✦ LIBER ✦

Minimum latency data aggregation in the physical interference model

✍ Scribed by An, Min Kyung; Lam, Nhat X.; Huynh, Dung T.; Nguyen, Trac N.

Book ID: 123035339
Publisher: Elsevier Science
Year: 2012
Tongue: English
Weight: 839 KB
Volume: 35
Category: Article
ISSN: 0140-3664
DOI: 10.1016/j.comcom.2012.08.015

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Latency-minimizing data aggregation in w

Latency-minimizing data aggregation in wireless sensor networks under physical interference model

✍ Li, Hongxing; Wu, Chuan; Hua, Qiang-Sheng; Lau, Francis C.M. 📂 Article 📅 2014 🏛 Elsevier Science 🌐 English ⚖ 956 KB

Approximation algorithms for minimum lat

Approximation algorithms for minimum latency data aggregation in wireless sensor networks with directional antenna

✍ Liu, Hui; Liu, Zewen; Li, Deying; Lu, Xianling; Du, Hongwei 📂 Article 📅 2013 🏛 Elsevier Science 🌐 English ⚖ 572 KB

Minimum Latency Broadcast in the SINR Mo

Minimum Latency Broadcast in the SINR Model: A Parallel Routing and Scheduling Approach

✍ Xiao, Shiliang; Pei, Jun; Chen, Xinwei; Wang, Wenbin 📂 Article 📅 2014 🏛 IEEE 🌐 English ⚖ 280 KB

Data aggregation in stochastic frontier

Data aggregation in stochastic frontier models: the closed skew normal distribution

✍ B. Wade Brorsen, Taeyoon Kim 📂 Article 📅 2012 🏛 Springer 🌐 English ⚖ 322 KB

Stable equivalent models with minimum ph

Stable equivalent models with minimum phase transfer functions in the dynamic aggregation of voltage regulators

✍ Eduardo J.S. Pires de Souza 📂 Article 📅 2011 🏛 Elsevier Science 🌐 English ⚖ 491 KB

Estimation of the maximum and minimum in

Estimation of the maximum and minimum in a model for bounded, dependent data

✍ Adam T. Martinsek 📂 Article 📅 2002 🏛 Elsevier Science 🌐 English ⚖ 140 KB

Estimation of the maximum and minimum is considered in a random coe cient autoregressive model for bounded data. Limiting distributions and conÿdence intervals are obtained, for nonrandom sample sizes and also for a stopping rule designed to achieve su cient precision of the estimates.