A Distributed Publish–Subscribe Algorithm Based on Spatial Text Information Flow


  • Yangtao Liu School of Computer and Software, Nanyang Institute of Technology, Nanyang 473004, China
  • Xiaofeng Yu School of Computer and Information Technology, Nanyang Vocational College, Nanyang 474599, China




Publish-and-subscribe systems, Distributed systems, Clustering algorithms


With the rapid development of society and the popularity of smart devices, the volume of information sent and received is increasing day by day. It has become very difficult to accurately and efficiently match a large number of events with a large number of subscriptions, and the event and subscription matching speed can no longer meet demand. To speed up the matching speed of events and subscriptions, this paper uses similarity and correlation to optimize the clustering operation and increase the data transfer and data throughput of the category fusion strategy. Firstly, the clustering operation is performed on the subscription messages, and the category to which the events belong is found according to the clustering result. Subsequently, in the category, the subscriptions matching the events are found. An on-the-fly subscription publishing algorithm is proposed to coordinate spatial information and event attribute information to handle not only the matching operation of events and subscriptions on-the-fly but also to perform subscription updates and category updates on the distributed environment on-the-fly. It can also perform clustering operations and matching operations instantly without prior knowledge. We design a distributed system for the publish–subscribe algorithm and propose a load balancing strategy for this algorithm on the distributed system. Subsequently, we experimentally validate the proposed publish–subscribe algorithm in this paper by building our own cluster and using real data.


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Author Biographies

Yangtao Liu, School of Computer and Software, Nanyang Institute of Technology, Nanyang 473004, China

Yangtao Liu received his master’s degree in Computer Technology from Huazhong University of Science and Technology, China, in 2010. He joined Nanyang Institute of Technology, China, in 2004, where he is currently a lecturer. His research interests include big data technology and software engineering.

Xiaofeng Yu, School of Computer and Information Technology, Nanyang Vocational College, Nanyang 474599, China

Xiaofeng Yu received his bachelor’s degree in computer science and technology from Nanyang Institute of Technology, China, in 2008 and his master’s degree in education administration from Krirk University, Thailand, in 2021. He joined Nanyang Vocational College in 2011. His research interest is software engineering.


T. Vaiyapuri, V. S. Parvathy, V. Manikandan, et al., “A novel hybrid optimization for cluster-based routing protocol in information-centric wireless sensor networks for IoT based mobile edge computing,” Wireless Personal Communications, vol. 27, no. 1, pp. 39–62, 2022.

Y. Gao, F. He, S. Yu, et al., “Publish/subscribe architecture for airborne time-triggered network in avionics system,” 2022 IEEE/AIAA 41st Digital Avionics Systems Conference (DASC), 2022, pp. 1–8.

S. Kul, A. Sayar, “A survey of publish/subscribe middleware systems for microservice communication,” 2021 5th International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT), 2021, pp. 781–785.

A. D. Hristozov, E. T. Matson, “A methodology for estimation of software architectural complexity in publish-subscribe systems,” 2022 International Conference Automatics and Informatics (ICAI), 2022, pp. 29–34.

A. Lazidis, E. G. M. Petrakis, S. Chouliaras S, et al., “Open-source publish-subscribe systems: A comparative study. International Conference on Advanced Information Networking and Applications, 2022, pp. 105–115.

A. Lazidis, K. Tsakos, E. G. M. Petrakis, “Publish–subscribe approaches for the IoT and the cloud: Functional and performance evaluation of open-source systems. Internet of Things, vol. 19, pp. 100538, 2022.

I. Livaja, K. Pripužić, S. Sovilj S, et al., “ A distributed geospatial publish/subscribe system on Apache Spark,” Future Generation Computer Systems, vol. 132, pp. 282–298, 2022.

A. Fertier, A. M. Barthe-Delanoë, A. Montarnal, et al., “A new emergency decision support system: the automatic interpretation and contextualisation of events to model a crisis situation in real-time,” Decision Support Systems, vol. 133, pp. 113260, 2020.

Zhang H, Zhang X, Ding K, et al., “A fuzzy matching with reasoning publish/subscribe system based on ontology,” 2022 2nd International Conference on Consumer Electronics and Computer Engineering (ICCECE). IEEE, 2022, pp. 150–156.

S. K. Pande, S. K. Panda, S. Das, “Dynamic service migration and resource management for vehicular clouds,” Journal of Ambient Intelligence and Humanized Computing, vol. 12, pp. 1227–1247, 2021.

G. Zhou, R. Zhang, S. Huang, “Generalized buffering algorithm,” IEEE Access, vol. 9, pp. 27140–27157, 2021.

J. Zhang, X. Liu, “Evaluation and optimization of QoS-aware network management framework based on process synergy and resource allocation,” Journal of Ambient Intelligence and Humanized Computing, pp. 1–9, 2018.

H. Abbasimehr, M. Shabani, “A new framework for predicting customer behavior in terms of RFM by considering the temporal aspect based on time series techniques,” Journal of Ambient Intelligence and Humanized Computing, vol. 12, no. 1, pp. 515–531, 2021.

R. Chen, Z. Wang, Y. Hong, “Pipelined XPath query based on cost optimization,” Scientific Programming, vol. 2021, pp. 1–16, 2021.

B. Cao, Y. Gu, Z. Lv, et al., “RFID reader anticollision based on distributed parallel particle swarm optimization,” IEEE Internet of Things Journal, vol. 8, no. 5, pp. 3099–3107, 2021.

M. Rinne, E. Nuutila, “User-configurable semantic data stream reasoning using SPARQL update,” Journal on Data Semantics, vol. 6, no. 3, pp. 125–138, 2017.

C. Huang, C. Zhang, J. Zhao, et al., “Mist: A multiview and multimodal spatial-temporal learning framework for citywide abnormal event forecasting,” The World Wide Web Conference, 2019, pp. 717–728.

F. Mo, H. U. Rehman, F. M. Monetti, et al., “A framework for manufacturing system reconfiguration and optimisation utilising digital twins and modular artificial intelligence,” Robotics and Computer-Integrated Manufacturing, vol. 82, pp. 102524, 2023.

Durkovic S, Cica Z. Multicast Load-Balanced Birkhoff-Von Neumann Switch With Greedy Scheduling. IEEE Access, 2020, 8, pp. 120654–120667.

M. Florea, C. Potlog, P. Pollner, et al., “Complex project to develop real tools for identifying and countering terrorism: real-time early detection and alert system for online terrorist content based on natural language processing, social network analysis, artificial intelligence and complex event processing,” Challenges in Cybersecurity and Privacy-the European Research Landscape, River Publishers, 2022, pp. 181–206.

I. Livaja, K. Pripužic, S. Sovilj, et al., “A distributed geospatial publish/subscribe system on Apache Spark,” Future Generation Computer Systems, vol. 132, pp. 282–298, 2022.

D. A Tran, L. H. Truong, “Enabling publish/subscribe services in sensor networks,” Future Internet Services and Service Architectures. River Publishers, 2022, pp. 339–363.

V. Rampérez, J. Soriano, D. Lizcano, et al., “Automatic evaluation and comparison of pub/sub systems performance improvements,” Journal of Web Engineering, pp. 1055–1080, 2022.

M. Nast, H. Raddatz, B. Rother, et al., “A survey and comparison of publish/subscribe protocols for the Industrial Internet of Things (IIoT),” Proceedings of the 12th International Conference on the Internet of Things, 2022, pp. 193–200.

R. Van Glabbeek, D. Deac, T. Perale, et al., “Flexible and efficient security framework for many-to-many communication in a publish/subscribe architecture,” Sensors, vol. 22, no. 19, p. 7391, 2022.

C. Miguel, V. Rampérez, J. Soriano, et al., “Towards SLA-driven autoscaling of cloud distributed services for mobile communications,” Mobile Information Systems, vol. 2022, 2022.

C. Prajisha, A. R. Vasudevan, “An efficient intrusion detection system for MQTT-IoT using enhanced chaotic salp swarm algorithm and LightGBM,” International Journal of Information Security, vol. 21, no. 6, pp. 1263–1282, 2022.

M. Cheng, T. Ma, L. Ma, et al., “Adaptive grid-based forest-like clustering algorithm,” Neurocomputing, vol. 481, pp. 168–181, 2022.

W. Zhu, Y. Deng, S. Qian, et al., “PEM: A parallel ensemble matching framework for content-based publish/subscribe systems,” The 34th International Conference on Software Engineering and Knowledge Engineering, 2022.

M. Shahbazi, M. Simsek, B. Kantarci, “Density-based clustering and performance enhancement of aeronautical ad hoc networks,” 2022 International Balkan Conference on Communications and Networking (BalkanCom), 2022, pp. 51–56.

G. Wu, L. Cao, H. Tian, et al., “HY-DBSCAN: A hybrid parallel DBSCAN clustering algorithm scalable on distributed-memory computers,” Journal of Parallel and Distributed Computing, vol. 168, pp. 57–69, 2022.

V. Rampérez, J. Soriano, D. Lizcano, et al., “FLAS: A combination of proactive and reactive auto-scaling architecture for distributed services,” Future Generation Computer Systems, vol. 118, pp. 56–72, 2021.

T. Ouyang, X. Shen, “Online structural clustering based on DBSCAN extension with granular descriptors,” Information Sciences, vol. 607, pp. 688–704, 2022.



How to Cite

Liu, Y. ., & Yu, X. . (2023). A Distributed Publish–Subscribe Algorithm Based on Spatial Text Information Flow. Journal of Web Engineering, 22(03), 385–404. https://doi.org/10.13052/jwe1540-9589.2231