Roger Wattenhofer and Quentin Kniep propose speeding Solana’s block production by scheduling nearby validators consecutively. Their plan relies on self-reported locations, bringing an unverifiable physical input into the order of block producers. Each scheduled turn at block production is called a leader window.

The aim is to make fast handovers less dependent on operating near Solana’s biggest stake centers. The authors’ simulation cuts the mean handover delay between honest validators from 36.2 milliseconds to 17.0 milliseconds without giving any validator more leader windows. Reordering also changes the continuity of control: three-window groups can combine into longer consecutive stretches.

Wattenhofer, Anza’s head of research and an ETH Zurich professor , coauthored the geographic schedule with Kniep, who identifies himself as a researcher at Anza and ETH Zurich . Their SIMD-0675 draft makes that tension explicit, recording six adversarial windows in succession under its proposed three-window setting.

Both the scheduling proposal and its companion location-registration proposal were introduced as pull requests on Sept. 29. As of Oct. 7, they remain open. These are proposed rules and modeled outcomes, rather than results from a deployed geographic schedule.

Under the design, Solana would first calculate its stake-weighted random leader schedule as usual. A second pass would rearrange those leader windows into small groups, called bins, using reported geographic proximity.

A leader is the validator assigned to build blocks during a window. Every validator would retain exactly the number of windows it received in the original schedule; the change concerns when those opportunities arrive and which leader precedes them.

That predecessor matters under Alpenglow’s fast leader handover, where the previous leader sends its block directly to the next one. The authors argue that a random schedule favors validators near large concentrations of stake: they are more likely to be close to the leader they follow, while remote validators more often face a long hop.

Grouping nearby leaders seeks to give validators outside those centers more local handovers. The intended decentralization benefit is therefore an incentive to operate away from existing hubs, rather than a redistribution of stake or additional leader allocations. The simulations measure scheduling and latency, leaving actual operator relocation and stake concentration outside their results.