IoT and big data applications in smart cities: recent advances, challenges, and critical issues
The notion of smart cities has remained under evolution as its global implementations are
challenged by numerous technological, economic, and governmental obstacles. Moreover …
challenged by numerous technological, economic, and governmental obstacles. Moreover …
A game-based deep reinforcement learning approach for energy-efficient computation in MEC systems
Many previous energy-efficient computation optimization works for mobile edge computing
(MEC) systems have been based on the assumption of synchronous offloading, where all …
(MEC) systems have been based on the assumption of synchronous offloading, where all …
Blockchain for federated learning toward secure distributed machine learning systems: a systemic survey
Federated learning (FL) is a promising decentralized deep learning technology, which
allows users to update models cooperatively without sharing their data. FL is reshaping …
allows users to update models cooperatively without sharing their data. FL is reshaping …
A survey on nature-inspired techniques for computation offloading and service placement in emerging edge technologies
Abstract Internet of Things (IoT) aims to make an environment more innovative and
productive by connecting physical things to the internet. Processing generated data from IoT …
productive by connecting physical things to the internet. Processing generated data from IoT …
Deep reinforcement learning-based microservice selection in mobile edge computing
In mobile edge computing environment, due to resources constraints of edge devices, when
user locations continue changing, the network will be delayed or interrupted, which affects …
user locations continue changing, the network will be delayed or interrupted, which affects …
Constraint‐aware and multi‐objective optimization for micro‐service composition in mobile edge computing
J Wu, J Zhang, Y Zhang, Y Wen - Software: Practice and …, 2023 - Wiley Online Library
As a new paradigm of distributed computing, mobile edge computing (MEC) has gained
increasing attention due to its ability to expand the capabilities of centralized cloud …
increasing attention due to its ability to expand the capabilities of centralized cloud …
A Review of Service Selection Strategies in Mobile IoT Networks
With the proliferation of service-oriented architectures, the ubiquity of mobile networks, and
an expanding spectrum of services available to users, the service selection process has …
an expanding spectrum of services available to users, the service selection process has …
DoME: Dew computing based microservice execution in mobile edge using Q-learning
S Chakraborty, D De, K Mazumdar - Applied Intelligence, 2023 - Springer
The microservice approach unlatched a new window of distributed service-oriented
architecture over the computational horizon. Microservice coordination in a heterogeneous …
architecture over the computational horizon. Microservice coordination in a heterogeneous …
Energy–latency tradeoffs edge server selection and DQN-based resource allocation schemes in MEC
C Li, Z Ke, Q Liu, C Hu, C Lu, Y Luo - Wireless Networks, 2023 - Springer
This paper discusses the challenges of mobile edge computing with low latency and energy
consumption caused by the explosive growth of communication traffic and data generated …
consumption caused by the explosive growth of communication traffic and data generated …
Stateful versus stateless selection of edge or cloud servers under latency constraints
We consider a radio access network slice serving mobile users whose requests imply
computing requirements. Service is virtualized over either a powerful but distant cloud …
computing requirements. Service is virtualized over either a powerful but distant cloud …