Improving load balancing for data-duplication in big data cloud computing networks

Data transmission and retrieval in a cloud computing environment are usually handled by storage device providers or physical storage units leased by third parties. Improving network performance considering power connectivity and resource stability while ensuring workload balance is a hot topic in cloud computing. In this research, we have addressed the data duplication problem by providing two dynamic models with two variant architectures to investigate the strengths and shortcomings of architectures in Big Data Cloud Computing Networks. The problems of the data duplication process will be discussed accurately in each model. Attempts have been made to improve the performance of the cloud network by taking into account and correcting the flaws of the previously proposed algorithms. The accuracy of the proposed models have been investigated by simulation. Achieved results indicate an increase in the workload balance of the network and a decrease in response time to user requests in the model with a grouped architecture for all the architectures. Also, the proposed duplicate data model with peer-to-peer network architecture has been able to increase the cloud network optimality compared to the models presented with the same architecture.

[1]  Guojun Wang,et al.  Power Curtailment in Cloud Environment Utilising Load Balancing Machine Allocation , 2018, 2018 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI).

[2]  Kuan-Ching Li,et al.  Optimal Execution Strategy for Large Orders in Big Data: Order Type using Q-learning Considerations , 2020, Wireless Personal Communications.

[3]  Najme Mansouri Adaptive data replication strategy in cloud computing for performance improvement , 2016, Frontiers of Computer Science.

[4]  Nima Jafari Navimipour,et al.  A comprehensive study of the resource discovery techniques in Peer-to-Peer networks , 2015 .

[5]  Ayaz Isazadeh,et al.  PHFS: A dynamic replication method, to decrease access latency in the multi-tier data grid , 2011, Future Gener. Comput. Syst..

[6]  Xin Huang,et al.  A Cost-Effective Data Replica Placement Strategy Based on Hybrid Genetic Algorithm for Cloud Services , 2018, CONFENIS.

[7]  Amir Javadpour,et al.  Providing a Way to Create Balance Between Reliability and Delays in SDN Networks by Using the Appropriate Placement of Controllers , 2019, Wireless Personal Communications.

[8]  Meng Xue,et al.  Replica Placement in Cloud Storage based on Minimal Blocking Probability , 2015 .

[9]  Nima Jafari Navimipour,et al.  A comprehensive study of the resource discovery techniques in Peer-to-Peer networks , 2015, Peer-to-Peer Netw. Appl..

[10]  Dan Feng,et al.  CDRM: A Cost-Effective Dynamic Replication Management Scheme for Cloud Storage Cluster , 2010, 2010 IEEE International Conference on Cluster Computing.

[11]  R. H. Goudar,et al.  Cloud Computing - Research Issues, Challenges, Architecture, Platforms and Applications: A Survey , 2012 .

[12]  Robert John Walters,et al.  Fog Computing and the Internet of Things: A Review , 2018, Big Data Cogn. Comput..

[13]  Rodica Potolea,et al.  Opinion Leader Detection , 2017 .

[14]  Mohamed-K Hussein,et al.  A Light-weight Data Replication for Cloud DataCenters Environment , 2014 .

[15]  Xiaojun Chang,et al.  Feature Interaction Augmented Sparse Learning for Fast Kinect Motion Detection , 2017, IEEE Transactions on Image Processing.

[16]  Farshad Lahouti,et al.  Automatic fault detection and diagnosis in cellular networks using operations support systems data , 2016, NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium.

[17]  María S. Pérez-Hernández,et al.  Keeping up with storage: Decentralized, write-enabled dynamic geo-replication , 2017, Future Gener. Comput. Syst..

[18]  Wenbin Yao,et al.  DARS: A dynamic adaptive replica strategy under high load Cloud-P2P , 2018, Future Gener. Comput. Syst..

[19]  Albert Y. Zomaya,et al.  Energy-efficient data replication in cloud computing datacenters , 2013, 2013 IEEE Globecom Workshops (GC Wkshps).

[20]  Azlan Ismail,et al.  Energy-driven cloud simulation: existing surveys, simulation supports, impacts and challenges , 2020, Cluster Computing.

[21]  Najme Mansouri,et al.  DPRS: A dynamic popularity aware replication strategy with parallel download scheme in cloud environments , 2017, Simul. Model. Pract. Theory.

[22]  Chunming Tang,et al.  Using Markov Learning Utilization Model for Resource Allocation in Cloud of Thing Network , 2020, Wireless Personal Communications.

[23]  Bahman Javadi,et al.  Cloud storage reliability for Big Data applications: A state of the art survey , 2017, J. Netw. Comput. Appl..

[24]  Guojun Wang,et al.  Feature Selection and Intrusion Detection in Cloud Environment Based on Machine Learning Algorithms , 2017, 2017 IEEE International Symposium on Parallel and Distributed Processing with Applications and 2017 IEEE International Conference on Ubiquitous Computing and Communications (ISPA/IUCC).

[25]  Abdelkader Hameurlain,et al.  Ensuring performance and provider profit through data replication in cloud systems , 2017, Cluster Computing.

[26]  Amir Masoud Rahmani,et al.  Reliability and high availability in cloud computing environments: a reference roadmap , 2018, Human-centric Computing and Information Sciences.

[27]  Alptekin Küpçü,et al.  Decentralized Utility- and Locality-Aware Replication for Heterogeneous DHT-Based P2P Cloud Storage Systems , 2019, IEEE Transactions on Parallel and Distributed Systems.

[28]  Kuan-Ching Li,et al.  A Scalable Feature Selection and Opinion Miner Using Whale Optimization Algorithm , 2020, ArXiv.

[29]  Wenzhong Guo,et al.  Data Replication Placement Strategy Based On Bidding Mode for Cloud Storage Cluster , 2014, 2014 11th Web Information System and Application Conference.

[30]  Abdelkader Hameurlain,et al.  A data replication strategy with tenant performance and provider economic profit guarantees in Cloud data centers , 2020, J. Syst. Softw..

[31]  Wenhao Li,et al.  2 – Literature review , 2015 .

[32]  Damanpreet Singh,et al.  Energy and resource efficient workflow scheduling in a virtualized cloud environment , 2020, Cluster Computing.

[33]  Guojun Wang,et al.  Resource Management in a Peer to Peer Cloud Network for IoT , 2020, Wireless Personal Communications.

[34]  Amir Javadpour,et al.  Improving Resources Management in Network Virtualization by Utilizing a Software-Based Network , 2019, Wireless Personal Communications.

[35]  Amir Javadpour,et al.  LBPSGORA: Create Load Balancing with Particle Swarm Genetic Optimization Algorithm to Improve Resource Allocation and Energy Consumption in Clouds Networks , 2021 .

[36]  Leigh Metcalf Chapter 5 – Graph theory , 2016 .

[37]  Emad Jafari,et al.  An intelligent botnet blocking approach in software defined networks using honeypots , 2020, Journal of Ambient Intelligence and Humanized Computing.

[38]  Hassina Nacer,et al.  Efficient dynamic resource allocation method for cloud computing environment , 2020, Cluster Computing.

[39]  Chetna Dabas,et al.  Delayed Replication Algorithm with Dynamic Threshold for Cloud Datacenters , 2019, Lecture Notes in Electrical Engineering.

[40]  Charles M. Judd,et al.  Introduction to data analysis , 2016 .

[41]  Elsayed E. Hemayed,et al.  Trusted Cloud Computing Architectures for infrastructure as a service: Survey and systematic literature review , 2019, Comput. Secur..

[42]  Guojun Wang,et al.  Managing Heterogeneous Substrate Resources by Mapping and Visualization Based on Software-Defined Network , 2018, 2018 IEEE Intl Conf on Parallel & Distributed Processing with Applications, Ubiquitous Computing & Communications, Big Data & Cloud Computing, Social Computing & Networking, Sustainable Computing & Communications (ISPA/IUCC/BDCloud/SocialCom/SustainCom).

[43]  Albert Y. Zomaya,et al.  DROPS: Division and Replication of Data in Cloud for Optimal Performance and Security , 2018, IEEE Transactions on Cloud Computing.

[44]  Mounir Ben Ayed,et al.  An enhanced healthcare system in mobile cloud computing environment , 2016, Vietnam Journal of Computer Science.

[45]  Detecting straggler MapReduce tasks in big data processing infrastructure by neural network , 2020, The Journal of Supercomputing.