A Novel Approach for Fair and Secure Resource Allocation in Storage Cloud Architectures Based on DRF Mechanism

2014 ◽  
Author(s):  
Maha Jebalia ◽  
Asma Ben Letaifa ◽  
Mohamed Hamdi ◽  
Sami Tabbane
Keyword(s):  
Resource Allocation ◽  
Novel Approach

Resource Allocation for Reduction of Epistemic Uncertainty in Simulation-Based Multidisciplinary Design

2015 ◽  
Author(s):  
Zhen Jiang ◽  
Shishi Chen ◽  
Daniel W. Apley ◽  
Wei Chen
Keyword(s):  
Resource Allocation ◽  
Epistemic Uncertainty ◽  
Complex Structure ◽  
Simulation Models ◽  
Multidisciplinary Design ◽  
Input Space ◽  
Novel Approach ◽  
Critical Responses ◽  
Reliable Design ◽  
Multidisciplinary System

Epistemic model uncertainty is a significant source of uncertainty that affects a multidisciplinary system. In order to achieve a reliable design, it is critical to ensure that the disciplinary/subsystem simulation models are trustworthy, so that the aggregated uncertainty of system quantities of interest (QOIs) is acceptable. Uncertainty reduction can be achieved by gathering additional experiments and simulations data; however resource allocation for multidisciplinary design optimization (MDO) remains a challenging task due to the complex structure of a multidisciplinary system. In this paper, we develop a novel approach by integrating multidisciplinary uncertainty analysis (MUA) and multidisciplinary statistical sensitivity analysis (MSSA) to answer the questions about where (sampling locations), what (disciplinary responses), and which (simulations versus experiments) for allocating more resources. To manage the complexity in making the above decisions, a sequential procedure is proposed. First, the input space of a multidiscipline system is explored to identify the locations with unacceptable amounts of uncertainty with respect to the system QOIs. Next, these input locations are selected through a correlation check so that they are sparsely located in the input space, and their corresponding critical responses are identified based on MSSA. Finally, using a preposterior analysis, decisions are made about what type of resources (experimental or computational) should be allocated to the critical responses at the chosen input locations. The proposed method is applied to a benchmark electronic packaging problem to demonstrate how epistemic uncertainty is gradually reduced via gathering more data.

scholarly journals An Ontological Representation of an Adaptive Access Control Mechanism for Enterprise Cloud

2020 ◽  
Vol 8 (5) ◽  
pp. 2390-2396
Keyword(s):  
Resource Allocation ◽  
Access Control ◽  
Control Mechanism ◽  
Peak Load ◽  
Role Based Access Control ◽  
Control Policies ◽  
Access Control Policies ◽  
Novel Approach ◽  
Access Control Mechanism ◽  
Security Concern

With the increased development of cloud computing, access control is of paramount importance as a security concern. Numerous access control approaches exist in various published works. Among such prevalent approaches, Role Based Access Control (RBAC) model for enterprise cloud is scope of the present study. Nowadays, resource management, along with the primary aspect of security concern, is also addressed by the access control policies through restricting the allocation of the computing resources based on the roles assigned to the users. Keeping in view of the upcoming peak-load requirements or certain constraints, the policies may have ineffective resource allocation which leads to over/under-utilization of the resources over a period of time. So, an adaptive access control mechanism is desired that can vary their policies dynamically for resource allocation depending upon the ongoing requirements, for its efficient utilization. This is presented in the form of an adaptive access control mechanism (AACM) that aims to effectively utilize the computing resources in the enterprise cloud. It will aid in identifying the over- and under-allocation of the computing resources defined as access control policies and redefine these policies so as to ensure efficient and effective usage of the enterprise cloud resources. In this paper, this novel approach to access control mechanism for the enterprise cloud is represented using ontologies developed in Protégé. This is developed by identification of the underlying concepts and their interrelationships through properties, in the enterprise cloud. The presented ontology is for the sake of knowledge representation to represent knowledge and facts.

scholarly journals A novel approach for traffic accidents sanitary resource allocation based on multi-objective genetic algorithms

2013 ◽  
Vol 40 (1) ◽  
pp. 323-336 ◽  
Author(s):  
Manuel Fogue ◽  
Piedad Garrido ◽  
Francisco J. Martinez ◽  
Juan-Carlos Cano ◽  
Carlos T. Calafate ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Genetic Algorithms ◽  
Traffic Accidents ◽  
Multi Objective ◽  
Novel Approach

scholarly journals Simulation Model for the Estimation of Energy Consumption of the Baggage Handling System in the Landside Area of the Airport

Energies ◽  
2021 ◽  
Vol 15 (1) ◽  
pp. 256
Author(s):  
Artur Kierzkowski ◽  
Tomasz Kisiel
Keyword(s):  
Resource Allocation ◽  
Energy Consumption ◽  
Simulation Model ◽  
Mixed Strategy ◽  
Detailed Structure ◽  
Handling System ◽  
Novel Approach ◽  
Baggage Handling ◽  
Resource Allocation Strategy ◽  
New System

The purpose of this paper was to develop a simulation model to perform a sensitivity analysis of the energy consumption of an airport baggage handling system to a change in resource allocation strategy. This is a novel approach as this aspect has not been considered until now. This aspect, in turn is very important in terms of sustainability. The paper presents the detailed structure of the model and the data on which it operates. It is universal and can be the basis for analyzing any structure of the baggage handling system in the landside of any airport. An example analysis has shown that even up to 35% benefits can be gained by using the model. Three scenarios were analyzed in the model (dedicated check-in desks scenario, common desks scenario and mixed strategy scenario). However, the model is not limited to these strategies and any resource allocation is possible. The model is useful both for planning a new system as well as optimizing an existing system during its operation.

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