سال انتشار:
2020
عنوان انگلیسی مقاله:
To chain or not to chain: A reinforcement learning approach for blockchain-enabled IoT monitoring applications
ترجمه فارسی عنوان مقاله:
به زنجیر کردن یا نکردن : رویکرد یادگیری تقویت کننده برای برنامه های نظارت بر اینترنت اشیا-با استفاده از بلاکچین
منبع:
Sciencedirect - Elsevier - Future Generation Computer Systems, 111 (2020) 39-51. doi:10.1016/j.future.2020.04.035
نویسنده:
Naram Mhaisen a,∗, Noora Fetais a, Aiman Erbad b, Amr Mohamedb, Mohsen Guizani
چکیده انگلیسی:
Traceability and autonomous business logic execution are highly desirable features in IoT monitoring
applications. Traceability enables verifying signals’ history for security or analytical purposes. On the
other hand, the autonomous execution of pre-defined rules establishes trust between parties involved
in such applications and improves the efficiency of their workflow. Smart Contracts (SCs) firmly
guarantee these two requirements due to the blockchain’s immutable distributed ledger and secure
cryptographic consensus rules. Thus, SCs emerged as an appealing technology for monitoring applications.
However, the cost of using public blockchains to harvest these guarantees can be prohibitive,
especially with the considerable fluctuation of coin prices and different use case requirements. In
this paper, we introduce a general SC-based IoT monitoring framework that can leverage the security
features of public blockchains while minimizing the corresponding monetary cost. The framework
contains a reinforcement learning agent that adapts to users’ needs and acts in real-time to smartly
set the data submission rate of IoT sensors. Results based on the Ethereum protocol show significant
potential cost saving depending on users’ preferences.
Keywords: Blockchain | Smart contracts | Monitoring applications | Internet of things | Reinforcement learning | Cost optimization
قیمت: رایگان
توضیحات اضافی:
تعداد نظرات : 0