An Evolutionary Approach for Cloud Learning Agents in Multi-cloud Distributed Contexts

Comi, Antonello; Fotia, Lidia; Messina, Fabrizio; Pappalardo, Giuseppe; Rosaci, Domenico; Sarné, Giuseppe M. L.

doi:10.1109/wetice.2015.27

Cited by 12 publications

(7 citation statements)

References 27 publications

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“…There are also recent agent-based efforts that try to fuse adaptivity in cloud resources usage. For example, (Comi et al,2015) present an approach based on agent cloning, i.e. a mechanism of agent reproduction allowing providers to substitute an "unsatisfactory" agent acting in a "cloud context" with a clone of an existing agent having suitable knowledge and good reputation in the multi-cloud context.…”

Section: Application-specific αDaptivitymentioning

confidence: 99%

Challenges and Research Directions in Big Data-driven Cloud Adaptivity

Τσαγκαρόπουλος

Papageorgiou

Apostolou

et al. 2018

Proceedings of the 8th International Conference on Cloud Computing and Services Science

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Abstract:Mainstream cloud technologies are challenged by real-time, big data processing requirements or emerging applications. This paper surveys recent research efforts on advancing cloud computing virtual infrastructures and real-time big data technologies in order to provide dynamically scalable and distributed architectures over federated clouds. We examine new methods for developing cloud systems operating in a real-time, big data environment that can sense the context of the application environment and can adapt the infrastructure accordingly. We describe research topics linked to the challenge of adaptivity such as situation awareness, context detection, service-level objectives, and the capability to predict extraordinary situations requiring remedying action. We also describe research directions for realising adaptivity in cloud computing and we present a conceptual framework that represents research directions and shows interrelations.

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Section: Application-specific αDaptivitymentioning

confidence: 99%

Challenges and Research Directions in Big Data-driven Cloud Adaptivity

Τσαγκαρόπουλος

Papageorgiou

Apostolou

et al. 2018

Proceedings of the 8th International Conference on Cloud Computing and Services Science

View full text Add to dashboard Cite

show abstract

“…The first one allocates the resources to VM while the second allocates VM in order to balance the load in federated cloud environment. Comi et al [11] proposed an evolutionary approach in addressing the problem of resource management in federated cloud providers by means of an agent cloning mechanism. Intelligent and adaptive software agents' features are made possible by the integration of learning techniques to multi agent systems.…”

Section: Related Workmentioning

confidence: 99%

“…As seen in [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19] most of the works in clouds concern the study of fixed system models or architecture. There is no possibility to the federated clouds to acquire new providers with challenged price.…”

Section: Related Workmentioning

confidence: 99%

AMACE: agent based multi-criterions adaptation in cloud environment

Sofiane

Zitouni

Djoudi

2018

Hum. Cent. Comput. Inf. Sci.

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Cloud computing is a rising technology. It represents a business model in which enterprises can make an enormous economy by reducing infrastructure investments. In cloud, users usually pay for the usage (i.e., CPU, storage, and network bandwidth, platforms, and application services) counted by the number of instance-hours incurred in a pay-as-you-go model. Cloud federation comprises services from different aggregated providers offering clients, in addition to sharing a wide range of resources, the opportunity to choose the best cloud service providers. We identify many basic features of cloud federation such as the best cost, service flexibility and availability to meet a particular business or technological need within their organization. An efficient multi-agent resource allocation technique is necessary for building an efficient system. Brokering agent resource allocation strategy must maximize the benefit in resource allocation, take advantage of the large services offered by the federation, which can be said to realize the best quality of service provision and improve

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“…As stated in the Section 1, the aim of agent-based modeling and simulation (ABMS) is to model the collective behaviors of interacting autonomous entities 11 . A wide range of applications can be mentioned, as supply chains, consumer markets 4 , IoT applications 12-13 , complex networks simulation 5,14-20 , mobile agents systems 21,22 , threat of bio-warfare and multi-robot simulations 6,23-26 .…”

Section: Related Workmentioning

confidence: 99%

“…Listing 1 reports a frame of the JavaScript code written for the simulation where two types of agents are defined: UAVs and Plants (lines [15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33][34][35]. The agents are linked to the shared Communication Bus, and coupled with a Movement Worker (the UAVs) and a shared Collision Worker.…”

Section: Case Study: Photo-voltaic Plant Aerial Inspection By Uav Flockmentioning

confidence: 99%

Web-based Simulations of Multi-agent Systems

et al. 2017

Self Cite

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This paper describes the architecture of AgentSimJs, a Javascript-based multi-agent simulator intended to execute and visualize simulations through a Web browser. It includes the needed capabilities to render a 3D scene with objects and agents. AgentSimJs has a modular architecture, the several different components provide a set of flexible primitives to program the agent behaviour. With AgentSimJs, a user can perform a fine tuning of all the aspects related to communication, motion, and group formation. Users can also define a custom network topology and communication model.

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An Evolutionary Approach for Cloud Learning Agents in Multi-cloud Distributed Contexts

Cited by 12 publications

References 27 publications

Challenges and Research Directions in Big Data-driven Cloud Adaptivity

Challenges and Research Directions in Big Data-driven Cloud Adaptivity

AMACE: agent based multi-criterions adaptation in cloud environment

Web-based Simulations of Multi-agent Systems

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