In this paper, we consider a system model in conjunction with two major technologies in 5G communications, i.e., mobile edge computing and spectrum sharing. An IoT network, which does not have access to any licensed spectrum, carries its computational task offloading activities with help of spectrum sharing. The IoT network cooperates with a licensed spectrum holding network by relaying its data and in return gets access to the licensed spectrum. The licensed spectrum holding network focuses on throughput maximization, whereas, the IoT network tries to maximize task computation rate. We formulate an optimization problem giving importance to both networks' interests. Typical IoT nodes may be energy-constrained, which is considered along with task computation time constraints. Parallel computation is considered while computing IoT nodes' computational tasks at the mobile edge computing server, where the processor is allocated based on IoT nodes' offloading capabilities. The advantage of such processor allocation is shown in the result section. Moreover, we also show how both IoT and licensed spectrum holding networks benefit from the spectrum sharing by caring for each other requirements, which echoes the fact, i.e., Sharing is Caring.
翻译:在本文中,我们结合5G通信中的两个主要技术(即移动边缘计算和频谱共享)来考虑一个系统模型,这个模型与5G通信中的两个主要技术(即移动边缘计算和频谱共享)结合使用。一个无法接触任何特许频谱的IoT网络携带其计算任务卸载活动,帮助共享频谱共享。IoT网络与特许频谱持有网络合作,转发其数据,作为回报,获取许可频谱持有网络进入许可频谱。许可的频谱持有网络侧重于通过量最大化,而IoT网络试图最大限度地优化任务计算率。我们形成了一个对两个网络都很重要的优化问题。典型的IoT节点可能受到能源限制,这与任务计算时间限制一起考虑。在移动边缘计算服务器计算 IoT节点计算计算计算计算任务时会考虑平行计算,处理器是根据IoT节卸载能力分配的。这种进程分配的优势在结果部分中显示。此外,我们还展示了IoT和特许频谱持有网络如何通过照顾其他要求共享而获益于频谱共享,这反映了这一事实,即分享汽车。