Research on the Resource Allocation Model for the Satellite Constellation Communication System

2010 ◽  
Vol 121-122 ◽  
pp. 669-677 ◽  
Author(s):  
Li Li Zhu ◽  
Yi Feng Duan
Keyword(s):  
Resource Allocation ◽  
Communication System ◽  
Large Scale ◽  
Mathematic Model ◽  
New Paradigm ◽  
Allocation Model ◽  
Satellite Constellation ◽  
Spatially Distributed ◽  
Degree Of Satisfaction ◽  
Task Oriented

Satellite constellation, emerging as a new paradigm for next-generation communicating, enables large-scale application of the geographically and spatially distributed heterogeneous resources for solving problems in science, engineering, and military affairs. The resource allocation in such a large-scale distributed environment is a complex task. Due to the factors that trigger the deployment of resources in satellite constellation communication system, the artificial immune theory is applied to resource allocation field to propose the task-oriented common mathematic model about resource allocation of communication system, which is aimed at the purpose of improving the effectiveness of resource allocation and is based on the 2 important indicators that are communication task’s effectiveness factors and the degree of satisfaction in the communication system. As the immune system has characteristics of self-adaptive, self-learning and self-organization, an immune allocation algorithm that fuzzy processing time is presented by applying the immune theory to resource allocation. Simulation results show that these methods are feasible and efficient in solving the problems of resource allocation for satellite constellation communication system, and the research on this object is a meaningful exploring.

scholarly journals Ultrahigh-Dimensional Model and Optimization Algorithm for Resource Allocation in Large-Scale Intelligent D2D Communication System

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Minxin Liang ◽  
Jiandong Liu ◽  
Jinrui Tang ◽  
Ruoli Tang
Keyword(s):  
Resource Allocation ◽  
Communication System ◽  
Large Scale ◽  
Novel Mutation ◽  
Pso Algorithm ◽  
Spectrum Efficiency ◽  
D2d Communication ◽  
Allocation Model ◽  
User Grouping ◽  
Mutation Strategies

The optimal resource allocation in the large-scale intelligent device-to-device (D2D) communication system is of great importance for improving system spectrum efficiency and ensuring communication quality. In this study, the D2D resource allocation is modelled as an ultrahigh-dimensional optimization (UHDO) problem with thousands of binary dimensionalities. Then, for efficiently optimizing this UHDO problem, the coupling relationships among those dimensionalities are comprehensively analysed, and several efficient variable-grouping strategies are developed, i.e., cellular user grouping (CU-grouping), D2D pair grouping (DP-grouping), and random grouping (R-grouping). In addition, a novel evolutionary algorithm called the cooperatively coevolving particle swarm optimization with variable-grouping (VGCC-PSO) is developed, in which a novel mutation operation is introduced for ensuring fast satisfaction of constraints. Finally, the proposed UHDO-based allocation model and VGCC-PSO algorithm as well as the grouping and mutation strategies are verified by a comprehensive set of case studies. Simulation results show that the developed VGCC-PSO algorithm performs the best in optimizing the UHDO model with up to 6000 dimensionalities. According to our study, the proposed methodology can effectively overcome the “curse of dimensionality” and optimally allocate the resources with high accuracy and robustness.

A Resource Allocation Model for Desktop Clouds

2015 ◽  
pp. 199-218 ◽  
Author(s):  
Abdulelah Alwabel ◽  
Robert John Walters ◽  
Gary B. Wills
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Cloud Services ◽  
New Paradigm ◽  
Allocation Mechanism ◽  
Desktop Grids ◽  
Allocation Model ◽  
Resource Allocation Model ◽  
Computing Services ◽  
New Type

Cloud computing is a new paradigm that promises to move IT a step further towards utility computing, in which computing services are delivered as a utility service. Traditionally, Cloud employs dedicated resources located in one or more data centres in order to provide services to clients. Desktop Cloud computing is a new type of Cloud computing that aims at providing Cloud capabilities at low or no cost. Desktop Clouds harness non dedicated and idle resources in order to provide Cloud services. However, the nature of such resources can be problematic because they are prone to failure at any time without prior notice. This research focuses on the resource allocation mechanism in Desktop Clouds.The contributions of this chapter are threefold. Firstly, it defines and explains Desktop Clouds by comparing them with both Traditional Clouds and Desktop Grids. Secondly, the paper discusses various research issues in Desktop Clouds. Thirdly, it proposes a resource allocation model that is able to handle node failures.

A Resource Allocation Model for Desktop Clouds

Web Services ◽  
2019 ◽  
pp. 258-279
Author(s):  
Abdulelah Alwabel ◽  
Robert John Walters ◽  
Gary B. Wills
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Cloud Services ◽  
New Paradigm ◽  
Allocation Mechanism ◽  
Desktop Grids ◽  
Allocation Model ◽  
Resource Allocation Model ◽  
Computing Services ◽  
New Type

Cloud computing is a new paradigm that promises to move IT a step further towards utility computing, in which computing services are delivered as a utility service. Traditionally, Cloud employs dedicated resources located in one or more data centres in order to provide services to clients. Desktop Cloud computing is a new type of Cloud computing that aims at providing Cloud capabilities at low or no cost. Desktop Clouds harness non dedicated and idle resources in order to provide Cloud services. However, the nature of such resources can be problematic because they are prone to failure at any time without prior notice. This research focuses on the resource allocation mechanism in Desktop Clouds.The contributions of this chapter are threefold. Firstly, it defines and explains Desktop Clouds by comparing them with both Traditional Clouds and Desktop Grids. Secondly, the paper discusses various research issues in Desktop Clouds. Thirdly, it proposes a resource allocation model that is able to handle node failures.

A Resource Allocation Model for Desktop Clouds

2016 ◽  
pp. 356-376 ◽  
Author(s):  
Abdulelah Alwabel ◽  
Robert John Walters ◽  
Gary B. Wills
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Cloud Services ◽  
New Paradigm ◽  
Allocation Mechanism ◽  
Desktop Grids ◽  
Allocation Model ◽  
Resource Allocation Model ◽  
Computing Services ◽  
New Type

Cloud computing is a new paradigm that promises to move IT a step further towards utility computing, in which computing services are delivered as a utility service. Traditionally, Cloud employs dedicated resources located in one or more data centres in order to provide services to clients. Desktop Cloud computing is a new type of Cloud computing that aims at providing Cloud capabilities at low or no cost. Desktop Clouds harness non dedicated and idle resources in order to provide Cloud services. However, the nature of such resources can be problematic because they are prone to failure at any time without prior notice. This research focuses on the resource allocation mechanism in Desktop Clouds. The contributions of this chapter are threefold. Firstly, it defines and explains Desktop Clouds by comparing them with both Traditional Clouds and Desktop Grids. Secondly, the paper discusses various research issues in Desktop Clouds. Thirdly, it proposes a resource allocation model that is able to handle node failures.

scholarly journals Cloud based Cost Effective Resource Allocation Model for Software-as-a-service Deployments

2013 ◽  
Vol 9 (2) ◽  
pp. 1068-1079
Author(s):  
Ibrahim A. Cheema ◽  
Mudassar Ahmad ◽  
Fahad Jan ◽  
Shahla Asadi
Keyword(s):  
Resource Allocation ◽  
Large Scale ◽  
Service Providers ◽  
Cost Effective ◽  
Software As A Service ◽  
Allocation Model ◽  
Application Service Providers ◽  
Resource Allocation Model ◽  
Application Service ◽  
Cloud Infrastructures

The Cloud Computing (CC) provides access to the resources with usage based payments model. The application service providers can seamlessly scale the services. In CC infrastructure, a different number of virtual machine instances can be created depending on the application requirements. The capability to scale Software-as-a-Service (SaaS) application is very attractive to the providers because of the potential to scale application resources to up or down, the user only pay for the resources required. Even though the large-scale applications are deployed on cloud infrastructures on pay-per-use basis, the cost of idle resources (memory, CPU) is still charged to application providers. The issues of saturation and wastage of cloud resources are still unresolved. This paper attempts to propose the resource allocation models for SaaS applications deployments over CC platforms. The best balanced resource allocation model is proposed keeping in view cost and user requirements.

scholarly journals Edge cloud task scheduling model based on layered excellent gene replication strategy

2021 ◽  
Vol 2132 (1) ◽  
pp. 012002
Author(s):  
Leilei Zhu ◽  
Ke Zhao ◽  
Huaze Lin ◽  
Dan Liu ◽  
Li Li
Keyword(s):  
Resource Allocation ◽  
Task Scheduling ◽  
Large Scale ◽  
Allocation Model ◽  
Good Convergence ◽  
Scheduling Strategy ◽  
Gene Replication ◽  
Individual Fitness ◽  
Replication Strategy ◽  
The Stability

Abstract With the development of the Internet of Things and 5G. Edge cloud technology has gradually become a research hotspot. When facing the massive and concurrent tasks of terminal users, reasonable resource scheduling strategy is a key technology. Because edge cloud needs to respond quickly to real-time tasks and ensure the stability of nodes at the same time, the optimal task scheduling strategy needs to be selected to meet the low latency requirements of edge users. In view of the above problems in resource allocation of edge cloud, this paper established a layered excellent gene replication strategy (HEGPSO model), in which the optimal replicator is added, and an evolutionary particle swarm optimization algorithm is proposed. In each iteration, the population is divided into three layers based on individual fitness. After that, the optimal replication factor is added to each layer of individuals to enhance the global search ability of the algorithm and ensure the good convergence of the algorithm. Finally, a balanced resource allocation model is established. Experiments show that the HEGPSO model proposed in this paper has high fitness and fast convergence speed, and is suitable for large-scale task access scenarios.

The sugar and alcohol industry in the biofuels and cogeneration era: a paradigm change (part II)

2014 ◽  
pp. 97-104 ◽  
Author(s):  
Electo Eduardo Silv Lora ◽  
Mateus Henrique Rocha ◽  
José Carlos Escobar Palacio ◽  
Osvaldo José Venturini ◽  
Maria Luiza Grillo Renó ◽  
...  
Keyword(s):  
Large Scale ◽  
New Technologies ◽  
Process Integration ◽  
Animal Feed ◽  
Raw Materials ◽  
Biofuel Production ◽  
New Paradigm ◽  
Alcohol Industry ◽  
Feed Production ◽  
Steam Parameters

The aim of this paper is to discuss the major technological changes related to the implementation of large-scale cogeneration and biofuel production in the sugar and alcohol industry. The reduction of the process steam consumption, implementation of new alternatives in driving mills, the widespread practice of high steam parameters use in cogeneration facilities, the insertion of new technologies for biofuels production (hydrolysis and gasification), the energy conversion of sugarcane trash and vinasse, animal feed production, process integration and implementation of the biorefinery concept are considered. Another new paradigm consists in the wide spreading of sustainability studies of products and processes using the Life Cycle Assessment (LCA) and the implementation of sustainability indexes. Every approach to this issue has as an objective to increase the economic efficiency and the possibilities of the sugarcane as a main source of two basic raw materials: fibres and sugar. The paper briefly presents the concepts, indicators, state-of-the-art and perspectives of each of the referred issues.

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