Results 1 
2 of
2
On optimal communication cost for gathering correlated data through wireless sensor networks
 in Proc. of ACM MobiCom
"... In many energyconstrained wireless sensor networks, nodes cooperatively forward correlated sensed data to data sinks. In order to reduce the communication cost (e.g. overall energy) used for data collection, previous works have focused on specific coding schemes, such as SlepianWolf Code or Expli ..."
Abstract

Cited by 30 (2 self)
 Add to MetaCart
(Show Context)
In many energyconstrained wireless sensor networks, nodes cooperatively forward correlated sensed data to data sinks. In order to reduce the communication cost (e.g. overall energy) used for data collection, previous works have focused on specific coding schemes, such as SlepianWolf Code or Explicit Entropy Code. However, the minimum communication cost under arbitrary coding/routing schemes has not yet been characterized. In this paper, we consider the problem of minimizing the total communication cost of a wireless sensor network with a single sink. We prove that the minimum communication cost can be achieved using SlepianWolf Code and Commodity Flow Routing when the link communication cost is a convex function of link data rate. Furthermore, we find it useful to introduce a new metric
On the Distance Entropy of a Data Collection Network
"... We study the communication cost of collecting correlated data at a sink over a network. To do so, we introduce Distance Entropy, an intrinsic quantity that characterizes the data gathering limit of networked sources. We demonstrate that, for any network embedded with any set of sources and a cost fu ..."
Abstract
 Add to MetaCart
We study the communication cost of collecting correlated data at a sink over a network. To do so, we introduce Distance Entropy, an intrinsic quantity that characterizes the data gathering limit of networked sources. We demonstrate that, for any network embedded with any set of sources and a cost function [cost]=[data rate] ¢ [link weight], distance entropy is a lower bound on the optimal communication cost. This is true for the most general data collection schemes that allow arbitrary routing and coding operations, including network coding and source coding. This lower bound can be matched using optimal rate SlepianWolf encoding plus shortest path routing. For more general communication cost functions, we show that the optimal scheme among schemes using SlepianWolf codes is also optimal over all of the possible schemes. Our results imply that for collecting data from correlated sources at a single sink, Network Coding does not help in the sense of lowering the optimal communication cost. We then extend our results to the case that includes broadcast links in the network. We show that the same optimal cost holds even if we allow broadcasting. In other words, neither broadcasting nor Network Coding improves the total cost of collecting data from correlated sources at a single sink.