A Strategic Genetic Algorithm for Resource Allocation in LTE Uplink Netwoks

2018 ◽  
Author(s):  
Leeban Moses ◽  
Srisakthi Karthikeyan
Keyword(s):  
Genetic Algorithm ◽  
Resource Allocation ◽  
Lte Uplink

Grid Resource Allocation with Genetic Algorithm Using Population Based on Multisets

2017 ◽  
Vol 26 (1) ◽  
pp. 169-184 ◽  
Author(s):  
Absalom E. Ezugwu ◽  
Nneoma A. Okoroafor ◽  
Seyed M. Buhari ◽  
Marc E. Frincu ◽  
Sahalu B. Junaidu
Keyword(s):  
Genetic Algorithm ◽  
Resource Allocation ◽  
Grid Computing ◽  
Resource Selection ◽  
Computing System ◽  
Population Based ◽  
Fine Tuning ◽  
Grid Resource ◽  
Performance Results ◽  
Grid Resources

AbstractThe operational efficacy of the grid computing system depends mainly on the proper management of grid resources to carry out the various jobs that users send to the grid. The paper explores an alternative way of efficiently searching, matching, and allocating distributed grid resources to jobs in such a way that the resource demand of each grid user job is met. A proposal of resource selection method that is based on the concept of genetic algorithm (GA) using populations based on multisets is made. Furthermore, the paper presents a hybrid GA-based scheduling framework that efficiently searches for the best available resources for user jobs in a typical grid computing environment. For the proposed resource allocation method, additional mechanisms (populations based on multiset and adaptive matching) are introduced into the GA components to enhance their search capability in a large problem space. Empirical study is presented in order to demonstrate the importance of operator improvement on traditional GA. The preliminary performance results show that the proposed introduction of an additional operator fine-tuning is efficient in both speed and accuracy and can keep up with high job arrival rates.

On Demand Resource Allocation for LTE Uplink Transmission Based on Logical Channel Groups

2017 ◽  
Vol 22 (5) ◽  
pp. 868-879 ◽  
Author(s):  
Fang-Chang Kuo ◽  
Kuo-Chang Ting ◽  
Hwang-Cheng Wang ◽  
Chih-Cheng Tseng
Keyword(s):  
Resource Allocation ◽  
On Demand ◽  
Logical Channel ◽  
Lte Uplink

scholarly journals Dynamic Beam Hopping Time Slots Allocation Based on Genetic Algorithm of Satellite Communication under Time-Varying Rain Attenuation

Electronics ◽  
2021 ◽  
Vol 10 (23) ◽  
pp. 2909
Author(s):  
Chen Zhang ◽  
Jiangtao Yang ◽  
Yong Zhang ◽  
Ziwei Liu ◽  
Gengxin Zhang
Keyword(s):  
Genetic Algorithm ◽  
Resource Allocation ◽  
Satellite Communication ◽  
Rain Attenuation ◽  
Time Varying ◽  
Dynamic Allocation ◽  
Satellite Systems ◽  
Flexible Resource ◽  
Conventional Methods ◽  
High Level

Beam hopping technology is considered to provide a high level of flexible resource allocation to manage uneven traffic requests in multi-beam high throughput satellite systems. Conventional beam hopping resource allocation methods assume constant rainfall attenuation. Different from conventional methods, by employing genetic algorithm this paper studies dynamic beam hopping time slots allocation under the effect of time-varying rain attenuation. Firstly, a beam hopping system model as well as rain attenuation time series based on Dirac lognormal distribution are provided. On this basis, the dynamic allocation method by employing genetic algorithm is proposed to obtain both quantity and arrangement of time slots allocated for each beam. Simulation results show that, compared with conventional methods, the proposed algorithm can dynamically adjust time slots allocation to meet the non-uniform traffic requirements of each beam under the effect of time-varying rain attenuation and effectively improve system performance.

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