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Energy-Aware Optimal Data Aggregation in Smart Grid Wireless Communication Networks

机译:智能电网无线通信网络中的能源感知最佳数据聚合

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We propose a two-hop wireless communication architecture for smart grid (SG) consisting of smart meters (SMs), aggregators (AGs) and cellular base stations (BSs). The architecture is then considered to transfer the periodic traffic of the SMs to the BSs via the AGs with data concatenation or direct transmission. We formulate an optimization problem to minimize the energy consumption by the optimal AG selection for the SMs, data concatenation and transmit power allocation which turns out as a mixed integer non-linear programming. By means of several analytical formulations and an optimization tool, we solve the problem for many SG network instances and demonstrate that two hop communication architecture with the optimal configuration requires significantly less energy compared to a single hop communication architecture without data aggregation. We also investigate the effects of the number of the SMs, modulation order, wireless channel, and sizes of packets on energy consumption and provide various engineering insights. Further, a heuristic algorithm is developed for solving the optimization problem without any optimization tool. The effectiveness of the heuristic algorithm is verified by comparing the energy consumptions of the heuristic and the optimal algorithms. The comparison results show that the difference of the energy consumptions is not significant.
机译:我们为智能电网(SG)提出了一种两跳无线通信体系结构,该体系结构由智能电表(SM),聚合器(AG)和蜂窝基站(BS)组成。然后考虑该架构以具有数据级联或直接传输的方式经由AG将SM的周期性业务传输到BS。我们提出了一个优化问题,通过针对SM的最佳AG选择,数据级联和发射功率分配来最小化能量消耗,结果证明是混合整数非线性规划。通过几种分析公式和一种优化工具,我们解决了许多SG网络实例的问题,并证明与没有数据聚合的单跳通信体系结构相比,具有最佳配置的两跳通信体系结构所需的能源明显更少。我们还研究了SM数量,调制阶数,无线通道和数据包大小对能耗的影响,并提供了各种工程见解。此外,开发了一种启发式算法,无需任何优化工具即可解决优化问题。通过比较启发式算法和最优算法的能耗,验证了启发式算法的有效性。比较结果表明,能耗差异不大。

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