Capacity of Arbitrary Wireless Networks

Goussevskaia, Olga; Wattenhofer, Roger; Halldórsson, Magnús M.; Welzl, Emo

doi:10.1109/infcom.2009.5062108

Cited by 216 publications

(244 citation statements)

References 18 publications

Supporting

Mentioning

239

Contrasting

Order By: Relevance

“…The nodes are uniformly randomly distributed in Uniform topologies, and are distributed with the Poisson distribution in Poisson topologies. In Cluster topologies [9], n C cluster centers are uniformly randomly located in the square and n nC nodes are uniformly randomly distributed within the disk of radius r C centered at each cluster center. We use the same settings as in [9], n C = 10 and r C = 20, in our experiments.…”

Section: Empirical Studymentioning

confidence: 99%

“…In Cluster topologies [9], n C cluster centers are uniformly randomly located in the square and n nC nodes are uniformly randomly distributed within the disk of radius r C centered at each cluster center. We use the same settings as in [9], n C = 10 and r C = 20, in our experiments. We set N 0 to the same constant value 0.1 as in [11] (which nevertheless would not affect the aggregation latency).…”

Section: Empirical Studymentioning

confidence: 99%

See 1 more Smart Citation

Minimum-latency aggregation scheduling in wireless sensor networks under physical interference model

Hua

et al. 2010

Proceedings of the 13th ACM International Conference on Modeling, Analysis, and Simulation of Wireless and Mobile Systems

View full text Add to dashboard Cite

Abstract-Minimum-Latency Aggregation Scheduling (MLAS)is a problem of fundamental importance in wireless sensor networks. There however has been very little effort spent on designing algorithms to achieve sufficiently fast data aggregation under the physical interference model which is a more realistic model than traditional protocol interference model. In particular, a distributed solution to the problem under the physical interference model is challenging because of the need for globalscale information to compute the cumulative interference at any individual node. In this paper, we propose a distributed algorithm that solves the MLAS problem under the physical interference model in networks of arbitrary topology in O(K) time slots, where K is the logarithm of the ratio between the lengths of the longest and shortest links in the network. We also give a centralized algorithm to serve as a benchmark for comparison purposes, which aggregates data from all sources in O(log 3 (n)) time slots (where n is the total number of nodes). This is the current best algorithm for the problem in the literature. The distributed algorithm partitions the network into cells according to the value K, thus obviating the need for global information. The centralized algorithm strategically combines our aggregation tree construction algorithm with the non-linear power assignment strategy in [13]. We prove the correctness and efficiency of our algorithms, and conduct empirical studies under realistic settings to validate our analytical results.

show abstract

Section: Empirical Studymentioning

confidence: 99%

Section: Empirical Studymentioning

confidence: 99%

Minimum-latency aggregation scheduling in wireless sensor networks under physical interference model

Hua

et al. 2010

Proceedings of the 13th ACM International Conference on Modeling, Analysis, and Simulation of Wireless and Mobile Systems

View full text Add to dashboard Cite

show abstract

“…We then try to add more links greedily without destroying the SINR threshold constraint ( Equation (1) ); • apply Algorithm 1 in [15] to find a feasible solution £2 which is a subset of E;…”

Section: B Compare Algorithm 4 With Compressive Schedulingmentioning

confidence: 99%

“…Obviously, it can be arbitrarily larger than 19(L). Most recently, Goussevskaia et ale [15] propose an algorithm which has a constant approximation guarantee. Unfortunately, their method [15] works correctly only if the background noise is o.…”

Section: B Link Scheduling Under the Physical Interference Modelmentioning

confidence: 99%

Efficient data aggregation in multi-hop wireless sensor networks under physical interference model

Wang

et al. 2009

2009 IEEE 6th International Conference on Mobile Adhoc and Sensor Systems

View full text Add to dashboard Cite

Abstract-Efficient aggregation of data collected by sensors is crucial for a successful application of wireless sensor networks (WSNs). Both minimizing the energy cost and reducing the time duration (or called latency) of data aggregation have been extensively studied for WSNs. Algorithms with theoretical performance guarantees are only known under the protocol interference model, or graph-based interference models generally. In this paper, we study the problem of designing time efficient aggregation algorithm under the physical interference model. To the best of our knowledge, no algorithms with theoretical performance guarantees are known for this problem in the literature. We propose an efficient algorithm that produces a data aggregation tree and a collision-free aggregation schedule. We theoretically prove that the latency of our aggregation schedule is bounded by O(R+~) time-slots. Here R is the network radius and~is the maximum node degree in the communication graph of the original network. In addition, we derive the lower-bound of latency for any aggregation scheduling algorithm under the physical interference model. We show that the latency achieved by our algorithm asymptotically matches the lower-bound for random wireless networks. Our extensive simulation results corroborate our theoretical analysis.

show abstract

“…Second, although there are some approximated algorithms for either the MLSAT problem or the general minimum length link scheduling problem (Goussevskaia et al, 2009), all their approximation ratios are obtained with the assumption of no power control. So it seems necessary to study approximation algorithms under power control.…”

Section: Discussionmentioning

confidence: 99%

Joint Link Scheduling and Topology Control for Wireless Sensor Networks with SINR Constraints

Hua

Lau

Handbook of Research on Developments and Trends in Wireless Sensor Networks

View full text Add to dashboard Cite

This chapter studies the joint link scheduling and topology control problems in wireless sensor networks. Given arbitrarily located sensor nodes on a plane, the task is to schedule all the wireless links (each representing a wireless transmission) between adjacent sensors using a minimum number of timeslots. There are two requirements for these problems: first, all the links must satisfy a certain property, such as that the wireless links form a data gathering tree towards the sink node; second, all the links simultaneously scheduled in the same timeslot must satisfy the SINR constraints. This chapter focuses on various scheduling algorithms for both arbitrarily constructed link topologies and the data gathering tree topology. We also discuss possible research directions.

show abstract

Capacity of Arbitrary Wireless Networks

Cited by 216 publications

References 18 publications

Minimum-latency aggregation scheduling in wireless sensor networks under physical interference model

Minimum-latency aggregation scheduling in wireless sensor networks under physical interference model

Efficient data aggregation in multi-hop wireless sensor networks under physical interference model

Joint Link Scheduling and Topology Control for Wireless Sensor Networks with SINR Constraints

Contact Info

Product

Resources

About