Load Balancing for Massively-Parallel Soft-Real-Rime Systems
Abstract
Global load balancing, if practical, would allow the effective use of massively-parallel ensemble architectures for large soft-real-problems. The challenge is to replace quick global communications, which is impractical in a massively-parallel system, with statistical techniques. In this vein, the author proposes a novel approach to decentralized load balancing based on statistical time-series analysis. Each site estimates the system-wide average load using information about past loads of individual sites and attempts to equal that average. This estimation process is practical because the soft-real-time systems we are interested in naturally exhibit loads that are periodic, in a statistical sense akin to seasonality in econometrics. It is shown how this load-characterization technique can be the foundation for a load-balancing system in an architecture employing cut-through routing and an efficient multicast protocol.
Document Details
- Document Type
- Technical Report
- Publication Date
- Sep 01, 1988
- Accession Number
- ADA200912
Entities
People
- Max Hailperin
Organizations
- Stanford University