Device-to-device (D2D) communication technique is used to establish direct links among mobile devices (MDs) to reduce communication delay and increase network capacity over the underlying wireless networks. Existing D2D schemes for task offloading focus on system throughput, energy consumption, and delay without considering data security. This paper proposes a Security and Energy-aware Collaborative Task Offloading for D2D communication (Sec2D). Specifically, we first build a novel security model, in terms of the number of CPU cores, CPU frequency, and data size, for measuring the security workload on heterogeneous MDs. Then, we formulate the collaborative task offloading problem that minimizes the time-average delay and energy consumption of MDs while ensuring data security. In order to meet this goal, the Lyapunov optimization framework is applied to implement online decision-making. Two solutions, greedy approach and optimal approach, with different time complexities, are proposed to deal with the generated mixed-integer linear programming (MILP) problem. The theoretical proofs demonstrate that Sec2D follows a [O(1∕V),O(V)] energy-delay tradeoff. Simulation results show that Sec2D can guarantee both data security and system stability in the collaborative D2D communication environment.
|Number of pages||16|
|Journal||Future Generation Computer Systems|
|Early online date||23 Jan 2021|
|Publication status||Published - 1 May 2021|
Bibliographical note© 2021, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/
This work was supported by the National Natural Science Foundation of China (No. 61802095, 61572162), the Zhejiang Provincial Key Science and Technology Project Foundation, China (No. 2018C01012), the National Key R&D Program of China (2016YFC0800803), the VC Research, China (No. VCR 0000126) for Prof Chang.
- Collaborative task offloading
- D2D communication
- Lyapunov optimization
- Mixed-integer linear programming (MILP)
- Security modeling