ACC
Consistency Optimization Strategies for Distributed Advertising Systems Under Cross-regional Deployment
TOTAL VIEWS: 439
Abstract
Cross-regional deployment has become a common approach for advertising platforms to enhance access coverage, disaster resilience, and delivery continuity. However, when multiple regional nodes concurrently handle requests, coordinating state across budget deduction, frequency control, strategy distribution, event transmission, and report aggregation becomes increasingly challenging. Local delays, version mismatches, and link inconsistencies can escalate into global consistency deviations. For the business loop of distributed advertising systems, consistency control must extend beyond single-point data synchronization to encompass collaborative governance of delivery decisions, status writes, asynchronous compensation, and fault switching. By focusing on key state objects in the advertising delivery chain, this paper employs state classification, arbitration-based writes, version isolation, event backfilling, and full-chain verification to reduce the scope of cross-regional state drift while improving budget accuracy, frequency control stability, and settlement credibility under low-latency response constraints. The proposed optimization strategies provide a reference value for the architecture adjustment and operational governance of global advertising platforms.
Keywords
Cross-regional deployment; Distributed advertising system; Consistency optimization; Advertising delivery chain
References
[1] Gilbert S, Lynch N. Brewer’s conjecture and the feasibility of consistent, available, partition-tolerant web services. ACM SIGACT News. 2002;33(2):51-9.
[2] DeCandia G, Hastorun D, Jampani M, et al. Dynamo: Amazon’s highly available key-value store. In: Proceedings of the 21st ACM SIGOPS Symposium on Operating Systems Principles (SOSP). 2007:205-20.
[3] Corbett JC, Dean J, Epstein M, et al. Spanner: Google’s globally distributed database. ACM Trans Comput Syst. 2013;31(3):8.
[4] Bailis P, Venkataraman S, Franklin MJ, et al. Probabilistically bounded staleness for practical partial quorums. Proc VLDB Endow. 2012;5(8):776-87.
[5] Lee KC, Jalali A, Dasdan A. Real time bid optimization with smooth budget delivery in online advertising. In: Proceedings of the KDD Workshop on Data Mining for Online Advertising. 2013:1-9.
[6] Chen Y. A practical guide to budget pacing algorithms in digital advertising. arXiv:2503.06942. 2025.
[7] Fragkoulis M, Carbone P, Kalavri V, et al. A survey on the evolution of stream processing systems. VLDB J. 2024;33(2):507-41.
[8] Jasmina D, Zikrija A, Fahrudin O, et al. Advanced consistency management of highly-distributed transactional database in a hybrid cloud environment using novel R-TBC/RTA approach. J Cloud Comput. 2021;10(1):46.
[9] M RC, Park S, Pil SH, et al. Bypassing Performance Optimizers of Real Time Bidding Systems in Display Ad Valuation. Inf Syst Res. 2022;33(2):471-89.
[10] Debadatta N, Dharavath R, HA G, et al. Parallel and distributed paradigms for community detection in social networks: A methodological review. Expert Syst Appl. 2022;187:115916.
How to cite this paper
Consistency Optimization Strategies for Distributed Advertising Systems Under Cross-regional Deployment
How to cite this paper: Linlin Sun. (2026) Consistency Optimization Strategies for Distributed Advertising Systems Under Cross-regional Deployment. Advances in Computer and Communication, 7(2), 72-76.
DOI: http://dx.doi.org/10.26855/acc.2026.06.002
More Articles
- Research on Standardized Pathways for Automotive Manufacturing Process Quality Systems Oriented Toward Defect Prevention
- Consistency Optimization Strategies for Distributed Advertising Systems Under Cross-regional Deployment
- Research on Performance Monitoring and Data-driven Optimization Mechanisms for AI Systems Oriented Toward Decision Support
- Artificial Intelligence in Cerebral Palsy Rehabilitation: Current Progress and Future Directions
- Research on Heterogeneous Server Upgrade Strategies and Resource Utilization Efficiency Oriented Toward Green Computing Objectives
- Research on Evaluation and Optimization Models of Enterprise Resource Allocation Efficiency from a Data-driven Perspective