期刊
IEEE INTERNET OF THINGS JOURNAL
卷 8, 期 10, 页码 8119-8132出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JIOT.2020.3042433
关键词
Cloud computing; Servers; Task analysis; Security; Computational modeling; Mobile handsets; Load management; Computation offloading (CO); Internet of Things (IoT); load balancing; mobile-edge cloud computing; optimization; security
资金
- Key Research and Development Program for Guangdong Province [2019B010136001]
- National Key Research and Development Plan [2017YFB0801801]
- National Natural Science Foundation of China [61672186, 61872110]
- Shenzhen Science and Technology Research and Development Foundation [JCYJ20190806143418198]
- Prince Sattam Bin Abdulaziz University via the Deanship for Scientific Research Grant [2020/01/12173]
- TYSP-Talented Young Scientist Program (China)
- Menoufia University (Egypt)
Mobile-edge computing (MEC) introduces a new load balancing and computation offloading (CO) technique, along with a new security layer to address potential security issues. Experimental results demonstrate that redistributing MDUs among different sBSs can effectively reduce system consumption, while adopting AES encryption technology can better protect data during transmission.
Mobile-edge computing (MEC) has emerged as a new computing paradigm with great potential to alleviate resource limitations attributed to mobile device users (MDUs) by offloading intensive computations to ubiquitous MEC server. However, most of the current offloading policies allow MDUs to transmit their tasks to the same connected small base stations (sBSs), which invariably increases latency and limits performance gain due to overload. Moreover, the security issue mitigating sensitive communication of information is not adequately addressed. Therefore, in this study, in addition to proposing a joint load balancing and computation offloading (CO) technique for MEC systems, we introduce a new security layer to circumvent potential security issues. First, a load balancing algorithm for efficient redistribution of MDUs among sBSs is proposed. In addition, a new advanced encryption standard (AES) cryptographic technique suffused with electrocardiogram (ECG) signal-based encryption and decryption key is presented as a security layer to safeguard the vulnerability of data during the transmission. Furthermore, an integrated model of load balancing, CO and security is formulated as a problem whose goal is to decrease the time and energy demands of the system. Detailed experimental results prove that our model with and without the additional security layers can save about 68.2% and 72.4% of system consumption compared to the local execution.
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