, research issues and the roles of AI as well as the citation and co-citation relationships, are taken into account. Accordingly, the advancements of AI in mathematics education research are reported, and potential research topics for future research are recommended.

Intelligent Agents for Business Process Management Systems

2010 ◽  
pp. 97-131 ◽  
Author(s):  
Janis Grundspenkis ◽  
Antons Mislevics
Keyword(s):  
Business Process ◽  
Intelligent Agents ◽  
Business Process Management ◽  
Process Management ◽  
Management Systems ◽  
Future Research ◽  
Multi Agent Systems ◽  
Agent Based ◽  
Multi Agent ◽  
Insight Into

The chapter is focused on the usage of intelligent agents in business process modelling and business process management systems in particular. The basic notions of agent-based systems and their architectures are given. Multiagent systems as sets of multiple interacting software agents, as well as frameworks and methodologies of their development are discussed. Three kinds of architectures of agent-based systems – holons, multi-multi-agent systems and aspect-oriented architecture are described. Examples of already implemented agent-based systems in logistics, transportation and supply chain management are given. The chapter gives an insight into recent business process management systems and their architectures, and highlights several issues and challenges which underpin the necessity for agent-based business process management. Methodologies and implementation of agent-based business process management systems are discussed and directions of future research in this area are outlined.

Applications of multi-agent systems from the perspective of construction management: A literature review

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Liqun Xiang ◽  
Yongtao Tan ◽  
Geoffrey Shen ◽  
Xin Jin
Keyword(s):  
Literature Review ◽  
Construction Management ◽  
Future Research ◽  
Multi Agent Systems ◽  
Agent Based Models ◽  
Content Type ◽  
Agent Based ◽  
Agent Systems ◽  
Complex Problems ◽  
Multi Agent

PurposeThe applications of multi-agent systems (MASs) are considered to be among the most promising paradigms for detailed investigations and reliable problem-solving methods, and MAS applications make it possible for researchers and practitioners to better understand complex systems. Although a number of prior studies have been conducted to address complex issues that arise from construction projects, few studies have summarised the applications and discussed the capacity of MASs from the perspective of construction management. To fill the gap, this paper provides a comprehensive literature review of MAS applications from the perspective of construction management.Design/methodology/approachWeb of Science and Scopus are the most commonly used international databases in conducting the literature reviews. A total of 86 relevant papers published in SCI-Expanded, SSCI and Ei Compendex journals related to the application of MASs from the perspective of construction management are selected to be analysed and discussed in this paper.FindingsBased on the 86 collected publications, the utilisations of MASs to support the management of the supply chain and the improvement of project performance are identified from the perspective of construction management, the characteristics and barriers of current MAS applications are analysed, a framework for developing agent-based models to address complex problems is proposed, and future research directions of MAS applications are discussed.Originality/valueThis review can serve as a useful reference for scholars to enhance their understanding of the current research and guide future research on MASs. The proposed framework can help build agent-based models to address complex problems in construction management.

Multi-Agent-Based Middleware over Grid Computing

2005 ◽  
Author(s):  
Chen Jia ◽  
Wu Yue ◽  
Hui Bei ◽  
Ye Yalan
Keyword(s):  
Grid Computing ◽  
Agent Based ◽  
Multi Agent

The Study on the Key Technologies in Multiple Agent-Based Intelligent Tutoring System

2013 ◽  
Vol 846-847 ◽  
pp. 1889-1892
Author(s):  
Yan Yu ◽  
Jian Hua Wang
Keyword(s):  
Intelligent Tutoring ◽  
Intelligent Tutoring System ◽  
Multi Agent Systems ◽  
Teaching System ◽  
Network Teaching ◽  
Agent Based ◽  
Agent Systems ◽  
Multiple Agent ◽  
Key Technologies ◽  
Multi Agent

Network teaching system has changed the way of teaching, with the artificial intelligence technology, Currently, many traditional network teaching system has been unable to meet the needs of the public.After studying the defects in current teaching systems and combining features of multi-agent systems and their application theories in intelligent teaching systems, this paper, integrating the concept of multi-agent systems, discusses the key technologies in multiple agent-based intelligent tutoring systems based on multiple agent-based intelligent tutoring system models. To achieve true intelligent teaching system, simulate real teaching environments, offer customized teaching services, and really realize students' independent learning and collaborative learning.

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