Low load DIDS task scheduling based on Q-learning in edge computing environment
Published 2021 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Low load DIDS task scheduling based on Q-learning in edge computing environment
Authors
Keywords
Reinforcement learning, Intrusion detection, Task scheduling, Q-learning
Journal
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
Volume 188, Issue -, Pages 103095
Publisher
Elsevier BV
Online
2021-05-29
DOI
10.1016/j.jnca.2021.103095
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Applying machine learning techniques for caching in next-generation edge networks: A comprehensive survey
- (2021) Junaid Shuja et al. JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
- Refining Network Lifetime of Wireless Sensor Network Using Energy-Efficient Clustering and DRL-Based Sleep Scheduling
- (2020) Ramadhani Sinde et al. SENSORS
- A Stochastic Approximation Approach for Foresighted Task Scheduling in Cloud Computing
- (2020) Seyedakbar Mostafavi et al. WIRELESS PERSONAL COMMUNICATIONS
- Privacy-preserving federated k-means for proactive caching in next generation cellular networks
- (2020) Yang Liu et al. INFORMATION SCIENCES
- Optimization of lightweight task offloading strategy for mobile edge computing based on deep reinforcement learning
- (2019) Haifeng Lu et al. Future Generation Computer Systems-The International Journal of eScience
- DA-DRLS: Drift adaptive deep reinforcement learning based scheduling for IoT resource management
- (2019) Abishi Chowdhury et al. JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
- Joint Computation Offloading and Multiuser Scheduling Using Approximate Dynamic Programming in NB-IoT Edge Computing System
- (2019) Lei Lei et al. IEEE Internet of Things Journal
- A Q-learning algorithm for task scheduling based on improved SVM in wireless sensor networks
- (2019) Zhenchun Wei et al. Computer Networks
- LD2FA-PSO: A novel Learning Dynamic Deterministic Finite Automata with PSO algorithm for secured energy efficient routing in Wireless Sensor Network
- (2019) S. Prithi et al. Ad Hoc Networks
- Load balance based workflow job scheduling algorithm in distributed cloud
- (2019) Chunlin Li et al. JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
- Reinforcement-Learning- and Belief-Learning-Based Double Auction Mechanism for Edge Computing Resource Allocation
- (2019) Quanyi Li et al. IEEE Internet of Things Journal
- Edge Computing in the Industrial Internet of Things Environment: Software-Defined-Networks-Based Edge-Cloud Interplay
- (2018) Kuljeet Kaur et al. IEEE COMMUNICATIONS MAGAZINE
- Secure and Sustainable Load Balancing of Edge Data Centers in Fog Computing
- (2018) Deepak Puthal et al. IEEE COMMUNICATIONS MAGAZINE
- Intrusion detection model of wireless sensor networks based on game theory and an autoregressive model
- (2018) Lansheng Han et al. INFORMATION SCIENCES
- Scheduling framework for distributed intrusion detection systems over heterogeneous network architectures
- (2018) José Francisco Colom et al. JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
- Novel Sensor Scheduling Scheme for Intruder Tracking in Energy Efficient Sensor Networks
- (2018) Raghuram Bharadwaj Diddigi et al. IEEE Wireless Communications Letters
- Security in the Internet of Things Supported by Mobile Edge Computing
- (2018) Daojing He et al. IEEE COMMUNICATIONS MAGAZINE
- EdgeCloudSim: An environment for performance evaluation of edge computing systems
- (2018) Cagatay Sonmez et al. Transactions on Emerging Telecommunications Technologies
- Fair Resource Allocation in an Intrusion-Detection System for Edge Computing: Ensuring the Security of Internet of Things Devices
- (2018) Fuhong Lin et al. IEEE Consumer Electronics Magazine
- Suspicious Flow Forwarding for Multiple Intrusion Detection Systems on Software-Defined Networks
- (2016) Taejin Ha et al. IEEE NETWORK
- Proactive scheduling in distributed computing—A reinforcement learning approach
- (2014) Zhao Tong et al. JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING
Discover Peeref hubs
Discuss science. Find collaborators. Network.
Join a conversationBecome a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get Started