Minimum Latency Aggregation Scheduling for Arbitrary Tree Topologies under the SINR Model

Wang, Guanyu; Hua, Qiang-Sheng; Wang, Yuexuan

doi:10.1007/978-3-642-31638-8_11

Cited by 6 publications

(2 citation statements)

References 17 publications

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“…With respect to the first aspect, most works explicitly force parent nodes to only transmit after they have received the transmission from all their designated children [12], [16], while other works use the same restriction implicitly [1], [16]. On the second aspect, to the best of our knowledge, all previous algorithms decide first about aggregation tree, and later about the node's transmission time/schedule.…”

Section: Related Workmentioning

confidence: 97%

On the application of pipelining in aggregation convergecast scheduling

Souza

Nikolaidis

2013

2013 IEEE 14th International Symposium on "A World of Wireless, Mobile and Multimedia Networks" (WoWMoM)

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We consider the problem of scheduling wireless transmissions in a sensor network to perform aggregation convergecast. In contrast to studies that attempt to shorten the schedule for completing a single data collection cycle, we aim to increase the frequency at which updates are collected (higher throughput). To achieve higher throughput, we use a form of pipelined concurrent collection of multiple data snapshots through the network. To attain high performance pipelining, we "expand" the time in which precedence constraints need to be satisfied such that they span over multiple schedule cycles. Our approach involves the unconventional approach of constructing the schedule before finalizing the exact form of the precedence constraints, i.e., before determining the data aggregation tree, which in turn requires that the schedule construction phase guarantees that every node can reach the sink. We compare our results using pipelining against a previously proposed algorithm that also uses pipelining, as well as against an algorithm that, although lacking pipelining, exhibits the ability to produce very short schedules. The results confirm the potential to achieve a substantial throughput increase at the cost of increased latency.

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Section: Related Workmentioning

confidence: 97%

On the application of pipelining in aggregation convergecast scheduling

Souza

Nikolaidis

2013

2013 IEEE 14th International Symposium on "A World of Wireless, Mobile and Multimedia Networks" (WoWMoM)

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“…We consider three relevant aspects for the purpose of comparison with the current work: the relaxation of precedence constraints; the sequence (order of steps) to obtain a solution (node scheduling first, aggregation tree later); and the use of pipelining. With respect to the first aspect, most works explicitly force parent nodes to only transmit after they have received the transmission from all their designated children [9], while other works use the same restriction implicitly [12,13]. On the second aspect, to the best of our knowledge, with the exception of our earlier work [1], no previous algorithms decide first about the node's transmission time/schedule and later about the aggregation tree.…”

Section: Related Workmentioning

confidence: 99%

Increasing Aggregation Convergecast Data Collection Frequency through Pipelining

Souza

Nikolaidis

2018

Wireless Communications and Mobile Computing

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We consider the problem of increasing the data collection frequency of aggregation convergecast. Previous studies attempt to increase the data collection frequency by shortening the completion of a single data collection cycle. We aim at increasing the frequency at which data collection updates are collected by the use of pipelining and, consequently, increasing the overall data collection frequency and throughput. To achieve this, we overlap the propagation schedule of multiple data snapshots within the same overall schedule cycle, thus increasing parallelism through pipelining. Consequently, the effective data collection time of an individual snapshot may span over multiple, successive, schedule cycles. To this end, we modify the aggregation convergecast model, decoupling schedule length, and data collection delay, by relaxing its precedence constraints. Our solution for this new problem involves the unconventional approach of constructing the schedule before finalizing the exact form of the data aggregation tree, which, in turn, requires that the schedule construction phase guarantees that every node can reach the sink. We compare our results using snapshot pipelining against a previously proposed algorithm that also uses a form of pipelining, as well as against an algorithm that though lacking pipelining, exhibits the ability to produce very short schedules. The results confirm the potential to achieve a substantial throughput increase, at the cost of some increase in latency.

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