@InProceedings{chang:reuse,
  author = {Tai-Sheng Chang and Sangyup Shim and David H.~C. Du},
  title = {The Scalability of Spatial Reuse Based Serial Storage Interfaces},
  booktitle = {Proceedings of the Fifth Workshop on Input/Output in Parallel
  and Distributed Systems},
  year = {1997},
  month = {November},
  pages = {93--101},
  publisher = {ACM Press},
  address = {San Jose, CA},
  URL = {http://doi.acm.org/10.1145/266220.266229},
  keywords = {I/O interface, I/O network, I/O architecture, parallel I/O,
  pario-bib},
  abstract = {Due to the growing popularity of emerging applications such as
  digital libraries, Video-On Demand, distance learning, and Internet
  World-Wide Web, multimedia servers with a large capacity and high performance
  storage subsystem are in high demand. Serial storage interfaces are emerging
  technologies designed to improve the performance of such storage subsystems.
  They provide high bandwidth, fault tolerance, fair bandwidth sharing and long
  distance connection capability. All of these issues are critical in designing
  a scalable and high performance storage subsystem. Some of the serial storage
  interfaces provide the spatial reuse feature which allows multiple concurrent
  transmissions. That is, multiple hosts can access disks concurrently with
  full link bandwidth if their access paths are disjoint. Spatial reuse
  provides a way to build a storage subsystem whose aggregate bandwidth may be
  scaled up with the number of hosts. However, it is not clear how much the
  performance of a storage subsystem could be improved by the spatial reuse
  with different configurations and traffic scenarios. Both limitation and
  capability of this scalability need to be investigated. To understand their
  fundamental performance characteristics, we derive an analytic model for the
  serial storage interfaces with the spatial reuse feature. Based on this
  model, we investigate the maximum aggregate throughput from different system
  configurations and load distributions. We show how the number of disks needed
  to saturate a loop varies with different number of hosts and different load
  scenarios. We also show how the load balancing by uniformly distributing the
  load to all the disks on a loop may incur high overhead. This is because the
  accesses to far away disks need to go through many links and consume the
  bandwidth of each link it goes through. The results show the achievable
  throughput may be reduced by more than half in some cases.}
}