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1 |
Enhanced resource allocation in mobile edge computing using reinforcement learning based MOACO algorithm for IIOT
تخصیص منابع پیشرفته در محاسبات لبه تلفن همراه با استفاده از الگوریتم MOACO مبتنی بر یادگیری تقویت کننده برای IIOT-2020 The Mobile networks deploy and offers a multiaspective approach for various resource allocation paradigms
and the service based options in the computing segments with its implication in the Industrial Internet of Things
(IIOT) and the virtual reality. The Mobile edge computing (MEC) paradigm runs the virtual source with the
edge communication between data terminals and the execution in the core network with a high pressure load.
The demand to meet all the customer requirements is a better way for planning the execution with the support
of cognitive agent. The user data with its behavioral approach is clubbed together to fulfill the service type for
IIOT. The swarm intelligence based and reinforcement learning techniques provide a neural caching for the
memory within the task execution, the prediction provides the caching strategy and cache business that delay
the execution. The factors affecting this delay are predicted with mobile edge computing resources and to
assess the performance in the neighboring user equipment. The effectiveness builds a cognitive agent model to
assess the resource allocation and the communication network is established to enhance the quality of service.
The Reinforcement Learning techniques Multi Objective Ant Colony Optimization (MOACO) algorithms has
been applied to deal with the accurate resource allocation between the end users in the way of creating the
cost mapping tables creations and optimal allocation in MEC Keywords: Mobile edge computing | Industrial IOT | Reinforcement learning | Multi objective ant colony optimization | Resource allocation | Cognitive agent |
مقاله انگلیسی |
2 |
A Blockchain Tokenizer for Industrial IOT trustless applications
یک بلاکچین Tokenizer برای برنامه های کاربردی بی اعتماد صنعتی IOT-2019 The Blockchain is a novel technology with a wide range of potential industrial applications. Despite
a vast range of tests, prototypes, and proof of concepts implemented in the last years, the industrial
use of Blockchain technology is still in the early stages. Enabling the interaction of industrial Internet
of Things (IOT) platforms with Blockchain might be challenging because standards are still missing in
both these technologies. Moreover, integrating productive assets with distributed data exchange and
storage technologies is a kind of activity that needs to take into account various aspects, in particular:
interoperability, portability, scalability, and security that need to be guaranteed by design.
This paper describes the implementation of a portable, platform-agnostic and secure Blockchain
Tokenizer for Industrial IOT trustless applications. The Industrial Blockchain Tokenizer (IBT) is based
on an industrial data acquisition unit able to gather data from both modern and legacy machines while
also interfacing directly with sensors. Acquired data can be processed locally enabling an edge filtering
paradigm and then sent to any Blockchain platform. The system has been designed, implemented
and then tested on two supply chain scenarios. Tests demonstrated the system capability to act as a
bridge between industrial assets and Blockchain platforms enabling the generation of immutable and
trust-less ‘‘digital twins’’ for industrial IOT applications. Keywords: Industrial IOT | Blockchain | Ethereum | Smart contract | Supply chain | Industry 4.0 |
مقاله انگلیسی |