Integrating Distributed Data Storage of a Smart City Public

Administration

Carmelo Pino, Salvatore Ravidà and Santo Scibilia

University of Catania, Department of Electrical, Electronics and Computer Engineering (DIEEI),

V.le Andrea Doria, 6, 95125 Catania, Italy

Keywords: Smart City, e-Government, Cloud Computing, Data Storage Integration, RDF.

Abstract: The developments and increasing solutions offered by Cloud Computing technologies represent a great

opportunity for e-governance of smart-cities. The benefits provided by Cloud-based technologies allow us

to re-design new services to solve many problems afflicting e-governance and public administration in each

country. In particular, one of the primarily need of Public Administration (PA) is the interoperability be-

tween the different areas and districts, which is rather complex due to the lack of standard schemes for data

modeling. In this paper we propose a cloud-based approach for supporting such interoperability by a cus-

tomizable DBMS mapping tool especially dedicated to smart city governance.

1 INTRODUCTION

As known, a smart city arises when citizens are

ready to use technologies to improve relevant city

life aspects such as governance, local development,

cultural events, mobility and logistics, environment

and health services (Chourabi et al., 2012), (Berthon

et al., 2011). Cloud computing can be considered as

a collection of technologies to store or process data

through the use of distributed hardware/software

over a virtualized Network. It’s a model for structur-

ing IT resources that redefines the way to manage

computer systems (Rimal et al., 2009), (Dillon et al.,

2010). Nowadays, the diffusion of Cloud Computing

and the perception of its benefits represents an op-

portunity to increase the capabilities of the e-

governance in term of offered services, cost reduc-

tion, distributed data storage, security management

(Mukherjee and Sahoo, 2012), (Ramgovind et al.,

2010), scalability, accountability, interoperability

(Cellary and Strykowski, 2009), and reliability

(Chandra and Bhadoria, 2012).

Among the different challenges in e-governance

the interoperability between the existing hardware,

software and data storage is a major issue (Smitha et

al., 2012) that often systems providing e-services in

different administrative units are not able to guaran-

tee.

There exists several e-governance applications

and services that can be categorized at different

levels: Government to Government (G2G), Gov-

ernment to Business (G2B), Government to Citizens

(G2C) and Government to Enterprise (G2E) (Jeong,

2007), (Giordano et al., 2013), (Faro et al.,2008),

(Constanzo et al., 2012). Each category is related to

a specific set of applications and the common need

is the communication between multiple data sources

(e.g. the storage related to “municipal maintenance”

has the need to retrieve data about a citizen from the

“registry office storage”). The miscellaneous of data

contained in different archives suggests the use of

RDF or OWL to define a common semantic schema

to map the different terms used in the various data

bases with the same meaning to a standard vocabu-

lary of concepts.

Interoperability is therefore one of main issue for

the development of future e-government systems,

called in following as e-gov systems, which can be

tackled with the use of cloud computing (Tripathi

and Parihar, 20119) and the advantages provided by

its model of services (SaaS, PaaS, IaaS) and distri-

bution (Public, Private, Hybrid) (Armbrust et al.,

2010).

In this paper we propose a private cloud archi-

tecture for supporting the interoperability and inte-

gration between distributed e-gov data storages. The

idea behind this work is to collect each data storage

239

Pino C., Ravidà S. and Scibilia S..

Integrating Distributed Data Storage of a Smart City Public Administration.

DOI: 10.5220/0004407802390243

In Proceedings of the 2nd International Conference on Smart Grids and Green IT Systems (SMARTGREENS-2013), pages 239-243

ISBN: 978-989-8565-55-6

 2013 SCITEPRESS (Science and Technology Publications, Lda.)

belonging to a Administrative Unit (AU) in a private

cloud architecture (without changing the storage

structure) and to create a layer hiding the storage

details so that it is possible to view the distributed

data storage as a centralized storage that exposes the

data according to a standard data model provided by

a RDFs/XML schema.

This data schema for e-gov data management has

been created analyzing the structures of several data

storages belonging to different AUs. Then, the cloud

has been used as in the Software as a Service (SaaS)

to offer to citizens and employees the possibility to

manage and retrieve data residing on different nodes

using a single front end. In section two, the details

about the developed architecture are discussed,

whereas some examples of how using the proposed

cloud are shown in section three. Concluding re-

marks are given in the last section.

2 THE PROPOSED

ARCHITECTURE

The proposed system is based on a general architec-

ture that supports the interoperability between dis-

tributed data storages belonging to the same or dif-

ferent AUs, e.g. registry office, garbage fee, cadas-

ter, etc. It consists of two main modules: 1) Data

mapping and exposing, 2) Data querying. The first

module creates a transparent layer hiding the details

of each storage in terms of DBMS and data storage

schemata. The second module aims at: a) retrieving

the data exposed by the previous module, and b)

integrating such data according to the user’s query.

More in details:

 Data Mapping and Exposing (DME) Module: it

executes the mapping and returns the data accord-

ing to a standard vocabulary, i.e. also called data

ontology. It’s installed on each storage node to in-

terface the query issued by the users to the local

DBMS. Currently, the local DBMSs considered in

our approach are MySql, Oracle and DB2, but oth-

er DBMSs will be considered in future by simply

attaching the relevant driver to the DME module.

 Data Querying (DQ) Module: This module be-

haves as a front end for the user and represents the

consumer of the service installed on each storage.

It communicates with each VM in order to perform

a specific query and to obtain the results. The

XML data returned by the different VMs represent

different views and are parsed, collected and

stored locally.

Figure 1: The proposed architecture: each VM has its storage and hides storage details through the DME tool. The DQ

modules resides on the Front-End using the DME tools.

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240

In our private cloud architecture these two mod-

ules are used by each Virtual Machine (VM) to

expose the data through the web service described

above. Another VM houses the service that com-

municates with each VM in order to perform the

requests (Front-End). It interacts with the user

through a specific interface to authenticate the re-

quest and to query the distributed data storage. Each

request is redirected from the front end to the rele-

vant VMs that retrieve the data and return them to

the front-end which takes care of the data integra-

tion.

Figure 1 shows the proposed architecture. An

example of usage for public employees could be:

“search for cadastral situation related to a citizen

called ‘Mario Rossi’ and how many people live

together with him”. The front end implemented by a

specific VM, i.e., VM4 in figure 1, receives and

parses the request identifying the VMs which ex-

pose the cadastral and registry data, i.e., VM2 and

VM3 in figure 1. The data querying module residing

on the front end integrates the retrieved data and

provides the information (always updated to the

latest change) to the user in real time.

Our private Cloud infrastructure is based on Mi-

crosoft System Center 2012

and is composed by an

HP C7000 enclosure with 8 blades for a total of 64

processors and storage capabilities of 20 TB. Each

VM is managed by Hyper V for a total of 4 VMs

respectively related to: the garbage fee storage

(VM1), the registry office storage (VM2), cadastral

storage (VM3), the front end (VM4). In VMs 1, 2

and 3 we have installed the DME tool. DQ is ob-

tained by a module residing on the front end cooper-

ating with the DMEs residing on the VMs. The

account, privileges and access policy are configured

and managed with system center 2012.

3 SOME EXAMPLES

In this section we illustrate two examples of use.

The first example regards the configuration of a

DME related to a storage. This is an essential step to

select which data will be exposed and mapped.

Fig. 2 shows the DME configuration step: an AU

administrator configures the DME through a graph-

ical interface specifying the DBMS type and a set of

queries that will be exposed as views. The queries

http://www.microsoft.com/en-us/server-cloud/system-

center/default.aspx

that will be exposed can be specified using SQL,

and will be executed when the front-end sends a

request to the DME. The data obtained from each

query are mapped and returned according to an

ontology.

Fig. 3 shows an example of interaction between

the front-end and different DME modules. When a

user (citizens or public employees) performs a re-

quest through the graphical interface, the front-end

identifies which are the DMEs useful for the data

retrieval. For example, if the request is: “search for

garbage fee and cadastral situation related to a

citizen called ‘Giuseppe Bianchi’”, the Front-End

understands that three storages are involved in this

search, i.e., garbage fee, cadastral and registry fee.

For this reason it sends a request to three DMEs for

a specific query. Each DME return the data related

to the request in RDF format. The returned data are

integrated by the front-end thanks to the common

RDF schema used.

4 CONCLUSIONS AND FUTURE

DIRECTIONS

In this work we have sketched a cloud-based e-gov

system for the integration of PA storages which use

different DBMS and schemas. Our solution has been

tested in public district of Catania (Italy) for the

following archives related to: registry office, gar-

bage fee and cadaster. This architecture is a practical

solution to integrate and retrieve data from multiple

sources.

As future work we plan to extend the ontology

for any type of data involved in e-government appli-

cations and to publish this data as part of linked

data. Moreover a hybrid cloud solution will be test-

ed in order to possibly improve the efficiency of the

proposed approach thanks to the advantages of a

consolidated private cloud in term of performance

and computing power.

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DME1

Data Storage

DME

Query

Configuration

Interface

DME 1

Data

Exposition

Query 1

Query 2

Query 3

Query n

Admin

User

Set of configured queries

Figure 2: Example of DME configuration.

Figure 3: Example of Interaction between Front-End and DME modules.

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