Joint opportunistic power and rate allocation for wireless ad hoc networks: An adaptive particle swarm optimization approach
Joint opportunistic power and rate allocation for wireless ad hoc networks: An adaptive particle swarm optimization approach
复制标题
无线自组织网络的联合机会功率和速率分配：自适应粒子群优化方法
DOI：
10.1016/j.jnca.2011.03.020
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发表时间：
2011-07
影响因子：
8.7
通讯作者：
Liao, Xiaofeng
中科院分区：
文献类型：
--
作者：
Guo, Songtao;Dang, Chuangyin;Liao, Xiaofeng
针对无线自组织网络中以最大化资源效用和最小化链路功率分配为目标的联合机会功率速率分配（JOPRA）算法，提出了一种改进的自适应粒子群优化算法（IAPSO），克服了传统对偶和次梯度算法的局限性.与原APSO算法相比，IAPSO算法中粒子的最大运动速度动态变化，约束处理采用了一种不引入附加参数的改进的替换过程，停止准则考虑了优化运行的状态和种群的多样性.仿真结果表明，该算法能够快速收敛到最优解，在降低总功耗的同时，获得更高的总数据速率和更大的数据利用率。通过与原APSO的数值比较，进一步说明了我们的方法的有效性。该工作是将自适应进化算法与无线自组织网络资源分配相结合的一次有益尝试。
In this paper, the joint opportunistic power and rate allocation (JOPRA) algorithm, which aims at maximizing the sum of source utilities while minimizing power allocation for all links in wireless ad hoc networks, is solved by means of an improved adaptive particle swarm optimization (IAPSO), which can overcome some limitations of the traditional dual and subgradient method. Compared with the original APSO, in our IAPSO, the maximum movement velocity of the particles changes dynamically, a modified replacement procedure with no introduced additional parameters is employed in constraint handling, and the state of the optimization run and the diversity in the population are taken into account in stopping criteria. It is shown that the proposed JOPRA algorithm can fast converge to the optimum and reach larger total data rate and utility while less total power is consumed. The efficiency of our approach is further illustrated via numerical comparison with the original APSO. This work is a beneficial attempt to integrate adaptive evolutionary algorithms with the resource allocation in wireless ad hoc networks.
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DOI：
10.1109/cec.2007.4424893
发表时间：
2007-09
期刊：
2007 IEEE Congress on Evolutionary Computation
影响因子：
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作者：
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通讯作者：
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影响因子：
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DOI：
10.1145/2598394.2605342
发表时间：
2014-07
期刊：
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影响因子：
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作者：
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通讯作者：
A. Engelbrecht
影响因子：
8.3
作者：
Q. Qu;L. Milstein;D. Vaman
通讯作者：
Q. Qu;L. Milstein;D. Vaman
DOI：
10.1016/b978-0-12-409547-2.14581-0
发表时间：
2020
期刊：
Comprehensive Chemometrics
影响因子：
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作者：
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通讯作者：
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