MABO-TSCH: Multihop and blacklist-based optimized time synchronized channel hopping

Transactions on Emerging Telecommunications Technologies

Volumn 29, Issue 7, 2018, Pages

  Gomes, Pedro Henrique ^a   Watteyne, Thomas ^b   Krishnamachari, Bhaskar ^a  

^a University of Southern California   (United States)

^b INRIA   (France)

Author keywords

[No Author keywords available]

Indexed keywords

SPECTROSCOPY;

CHANNEL QUALITY ESTIMATION; DIFFERENT PROTOCOLS; FREQUENCY HOPPING SPREAD SPECTRUM; INDUSTRIAL INTERNETS; MULTI-ARMED BANDIT PROBLEM; PACKET DELIVERY RATIO; RELIABLE COMMUNICATION; SEPARATE LEARNING;

FREQUENCY HOPPING;

EID: 85049685715     PISSN: 21615748     EISSN: 21613915     Source Type: Journal    
DOI: 10.1002/ett.3223     Document Type: Article

References (18)

1. Accenture. Driving Unconventional Growth through the Industrial Internet of Things; 2014.
2. 802.15.4-2015 - IEEE Standard for Low-Rate Wireless Personal Area Networks (WPANs); 2015.
3. Srinivasan K, Kazandjieva MA, Agarwal S, Levis P. The β-factor: measuring wireless link burstiness. Comput. 2008:29-41.
4. Sexton D, Mahony M, Lapinski M, Werb J. Radio channel quality in industrial wireless sensor networks. Paper presented at: 2005 Sensors for Industry Conference; 2005; Houston, TX, USA.
5. Watteyne T, Mehta A, Pister K. Reliability through frequency diversity: Why channel hopping makes sense. Paper presented at: ACM Symposium on Performance Evaluation of Wireless Ad Hoc, Sensor, and Ubiquitous Networks (PE-WASUN). ACM; 2009; Tenerife, Canary Islands, Spain.
6. Kohvakka M, Kuorilehto M. Performance analysis of IEEE 802.15.4 and ZigBee for large-scale wireless sensor network applications. ACM Symposium on Performance Evaluation of Wireless Ad Hoc, Sensor, and Ubiquitous Networks (PE-WASUN). ACM; 2006; Terromolinos, Spain.
7. Anastasi G, Conti M, Di FM. A comprehensive analysis of the MAC unreliability problem in IEEE 802.15.4 wireless sensor networks. IEEE Trans Ind Inform. 2011;7(1):52-65.
8. Baccour N, Koubâa A, Mottola L, et al. Radio link quality estimation in wireless sensor networks. ACM Trans Sens Netw. 2012;8(4):1-33.
9. Kuleshov V, Precup D. Algorithms for multi-armed bandit problems; CoRR 2014, abs/1402.6028.
10. Du P, Roussos G. Adaptive time slotted channel hopping for wireless sensor networks. Paper presented at: Computer Science and Electronic Engineering Conference (CEEC). IEEE; 2012; Colchester, UK.
11. Tavakoli R, Nabi M, Basten T, Goossens K. Enhanced time-slotted channel hopping in WSNs using non-intrusive channel-quality estimation. Paper presented at: International Conference on Mobile Ad Hoc and Sensor Systems (MASS). IEEE; 2015; Dallas, TX, USA.
12. Gai Y, Krishnamachari B. Distributed stochastic online learning policies for opportunistic spectrum access. IEEE Trans Signal Process. 2014;62(23):6184-6193.
13. Anandkumar A, Michael N, Tang A. Opportunistic spectrum access with multiple users: Learning under competition. Paper presented at: IEEE International Conference on Computer Communications (INFOCOM). IEEE; 2010; San Diego, CA, USA.
14. Liu K, Qing Z. Distributed learning in multi-armed bandit with multiple players. IEEE Trans Signal Process. 2010;58(11):5667-5681.
15. Welsh DJ, Powell MB. An upper bound for the chromatic number of a graph and its application to timetabling problems. Comput J. 1967;10(1):85-86.
16. Vermorel J, Mohri M. Multi-armed bandit algorithms and empirical evaluation. Paper presented at: European Conference on Machine Learning (ECML), chapter. Springer; 2005; Porto, Portugal.
17. Chen Y, Gomes PH, Krishnamachari B. Multichannel data collection for throughput maximization in wireless sensor networks. Paper presented at: IEEE International Conference on Mobile Ad hoc and Sensor Systems (MASS). IEEE; 2014; Philadelphia, PA, USA.
18. Watteyne T, Vilajosana X, Kerkez B, et al. openWSN: a Standards-based low-power wireless development environment. Trans Emerg Telecommun Technol. 2012;23(5):480-493.