Wireless data traffic surged in the United States in 2023, with more than 100 trillion megabytes of data transferred over mobile networks that year. This was almost twice the volume consumed two years prior, with demand for data soaring amid the adoption of data intensive mobile activities.

suburban and rural areas.

Global revenue generated from 5G wireless network infrastructure is forecast to reach more than 19.12 billion U.S. dollars in 2021, with total wireless network infrastructure revenues expected to amount to 48.82 billion U.S. dollars.

number of users

USAID's Guest Wireless uses Xirrus equipment to provide a wireless network so that mobile device users can access a Dedicated Internet Network System (DINS). It serves as a follow-on to USAID wireless efforts implemented at AID/Washington (AID/W) and overseas missions, but with modifications to the design, function, and use. The solution maintains the business purpose, which is to allow authorized agency personnel and guests or partners to have wireless, controlled Internet access.

As of December 2023, 5G data traffic in South Korea was in excess of 878 petabytes. As the user numbers of 5G increased, the traffic amount also rose accordingly.

110 years-iTaiwan wireless network statistics of Kaohsiung City Government agencies (unit: MiB)

CSV dataset generated gathering data from a production wireless mesh community network. Data is gathered every 5 minutes during the interval 2021-04-13 00:00:00 to 2021-04-16 00:00:00. During the interval 2021-04-14 02:00:00 2021-04-14 17:50:00 (both included) there is the failure of a gateway in the mesh (nodeid 24).

Live mesh network monitoring link: http://dsg.ac.upc.edu/qmpsu

The dataset consists of single gzip compressed CSV file. The first line of the file is a header describing the features. The first column is a GMT timestamp of the sample in the format as "2021-03-16 00:00:00". The rest of the columns provide the comma-separated values of the features collected from each node in the corresponding capture.

A suffix with the nodeid is added to each feature. For instance, the feature having the number of processes of node with nodeid 24 is named as "processes-24". In total, 63 different nodes showed up during the samples, each being assigned a different nodeid.

Features are of two types: (i) absolute values, for instance, the CPU 1-minute load average, and (ii) counters that are monotonically increased, for instance the number of transmitted packets. We have converted counter-type kernel variables to rates, by dividing the difference between two consecutive samples, over the difference of the corresponding timestamps in seconds, as shown in the following pseudo-code:
feature.rate are columns computed from feature as
feature.rate <- (feature[2:n]-feature[1:(n-1)])/(epoch[2:n]-epoch[1:(n-1)])
feature.rate <- feature.rate[feature.rate >= 0] # discard samples where the counter is restarted
where n is the number of samples

features
- processes number of processes
- loadavg.m1 1 minute load average
- softirq.rate servicing softirqs
- iowait.rate waiting for I/O to complete
- intr.rate
- system.rate processes executing in kernel mode
- idle.rate twiddling thumbs
- user.rate normal processes executing in user mode
- irq.rate servicing interrupts
- ctxt.rate total number of context switches across all CPUs
- nice.rate niced processes executing in user mode
- nr_slab_unreclaimable The part of the Slab that can't be reclaimed under memory pressure
- nr_anon_pages anonymous memory pages
- swap_cache Memory that once was swapped out, is swapped back in but still also is in the swapfile
- page_tables Memory used to map between virtual and physical memory addresses
- swap
- eth.txe.rate tx errors over all ethernet interfaces
- eth.rxe.rate rx errors over all ethernet interfaces
- eth.txb.rate tx bytes over all ethernet interfaces
- eth.rxb.rate rx bytes over all ethernet interfaces
- eth.txp.rate tx packets over all ethernet interfaces
- eth.rxp.rate rx packets over all ethernet interfaces
- wifi.txe.rate tx errors over all wireless interfaces
- wifi.rxe.rate rx errors over all wireless interfaces
- wifi.txb.rate tx bytes over all wireless interfaces
- wifi.rxb.rate rx bytes over all wireless interfaces
- wifi.txp.rate tx packets over all wireless interfaces
- wifi.rxp.rate rx packets over all wireless interfaces
- txb.rate tx bytes over all ethernet and wifi interfaces
- txp.rate tx packets over all ethernet and wifi interfaces
- rxb.rate rx bytes over all ethernet and wifi interfaces
- rxp.rate rx packets over all ethernet and wifi interfaces
- sum.xb.rate tx+rx bytes over all ethernet and wifi interfaces
- sum.xp.rate tx+rx packets over all ethernet and wifi interfaces
- diff.xb.rate tx-rx bytes over all ethernet and wifi interfaces
- diff.xp.rate tx-rx packets over all ethernet and wifi interfaces

111 years-iTaiwan wireless network statistics of Kaohsiung City Government

features

The global demand for mobile data is set to skyrocket in the coming years, with monthly data traffic forecast to exceed *** exabytes by 2029. A range of factors are set to drive this explosion in data consumption, not least the widespread adoption of data intensive technologies such as artificial intelligence and the cloud. FWA bridges connectivity gaps Around a ***** of total mobile traffic at the end of the decade is set to come from fixed wireless access (FWA) connections. FWA involves the use of mobile networks to provide broadband internet to a fixed location, and has gained traction in areas underserved by traditional fixed infrastructure. When using 5G mobile networks, FWA services can rival traditional fixed broadband in both reliability and connection quality. A lack of 5G investment Although FWA has been posed as a means of bridging the global digital divide, a lack of 5G investment in several regions prevents it from being an effective solution in the near future. For example, 5G adoption in Sub-Saharan Africa remained below **** percent in 2023, reflecting ongoing challenges related to 5G affordability and availability.

Dataset generated gathering data from a production wireless mesh community network. During the data gathering an unprovoked gateway outage is produced. The dataset allows testing unsupervised machine learning methods.

This statistic shows the wireless network coverage by provider as share of the population in rural and non-rural areas in the United States in December 2017. In December 2017, AT&T's wireless network reached 99.6 percent of the U.S. population in non-rural areas compared to 91.7 percent in rural areas.

National Taiwan Library Wi-Fi (NTL) internet usage statistics

Basic Information:

Number of entries: 374,661 Number of features: 19 Data Types:

15 integer columns 3 float columns 1 object column (label) Column Names:

id, Time, Is_CH, who CH, Dist_To_CH, ADV_S, ADV_R, JOIN_S, JOIN_R, SCH_S, SCH_R, Rank, DATA_S, DATA_R, Data_Sent_To_BS, dist_CH_To_BS, send_code, Consumed Energy, label Explore the Dataset First Five Rows:

id Time Is_CH who CH Dist_To_CH ADV_S ADV_R JOIN_S JOIN_R SCH_S SCH_R Rank DATA_S DATA_R Data_Sent_To_BS dist_CH_To_BS send_code Consumed Energy label 0 101000 50 1 101000 0.00000 1 0 0 25 1 0 0 0 1200 48 0.00000 1 0.00000 Attack 1 101001 50 0 101044 75.32345 0 4 1 0 0 1 2 38 0 0 0.00000 1 0.09797 Normal 2 101002 50 0 101010 46.95453 0 4 1 0 0 1 19 41 0 0 0.00000 1 0.09797 Normal 3 101003 50 0 101044 64.85231 0 4 1 0 0 1 16 38 0 0 0.00000 1 0.09797 Normal 4 101004 50 0 101010 4.83341 0 4 1 0 0 1 0 41 0 0 0.00000 1 0.09797 Normal Missing Values: No missing values detected in the dataset.

Statistical Summary:

The dataset includes various features related to network operations such as Time, Is_CH, who CH, Dist_To_CH, and more. The target variable label contains categorical values such as "Attack" and "Normal". Analyze Class Distribution Let's analyze the distribution of the classes within the dataset.

python Copy code class_distribution = dataset['label'].value_counts() class_distribution Handle Class Imbalance If a class imbalance is identified, appropriate techniques such as undersampling, oversampling, or SMOTE (Synthetic Minority Over-sampling Technique) will be applied to balance the dataset.

Next Steps:

Identify the class distribution. Apply balancing techniques if necessary. Continue with data preprocessing and feature engineering. We will perform the class distribution analysis and balancing in the subsequent step. ​​

i have found some duplicate values and drop them dataset.duplicated().sum() dataset.drop_duplicates(inplace=True)

ChatGPT Duplicate Handling Initial Duplicate Count Duplicates found: 8,873 Action Taken Duplicates dropped: The dataset has been cleaned by removing all duplicate entries. Verification Duplicates after cleaning: 0 The dataset is now free of duplicate entries. We can proceed with the analysis of the class distribution and any necessary steps to handle class imbalance.

Analyze Class Distribution Let's analyze the distribution of the label column to understand the balance between the classes.

python Copy code class_distribution = dataset['label'].value_counts() class_distribution I'll compute this now. ​​

Class Distribution Analysis The distribution of the classes within the dataset is as follows:

Normal: 332,040 Grayhole: 13,909 Blackhole: 10,049 TDMA: 6,633 Flooding: 3,157 Observations There is a significant class imbalance, with the majority class being "Normal" (332,040 instances). Minority classes include "Grayhole", "Blackhole", "TDMA", and "Flooding".

NYC Wi-Fi Hotspot Locations Wi-Fi Providers: CityBridge, LLC (Free Beta): LinkNYC 1 gigabyte (GB), Free Wi-Fi Internet Kiosks Spot On Networks (Free) NYC HOUSING AUTHORITY (NYCHA) Properties Fiberless (Free): Wi-Fi access on Governors Island Free - up to 5 Mbps for users as the part of Governors Island Trust Governors Island Connectivity Challenge AT&T (Free): Wi-Fi access is free for all users at all times. Partners: In several parks, the NYC partner organizations provide publicly accessible Wi-Fi. Visit these parks to learn more information about their Wi-Fi service and how to connect. Cable (Limited-Free): In NYC Parks provided by NYC DoITT Cable television franchisees. ALTICEUSA previously known as “Cablevision” and SPECTRUM previously known as “Time Warner Cable” (Limited Free) Connect for 3 free 10 minute sessions every 30 days or purchase a 99 cent day pass through midnight. Wi-Fi service is free at all times to Cablevision’s Optimum Online and Time Warner Cable broadband subscribers. Wi-Fi Provider: Chelsea Wi-Fi (Free) Wi-Fi access is free for all users at all times. Chelsea Improvement Company has partnered with Google to provide Wi-Fi a free wireless Internet zone, a broadband region bounded by West 19th Street, Gansevoort Street, Eighth Avenue, and the High Line Park. Wi-Fi Provider: Downtown Brooklyn Wi-Fi (Free) The Downtown Brooklyn Partnership - the New York City Economic Development Corporation to provide Wi-Fi to the area bordered by Schermerhorn Street, Cadman Plaza West, Flatbush Avenue, and Tillary Street, along with select public spaces in the NYCHA Ingersoll and Whitman Houses. Wi-Fi Provider: Manhattan Downtown Alliance Wi-Fi (Free) Lower Manhattan Several public spaces all along Water Street, Front Street and the East River Esplanade south of Fulton Street and in several other locations throughout Lower Manhattan. Wi-Fi Provider: Harlem Wi-Fi (Free) The network will extend 95 city blocks, from 110th to 138th Streets between Frederick Douglass Boulevard and Madison Avenue is the free outdoor public wireless network. Wi-Fi Provider: Transit Wireless (Free) Wi-Fi Services in the New York City subway system is available in certain underground stations. For more information visit http://www.transitwireless.com/stations/. Wi-Fi Provider: Public Pay Telephone Franchisees (Free) Using existing payphone infrastructure, the City of New York has teamed up with private partners to provide free Wi-Fi service at public payphone kiosks across the five boroughs at no cost to taxpayers. Wi-Fi Provider: New York Public Library Using Wireless Internet Access (Wi-Fi): All Library locations offer free wireless access (Wi-Fi) in public areas at all times the libraries are open. Connecting to the Library's Wireless Network •You must have a computer or other device equipped with an 802.11b-compatible wireless card. •Using your computer's network utilities, look for the wireless network named "NYPL." •The "NYPL" wireless network does not require a password to connect. Limitations and Disclaimers Regarding Wireless Access •The Library's wireless network is not secure. Information sent from or to your laptop can be captured by anyone else with a wireless device and the appropriate software, within three hundred feet. •Library staff is not able to provide technical assistance and no guarantee can be provided that you will be able to make a wireless connection. •The Library assumes no responsibility for the safety of equipment or for laptop configurations, security, or data files resulting from connection to the Library's network

The telecommunications firm Verizon is the leading provider of mobile services in the United States, with a market share of nearly ** percent of wireless subscriptions as of the last quarter of 2024. T-Mobile and AT&T are the other major wireless carriers in the U.S. market.  The market share is based on subscription figures reported by the companies in quarterly earnings and financial statements. Mobile virtual network operator (MVNO) subscriptions were not considered for the statistic. Seismic shift: T-Mobile and Sprint Merger T-Mobile’s **** billion U.S. dollar acquisition of Sprint Corp. became official on 1st April 2020, a merger that temporarily reduced the number of major wireless providers in the United States. Under the terms of the merger, T-Mobile acquired Sprint’s ***** million postpaid subscribers, joining the 47 million T-Mobile postpaid wireless subscribers. DISH Network Corporation acquired Sprint’s prepaid mobile business, Boost Mobile, raising that number to ****, satisfying the United States Department of Justice (DOJ) that the market would remain competitive.  T-Mobile is the largest U.S. telco by market cap As of 2024, T-Mobile had a market capitalization of over *** billion U.S. dollars, the highest of any U.S. telecommunications company. Beijing-based China Mobile and U.S. giant Verizon trailed, with a market cap of *** and *** billion U.S. dollars, respectively. Comcast and AT&T were valued at *** and *** billion U.S. dollars, respectively.

The OpenMobileNetwork is a dataset for mobile networks and devices, which is semantically modeled using the Linked Data principles. It provides structured RDF data describing mobile networks, their topology and components (e.g., base stations, mobile devices or WiFi access points). Utilizing this dataset in combination with interlinked information that is present in the LOD Cloud, various applications can be realized that depend on mobile network and positioning data (e.g., Semantic Location-based Services or Power Management in Mobile Networks).

The Wireless Data Communication Market offers a wide range of products, including:Wireless Modems: Used to transmit and receive data signals over wireless networks.Routers: Connect multiple devices to a wireless network and facilitate data routing.Access Points: Provide wireless connectivity and extend the range of wireless networks.Antennas: Enhance the signal strength and range of wireless devices.Network Management Software: Monitor and manage wireless networks to ensure optimal performance. Recent developments include: November 2022 Nokia revealed intentions to lead the KOMSENS-6G initiative established by the German Ministry of Research and Education in November 2022. This research aims to broaden the reach of wireless networks, such as sensors in the 6G future, via both digital and physical routes., August 2022 AT&T stated in August 2022 that it would bring its Fiber Internet Connectivity to Arizona, with the service scheduled to be accessible to local users in 2023. The business intends to provide fiber-based internet rates of up to 5 Gigabits/sec for 100,000 residences near Mesa., February 2022 Verizon launched the extension of its broadband service in February 2022, enabling access to dependable, fast, simple-to-use wireless internet access across the country, encompassing more than thirty million homes and over two million enterprises.. Key drivers for this market are: Increasing demand for faster internet speeds. Potential restraints include: Need for real-time communication in industries such as healthcare, automotive, and logistics. Notable trends are: The rise of the Internet of Things (IoT) and smart homes has also contributed to the expansion.

This dataset includes the usage statistics of the County's free wireless network (ArlingtonWireless) hotspots since 2020. See usage over time here: https://data.arlingtonva.us/visualization/OutdoorWirelessStats