Methods of Interaction Between Multiprotocol Unit and Telematics Map

Cloud Service

Chuvatov Mikhail, Glazunov Vadim, Kurochkin Michail and Popov Serge

Telematics department, Saint-Petersburg State Polytechnic University, Saint-Petersburg, Russia, 195251

Keywords:

Multiprotocol Unit, Telematics Map, Cloud Service, Vehicle Wireless Network, Intellectual Conveying

System, Dynamic Routing Protocols.

Abstract:

Continuous access to the service from the moving vehicle improves safety and provides ecological compatibil-

ity of transport infrastructure functioning in big agglomerations conditions. The lack of the guaranteed signal

level of global and local networks requires new approaches to form the strategy for connection continuity pro-

vision. We offer the technology enabling to form the transport facility network by appealing multiprotocol unit

and telematics map. The method suggest using external data concerning global and local wireless networks

in each vehicle. The approach involves collecting networks data by means of the multiprotocol units, trans-

mitting of these data into cloud service of telematics map, the data generalisation and to meat the query about

available networks in the vehicles vicinity. The completely automatic technology of data control is designed

in such a way that it can provides external data for multiprotocol routing in integrated vehicle networks. In

order to check the suggested approach we performed experiments and dives the information system prototype

that demonstrated its efﬁciency. Technical feasibility of the information system was conﬁrmed during the

experiments.

1 INTRODUCTION

Evolution of the telecommunication components of

intelligent transport systems involves the continu-

ous bidirectional communication between the vehi-

cle and cloud services through V2V, V2I mecha-

nisms (Zaborovskiy et al., 2013; Zaborovski et al.,

2013). The stable connection at any point along the

route of the vehicle performs MPU (Cheng et al.,

2010; Ku et al., 2014), which supports the connec-

tion of the vehicle to multiple networks by different

technologies. While driving on the highway MPU an-

alyzes the current state of available wireless networks

and connects the vehicle to the best of them (Jaworski

et al., 2011).

The fundamental problem is the limited range of

available networks: the vehicle can get information

about available DSRC and Wi-Fi networks in the ra-

dius of 300 meters, but it is impossible to construct

a map with all the connectivity options along the en-

tire route, including the network 3G/4G (Gramaglia

et al., 2011; Remy et al., 2011). On the other hand

the presence of a complete list of telematic resources

located on the route of the vehicle, would eliminate

the costs of implementing local dynamic routing pro-

tocols that create multiple additional service trafﬁc

on the wireless network which negatively affects the

bandwidth (Glazunov et al., 2013).

An alternative to the local dynamic routing can

be external routing is based upon the cloud service

telematics map. Telematics map shows a set of

telematic resources in the region of the generalized

time (Glazunov et al., 2013; Zaborovsky et al., 2011).

In this case, telematics card is used as a repository of

data about the location and the network access point

parameters. Then the problem of data management

telematics map is in continuous data collection, pro-

cessing and transmission of data on telematics en-

vironment with geographic coordinates and time of

each vehicle is connected to the system. Continuous

interaction of a large number of mobile subscribers

generates a large amount of raw data that requires

adaptation algorithms for acquisition, processing and

transfer between users.

The solution is to develop an adaptive algorithm

interaction between multiprotocol unit and the telem-

atics map cloud service in order to minimize the vol-

ume of service trafﬁc and maximize the connection

time to the network.

161

Mikhail C., Vadim G., Michail K. and Serge P..

Methods of Interaction Between Multiprotocol Unit and Telematics Map Cloud Service.

DOI: 10.5220/0005491501610166

In Proceedings of the 1st International Conference on Vehicle Technology and Intelligent Transport Systems (VEHITS-2015), pages 161-166

ISBN: 978-989-758-109-0

 2015 SCITEPRESS (Science and Technology Publications, Lda.)

2 THE INTERACTION

ALGORITHM OF CLOUD

SERVICES BETWEEN

TELEMATICS MAP AND

MULTIPROTOCOL UNIT

Telematics map cloud service also ensures data ac-

cumulation about potential access points to the Inter-

net, which includes the signal level and access mode.

This can be used for various technologies such as

LTE, DSRC, stationary Wi–Fi, and vehicle MESH

network. Figure 1 shows part of the internal descrip-

tion of the telematics map and its interpretation on the

roads map.

Figure 1: Access points to telematics resources and their

geographic interpretation chart.

To solve this problem, telematics service provides

a set of low-level map management techniques to in-

sure bidirectional exchange depending on the hard-

ware and software features of the multiprotocol unit.

The main methods should include:

1. The primary data collection about:

• interfaces status of the telematics devices in the

vehicle;

• interfaces sharing;

• signal levels available in networks on each ve-

hicle interface during movement;

2. Data aggregation on the network environment in

a speciﬁc geographic location.

3. Response to query about telematics capabilities in

the geographic region.

The main technological challenge is to maintain

the service state of the relevance of telematics envi-

ronment data. The system provides to each vehicle

the continuous data collection and systematisation on

the network state in asynchronous mode.

Interaction multiprotocol unit vehicle and cloud

service consists of three stages:

• transmitting data about telematics environment

from the vehicle;

• aggregation of data about position and access time

from access points;

• data about the available networks back to board

the vehicle.

Interaction scheme between software modules in

a telematics map and multiprotocol unit is shown in

Figure 2.

Figure 2: Modules interaction between cloud service telem-

atics map and MPU.

Periodic polling of signal level of global and local

networks is carried out continuously on multiproto-

col unit. The frequency of the survey depends on the

speed of the vehicle. Data is written to a local ﬁle

on MPU and will be transferred to the cloud service

upon the occurrence of the right moment: for example

if there is a wide or free link to the cloud.

Generalisation of the transmitted data on the net-

work state on the cloud is performed in the module

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based on two criteria: the network availability and the

time-averaged signal level at the current point.

If necessary, each node (MPU) performs request

to the cloud service, transferring data on the parame-

ters of their technical means and the desired region to

obtain data on telematics environment.

Selection of available networks is based on net-

work’s spatiotemporal database query for each net-

work type with a vehicle’s predetermined region.

The interaction of the vehicle and the cloud ser-

vice for the data transmission about the available

telematics resources is performed via local or global

communications channels available on MPU.

Interaction algorithm between the vehicle and

cloud service is implemented by means of data col-

lection and evaluation about the network state.

Parts of the algorithm are distributed between

multiprotocol node modules and analysis query mod-

ule of the network status of cloud service. They pro-

vide dynamic frequencyselection survey of Wi-Fi and

LTE networks, depending on the speed. The ﬂowchart

is shown in Figure 3.

The proposed concept and interaction algorithms

are implemented in the layout of data collection and

processing of telematics environment.

3 IMPLEMENTATION OF

INTERACTION BETWEEN

MULTIPROTOCOL UNIT AND

TELEMATICS SERVICE MAP

Implementation of algorithms interaction between

multiprotocol node and cloud service is carried out

by technical means of hardware and software testbed

of multiprotocol nodes (Popov et al., 2014). For the

experiment testbed was assembled shown in Figure 3.

Multiprotocol node is equipped with a GPS BU–

355S4 receiver, built-in Wi–Fi AR9285 adapter of

802.11bgn standard and 4G M100–4 modem for data

transmission.

The functions of MPU include periodic status

query for Wi-Fi and LTE networks. Data are collected

into a local ﬁle, and then sent to the server via LTE

channel.

The functions of the server is to receive the data

ﬁle, placing the original data in the database, the im-

plementation of a selection query in view of geo-

graphical and temporal parameters and the response

to a multiprotocol unit request. To perform these

functions on MPU and server the application pack-

ages are used: the database server MySQL and com-

munication channel openvpn. Registration of Wi-Fi

Figure 3: Interaction modules cloud service telematic maps

with multiprotocol node.

parameters and GPS coordinates is carried out using

the program kismet, LTE registration is performed by

periodic calls of AT-command ”CSQ”. These pack-

ages function in the operating system Linux Debian

7.4 on both the server and the MPU.

Scheme of interaction testbed software is shown in

Figure 4. Initial values for the experiment are shown

in Table 1.

Frequency of coordinate obtaining from the GPS

receiver is limited to 2 Hz due to the implementation

constraints of the average receiver chip range. Be-

sides, the device driver operates at a speed 4800bit/s

through a local communications port.

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163

Figure 4: Hardware and software stand conﬁguration for the

experiment.

Table 1: Initial values for hardware and software environ-

ment.

Parameter Value

The path length, km 3,21

Coordinates source GPS

Data storage method In local ﬁle

Coordinates polling

rate, Hz

Wi-Fi polling rate, Hz 10

LTE polling rate, Hz 2

Trafﬁc type UDP

Channel type Tunnel over LTE

The advantage of the installed software is the

polling frequency of local and global networks does

not depend on the GPS devices polling frequency,

which enables to run these processes in different

threads of the operating system and improves the sig-

nal representation accuracy. Scheme of software in-

teraction to survey local and global networks on MPU

is shown in Figure 5.

Figure 5: Software interaction chart for scanning the local

and global wireless networks.

4 TESTING OF SCANNING

TECHNOLOGY FOR

WIRELESS NETWORKS

AVAILABLE FROM THE

VEHICLE

To verify the algorithm operability and data manage-

ment technology of telematics map, we’ve conducted

a series of ﬁeld experiments in the driving conditions

of the vehicle with different average speed in a real ra-

dio situation of a large city. Main goal of these experi-

ments was to demonstrate the operability of proposed

algorithm during collection, processing and transmis-

sion of data about global and local wireless networks

while driving the vehicle in city trafﬁc conditions. For

this purpose the multiprotocol unit prototype was in-

stalled on the vehicle which moves on predeﬁned ring

route. In motion, the multiprotocol unit collects data

with signal level of available global and local wireless

networks. Vehicle’s trajectory is shown on Figure 6.

Figure 6: Vehicle’s driving route.

Experiment, which shows the operability of the

data collection technology, consisted in continuous

screening of global and local wireless networks for

availability and signal levelfrom the vehicle. For each

stage of experiment we determined average speed and

calculated driving time, number of GPS points, num-

ber of global and local networks polls, number of reg-

istered local networks, average signal level at given

point and the network working range. Summary re-

sults of this experiment are shown in Table 2.

During our experiments consisting of collection

and transmission of data about available wireless net-

works we’ve revealed the dependencies of transmit-

ted data size and number of networks on the average

vehicle’s speed under stable radio conditions. Fig-

ure 7 shows charts with dependencies of number of

networks and transmitted data size on the average ve-

hicle’s speed. Charts show that the number of regis-

tered stationary wireless networks drops with increase

of average speed, which is explained by decrease in

polling rate due to route length. Transmitted data

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Table 2: The parameter values.

Parameters

Vehicle speed

10 15 18 20 23 26 28

The driving duration, min 16 10 8 7 6 5 4

Data amount, KB 697 504 480 457 354 274 200

Average signal level LTE, dB -59 -64 -65 -67 -67 -68 -69

Number of registered networks Wi–

Fi, num

215 181 179 164 159 159 155

Average visibility time of Wi–Fi net-

works, s

28 19 10 7 6 4 3

size dramatically drops too with increase of average

speed owing to decreasing number of registered net-

works and decreasing polling rate, which is caused by

shortening the time spent on the route. This allows

to draw a conclusion about the multiprotocol unit’s

operational efﬁciency for the purposes of signal level

registration of global and local networks. Figure 8

shows dependency between visibility time of station-

ary wireless network by the vehicle’s multiprotocol

unit and vehicle’s average speed by the example of

four wireless networks.

Figure 7: The number of detected networks and the volume

of data for different the average speeds of the vehicle.

The volume of transmitted data decreases linearly

with the increase in the average speed as a conse-

quence of reducing the number of registered net-

works. As a smaller number of polls to the network

is caused by a decrease in travel time, which leads to

the conclusion about the effectiveness of the multi-

protocol node in signal level registration of local and

wide-area wireless networks.

Figure 8shows the dependence of the availability

of ﬁxed wireless network access point from multipro-

tocol node with the average vehicle speed for the four

networks.

The graph shows that for all achieved average ve-

hicle speeds range,networks availability is reduced

by no more than 35%, which reliably provides their

registration by technical means from multiprotocol

nodes.

Figure 8: availability duration of the wireless networks for

different average speeds of the vehicle.

Study of the dependence of LTE signal levels

shows a trend to some reduction in the ratio ”sig-

nal to noise” at higher speeds, but that does not dis-

connect link or reducing the speed of data exchange

between the multiprotocol unit and the hardware-

software testbed of telematic map cloud service. To

demonstrate the efﬁciency of data obtaining from the

telematics maps a series experiments was carried out.

In each experiment in each vehicle position the query

in of telematics maps cloud service was executed. The

results are compared with the radio environment.

To this end, the vehicle moving along the path

as shown in Figure6, polls the GPS sensor, runs the

queries to the telematic maps database, registering

current values of radio environment, and checked

their compliance with the data obtained from the

telematics service.

Figure 9 shows the results of comparison with

wireless networks identiﬁers that are received directly

on multiprotocol unit and those from cloud telematics

map database. The histogram shows sustainable coin-

cidence of the networks lists derived from cloud ser-

vice and those directly found in the air. This suggests

the applicability of the proposed technology for ob-

taining wireless networks lists from cloud telematics

service at all vehicle’s speeds.

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165

Figure 9: The histogram of the number of coincided wire-

less networks names between cloud and the multiprotocol

unit.

5 CONCLUSIONS AND FUTURE

WORK

The described technological environment of telematic

maps cloud service and multiprotocol unit interact-

ing with it provides data management of local and

wide area wireless networks in the moving vehicle.

This expands the of multiprotocol routing possibility

in heterogeneous vehicles networks by increasing the

visibility scope of the vehicle networks. Further de-

velopment of the work should be the realization of

user’s uninterrupted access to the network, by fore-

casting the most suitable moments and data channels

inside the software procedure of the routing multipro-

tocol node.

ACKNOWLEDGMENTS

This research was supported by a grant from the Ford

Motor Company. This paper was funded by RFBR

grant 13-07-12106.

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