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Resource allocation and computation offloading with data security for mobile edge computing

机译：资源分配和计算分流以及具有数据安全性的移动边缘计算

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摘要

With the considerable growth of mobile users (MUs) and IoT devices, complex applications and multimedia services are rapidly increasing, thereby requiring additional computations and high data communication. However, these devices are still resource-constrained with limited computation power and energy. Furthermore, security is considered a critical issue for sensitive information communication. This study presents a multiuser resource allocation and computation offloading model with data security to address the limitations of such devices. First, the computation and radio resources are jointly considered for multiuser scenarios to guarantee the efficient utilization of shared resources. In addition, an AES cryptographic technique is introduced as a security layer to protect sensitive information from cyber-attacks. Furthermore, an integrated model, which jointly considers security, computation offloading, and resource allocation, is formulated to minimize time and energy consumption of the entire system. Finally, an offloading algorithm is developed with detailed processes to determine the optimal computation offloading decision for MUs. Simulation results show that our model and algorithm can significantly improve the performance of the entire system compared with local execution and full offloading schemes. (C) 2019 Elsevier B.V. All rights reserved.
机译：随着移动用户（MU）和IoT设备的显着增长，复杂的应用程序和多媒体服务正在迅速增加，从而需要额外的计算和高数据通信。但是，这些设备仍然受限于计算能力和能源的资源约束。此外，安全性被认为是敏感信息通信的关键问题。这项研究提出了一种具有数据安全性的多用户资源分配和计算分流模型，以解决此类设备的局限性。首先，为多用户方案共同考虑计算和无线电资源，以确保共享资源的有效利用。此外，还引入了AES加密技术作为安全层，以保护敏感信息免受网络攻击。此外，制定了一个综合模型，该模型综合考虑了安全性，计算分流和资源分配，以最大程度地减少整个系统的时间和能耗。最后，开发了具有详细过程的卸载算法，以确定MU的最佳计算卸载决策。仿真结果表明，与局部执行和完整卸载方案相比，我们的模型和算法可以显着提高整个系统的性能。 （C）2019 Elsevier B.V.保留所有权利。

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