Ding Kaiqi, Zhao Haitao, Hu Xiping, Wei Jibo
College of Electronic Science, National University of Defense Technology, Changsha, 410073, China.
Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China.
Sensors (Basel). 2017 Oct 28;17(11):2479. doi: 10.3390/s17112479.
In sustainable smart cities, power saving is a severe challenge in the energy-constrained Internet of Things (IoT). Efficient utilization of limited multiple non-overlap channels and time resources is a promising solution to reduce the network interference and save energy consumption. In this paper, we propose a joint channel allocation and time slot optimization solution for IoT. First, we propose a channel ranking algorithm which enables each node to rank its available channels based on the channel properties. Then, we propose a distributed channel allocation algorithm so that each node can choose a proper channel based on the channel ranking and its own residual energy. Finally, the sleeping duration and spectrum sensing duration are jointly optimized to maximize the normalized throughput and satisfy energy consumption constraints simultaneously. Different from the former approaches, our proposed solution requires no central coordination or any global information that each node can operate based on its own local information in a total distributed manner. Also, theoretical analysis and extensive simulations have validated that when applying our solution in the network of IoT: (i) each node can be allocated to a proper channel based on the residual energy to balance the lifetime; (ii) the network can rapidly converge to a collision-free transmission through each node's learning ability in the process of the distributed channel allocation; and (iii) the network throughput is further improved via the dynamic time slot optimization.
在可持续智慧城市中,节能是能源受限的物联网(IoT)面临的严峻挑战。有效利用有限的多个非重叠信道和时间资源是减少网络干扰并节省能耗的一种有前景的解决方案。在本文中,我们提出了一种针对物联网的联合信道分配和时隙优化解决方案。首先,我们提出一种信道排序算法,使每个节点能够根据信道特性对其可用信道进行排序。然后,我们提出一种分布式信道分配算法,以便每个节点可以根据信道排序及其自身剩余能量选择合适的信道。最后,联合优化休眠持续时间和频谱感知持续时间,以最大化归一化吞吐量并同时满足能耗约束。与以前的方法不同,我们提出的解决方案不需要中央协调或任何全局信息,每个节点可以完全以分布式方式基于其自身的本地信息进行操作。此外,理论分析和广泛的仿真已经验证,当在物联网网络中应用我们的解决方案时:(i)每个节点可以根据剩余能量被分配到合适的信道以平衡生命周期;(ii)网络可以通过每个节点在分布式信道分配过程中的学习能力迅速收敛到无冲突传输;并且(iii)通过动态时隙优化进一步提高网络吞吐量。