Heuristic Algorithms for Flexible Resource Allocation in Beam Hopping Multi-Beam Satellite Systems

2011 ◽  
Author(s):  
Ricard Alegre ◽  
Nader Alagha ◽  
María Ángeles Vázquez-Castro
Keyword(s):  
Resource Allocation ◽  
Heuristic Algorithms ◽  
Satellite Systems ◽  
Flexible Resource

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.

scholarly journals Time-Sliced Flexible Resource Allocation for Optical Low Earth Orbit Satellite Networks

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 56753-56759 ◽  
Author(s):  
Zelin Zheng ◽  
Nan Hua ◽  
Zhizhen Zhong ◽  
Jialong Li ◽  
Yanhe Li ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Low Earth Orbit ◽  
Satellite Networks ◽  
Earth Orbit ◽  
Orbit Satellite ◽  
Low Earth Orbit Satellite ◽  
Flexible Resource

scholarly journals How to get the most bang for your buck: the evolution and physiology of nutrition-dependent resource allocation strategies

2017 ◽  
Vol 284 (1857) ◽  
pp. 20170445 ◽  
Author(s):  
Enoch Ng'oma ◽  
Anna M. Perinchery ◽  
Elizabeth G. King
Keyword(s):  
Resource Allocation ◽  
Natural Populations ◽  
Analytical Models ◽  
Major Question ◽  
Proximate Mechanisms ◽  
Level Data ◽  
Flexible Resource ◽  
Empirical Tests ◽  
Underlying Mechanisms ◽  
Allocation Strategies

All organisms use resources to grow, survive and reproduce. The supply of these resources varies widely across landscapes and time, imposing ultimate constraints on the maximal trait values for allocation-related traits. In this review, we address three key questions fundamental to our understanding of the evolution of allocation strategies and their underlying mechanisms. First, we ask: how diverse are flexible resource allocation strategies among different organisms? We find there are many, varied, examples of flexible strategies that depend on nutrition. However, this diversity is often ignored in some of the best-known cases of resource allocation shifts, such as the commonly observed pattern of lifespan extension under nutrient limitation. A greater appreciation of the wide variety of flexible allocation strategies leads directly to our second major question: what conditions select for different plastic allocation strategies? Here, we highlight the need for additional models that explicitly consider the evolution of phenotypically plastic allocation strategies and empirical tests of the predictions of those models in natural populations. Finally, we consider the question: what are the underlying mechanisms determining resource allocation strategies? Although evolutionary biologists assume differential allocation of resources is a major factor limiting trait evolution, few proximate mechanisms are known that specifically support the model. We argue that an integrated framework can reconcile evolutionary models with proximate mechanisms that appear at first glance to be in conflict with these models. Overall, we encourage future studies to: (i) mimic ecological conditions in which those patterns evolve, and (ii) take advantage of the ‘omic’ opportunities to produce multi-level data and analytical models that effectively integrate across physiological and evolutionary theory.

Sign in / Sign up

Export Citation Format

Share Document