| Optimal cloud assistance policy of end-edge-cloud ecosystem for mitigating edge distributed denial of service attacks |
| Li, Teng
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| 2021-12-01
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| 发表期刊 | Journal of Cloud Computing
 |
| EISSN | 2192-113X
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| 卷号 | 10期号:1 |
| 摘要 | Edge computing has become a fundamental technology for Internet of Things (IoT) applications. To provide reliable services for latency-sensitive applications, edge servers must respond to end devices within the shortest amount of time possible. Edge distributed denial-of-service (DDoS) attacks, which render edge servers unusable by legitimate IoT applications by sending heavy requests from distributed attacking sources, is a threat that leads to severe latency. To protect edge servers from DDoS attacks, a hybrid computing paradigm known as an end-edge-cloud ecosystem provides a possible solution. Cloud assistance is allowed with this architecture. Edge servers can upload their pending tasks onto a cloud center for a workload reduction when encountering a DDoS attack, similar to borrowing resources from the cloud. Nevertheless, before using the ecosystem to mitigate edge DDoS attacks, we must address the core problem that edge servers must decide when and to what extent they should upload tasks to the cloud center. In this study, we focus on the design of optimal cloud assistance policies. First, we propose an edge workload evolution model that describes how the workload of the edge servers change over time with a given cloud assistance policy. On this basis, we quantify the effectiveness of the policy by using the resulting overall latency and formulate an optimal control problem for seeking optimal policies that can minimize such latency. We then provide solutions by deriving the optimality system and discuss some properties of the optimal solutions to accelerate the problem solving. Next, we introduce a numerical iterative algorithm to seek solutions that can satisfy the optimality system. Finally, we provide several illustrative numerical examples. The results show that the optimal policies obtained can effectively mitigate edge DDoS attacks. © 2021, The Author(s). |
| 关键词 | Ecosystems
Internet of things
Iterative methods
Network security
Optimal control systems
Distributed denial of service attack
Evolution modeling
Internet of Things (IOT)
Numerical iterative algorithm
Optimal control problem
Optimality system
Sensitive application
Workload reduction
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| DOI | 10.1186/s13677-021-00257-3
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| 收录类别 | EI
; SCIE
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| 语种 | 英语
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| WOS研究方向 | Computer Science
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| WOS类目 | Computer Science, Information Systems
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| WOS记录号 | WOS:000679789900001
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| 出版者 | Springer Science and Business Media Deutschland GmbH
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| EI入藏号 | 20213110712303
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| EI分类号 | 454.3 Ecology and Ecosystems
; 723 Computer Software, Data Handling and Applications
; 731.1 Control Systems
; 921.6 Numerical Methods
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| 原始文献类型 | Journal article (JA)
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| 出版地 | NEW YORK
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| 引用统计 |
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| 文献类型 | 期刊论文
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| 条目标识符 | https://ir.cqcet.edu.cn/handle/39TD4454/3195
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| 专题 | 重庆电子科技职业大学
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| 作者单位 | Artificial Intelligence and Big Data College, Chongqing College of Electronic Engineering, Chongqing, China
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| 第一作者单位 | 重庆电子科技职业大学
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推荐引用方式
GB/T 7714 |
Li, Teng. Optimal cloud assistance policy of end-edge-cloud ecosystem for mitigating edge distributed denial of service attacks[J].
Journal of Cloud Computing,2021,10(1).
|
| APA |
Li, Teng.(2021).Optimal cloud assistance policy of end-edge-cloud ecosystem for mitigating edge distributed denial of service attacks.Journal of Cloud Computing,10(1).
|
| MLA |
Li, Teng."Optimal cloud assistance policy of end-edge-cloud ecosystem for mitigating edge distributed denial of service attacks".Journal of Cloud Computing 10.1(2021).
|
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