Cost-sensitive Layer-7 Load Balancing Under Bursty Enterprise Cloud Traffic Conditions
DOI:
https://doi.org/10.66238/smsrj.v4i2.81Keywords:
Layer-7 load balancing, cost-sensitive routing, bursty traffic, enterprise cloud computing, resource allocation.Abstract
Modern enterprise cloud environments face significant challenges in managing operational costs while maintaining high quality of service during periods of sudden, unpredictable traffic surges. Traditional Layer-4 network load balancers often lack the application-level awareness required to route requests based on granular resource consumption, whereas standard Layer-7 solutions typically prioritize performance and latency over financial expenditure. This paper investigates a novel paradigm for cost-sensitive Layer-7 load balancing specifically designed to mitigate the financial impact of bursty enterprise cloud traffic conditions. By analyzing incoming HTTP request payloads, headers, and user session data, the proposed architecture dynamically calculates the operational cost associated with fulfilling each request across a heterogeneous pool of backend instances, including on-demand, reserved, and spot virtual machines. The study proposes a comprehensive decision-making framework that continuously ingests real-time pricing metrics, server utilization rates, and application profiling data to perform financially optimized traffic distribution. Through extensive simulation and empirical analysis, this paper demonstrates that integrating cost awareness directly into the application-layer routing logic can yield substantial reductions in overall cloud infrastructure expenditures without inducing unacceptable degradation in user-perceived latency. The findings highlight the critical importance of multidimensional metrics in modern load balancing and provide a robust architectural blueprint for enterprises seeking to balance financial constraints with the computational demands of bursty workloads.
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Copyright (c) 2026 Katharina Schmitz, Matthias F. Baumann, Finn F. Weiß
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