Name
Title | ||
|---|---|---|
Modeling and designing efficient data aggregation in wireless sensor networks under entropy and energy bounds |
Abstract | ||
|---|---|---|
Sensor networks are characterized by limited energy, processing power, and bandwidth capabilities. These limitations become
particularly critical in the case of event-based sensor networks where multiple collocated nodes are likely to notify the
sink about the same event, at almost the same time. The propagation of redundant highly correlated data is costly in terms
of system performance, and results in energy depletion, network overloading, and congestion. Data aggregation is considered
to be an effective technique to reduce energy consumption and prevent congestion in wireless sensor networks. In this paper,
we derive a number of important insights concerning the data aggregation process, which have not been discussed in the literature
so far. We first estimate the conditions under which aggregation is a costly process in comparison to a non aggregation approach,
by considering a realistic scenario where the processing costs related to aggregation of data are not neglected. We also consider
that aggregation should preserve the integrity of data, and therefore, the entropy of the correlated data sent by sources
can be considered in order to both decrease the amount of redundant data forwarded to the sink and perform an overall lossless
process. We also derive the cumulative and the probability distribution functions of the delay in an aggregator node queue,
which can be used to relate the delay to the amount of aggregation being considered. The framework we present in this paper
serves to investigate the tradeoff between the increase in data aggregation required to reduce energy consumption, and the
need to maximize information integrity, while also understanding how aggregation impacts the network propagation delay of
a data packet. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1007/s10776-009-0107-z | IJWIN |
Keywords | Field | DocType |
wireless sensor networksdata aggregation � entropyenergy consumptiondelay,system performance,wireless sensor network,data aggregation,cumulant,information integration,probability distribution function,propagation delay,sensor network | Key distribution in wireless sensor networks,Propagation delay,Computer science,Queue,Network packet,Computer network,Real-time computing,Probability distribution,Wireless sensor network,Energy consumption,Data aggregator | Journal |
Volume | Issue | ISSN |
16 | 3 | 1572-8129 |
Citations | PageRank | References |
9 | 0.74 | 17 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| L. Galluccio | 1 | 562 | 56.09 |
| Sergio Palazzo | 2 | 835 | 85.49 |
| Andrew T. Campbell | 3 | 8958 | 759.66 |