Citation :

Rahul Verma, 2026. "A Lightweight Decision Framework for Choosing Between Edge and Cloud Processing in Latency-Sensitive Applications" ESP International Journal of Advancements in Science & Technology (ESP-IJAST)  Volume 4, Issue 3: 34-47.

Abstract :

Latency sensitive applications demand fast processing and timely response to ensure correct, reliable and efficient operation of the application. Autonomous Vehicles, Industrial Automation, Health Monitoring Systems, Smart Cities, Interactive Systems etc. usually require strict response times. Traditional cloud computing offers scalable processing power and central control; however, sending data to remote servers introduces delay in transmission (network delay), congestion, and communication overhead. Edge Computing reduces delays by processing information near the source of data, however edge devices are restricted in terms of computing power, memory, and power. This paper proposes a light-weight decision support system to help determine whether to process on the Edge or Cloud based on the requirements of the application and the operational environment. The system will evaluate the following parameters: Response Time Requirements, Network Delay, Bandwidth Available, Computational Complexity, Power Usage, Data Privacy, and Resource Availability. The system will use a straightforward decision process to determine where to perform the processing of data and does not require complex optimization techniques. The proposed approach will also allow for dynamic decision making based on changes in network environments and/or application workloads. With the evaluation of several operational parameters, the proposed approach intends to increase response time reliability, resource utilization, and processing efficiency. This paper creates a theoretical base for the development of real world decision support systems for latency sensitive applications. System designers will find value in this decision support system as it assists them in balancing responsiveness, scalability, security, and resource constraints when deciding if computational tasks should be performed at the edge or remotely in the cloud.

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Keywords :

Edge Computing, Cloud Computing, Latency-Sensitive Applications, Decision Framework, Response Time, Network Latency, Resource Allocation, Energy Efficiency, Data Privacy, Computational Offloading