Recently, cross-layer optimization has been emphasized by researchers for Internet of Things (IoT) where billions of devices communicate intelligently making every day communication highly informative. Medium Access Control (MAC) sub-layer is part of data link layer in IoT protocol stack. The energy consumption of things is greatly affected by MAC protocol which controls the node radio functionalities. In this article, we propose the design of an efficient MAC for IoT by minimizing its energy consumption at various levels. The minimization model is subject to reduction in distortion levels while simultaneously extending network lifetime. This article synthesizes and optimizes MAC layer of IoT based protocols using a novel delta diagram synthesizer and accurately captures both the high heterogeneity of the IoT and the impact of the Internet as part of the MAC layer architecture. Furthermore a novel hybrid Whale-Artificial Bee Colony optimizer framework is proposed to obtain optimal nodes based on energy consumption and the communication parameters among things, by exploiting the interrelations among different layer functionalities in the IoT. This novel system saves considerable computation resources of the resource constrained IoT devices and adapts to various data sources with different distortion levels rapidly.

中文翻译：

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物联网中基于TDMA的媒体访问控制的新型多目标优化器框架

最近，物联网（IoT）的研究人员强调了跨层优化，其中数十亿个设备进行智能通信，从而使日常通信具有很高的信息量。媒体访问控制（MAC）子层是IoT协议栈中数据链路层的一部分。物联网的能耗极大地受到控制节点无线电功能的MAC协议的影响。在本文中，我们通过最小化各个级别的能耗，提出了一种用于IoT的高效MAC的设计。最小化模型可以降低失真水平，同时延长网络寿命。本文使用新颖的三角图合成器对基于IoT的协议的MAC层进行了综合和优化，并准确地捕获了IoT的高度异构性以及作为MAC层体系结构一部分的Internet的影响。此外，提出了一种新颖的混合鲸鱼-人工蜂群优化器框架，通过利用物联网中不同层功能之间的相互关系，基于能耗和事物之间的通信参数获得最佳节点。这种新颖的系统节省了资源受限的物联网设备的大量计算资源，并迅速适应了具有不同失真级别的各种数据源。此外，提出了一种新颖的混合鲸鱼-人工蜂群优化器框架，通过利用物联网中不同层功能之间的相互关系，基于能耗和事物之间的通信参数获得最佳节点。这种新颖的系统节省了资源受限的物联网设备的大量计算资源，并迅速适应了具有不同失真级别的各种数据源。此外，提出了一种新颖的混合鲸鱼-人工蜂群优化器框架，通过利用物联网中不同层功能之间的相互关系，基于能耗和事物之间的通信参数获得最佳节点。这种新颖的系统节省了资源受限的物联网设备的大量计算资源，并迅速适应了具有不同失真级别的各种数据源。