3,262 research outputs found
A Multiagent System for Resource Distribution into a Cloud Computing Environment
It is undeniable that the term Cloud Computing has gained in importance at a remarkable pace. It is a technology which is becoming a common element of our life, due to the variety of devices related to the Internet of Things. In this technological frame, there are not many studies in which a Multiagent system has facilitated the management of a cloud-based computational environment; although a first sight its features (autonomy, decentralization, auto-organization, etc.) seem suitable for the task. This study presents the +Cloud which is a cloud platform managed by a Multiagent System
Agent and cyber-physical system based self-organizing and self-adaptive intelligent shopfloor
The increasing demand of customized production results in huge challenges to the traditional manufacturing systems. In order to allocate resources timely according to the production requirements and to reduce disturbances, a framework for the future intelligent shopfloor is proposed in this paper. The framework consists of three primary models, namely the model of smart machine agent, the self-organizing model, and the self-adaptive model. A cyber-physical system for manufacturing shopfloor based on the multiagent technology is developed to realize the above-mentioned function models. Gray relational analysis and the hierarchy conflict resolution methods were applied to achieve the self-organizing and self-adaptive capabilities, thereby improving the reconfigurability and responsiveness of the shopfloor. A prototype system is developed, which has the adequate flexibility and robustness to configure resources and to deal with disturbances effectively. This research provides a feasible method for designing an autonomous factory with exception-handling capabilities
Allocating Limited Resources to Protect a Massive Number of Targets using a Game Theoretic Model
Resource allocation is the process of optimizing the rare resources. In the
area of security, how to allocate limited resources to protect a massive number
of targets is especially challenging. This paper addresses this resource
allocation issue by constructing a game theoretic model. A defender and an
attacker are players and the interaction is formulated as a trade-off between
protecting targets and consuming resources. The action cost which is a
necessary role of consuming resource, is considered in the proposed model.
Additionally, a bounded rational behavior model (Quantal Response, QR), which
simulates a human attacker of the adversarial nature, is introduced to improve
the proposed model. To validate the proposed model, we compare the different
utility functions and resource allocation strategies. The comparison results
suggest that the proposed resource allocation strategy performs better than
others in the perspective of utility and resource effectiveness.Comment: 14 pages, 12 figures, 41 reference
Energy-aware Service Allocation for Cloud Computing
Energy efficiency has become an important managerial variable of IT management. Whereas cloud computing promises significantly higher levels of energy efficiency, it is still not known, if and to what extent outsourcing of software applications to cloud service providers affects the overall energy efficiency. This research is concerned with the allocation of cloud services from providers to customers and addresses the problem of energy-aware service allocation. The distributed nature of the problem, i.e., the multiple loci of control, entails the failure of centralised solutions. Hence, we approach this problem from a multiagent system perspective, which preserves the distributed setting of multiple service providers and customers. The contribution of our research is a game-theoretic framework for analysing service provider and customer interactions and a novel distributed allocation mechanism based on this framework to approximate energy-efficient, optimal allocations. We demonstrate the usefulness and efficacy of the proposed artifact in several simulation experiments
Improve the Performance of Industrial Agents using Fog Computing
In the last decade, the market requirements have been increasing by demanding
numerous different products being highly customizable. Given this need, the necessity
for dynamic and flexible production lines are a high priority to meet this change.
A traditional approach is not enough to meet the market demand and due to this,
several paradigms have been coined out to try and solve this problem. The proposed
approach is related to communication between the shop-floor modules in order to create
different products.
This work proposes an architecture where an integration layer will join a Multiagent
System capable of the more recent production paradigms with legacy hardware that
is present in the more traditional factories in order to have different products being
produced in the same production line.
This architecture that revolves an interface that can be used by the agents in the
factory in order to use the hardware modules to create a different product if need be.
The main features of this project is the fact that by using datamodels and an interface
created, it can be easily plugged new stations with different tools to modify the product
thus increasing the amount of products that can be created
Coalition Formation and Combinatorial Auctions; Applications to Self-organization and Self-management in Utility Computing
In this paper we propose a two-stage protocol for resource management in a
hierarchically organized cloud. The first stage exploits spatial locality for
the formation of coalitions of supply agents; the second stage, a combinatorial
auction, is based on a modified proxy-based clock algorithm and has two phases,
a clock phase and a proxy phase. The clock phase supports price discovery; in
the second phase a proxy conducts multiple rounds of a combinatorial auction
for the package of services requested by each client. The protocol strikes a
balance between low-cost services for cloud clients and a decent profit for the
service providers. We also report the results of an empirical investigation of
the combinatorial auction stage of the protocol.Comment: 14 page
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