Conference PaperPDF Available

Assisted network discovery for next generation wireless networks

Authors:

Abstract and Figures

IEEE 802.11 networks are the most popular option to have wireless access to the Internet. The popularity of these networks have raised a costly topology discovery and connection process, in which any device has to pass through an expensive scanning process of available Access Points. In order to improve the connection process, we propose a novel architecture for asynchronous assistance for topology discovery. We discuss the role of a Topology Manager that uses computational intelligence for generating optimal scanning sequences. Preliminary results show that this approach results in 30% to 70% improvements on AP discovery rate in chaotic deployments.
Content may be subject to copyright.
Assisted network discovery for next generation
wireless networks
Andr´
es Arcia-Moret, Arjuna Sathiaseelan, Antonio Araujo, Jos´
e Aguilar, Laudin Molina§
Computer Laboratory, University of Cambridge, Cambridge, UK
Centro Nacional de Desarrollo e Investigaci´
on en Tecnolog´
ıas Libres, M´
erida, Venezuela
Universidad de Los Andes, M´
erida, Venezuela
§Institut Telecom / Telecom Bretagne, Universit´
e Europ´
eene de Bretagne, Rennes, France
Email: {andres.arcia, arjuna.sathiaseelan}@cl.cam.ac.uk, aaraujo@cenditel.gob.ve, aguilar@ula.ve, laudin.molina@telecom-bretagne.eu
Abstract—IEEE 802.11 networks are the most popular option
to have wireless access to the Internet. The popularity of these
networks have raised a costly topology discovery and connection
process, in which any device has to pass through an expensive
scanning process of available Access Points. In order to improve
the connection process, we propose a novel architecture for
asynchronous assistance for topology discovery. We discuss the
role of a Topology Manager that uses computational intelligence
for generating optimal scanning sequences. Preliminary results
show that this approach results in 30% to 70% improvements
on AP discovery rate in chaotic deployments.
I. INTRODUCTION
Today, IEEE 802.11 networks are the first option to have
ubiquitous and low-cost wireless access to the Internet [1].
We count on millions of Wi-Fi devices in many different
new and challenging contexts: Community Networks, Sensor
Networks, Internet of Things, and personal computers in Home
Networks. In any of these scenarios, there has been a dramatic
increase on the number of devices requiring to connect to Wi-
Fi Access Points (AP). In order to connect to the wireless
access network, a device must scan its surrounding and find
an appropriate AP. However, the scanning process generally
embedded in mobile and desktop devices follow simple and
greedy sequential scanning.
In Wi-Fi spontaneous deployments, people chaotically de-
ploy APs. Nomadic users may also be able to access thousands
of community APs belonging to the same direct provider, or
have access to virtual service providers such as PAWS1. In
both cases a user has to pass through a scanning process,
being the most expensive sub-process within the discovery of
the wireless topology. In this respect, the discovery process is
becoming iterative and time consuming in dense deployments.
Recently, we have observed in [2] that in a regular discovery
process, the device has to scan multiple times to discover
available APs in a densely-covered urban area. World-wide
trends show that this is likely to be a regular case in the near
future2.
The current suboptimal behaviour of the scanning algo-
rithm is present in the vast majority of devices, significantly
consuming energy and impacting network performance [3].
It is also well-known that the full scanning is a default
scanning strategy implemented on mobile devices, and that
1http://www.cl.cam.ac.uk/ as2330/paws.html
2https://wigle.net/
the role of the scanning process represents about 80% of the
handover time. So, an efficient scanning will not only represent
an improvement on aggregated control traffic reduction for
public Wi-Fi access [3], but also could be an alternative for
load-balancing. The scanning traffic is becoming a potential
problem lowering the speed of the network and frequently
interrupting regular transmissions. This is mostly because of
the increasing number of devices using WiFi and congestion
induced by non-adapted scanning process [2].
Scanning process in 802.11 networks. The scanning is
the first sub-process for a client willing to attach to an IEEE
802.11 network, in which the interface looks for available APs
for later associate to them. Although the ultimate goal of a
scanning is to find all available APs to which the station might
be able to join, it is very costly in terms of aggregated number
of beacons and energy consumption at the client. To discover
all APs, i.e., the topology within an area, the device should be
properly adjusted with a pair of timers, that mainly determine
the efficiency of the discovery process [4]. As there are 11
channels and 2 timers per channel, there is a high number
of possibilities for timer configuration, i.e., 22 configurable
timers in total. Adapting these timers could depend not only on
the topology, but also on the application requirements. As the
computational complexity of finding an appropriate scanning
sequence increases, we propose the use of a computational
intelligent technique for improving the scanning process.
Using computational intelligence for assisting Wi-Fi
scanning. We propose a Topology Manager that uses a com-
putational intelligence (CI) technique to calculate efficient
scanning sequences that improve the Wi-Fi discovery process.
As suggested in [2], in future community Wi-Fi deployments,
these central entities or topology managers can help wireless
clients in the decision process for efficiently connecting to a
dense Wi-Fi network, and they could also serve for coarse
content or service indication by means of the 802.11u access
network query protocol.
II. A TOPOLOGY MANAGE R FO R IEEE 802.11
NE TWORKS
A Topology Manager (TM) conveniently hosted by the
wireless service provider, could opportunistically assist mobile
users to better discover and control a crowded wireless network
topology. It could also help mobile users to determine link
quality and best possible connection allowing improved access
to the network. As we have observed, within a single scanning,
a subset of the available APs are discovered, and usually, a
client does not have time to scan multiple times [2]. However,
an intelligent TM compute up-to-date and customized efficient
sequences, thus giving a more precise view of the topology.
The main advantage of this approach is that it allow clients
saving time during the expensive discovery process.
Topology
Manager
raw scan
Topology
aproximate topology
feeder
partial vision
regular client
Intelligent
Algorithm
ecient scan
required topology
local interface
external interface
yet another partial vision
optional message
intelligent sequence
F
C
Smart
Sequences
DB
raw
topology
model
Figure 1. Architecture for the Next Generation Wireless
In order to update the vision of the topology on the TM, we
rely upon two roles for participants. Firstly, new users would
act as feeders, as they push their vision of the topology from
time to time with a simple posts of their partial vision of the
network on the TM (through regular suboptimal scannings).
This update could be pushed through the IEEE 802.11u amend-
ment also known as Access Network Query Protocol (ANQP).
ANQP allows clients to query or to pass information to the TM
behind designated APs and before authentication. Moreover,
a client could use specific messages for finding out about a
specific mobile operator whose network is accessible through
the designated AP. Secondly, regular clients (RC) correspond
to those feeders that have already contributed enough to the
vision of the topology and that the TM has promoted to
RC. Hence, RCs looking for a candidate AP could retrieve
efficient sequences with special queries to the TM who, in
turn, asynchronously interacts with an intelligent algorithm.
Specific use-cases in which an RC benefits from this scheme,
correspond to handovers or when looking for a good candidate
AP. As shown in Fig. 1, a simple round trip between the RC
and the TM, or even by retrieving the appropriate scanning
sequence through an alternative interface (e.g., 3G), could
save several hundred of milliseconds through the increased
efficiency of the scanning.
Finally, Fig. 2 shows the comparison of various improved
sequences obtained from the TM. The discovery performance
was obtained from an emulated 802.11 spontaneously deployed
topology of about 2.5km and 1600 APs. Dots over the baseline
(within the dark grey area) show improved discovery rates
Ch1 Ch2 Ch3 Ch4 Ch5 Ch6 Ch7 Ch8 Ch9 Ch10 Ch11
Channels
0
0.1
0.2
0.3
rate (AP/s)
Baseline Sequence Rates
Efficient Sequence Rates
Figure 2. Comparison rates for the Cultural Algorithm efficient sequences
in APs per time unit, announced by the TM, and based on
data collected by a mobile client. Originally, the algorithm
residing at the TM, was fed with suboptimal sequences and
afterwards, an algorithm using computational intelligence de-
rived a variety of sequences. All sequences have considerably
higher discovery rate compared to the reference. Moreover,
delay improvements range from 30% to 70% with respect to
the reference.
III. CONCLUSION AND FUTURE WORK
In this work we have shown that the scanning process can
be significantly improved in chaotic Wi-Fi deployments by
using assisted network discovery. We have presented the design
of a Topology Manager and discussed the interaction with
mobile users, and we have shown the benefits for improving the
discovery process. Firstly, we propose different roles for users
contributing to build a vision of the chaotic Wi-Fi deployment.
Secondly, we propose the use of computational intelligence
to asynchronously calculate scanning sequences for improving
the overall discovery process.
ACKNOWLEDGMENT
The research leading to these results has received funding
from the European Union's (EU) Horizon 2020 research and
innovation programme under grant agreement No. 644663.
Action full title: architectuRe for an Internet For Everybody,
Action Acronym: RIFE. We would also like to thank Juan M.
Tirado for comments on an earlier draft.
REFERENCES
[1] J. Saldana, A. Arcia-Moret, B. Braem, E. Pietrosemoli, A. Sathiaseelan,
and M. Zennaro, “Alternative Network Deployments. Taxonomy, charac-
terization, technologies and architectures.” Internet Draft, GAIA - IETF,
July 2015.
[2] A. Arcia-Moret, L. Molina, N. Montavont, G. Castignani, and A. Blanc,
“Access Point Discovery in 802.11 Networks,” in IEEE WD, 2014.
[3] X. Hu, L. Song, D. V. Bruggen, and A. Striegel, “Is there wifi
yet? how aggressive wifi probe requests deteriorate energy and
throughput,” CoRR, vol. abs/1502.01222, 2015. [Online]. Available:
http://arxiv.org/abs/1502.01222
[4] G. Castignani, A. Arcia, and N. Montavont, “A study of the discovery
process in 802.11 networks,” SIGMOBILE Mob. Comput. Commun.
Rev., vol. 15, no. 1, pp. 25–36, Mar. 2011. [Online]. Available:
http://doi.acm.org/10.1145/1978622.1978626
... The core of the application is composed of helping modules that support the vcell calculation, namely the GPS location (for providing the ground truth), Wi-Fi scanning module and path approximation algorithm (to adjust the geo-position based on existent maps). From a user's perspective, a mobile can collect the surrounding WLAN topology to interact conveniently with a central service (e.g., a Topology Manager, see [19], [20] for further information). ...
... In our particular case, the scanning function can be conveniently and continuously invoked (and with different invocation frequencies) to obtain different perspectives of the surrounding topology. Since the full-scaning time varies on every mobile device, we suppose a central service that helps to build vcells (we discuss a similar service in [19], [20]). ...
... As we have mentioned in Section I, such a technique can be used during an initial topology recognition process to bootstrap the vcell database. Later on, this database can be regularly updated with incremental contributions of users (as in [20] Bloom filter assisted device location discovery. Two requirements are justifying this component: (1) simplicity in the implementation of a location discovery service, and (2) a CPU and energy efficient search of a fingerprint in the vcell database. ...
... In a recent paper [9], a novel approach based on multiobjective optimization approach to obtain the optimal number of channels to scan was developed. The optimal channel scanning sequence and its correspondent scanning timers including M inChannelT ime and M axChannelT ime are used as optimization parameters. ...
... where the constraints expressed in Eq.11 -13 are the boundary values for the scanning timers as used in [9]. This formulation presented in Eq.10 is a combinatorial problem of nonlinear objective and constraint functions. ...
... The core of the application is composed of helping modules that support the vcell calculation, namely the GPS location (for providing the ground truth), Wi-Fi scanning module and path approximation algorithm (to adjust the geo-position based on existent maps). From a user's perspective, a mobile can collect the surrounding WLAN topology to interact conveniently with a central service (e.g., a Topology Manager, see [19], [20] for further information). ...
... In our particular case, the scanning function can be conveniently and continuously invoked (and with different invocation frequencies) to obtain different perspectives of the surrounding topology. Since the full-scaning time varies on every mobile device, we suppose a central service that helps to build vcells (we discuss a similar service in [19], [20]). ...
Article
Full-text available
The success of Wi-Fi technology as an efficient and low-cost last-mile access solution has enabled massive spontaneous deployments generating storms of beacons all across the globe. Emerging location systems are using these beacons to observe mobility patterns of people through portable or wearable devices and offers promising use-cases that can help to solve critical problems in the developing world. In this paper, we design and develop a novel prototype to organise these spontaneous deployments of Access Points into what we call virtual cells (vcells). We compute virtual cells from a list of Access Points collected from different active scans for a geographical region. We argue that virtual cells can be encoded using Bloom filters to implement the location process. Lastly, we present two illustrative use-cases to showcase the suitability and challenges of the technique.
... Additionally, there are some proposals [19]- [21] that investigate the performance of IEEE 802.11 device discovery phase. However, they do not provide a mathematical model that separately captures the energy consumption of 802.11 protocol in the discovery phase. ...
... The trade-off between the scanning latency, the failure rate and the discovery rate has been optimized. Recently, in [2], the authors use a computational intelligence techniques to obtain the optimal scanning channel sequences. They characterized the trade-off between handover latency and discovery rate in Community Network(Wi-Fi) deployments. ...
Conference Paper
In IEEE 802.11 Wireless Local Area Network (WLAN), the mobile stations (STAs) have to perform handover to keep network connections when they move out of the range of an access point (AP). However, the STAs collect the information of surrounding APs by channel scanning, which will cause high handover latency and degrade the quality of mobility. Therefore, minimizing the scanning delay is key to enabling seamless communications over WLAN. In this paper, we propose a genetic algorithm (GA) algorithm combined with neighbor list mechanism to reduce handover latency. Using this proposed approach, the handover latency is minimized by reducing both the number of scanned channels and the waiting time for each channel. Simulation results demonstrate that our approach improves throughput up to 9.5% and reduces handover delay up to 74% compared to standard IEEE 802.11.
... The neighbor discovery process is extended for the oneway asynchronous discovery algorithm to a two-way asynchronous discovery algorithm. [78] Optimization of scanning sequences ...
Article
Full-text available
Device-to-Device (D2D) communication has emerged as a promising technology for optimizing spectral efficiency in future cellular networks. D2D takes advantage of the proximity of communicating devices for efficient utilization of available resources, improving data rates, reducing latency and increasing system capacity. The research community is actively investigating the D2D paradigm to realize its full potential and enable its smooth integration into the future cellular system architecture. Existing surveys on this paradigm largely focus on interference and resource management. We review recently proposed solutions in over explored and under explored areas in D2D. These solutions include protocols, algorithms, and architectures in D2D. Furthermore, we provide new insights on open issues in these areas. Finally, we discuss potential future research directions.
... However, we consider that a discussion in that direction is outside the scope of this paper, since we assume that the regulator has enough resources to provide backhaul connectivity, sufficient computational resources (i.e., in the cloud) and, legal, human expertise to process spectrum measurements. An example of how intensive computation for improved usage of the spectrum can be found in [1], we expose in detail the architectural role of an authoritative entity and an estimation of the required computational resources. ...
Conference Paper
TV White Spaces have recently been proposed as an alternative to alleviate the spectrum crunch, characterised by the need to reallocate frequency bands to accommodate the ever-growing demand for wireless communications. In this paper, we discuss the motivations and challenges for collecting spectrum measurements in developing regions and discuss a scalable system for communities to gather and provide access to White Spaces information through open and regionalised repositories. We further discuss two relevant aspects. First, we propose a cooperative mechanism for sensing spectrum availability using a detector approach. Second, we propose a strategy (and an architecture) on the database side to implement spectrum governance. Other aspects of the work include discussion of an extensive measurement campaign showing a number of white spaces in developing regions, an overview of our experience on low-cost spectrum analysers, and the architecture of Zebra − RFO, an application for processing crowd-sourced spectrum data. CCS Concepts • Computer systems organization → n-tier architectures;
... However, we consider that a discussion in that direction is outside the scope of this paper, since we assume that the regulator has enough resources to provide backhaul connectivity, sufficient computational resources (i.e., in the cloud) and, legal, human expertise to process spectrum measurements. An example of how intensive computation for improved usage of the spectrum can be found in [1], we expose in detail the architectural role of an authoritative entity and an estimation of the required computational resources. ...
Article
Full-text available
TV White Spaces have recently been proposed as an alternative to alleviate the spectrum crunch, characterised by the need to reallocate frequency bands to accommodate the ever-growing demand for wireless communications. In this paper, we discuss the motivations and challenges for collecting spectrum measurements in developing regions and discuss a scalable system for communities to gather and provide access to White Spaces information through open and regionalised repositories. We further discuss two relevant aspects. First, we propose a cooperative mechanism for sensing spectrum availability using a detector approach. Second, we propose a strategy (and an architecture) on the database side to implement spectrum governance. Other aspects of the work include discussion of an extensive measurement campaign showing a number of white spaces in developing regions, an overview of our experience on low-cost spectrum analysers, and the architecture of zebra-rfo, an application for processing crowd-sourced spectrum data.
... However, we consider that a discussion in that direction is outside the scope of this paper, since we assume that the regulator has enough resources to provide backhaul connectivity, sufficient computational resources (i.e., in the cloud) and, legal, human expertise to process spectrum measurements. An example of how intensive computation for improved usage of the spectrum can be found in [1], we expose in detail the architectural role of an authoritative entity and an estimation of the required computational resources. ...
Conference Paper
Full-text available
TV White Spaces have recently been proposed as an alternative to alleviate the spectrum crunch, characterised by the need to reallocate frequency bands to accommodate the ever-growing demand for wireless communications. In this article, we discuss the motivations and challenges for collecting spectrum measurements in developing regions and discuss a scalable system for the crowds to gather and provide access to White Spaces information through open and regionalised repositories. We further discuss two relevant aspects. Firstly, we propose a cooperative mechanism for sensing spectrum availability using a detector approach. Secondly, we propose a strategy (and an architecture) on the database side to implement spectrum governance. Other aspects of the work include discussion of an extensive measurement campaign showing a number of white spaces in developing regions, an overview of our experience on low-cost spectrum analysers, and the architecture of Zebra−RFO, an application for processing crowd-sourced spectrum data.
Research
Full-text available
This document presents a taxonomy of a set of "Alternative Network Deployments" that emerged in the last decade with the aim of bringing Internet connectivity to people or providing a local communication infrastructure to serve various complementary needs and objectives. hey employ architectures and topologies different from those of mainstream networks and rely on alternative governance and business models. The document also surveys the technologies deployed in these networks, and their differing architectural characteristics, including a set of definitions and shared properties. The classification considers models such as Community Networks, Wireless Internet Service Providers (WISPs), networks owned by individuals but leased out to network operators who use them as a low-cost medium to reach the underserved population, networks that provide connectivity by sharing wireless resources of the users, and rural utility cooperatives.
Article
Full-text available
This paper analyzes the scanning process in IEEE 802.11 networks in an urban setting characterized by a high Access Point (AP) density. Most of these APs belong to a community network, known as a collection of APs announcing the same network name (Service Set Identifier or SSID). The owner of an AP can optionally configure the community network of his/her AP, resulting in an irregular topology for each community network as there is no central planning authority. We investigate the relationship between the time spent in each channel while scanning for available APs and the number of AP actually detected. In particular we show that, in order to discover all available APs at a given location, we need to combine the results of multiple scans. Based on this result we argue that the efficiency of the scanning process could be greatly improved by using a database shared by all the users of a community network, containing the available APs at different locations.
Article
Full-text available
WiFi offloading has emerged as a key component of cellular operator strategy to meet the data needs of rich, mobile devices. As such, mobile devices tend to aggressively seek out WiFi in order to provide improved user Quality of Experience (QoE) and cellular capacity relief. For home and work environments, aggressive WiFi scans can significantly improve the speed on which mobile nodes join the WiFi network. Unfortunately, the same aggressive behavior that excels in the home environment incurs considerable side effects across crowded wireless environments. In this paper, we show through empirical studies at both large (stadium) and small (laboratory) scales how aggressive WiFi scans can have significant implications for energy and throughput, both for the mobile nodes scanning and other nearby mobile nodes. We close with several thoughts on the disjoint incentives for properly balancing WiFi discovery speed and ultra-dense network interactions.
Conference Paper
Wi-Fi based localization has proven to be a compelling alternative to GPS for mobile devices. But Wi-Fi scanning consumes a large amount of energy on smartphones because they perform full scans, i.e. all the channels in their band(s) are visited. This inefficient behavior greatly reduces battery life, raising the threshold for user acceptance. We propose a novel, incremental approach that reduces the energy consumption of Wi-Fi localization by scanning just a few selected channels. We evaluate our incremental scanning approach on eight Android devices using traces from five test subjects. Our results show that, compared to full scans, incremental scanning can reduce the energy consumption between 20.64% and 57.79%. The modern smartphones included in our study all show an energy reduction of at least 40%.
Conference Paper
Universal access to Internet is crucial. Several initiatives have recently emerged to enable wider access to the Internet. Public Access WiFi Service (PAWS) enables free Internet access to all and is based on Lowest Cost Denominator Networking (LCDNet) -- a set of network techniques that enable users to share their home broadband network with the public. LCDNet takes advantage of the available unused capacity in home broadband networks and allows Less-than-Best Effort (LBE) access to these resources. LCDNet can enable third-party stakeholders, such as local governments, to setup, configure and operate home networks for public Internet access in cooperation with Internet Service Providers. Software-defined networking (SDN) creates new opportunities for the remote configuration and management of such networks at large scale. In this paper, we present Virtual Public Networks (VPuN), home networks created, deployed and managed through an evolutionary SDN control abstraction. This offers more flexibility to users and network operators, allowing them to share and control the network, while providing opportunities for new stakeholders to emerge as virtual network operators.
Conference Paper
In this paper, we study the IEEE 802.11 discovery process needed for handovers and propose an adaptive scanning strategy based on application requirements. The scanning process consists in actively probing the radio channels to gather access points information. We consider a well decoupled situation in which the scanning latency, the scanning failure rate and the number of discovered access points define the scanning performance. We model these scanning metrics by analytical expressions to represent the performance trade-off, i.e., finding the largest number of access points with a minimum latency. We present a novel approach based on a multi-objective optimization approach to obtain the optimal number of channels to scan, the optimal channel sequence and its correspondent scanning timers. Finally, we compare one fixed and two adaptive scanning approaches by means of simulations. We show that our adaptive scanning strategies better manage the performance trade-off and allow different application profiles to match with specific scanning latency.
Article
Information-centric networking has been attracting increasing attention within the networking community. Technological solutions as well as entire architectures have been proposed with subtle but seemingly important differences. In this article, we define a set of design tenets for an information-centric architecture together with a demonstration of its feasibility. For the latter, we present an early prototype of an artifact that is directly based on our design framework. This prototype is available under open source, deployed in a European-wide testbed, and can be used for Planetlab-scale experiments. Early indications of its performance show promising results for our future work.
Article
The vision of Internet of Things calls for connectivity not only to consumer electronics and home appliances, but also to small battery powered devices which cannot be recharged. Such small devices, often various types of sensors and actuators, are required to sustain reliable operation for years on batteries even in the presence of heavy interference. The IEEE 802.11 standard has established itself as one of the most popular wireless technologies offering connectivity. Using commercially available chips, we demonstrate the feasibility of low-power Wi-Fi technology to enable IP connectivity of battery powered devices. Three typical sensor application scenarios are investigated. We evaluate the power consumption of Wi-Fi enabled devices for each of the scenarios, investigate the impact of interference, and measure the range performance.