The DOI matches its Crossref record.
Exploiting heterogeneity in sensor networks
Abstract
The presence of heterogeneous nodes (i.e., nodes with an enhanced energy capacity or communication capability) in a sensor network is known to increase network reliability and lifetime. However, questions of where how many, and what types of heterogeneous resources to deploy remain largely unexplored. We focus on energy and link heterogeneity in ad hoc sensor networks and consider resource-aware MAC and routing protocols to utilize those resources. Using analysis, simulation, and real testbed measurements, we evaluate the impact of number and placement of heterogeneous resources on performance in networks of different sizes and densities. While we prove that optimal deployment is very hard in general, we also show that only a modest number of reliable, long-range backhaul links and line-powered nodes are required to have a significant impact. Properly deployed, heterogeneity can triple the average delivery rate and provide a 5-fold increase in the lifetime (respectively) of a large batten-powered network of simple sensors.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Krishnamurthy, L., Adler, R., Buonadonna, P., Chhabra, J., Flanigan, M., Kushalnagar, N., Nachman, L., & Yarvis, M. (2005) · Proceedings of the 3rd international conference on Embedded networked sensor systems · doi:10.1145/1098918.1098926 · Cited by 317
Self-citationA Survey of Middleware for Sensor and Network Virtualization
Khalid, Z., Fisal, N., & Rozaini, M. (2014) · Sensors · doi:10.3390/s141224046 · Cited by 36
Metadata
- Authors
- Yarvis, M., Kushafnagar, N., Singh, H., Rangarajan, A., Lin, Y., & Singh, S.
- Venue
- Proceedings IEEE 24th Annual Joint Conference of the IEEE Computer and Communications Societies.
- Publisher
- IEEE
- Published
- 2005-08-24
- Volume
- 2
- Pages
- 878-890
- OpenAlex
- W1733162348
- Cited by
- 491
- References
- 0
- FWCI
- 25.60
- Type
- conference paper
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Exploiting heterogeneity in sensor networks. https://app.cochat.ai/papers/10.1109/infcom.2005.1498318
- The paper
- Yarvis, M., Kushafnagar, N., Singh, H., Rangarajan, A., Lin, Y., & Singh, S. (2005). Exploiting heterogeneity in sensor networks. Proceedings IEEE 24th Annual Joint Conference of the IEEE Computer and Communications Societies. https://doi.org/10.1109/infcom.2005.1498318
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
