Joint Optimization of Offloading and Resources Allocation in Secure Mobile Edge Computing Systems

Mobile edge computing (MEC) has become a promising technology for real-time communications. Mobile devices can reduce the energy consumption and prolong the lifetime significantly via offloading the computing tasks to the MEC server. Moreover, physical layer security techniques can ensure the secure transmission of the offloading data. This paper investigates a MEC system that consists of an access point, multiple mobile devices and a malicious eavesdropper. The tasks allocation, local central processor's frequency, offloading power, and offloading timeslots are optimized jointly to minimize the total energy consumption of the system. A difference of convex algorithm based scheme is proposed to solve the joint optimization problem. Moreover, a Karush Kuhn Tucker conditions based algorithm is also proposed to reduce the computational complexity. Numerical results show that the proposed algorithms are very effective. Moreover, the power consumption for secure offloading decreases with the increase of the distance between the mobile devices and the eavesdropper.

[1]  Shlomo Shamai,et al.  Secure Communication Over Fading Channels , 2007, IEEE Transactions on Information Theory.

[2]  Wenzhong Li,et al.  Efficient Multi-User Computation Offloading for Mobile-Edge Cloud Computing , 2015, IEEE/ACM Transactions on Networking.

[3]  Xin Chen,et al.  Energy-Efficient Link Selection and Transmission Scheduling in Mobile Cloud Computing , 2014, IEEE Wireless Communications Letters.

[4]  Sergio Barbarossa,et al.  Communicating While Computing: Distributed mobile cloud computing over 5G heterogeneous networks , 2014, IEEE Signal Processing Magazine.

[5]  Bruno Clerckx,et al.  Communications and Signals Design for Wireless Power Transmission , 2016, IEEE Transactions on Communications.

[6]  Kaibin Huang,et al.  Energy-Efficient Resource Allocation for Mobile-Edge Computation Offloading , 2016, IEEE Transactions on Wireless Communications.

[7]  Steffen Rebennack,et al.  Ellipsoid Method , 2009, Encyclopedia of Optimization.

[8]  Alec Wolman,et al.  MAUI: making smartphones last longer with code offload , 2010, MobiSys '10.

[9]  Tarik Taleb,et al.  Survey on Multi-Access Edge Computing for Internet of Things Realization , 2018, IEEE Communications Surveys & Tutorials.

[10]  Yung-Hsiang Lu,et al.  Cloud Computing for Mobile Users: Can Offloading Computation Save Energy? , 2010, Computer.

[11]  Xin Wang,et al.  Power-Efficient Resource Allocation for Time-Division Multiple Access Over Fading Channels , 2008, IEEE Transactions on Information Theory.

[12]  Ying Jun Zhang,et al.  Computation Rate Maximization for Wireless Powered Mobile-Edge Computing With Binary Computation Offloading , 2017, IEEE Transactions on Wireless Communications.

[13]  Tao Zhang,et al.  Fog and IoT: An Overview of Research Opportunities , 2016, IEEE Internet of Things Journal.

[14]  Marc St-Hilaire,et al.  Economic and Energy Considerations for Resource Augmentation in Mobile Cloud Computing , 2018, IEEE Transactions on Cloud Computing.

[15]  Ejaz Ahmed,et al.  A survey on mobile edge computing , 2016, 2016 10th International Conference on Intelligent Systems and Control (ISCO).

[16]  Yan Zhang,et al.  Deep Learning for Secure Mobile Edge Computing in Cyber-Physical Transportation Systems , 2019, IEEE Network.

[17]  Ke Zhang,et al.  Computation Offloading and Resource Allocation For Cloud Assisted Mobile Edge Computing in Vehicular Networks , 2019, IEEE Transactions on Vehicular Technology.

[18]  Sergiy A. Vorobyov,et al.  Robust Adaptive Beamforming for General-Rank Signal Model With Positive Semi-Definite Constraint via POTDC , 2012, IEEE Transactions on Signal Processing.

[19]  Tarik Taleb,et al.  On Multi-Access Edge Computing: A Survey of the Emerging 5G Network Edge Cloud Architecture and Orchestration , 2017, IEEE Communications Surveys & Tutorials.

[20]  Haiyun Luo,et al.  Energy-Optimal Mobile Cloud Computing under Stochastic Wireless Channel , 2013, IEEE Transactions on Wireless Communications.

[21]  Khaled Ben Letaief,et al.  Dynamic Computation Offloading for Mobile-Edge Computing With Energy Harvesting Devices , 2016, IEEE Journal on Selected Areas in Communications.

[22]  Dario Pompili,et al.  Joint Task Offloading and Resource Allocation for Multi-Server Mobile-Edge Computing Networks , 2017, IEEE Transactions on Vehicular Technology.

[23]  Rose Qingyang Hu,et al.  Computation Rate Maximization in UAV-Enabled Wireless-Powered Mobile-Edge Computing Systems , 2018, IEEE Journal on Selected Areas in Communications.

[24]  Zhiguo Ding,et al.  A Survey of Multi-Access Edge Computing in 5G and Beyond: Fundamentals, Technology Integration, and State-of-the-Art , 2019, IEEE Access.

[25]  Jean-Marc Menaud,et al.  Performance and Power Management for Cloud Infrastructures , 2010, 2010 IEEE 3rd International Conference on Cloud Computing.

[26]  Jiangzhou Wang,et al.  Chunk-Based Resource Allocation in OFDMA Systems—Part II: Joint Chunk, Power and Bit Allocation , 2012, IEEE Transactions on Communications.

[27]  Moritz Diehl,et al.  Sequential Convex Programming Methods for Solving Nonlinear Optimization Problems with DC constraints , 2011 .

[28]  Daniel Pérez Palomar,et al.  Power Control By Geometric Programming , 2007, IEEE Transactions on Wireless Communications.

[29]  Ha H. Nguyen,et al.  Fast Global Optimal Power Allocation in Wireless Networks by Local D.C. Programming , 2012, IEEE Transactions on Wireless Communications.

[30]  K. B. Letaief,et al.  A Survey on Mobile Edge Computing: The Communication Perspective , 2017, IEEE Communications Surveys & Tutorials.

[31]  Kaibin Huang,et al.  Energy Efficient Mobile Cloud Computing Powered by Wireless Energy Transfer , 2015, IEEE Journal on Selected Areas in Communications.

[32]  Nei Kato,et al.  Optimal Edge Resource Allocation in IoT-Based Smart Cities , 2019, IEEE Network.

[33]  Katsuhiro Temma,et al.  Cloudlets Activation Scheme for Scalable Mobile Edge Computing with Transmission Power Control and Virtual Machine Migration , 2018, IEEE Transactions on Computers.

[34]  Zhetao Li,et al.  Energy-Efficient Dynamic Computation Offloading and Cooperative Task Scheduling in Mobile Cloud Computing , 2019, IEEE Transactions on Mobile Computing.

[35]  A. D. Wyner,et al.  The wire-tap channel , 1975, The Bell System Technical Journal.

[36]  Zhisheng Niu,et al.  A Cooperative Scheduling Scheme of Local Cloud and Internet Cloud for Delay-Aware Mobile Cloud Computing , 2015, 2015 IEEE Globecom Workshops (GC Wkshps).

[37]  Qianbin Chen,et al.  Computation Offloading and Resource Allocation in Wireless Cellular Networks With Mobile Edge Computing , 2017, IEEE Transactions on Wireless Communications.

[38]  Yong Liu,et al.  Limited-Feedback-Based Adaptive Power Allocation and Subcarrier Pairing for OFDM DF Relay Networks With Diversity , 2012, IEEE Transactions on Vehicular Technology.

[39]  Jiangzhou Wang,et al.  Chunk-based resource allocation in OFDMA systems - part I: chunk allocation , 2009, IEEE Transactions on Communications.

[40]  Jie Xu,et al.  Exploiting Physical-Layer Security for Multiuser Multicarrier Computation Offloading , 2018, IEEE Wireless Communications Letters.

[41]  Yunlong Cai,et al.  Latency Optimization for Resource Allocation in Mobile-Edge Computation Offloading , 2017, IEEE Transactions on Wireless Communications.

[42]  Kun Yang,et al.  Fair Energy-Efficient Scheduling in Wireless Powered Full-Duplex Mobile-Edge Computing Systems , 2017, GLOBECOM 2017 - 2017 IEEE Global Communications Conference.

[43]  Zhen Xiao,et al.  Dynamic Resource Allocation Using Virtual Machines for Cloud Computing Environment , 2013, IEEE Transactions on Parallel and Distributed Systems.

[44]  Junyuan Wang,et al.  A Machine Learning Framework for Resource Allocation Assisted by Cloud Computing , 2017, IEEE Network.

[45]  Meixia Tao,et al.  Power and Subcarrier Allocation for Physical-Layer Security in OFDMA-Based Broadband Wireless Networks , 2011, IEEE Transactions on Information Forensics and Security.

[46]  Christos Masouros,et al.  Constructive Interference Based Secure Precoding: A New Dimension in Physical Layer Security , 2016, IEEE Transactions on Information Forensics and Security.

[47]  Thomas D. Burd,et al.  Processor design for portable systems , 1996, J. VLSI Signal Process..