Mobile data offloading

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Mobile data offloading is the use of complementary network technologies for delivering data originally targeted for cellular networks. Offloading reduces the amount of data being carried on the cellular bands, freeing bandwidth for other users. It is also used in situations where local cell reception may be poor, allowing the user to connect via wired services with better connectivity.

Rules triggering the mobile offloading action can be set by either an end-user (mobile subscriber) or an operator.[1] The code operating on the rules resides in an end-user device, in a server, or is divided between the two. End users do data offloading for data service cost control and the availability of higher bandwidth. The main complementary network technologies used for mobile data offloading are Wi-Fi, femtocell and Integrated Mobile Broadcast. It is predicted[by whom?] that mobile data offloading will become a new industry segment due to the surge of mobile data traffic.[2][timeframe?]

Mobile data surge[edit]

Increasing need for offloading solutions is caused by the explosion of Internet data traffic, especially the growing portion of traffic going through mobile networks. This has been enabled by smartphone devices possessing Wi-Fi capabilities together with large screens and different Internet applications, from browsers to video and audio streaming applications. In addition to smart phones, laptops with 3G access capabilities are also seen as a major source of mobile data traffic. Additionally, Wi-Fi is typically much less costly to build than cellular networks.[3] It has been estimated that the total Internet traffic would pass 235.7 Exabytes per month in 2021, up from 73.1 Exabytes per month in 2016.[4] Annual growth rate of 50% is expected to continue and it will keep out phasing the respected revenue growth.[5][6][timeframe?]

Alternatives[edit]

Wi-Fi and femtocell technologies are the primary offload technologies used by the industry.[7] In addition, WiMax[8] and terrestrial networks (LAN)[9] are also candidates for offloading of 3G mobile data. Femtocells use standard cellular radio technologies, thus any mobile device is capable of participating in the data offloading process, though some modification is needed to accommodate the different backhaul connection.[7] On the other hand, cellular radio technologies are founded on the ability to do network planning within licensed spectrum. Hence, it may turn out to be difficult, both technically and business wise, to mass deploy femtocell access points. Self-Organizing Network (SON)[10] is an emerging technology for tackling unplanned femtocell deployment (among other applications). Wi-Fi technology is different radio technology than cellular, but most Internet capable mobile devices now come with Wi-Fi capability. There are already millions of installed Wi-Fi networks mainly in congested areas such as airports, hotels and city centers and the number is growing rapidly.[11] Wi-Fi networks are very fragmented but recently there have been efforts to consolidate them. The consolidation of Wi-Fi networks is proceeding both through a community approach, Fon as the prime example, and by the consolidation of Wi-Fi network operators.[12][timeframe?]

Wi-Fi[edit]

Wi-Fi offloading is an emerging business domain with multiple companies entering to the market with proprietary solutions. As standardization has focused on degree of coupling between the cellular and Wi-Fi networks, the competing solutions can be classified based on the minimum needed level of network interworking. Besides standardization, research communities have been exploring more open and programmable design in order to fix the deployment dilemma. [13] [14] [15] A further classification criterion is the initiator of the offloading procedure.

Cellular and Wi-Fi network interworking[edit]

Depending on the services to be offloaded and the business model there may be a need for interworking standardization. Standardization efforts have focused on specifying tightly or loose coupling between the cellular and the Wi-Fi networks, especially in a network-controlled manner.[16] 3GPP based Enhanced Generic Access Network ()[17] architecture applies tight coupling as it specifies rerouting of cellular network signaling through Wi-Fi access networks. Wi-Fi is considered to be a non-3GPP WLAN radio access network (RAN).[18] 3GPP has also specified an alternative loosely coupled solution for Wi-Fi. The approach is called Interworking Wireless LAN (IWLAN)[19] architecture and it is a solution to transfer IP data between a mobile device and operator’s core network through a Wi-Fi access. In the IWLAN architecture, a mobile device opens a VPN/IPsec tunnel from the device to the dedicated IWLAN server in the operator’s core network to provide the user either an access to the operator’s walled-garden services or to a gateway to the public Internet. With loose coupling between the networks the only integration and interworking point is the common authentication architecture.[timeframe?]

The most straightforward way to offload data to the Wi-Fi networks is to have a direct connection to the public Internet. This no coupling alternative omits the need for interworking standardization. For majority of the web traffic there is no added value to route the data through the operator core network. In this case the offloading can simply be carried out by switching the IP traffic to use the Wi-Fi connection in mobile client instead of the cellular data connection. In this approach the two networks are in practice totally separated and network selection is done by a client application. Studies show that significant amount of data can be offloaded in this manner to Wi-Fi networks even when users are mobile.[20][21][timeframe?] [22]

However, offloading does not always mean reduction of resource consumption (required system capacity) in the network of the operator. Under certain conditions and due to an increase of the burstiness of the non-offloaded traffic (i.e. traffic that eventually reaches the network of the operator in a regular way), the amount of network resources to offer a given level of QoS is increased.[23] In this context, the distribution of offloading periods turns out to be the main design parameter to deploy effective offloading strategies in the network of MNOs making non-offloaded traffic less heavy-tailed, hence reducing the resources needed in the network of the operator.[timeframe?]. The energy consumption in offloading is also another concern.[24]

Initiation of offloading procedure[edit]

There are three main initiation schemes: WLAN scanning initiation, user initiation and remotely managed initiation. In the WLAN scanning-based initiation the user device periodically performs WLAN scanning. When a known or an open Wi-Fi network is found, an offloading procedure is initiated. In the user-initiated mode, a user is prompted to select which network technology is used. This happens usually once per a network access session. In the remotely managed approach, a network server initiates each offloading procedure by prompting the connection manager of a specific user device. Operator-managed is a subclass of the remotely managed approach. In the operator-managed approach, the operator is monitoring its network load and user behavior. In the case of forthcoming network congestion, the operator initiates the offloading procedure.

ANDSF[edit]

Access network discovery and selection function (ANDSF) is the most complete 3GPP approach to date[25] for controlling offloading between 3GPP and non-3GPP access networks (such as Wi-Fi). The purpose of the ANDSF is to assist user devices to discover access networks in their vicinity and to provide rules (policies) to prioritize and manage connections to all networks.[timeframe?]

ATSSS[edit]

3GPP has started to standardize the Access Traffic Steering, Switching & Splitting (ATSSS) function to enable 5G devices to use different types of access networks, including Wi-Fi. The ATSSS service leverages the Multipath TCP protocol to enable 5G devices to simultaneously utilize different access networks. Experience with the utilisation of Multipath TCP on iPhones has shown that the ability to simultanesouly use Wi-Fi and cellular was key to provide support seamless handovers. The first version of the ATSSS specification leverages the 0-rtt convert protocol developed within the IETF. A prototype implementation of this service has been demonstrated in August 2019.

Operating system connection manager[edit]

Many operating systems provide a connection manager that can automatically switch to Wi-Fi network if the connection manager detects a known Wi-Fi network. Such functionality can be found from most modern operating systems (for example from all Windows versions beginning from XP SP3, Ubuntu, Nokia N900, Android and Apple iPhone). The connection managers use various heuristics to detect the best performing network connections. These include performing DNS requests for known names over the newly activated network interfaces, sending queries to specific servers, ... When both the Wi-Fi and the cellular interfaces are activate, Android smartphones will usually prefer the Wi-Fi one since it is usually unmetered. When such a smartphone decides to switch from one interface to another, all the active TCP connections need to be reestablished.

Multipath TCP solves this handover problem in a clean way. With Multipath TCP, TCP connections can use both the Wi-Fi interface and the cellular one during the handover.[26] This means that ongoing TCP connections are not stopped when the smartphone decides to switch from one network to another. As of January 2020, Multipath TCP is natively supported on iPhones, but less frequently used on Android smartphones except in South Korea. On iPhones since iOS9, the Wi-Fi Assist subsystem monitors the quality of the underlying network connection. If the quality drops below a given threshold, Wi-Fi Assist may decide to move established Multipath TCP connections to another interface. Initially, this feature was used for the Siri application. Since iOS12, any [Multipath TCP] enabled application can benefit from this feature. Since iOS13, Apple Maps and Apple Music can also be offloaded from Wi-Fi to cellular and vice versa without any interruption.

Opportunistic offloading[edit]

With the increasing availability[when?] of inter-device networks (e.g. Bluetooth or WifiDirect) there is also the possibility of offloading delay tolerant data to the ad hoc network layer. In this case, the delay tolerant data is sent to only a subset of data receivers via the 3G network, with the rest forwarded between devices in the ad hoc layer in a multi-hop fashion. As a result, the traffic on the cellular network is reduced, or gets shifted to inter-device networks.[27][timeframe?][28]

See also[edit]

References[edit]

  1. ^ https://ieeexplore.ieee.org/document/8014290
  2. ^ Perez Sarah (February 11, 2010). "Mobile data traffic surge: 40 exabytes by 2014". Read Write web blog. Archived from the original on August 29, 2011. Retrieved August 25, 2011. CS1 maint: discouraged parameter (link)
  3. ^ "Seamless Wi-Fi Offload: A business opportunity today," white paper from Hetting Consulting (Aptilo Networks release)
  4. ^ Cisco 2021 Forecast Highlights[1]
  5. ^ Warrior Padmasree, CTO Cisco "Keynote speech in CTIA 2010"
  6. ^ Cisco Visual Networking Index: Global Mobile Data Traffic Forecast Update, 2009–2014; Cisco 2010
  7. ^ a b Scherzer Shimon "Femtocell vs. Wi-Fi for Data Offloading & Indoor Coverage" [2] Archived 2010-05-23 at the Wayback Machine
  8. ^ Robb Henshaw "The Role of WiMAX in Enabling Wi-Fi Data Offload Networks"[3]
  9. ^ Netsnapper
  10. ^ NokiaSiemensNetworks "Self-Organizing Network (SON) Introducing the Nokia Siemens Networks SON Suite – an efficient, future-proof platform for SON" [4]
  11. ^ ABI Research "ABI Research Forecasts Wi-Fi Access Point Shipments to Exceed 70 Million by 2010" [5] Archived 2011-07-11 at the Wayback Machine
  12. ^ "More Than 12 Million AT&T, Starbucks Customers to Get Free Wi-Fi Access for a Rich In-Store Experience". Att.com (Press release). AT&T Intellectual Property. 2008-02-11. Retrieved 2014-07-05. AT&T Inc. (NYSE:T) and Starbucks (NASDAQ:SBUX) today announced plans to deliver AT&T Wi-FiSM service at more than 7,000 company-operated Starbucks locations across the United States. CS1 maint: discouraged parameter (link)
  13. ^ X. Kang et. al ``Mobile Data Offloading Through A Third-Party WiFi Access Point: An Operator's Perspective, in IEEE Transactions on Wireless Communications, vol. 13, no. 10, pp. 5340-5351, Oct. 2014.
  14. ^ J. Cho, et al., SMORE: Software-defined Networking Mobile Offloading Architecture Proc. ACM SIGCOMM AllThingsCellular 2014
  15. ^ A. Y. Ding, et al., Vision: Augmenting WiFi Offloading with An Open-source Collaborative Platform Proc. ACM MobiCom MCS 2015
  16. ^ Jouni Korhonen, et al. Toward Network Controlled IP Traffic Offloading IEEE Communications Magazine, Volume 51, Issue 3, p.96 - 102 (2013)
  17. ^ 3GPP TR 43.902
  18. ^ 3GPP TS 23.402
  19. ^ 3GPP TS 23.234
  20. ^ Aruna Balasubramanian, Ratul Mahajan, Arun Venkataramani. Augmenting Mobile 3G using WiFi Proc. MobiSys 2010
  21. ^ Kyunghan Lee, Joohyun Lee, Yung Yi, Injong Rhee and Song Chong. Mobile Data Offloading: How Much Can WiFi Deliver? Proc. CoNEXT 2010
  22. ^ Dimatteo, Savio; Hui, Pan; Han, Bo; Li, Victor O.K. (2011). Cellular Traffic Offloading through WiFi Networks. IEEE 8th International Conference on Mobile Adhoc and Sensor Systems (MASS). p. 192. CiteSeerX 10.1.1.378.5023. doi:10.1109/MASS.2011.26. ISBN 978-1-4577-1345-3.
  23. ^ A. Krendzel, M. Portolés, J. Mangues, Modeling Network Traffic in Mobile Networks Implementing Offloading, in proceedings of the 14th ACM MSWIM-2011, November 2011, USA
  24. ^ Aaron Yi Ding, Bo Han, et al. Enabling Energy-Aware Collaborative Mobile Data Offloading for Smartphones Proc. IEEE SECON 2013
  25. ^ 3GPP TS 23.402
  26. ^ Paasch, Christoph; Detal, Gregory; Duchene, Fabien; Raiciu, Costin; Bonaventure, Olivier (2012). Exploring mobile/WiFi handover with multipath TCP. ACM SIGCOMM workshop on Cellular Networks (Cellnet'12). p. 31. doi:10.1145/2342468.2342476. ISBN 9781450314756.
  27. ^ Patrick Baier, Frank Dürr and Kurt Rothermel. TOMP: Opportunistic Traffic Offloading Using Movement Predictions Proc. LCN 2012
  28. ^ Han, Bo; Hui, Pan; Kumar, V.S. Anil; Marathe, Madhav V.; Shao, Jianhua; Srinivasan, Aravind (May 2012). "Mobile data offloading through opportunistic communications and social participation". IEEE Transactions on Mobile Computing. 11 (5): 821. CiteSeerX 10.1.1.224.8056. doi:10.1109/TMC.2011.101.

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