One of the major bottlenecks toward realizing IoT systems is the energy constraint of sensors. Prolonging network lifetime is a fundamental issue for implementing IoT systems. The energy optimization problem, being NP-hard in nature for scalable networks, has been addressed in the literature using traditional metaheuristic techniques. Quantum inspired metaheuristics have shown better performance than their traditional counterparts in solving such optimization problems in different domains. Toward this end, this article proposes a quantum inspired green communication framework for Energy Balancing in sensor enabled IoT systems (Q-EBIoT). First, an energy optimization model for sensor enabled IoT environments is presented, where energy consumption is derived as cost of the energy-oriented paths. Second, a quantum computing oriented solution is developed for the optimization problem focusing on energy centric solution representation, measurement, and rotation angle. The proposed solution is implemented to evaluate the comparative performance with the state-of-the-art techniques. The evaluation demonstrates the benefit of the proposed framework in terms of various energy-related metrics for sensor enabled IoT environments.

中文翻译：

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面向传感器的物联网环境中面向能源优化的绿色通信

实现物联网系统的主要瓶颈之一是传感器的能源约束。延长网络寿命是实施物联网系统的基本问题。对于可扩展网络而言，本质上是NP难题的能量优化问题已在文献中使用传统的元启发式技术解决。在解决不同领域的此类优化问题方面，受量子启发的元启发式方法已显示出比传统方法更好的性能。为此，本文提出了一种基于量子的绿色通信框架，用于支持传感器的物联网系统（Q-EBIoT）中的能量平衡。首先，提出了一种基于传感器的物联网环境的能源优化模型，其中能源消耗是作为能源导向路径的成本得出的。第二，针对优化问题，开发了一种面向量子计算的解决方案，该解决方案侧重于以能量为中心的解决方案表示，测量和旋转角度。所提出的解决方案可通过最新技术来评估比较性能。评估显示了针对传感器启用的IoT环境在各种与能源相关的指标方面所提议框架的好处。