Taming the underlying challenges of reliable multihop routing in sensor networks

By Alec Woo, Terence Tong, David E. Culler. ACM International Conference on Embedded Networked Sensor Systems, 2003

1,841 citations recorded by the source corpus.

The dynamic and lossy nature of wireless communication poses major challenges to reliable, self-organizing multihop networks. These non-ideal characteristics are more problematic with the primitive, low-power radio transceivers found in sensor networks, and raise new issues that routing protocols must address. Link connectivity statistics should be captured dynamically through an efficient yet adaptive link estimator and routing decisions should exploit such connectivity statistics to achieve reliability. Link status and routing information must be maintained in a neighborhood table with constant space regardless of cell density. We study and evaluate link estimator, neighborhood table management, and reliable routing protocol techniques. We focus on a many-to-one, periodic data collection workload. We narrow the design space through evaluations on large-scale, high-level simulations to 50-node, in-depth empirical experiments. The most effective solution uses a simple time averaged EWMA estimator, frequency based table management, and cost-based routing.

Subfields: Computer Networks and Communications

View Paper: https://www.semanticscholar.org/paper/bf6515f80fc5df7bc9bd3cfedc29e3ea90d48248

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

Citations in the corpus

Machine Learning in Wireless Sensor Networks: Algorithms, Strategies, and Applications (2014, methodology): “Experiments reveal that up to three times improvement in data delivery rate over basic MintRoute method can be achieved.”
A wireless sensor network for structural health monitoring: performance and experience (2005, positive): “For this, Wisden leverages the parent selection and tree construction module from the software prototype BLAST [11] 2.”
Comparison of routing metrics for static multi-hop wireless networks (2004, background): “[28] examines the interaction of link quality and”
Sensor network security: a survey (2009, methodology): “2) Multi-Path Routing: Some approaches use multi-path routing and neighbor collaboration techniques, such as [100], [101].”
Measurement-based models of delivery and interference in static wireless networks (2006, methodology): “[20] uses measurements to construct link quality estimators in sensor networks.”
Mitigating congestion in wireless sensor networks (2004, background): “examine routing in sensor networks [25], studying link estimation and neighborhood table management in particular.”
Four-Bit Wireless Link Estimation (2007, background): “We present a link estimator design with these interfaces that reduces packet delivery costs by up to 44% over current approaches and maintains a 99% delivery ratio over large, multihop testbeds.”
Design of an application-cooperative management system for wireless sensor networks (2005, methodology): “These link quality estimates are then used to form a tree that minimizes the expected number of transmissions necessary to forward a message to the root [5].”
FireWxNet: a multi-tiered portable wireless system for monitoring weather conditions in wildland fire environments (2006, background): “Algorithms that function on link or route quality such as [4, 21] would be more appropriate for such situations where interference causes short duration asymmetries, and are an aspect of our future work.”
Joint mobility and routing for lifetime elongation in wireless sensor networks (2005, neutral): “, MintRoute [29]) apply a table-driven scheme.”
Multipath Routing in Wireless Sensor Networks: Survey and Research Challenges (2012, background): “However, according to the experimental results provided in [9], probability of successful data transmission over low-power wireless links highly depends on the sender-receiver distance and interference power of the receiver.”
Models and solutions for radio irregularity in wireless sensor networks (2006, methodology): “MODELING RADIO IRREGULARITY As we have shown in our experiments as well as demonstrated in other research results [Ganesan et al. 2002; Woo et al. 2003; Zhao and Govindan 2003; Cerpa et al. 2003], radio irregularity is a common phenomenon in wireless sensor networks.”
ATPC: adaptive transmission power control for wireless sensor networks (2006, neutral): “In [10] [40], the authors extensively study communication reality in a large scale sensor network.”