Name
Abstract | ||
|---|---|---|
Dynamic information management via Distributed Hash Tables (DHT) is an important problem which revolves around the trade-off between data freshness and the overhead due to information updates. We propose two different algorithms based on information pull and information push models, that enable dynamic information dissemination with low overhead over a DHT. We exploit the concept of popularity of specific items, which is evaluated by performing a real-time analysis of the query distribution, and allows to decrease a significant fraction of messages without impairing the query resolution process. We have measured the overhead savings and compared the performance of the two approaches by extensive simulations using real workload traces. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/CIT.2011.94 | CIT |
Keywords | Field | DocType |
cryptography,distributed processing,information dissemination,information management,probability,query processing,DHT,data freshness,distributed hash table,dynamic information dissemination,dynamic information management,information pull model,information push model,probabilistic dropping,query distribution,query resolution process,real workload traces,real-time analysis | Data modeling,Information management,Workload,Computer science,Cryptography,Computer network,Exploit,Information Dissemination,Probabilistic logic,Distributed computing,Hash table | Conference |
Citations | PageRank | References |
3 | 0.37 | 13 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Emanuele Carlini | 1 | 166 | 20.15 |
| Massimo Coppola | 2 | 38 | 4.11 |
| Laura Ricci | 3 | 151 | 14.12 |