Geographic routing without location information
Proceedings of the 9th annual international conference on Mobile computing and networking
The flooding time synchronization protocol
SenSys '04 Proceedings of the 2nd international conference on Embedded networked sensor systems
Topology control meets SINR: the scheduling complexity of arbitrary topologies
Proceedings of the 7th ACM international symposium on Mobile ad hoc networking and computing
The worst-case capacity of wireless sensor networks
Proceedings of the 6th international conference on Information processing in sensor networks
Proceedings of the 8th ACM international symposium on Mobile ad hoc networking and computing
Local broadcasting in the physical interference model
Proceedings of the fifth international workshop on Foundations of mobile computing
Minimum-latency aggregation scheduling in multihop wireless networks
Proceedings of the tenth ACM international symposium on Mobile ad hoc networking and computing
An improved approximation algorithm for data aggregation in multi-hop wireless sensor networks
Proceedings of the 2nd ACM international workshop on Foundations of wireless ad hoc and sensor networking and computing
Algorithmic models for sensor networks
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
Minimum data aggregation time problem in wireless sensor networks
MSN'05 Proceedings of the First international conference on Mobile Ad-hoc and Sensor Networks
Minimum latency data aggregation in the physical interference model
Proceedings of the 14th ACM international conference on Modeling, analysis and simulation of wireless and mobile systems
Wireless connectivity and capacity
Proceedings of the twenty-third annual ACM-SIAM symposium on Discrete Algorithms
Distributed connectivity of wireless networks
PODC '12 Proceedings of the 2012 ACM symposium on Principles of distributed computing
Deterministic distributed data aggregation under the SINR model
TAMC'12 Proceedings of the 9th Annual international conference on Theory and Applications of Models of Computation
Minimum latency aggregation scheduling for arbitrary tree topologies under the SINR model
ADHOC-NOW'12 Proceedings of the 11th international conference on Ad-hoc, Mobile, and Wireless Networks
Distributed multiple-message broadcast in wireless ad-hoc networks under the SINR model
SIROCCO'12 Proceedings of the 19th international conference on Structural Information and Communication Complexity
Minimum latency data aggregation in the physical interference model
Computer Communications
Connectivity and aggregation in multihop wireless networks
Proceedings of the 2013 ACM symposium on Principles of distributed computing
Improved minimum latency aggregation scheduling in wireless sensor networks under the SINR model
International Journal of Sensor Networks
IEEE/ACM Transactions on Networking (TON)
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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 global-scale 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(log3n) 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 [9]. We prove the correctness and efficiency of our algorithms, and conduct empirical studies under realistic settings to validate our analytical results.