Temporal Elasticity Orchestration (TEO): A Novel Time Domain Optimization Framework for Cloud Computing

Author(s)	Aditya Rautaray
Country	India
Abstract	Cloud optimization today focuses almost exclusively on spatial and resource dimensions—scaling workloads across machines, regions, or instance types. However, modern cloud platforms contain billions of micro idle intervals across CPUs, GPUs, memory controllers, and network interfaces that remain unexploited due to their extremely short duration. This paper introduces Temporal Elasticity Orchestration (TEO), a fundamentally new cloud optimization paradigm that treats time as a first class scheduling resource. TEO identifies micro idle windows across the cloud fabric and executes workloads in Temporal Micro Fragments (TMFs) that fit into these sub millisecond gaps. By shifting computation across time rather than space, TEO enables temporal arbitrage, dramatically improving utilization, reducing cost, and accelerating long running jobs. Experimental simulations demonstrate that TEO can reduce compute cost by up to 70%, increase effective utilization to 95–99%, and accelerate AI training workloads by 20–40% through opportunistic micro execution. This work proposes a new dimension of cloud optimization: time aware compute orchestration.
Keywords	Cloud optimization; Temporal scheduling; Micro idle windows; Distributed systems; Cloud orchestration; AI acceleration.
Field	Engineering
Published In	Volume 7, Issue 2, February 2026
Published On	2026-02-11

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