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Secure and Optimized Load Balancing for Multitier IoT and Edge-Cloud Computing Systems
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AI
DOI：10.1109/JIOT.2020.3042433.png)
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Abstract
En 中文
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.
Keywords:
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
Journal
IF:
8.9
Papers:
1.4W
Citations:
7.8W
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