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	Booktitle = {17th IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks (IEEE WoWMoM 2016)},
	Year = {2016},
	Location = {Coimbra, Portugal},
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	Note = {accepted for publication},
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	Pages = {254--256},
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	keywords={IEEE standards;carrier sense multiple access;packet radio networks;standardisation;telecommunication standards;wireless LAN;CSMA/CA;DCF;IEEE 802.11 distributed coordination function;IEEE 802.11 protocol;MAC;analytical model;binary slotted exponential backoff;carrier sense multiple access;collision avoidance;ideal channel conditions;medium access control;packet transmission;performance analysis;standardization;terminals;threshold;throughput performance evaluation;wireless local area networks;Access protocols;Analytical models;Collision avoidance;Media Access Protocol;Multiaccess communication;Performance analysis;Physical layer;Throughput;Wireless LAN;Wireless application protocol}, 
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		doi = {10.1145/1282427.1282424},
		acmid = {1282424},
		publisher = {ACM},
		address = {New York, NY, USA},
		keywords = {802.11, RF interference, SINR, channel hopping, jamming},
}
@misc{Gartner,
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},
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}
@misc{wifialliance,
	author={WiFi Alliance},
	title={WiFi Alliance News Release},
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	author={}, 
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		publisher = {USENIX Association},
		address = {Berkeley, CA, USA},
	} 

@inproceedings{Suresh,
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} 

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	publisher = {USENIX Association},
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@INPROCEEDINGS{SCIFI, 
	author={H. Balbi and N. Fernandes and F. Souza and R. Carrano and C. Albuquerque and D. Muchaluat-Saade and L. Magalhaes}, 
	booktitle={2012 Global Information Infrastructure and Networking Symposium (GIIS)}, 
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	year={2012}, 
	volume={}, 
	number={}, 
	pages={1-7}, 
	keywords={channel allocation;communication complexity;interference (signal);packet radio networks;public domain software;radio spectrum management;telecommunication control;wireless LAN;aggregate performance;central controllers;centralized channel allocation algorithm;controlled access points;infrastructured IEEE 802.11 networks;interference;low complexity algorithm;low cost devices;low cost equipment;managed access points;network administrators;open source software;operating channels;packet transmission;unmanaged networks;wireless environment;wireless networks;wireless spectrum;Channel allocation;Heuristic algorithms;IEEE 802.11 Standards;Interference;Proposals;Throughput;Wireless networks}, 
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}
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		year = 2011,
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		adsnote = {Provided by the SAO/NASA Astrophysics Data System}
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@inproceedings{raftio,
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	year = {2014},
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	ISBN = {0-521-64298-1},
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	pages = {112--115},
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	url = {http://doi.acm.org/10.1145/1164783.1164804},
	doi = {10.1145/1164783.1164804},
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	publisher = {ACM},
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	keywords = {Kalman filter, RSSI, attenuation, center of mass, trilateration},
} 
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}
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	pages={536--539},
	year={2004},
	organization={IEEE}
}


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} 
@misc{cisco_2009,
	title={Wireless LAN Controller (WLC) FAQ},
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	journal={Cisco},
	year={2009},
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	note={Accessed 21. January, 2018}
}
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	acmid = {63239},
	publisher = {ACM},
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} 

@INPROCEEDINGS{Basagni, 
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	booktitle={Parallel Architectures, Algorithms, and Networks, 1999. (I-SPAN '99) Proceedings. Fourth InternationalSymposium on}, 
	title={Distributed clustering for ad hoc networks}, 
	year={1999}, 
	volume={}, 
	number={}, 
	pages={310-315}, 
	keywords={computational complexity;parallel algorithms;ad hoc networks;distributed clustering;fully mobile network;hierarchical organization;mobile environment;network parameter;time complexity;Ad hoc networks;Clustering algorithms;Computer science;Electronic mail;Mobile computing;Network topology;Partitioning algorithms;Routing;Telecommunication network topology;Wireless networks}, 
	doi={10.1109/ISPAN.1999.778957}, 
	ISSN={1087-4089}, 
	month={},}

	@INPROCEEDINGS{Mamalis,
		author={D. Gavalas and G. Pantziou and C. Konstantopoulos and B. Mamalis}, 
		booktitle={2006 IEEE International Conference on Communications}, 
		title={Clustering of Mobile Ad Hoc Networks: An Adaptive Broadcast Period Approach}, 
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		ISSN={1550-3607}, 
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			doi = {10.1109/TPAMI.1979.4766909},
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			keywords = {Cluster, data partitions, multidimensional data analysis, parametric clustering, partitions, similarity measure},
		} 
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	url = {http://dx.doi.org/10.1007/s10115-008-0150-6},
	doi = {10.1007/s10115-008-0150-6},
	acmid = {1554491},
	publisher = {Springer-Verlag New York, Inc.},
	address = {New York, NY, USA},
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} 

@Inbook{Coates2012,
	author="Coates, Adam
		and Ng, Andrew Y.",
	editor="Montavon, Gr{\'e}goire
		and Orr, Genevi{\`e}ve B.
		and M{\"u}ller, Klaus-Robert",
	title="Learning Feature Representations with K-Means",
	bookTitle="Neural Networks: Tricks of the Trade: Second Edition",
	year="2012",
	publisher="Springer Berlin Heidelberg",
	address="Berlin, Heidelberg",
	pages="561--580",
	abstract="Many algorithms are available to learn deep hierarchies of features from unlabeled data, especially images. In many cases, these algorithms involve multi-layered networks of features (e.g., neural networks) that are sometimes tricky to train and tune and are difficult to scale up to many machines effectively. Recently, it has been found that K-means clustering can be used as a fast alternative training method. The main advantage of this approach is that it is very fast and easily implemented at large scale. On the other hand, employing this method in practice is not completely trivial: K-means has several limitations, and care must be taken to combine the right ingredients to get the system to work well. This chapter will summarize recent results and technical tricks that are needed to make effective use of K-means clustering for learning large-scale representations of images. We will also connect these results to other well-known algorithms to make clear when K-means can be most useful and convey intuitions about its behavior that are useful for debugging and engineering new systems.",
	isbn="978-3-642-35289-8",
	doi="10.1007/978-3-642-35289-8_30",
	url="https://doi.org/10.1007/978-3-642-35289-8_30"
}

@ARTICLE{sloyd,
	author={S. Lloyd}, 
	journal={IEEE Transactions on Information Theory}, 
	title={Least squares quantization in PCM}, 
	year={1982}, 
	volume={28}, 
	number={2}, 
	pages={129-137}, 
	keywords={Least-squares approximation;PCM communication;Quantization (signal);Signal quantization}, 
	doi={10.1109/TIT.1982.1056489}, 
	ISSN={0018-9448}, 
	month={March},}


	@article{murtycluster,
		author = {Jain, A. K. and Murty, M. N. and Flynn, P. J.},
		title = {Data Clustering: A Review},
		journal = {ACM Comput. Surv.},
		issue_date = {Sept. 1999},
		volume = {31},
		number = {3},
		month = sep,
		year = {1999},
		issn = {0360-0300},
		pages = {264--323},
		numpages = {60},
		url = {http://doi.acm.org/10.1145/331499.331504},
		doi = {10.1145/331499.331504},
		acmid = {331504},
		publisher = {ACM},
		address = {New York, NY, USA},
		keywords = {cluster analysis, clustering applications, exploratory data analysis, incremental clustering, similarity indices, unsupervised learning},
	}