Applying the Prometheus Methodology for an Internet of Things Architecture

Manațe, Bogdan; Fortiş, Teodor-Florin; Moore, Philip

doi:10.1109/ucc.2014.55

Cited by 12 publications

(7 citation statements)

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“…Because the multi-agent architecture proposed in [19] was developed to target a wide-spread geographical area, the audit information is useful to determine which area offers a high QoS/QoE for end-users. Thus, the edge computing services offered for certain geographical areas can be configured for best performance results considering the audit data collected for the specified areas.…”

Section: Managing Gpu Instancesmentioning

confidence: 99%

“…In order to scale the multi-agent architecture proposed in [19], a large number of virtual machine instances are launched in the cloud so that the system load can be evenly distributed on the available resources. The system can be scaled as long as the cloud provider has the necessary resources available, otherwise additional resources may be launched using another public cloud provider or a private cloud.…”

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confidence: 99%

“…Given the fact that it is impossible for a single cloud provider to scatter its data centers around the globe to The multi-agent architecture [19] offer on demand computing power as close as possible to their clients, a viable solution to overcome this problem is represented by a cloud federation [5]. By using a federation of clouds and a location discovery services, the resources are rented from the closest available cloud provider thus enabling the infrastructure to offer fast and localized support.…”

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confidence: 99%

“…Architecture. The proposed architecture for the multi-agent system [19] presented in Figure 3.1 uses the agents as independent and mobile entities, which are specialized to solve specific domain oriented issues that are introduced by the Internet of Things paradigm. As seen in Fig.…”

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Optimizing cloud resources allocation for an Internet of Things architecture

Manațe¹,

Fortiş²,

Negru³

2015

SCPE

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Abstract. The optimization of the cloud resources used to power a multi-agent Internet of Things architecture is an important issue which has an important impact on the overall operation cost of the architecture. The resources tenancy is a costly operation, thus their allocation and management should be optimized based on the usage patterns. The infrastructure for the multi-agent system should not be affected by the deployment or maintenance life cycle, operations require parts of the system, or even the entire system to be offline during the execution of scheduled procedures. This paper outlines of the importance of the infrastructure audit, which offers a good insight of how the resources are used, the geographical areas which are heavily used and where the allocation or release of used resources is mandatory. Also, the security audit, in a distributed multi-agent architecture that handles a large number of heterogeneous devices, represents a good mechanism for performance improvement.Key words: Internet of Things, cloud computing, multi-agent systems 1. Introduction. The recent advances in Internet of Things (IoT) technologies and the cloud computing adoption have led to an increased usage of this two paradigms to create solid architectures that are able to handle hundred of thousands of concurrent connections, at the same time offering a good Quality of Service (QoS) and Quality of Experience (QoE) for the end user. The resources renting from public cloud providers for supporting the backbone infrastructure for an IoT architecture is beneficial for small and medium-sized enterprises (SME) or academic institutions which are trying to reach a large number of clients, because there is no need to upgrade or maintain the physical infrastructure. Even though the cloud client is not completely aware of the exact location of the hardware that delivers the required information, there are methods available that can determine the best route (considering both geographical location and bandwidth) for optimal performance [39].For handling a big number of connections from a wide range of devices, an Internet of Things architecture should employ a fast, secure, reliable and fail safe infrastructure for the services offered to the end users which rely upon the manner in which the information is collected. Because of different usage patterns that result from the daily routine of different groups of users, the best solution for building an infrastructure for the IoT framework relies on the elasticity provided by the cloud computing paradigm [11,15,23,33]. Also, the operational cost for maintaining the architecture up and running can be significantly reduced by releasing unused resources at daily time intervals when the audit operations report a low usage of the infrastructure.From the reliability and operational standpoint, the core infrastructure for the multi-agent system needs to bypass any bottlenecks introduced by the on demand created infrastructure. Therefore, any replacement or restart of the virtual machines should be...

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Section: Managing Gpu Instancesmentioning

confidence: 99%

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confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Optimizing cloud resources allocation for an Internet of Things architecture

Manațe¹,

Fortiş²,

Negru³

2015

SCPE

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“…A similar ontology based multi-agent system is presented in [6] where the concepts related to Internet of Things (IoT) are described using an ontology to facilitate the discovery and identification of various devices. In [7] is presented an ubiquitous sensing system based on Wireless sensor networks, which is capable to collect data from multiple monitored environments.…”

Section: Background and Related Workmentioning

confidence: 99%

A Multi-agent Architecture for Ontology-Based Diagnosis of Mental Disorders

Ivașcu

Manațe

Negru

2015

2015 17th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)

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This paper presents a Multi-agent system that facilitates the remote monitoring of the elderly patients which are susceptible to mental disorder diseases. In order to find early signs of health condition depreciation we have assessed four of the most common mental disorder diseases to find which kind of sensors can detect specific symptoms with the main purpose of creating an early warning system. The diagnosis component is based on an ontology that defines the relations between sensors, symptoms and diseases. Based on these relationships a specialized agent can inform the medical personnel about the detected symptoms.

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