Results 1 -
3 of
3
The Impact of DHT Routing Geometry on Resilience and Proximity
, 2003
"... The various proposed DHT routing algorithms embody several di#erent underlying routing geometries. These geometries include hypercubes, rings, tree-like structures, and butterfly networks. In this paper we focus on how these basic geometric approaches a#ect the resilience and proximity properties of ..."
Abstract
-
Cited by 213 (6 self)
- Add to MetaCart
The various proposed DHT routing algorithms embody several di#erent underlying routing geometries. These geometries include hypercubes, rings, tree-like structures, and butterfly networks. In this paper we focus on how these basic geometric approaches a#ect the resilience and proximity properties of DHTs. One factor that distinguishes these geometries is the degree of flexibility they provide in the selection of neighbors and routes. Flexibility is an important factor in achieving good static resilience and e#ective proximity neighbor and route selection. Our basic finding is that, despite our initial preference for more complex geometries, the ring geometry allows the greatest flexibility, and hence achieves the best resilience and proximity performance.
Pond: the OceanStore Prototype
, 2003
"... OceanStore is an Internet-scale, persistent data store designed for incremental scalability, secure sharing, and long-term durability. Pond is the OceanStore prototype; it contains many of the features of a complete system including location-independent routing, Byzantine update commitment, push-bas ..."
Abstract
-
Cited by 158 (14 self)
- Add to MetaCart
OceanStore is an Internet-scale, persistent data store designed for incremental scalability, secure sharing, and long-term durability. Pond is the OceanStore prototype; it contains many of the features of a complete system including location-independent routing, Byzantine update commitment, push-based update of cached copies through an overlay multicast network, and continuous archiving to erasure-coded form. In the wide area, Pond outperforms NFS by up to a factor of 4.6 on readintensive phases of the Andrew benchmark, but underperforms NFS by as much as a factor of 7.3 on writeintensive phases. Microbenchmarks show that write performance is limited by the speed of erasure coding and threshold signature generation, two important areas of future research. Further microbenchmarks show that Pond manages replica consistency in a bandwidthefficient manner and quantify the latency cost imposed by this bandwidth savings.

