Converging Future Internet, “Things”, and Big Data: A Specification
Following NovaGenesis Model
Antonio M. Alberti
, Eduardo S. dos Reis
, Rodrigo da R. Righi
, V´ıctor M. Mu˜noz
and Victor Chang
ICT Laboratory, Instituto Nacional de Telecomunicac¸˜oes - INATEL, Santa Rita do Sapuca´ı, Minas Gerais, Brazil
PIPCA, Universidade do Vale do Rio dos Sinos, S˜ao Leopoldo, Rio Grande do Sul, Brazil
Universitat Autonoma de Barcelona, UAB, Barcelona, Spain
School of Computing, Creative Tech. and Eng., Leeds Beckett University, Leeds, U.K.
Internet of Things, Big Data, Cloud Computing, Future Internet, NovaGenesis, FIWARE, Spark.
The convergence of Internet of “things” (IoT) with big data platforms and cloud computing is already happen-
ing. However, the vast majority, if not all the proposals are based on the current Internet technologies. The
convergence of IoT, big data and cloud in “clean slate” architectures is an unexplored topic. In this article,
we discuss this convergence considering the viewpoint of a “clean slate” proposal called NovaGenesis. We
specify a set of NovaGenesis services to publish sensor device’s data in distributed hash tables employing self-
verifying addresses and contract-based trust network formation. IoT devices capabilities and configurations
are exposed to software-controllers, which control their operational parameters. The specification covers how
the “things” sensed information are subscribed by a big data service and injected in Spark big data platform,
allowing NovaGenesis services to subscribe data analytics from Spark. Future work include implementation
of the proposed specifications and further investigation of NovaGenesis services performance and scalability.
Internet of “things” (IoT) (Conti, 2006) can be de-
fined as to connect the ordinary things to the Inter-
net. In the last years, many initiatives appeared to
converge IoT with big data. Among them there are:
FIWARE (Ramparany et al., 2014), SmartSantander
(Sanchez et al., 2013) and SENSEI (Presser et al.,
2009). FIWARE provides a platform to integrate
services via next generation service interfaces (NG-
SIs). SmartSantander provides a platform for smart
city services integration using RESTful (Richardson
and Ruby, 2007) application programming interfaces.
SENSEI focus was on wireless sensor and actuator
networks interoperation, creating a market of sensed
information via RESTFul interfaces.
FIWARE integrates Cosmos big data platform ser-
vices, which are based on Hadoop (Hu et al., 2014).
SmartSantander employed a combination of Spark
(Zaharia et al., 2010) and Cassandra (Lakshman and
Malik, 2010). These approaches solidly depend on
current Internet support, since they use RESTFul
APIs. However, many IoT challenges, like security,
trust, privacy, software-control, to name a few, will
require more than incremental solutions or the appli-
cation of models already established. New architec-
ture models will be demanded, since the current cloud
and networking technologies and their protocols are
inherently limited for several expected scenarios (Pan
et al., 2011). “Clean slate” architectures for Internet
(and consequently for IoT) are being engineered un-
der the banner of future Internet design.
The convergence of IoT, big data, and cloud in
“clean slate” future Internet architectures is an unex-
plored topic and the main contribution of this paper is
on specifying an architecture to integrate them. In this
context, we are developing NovaGenesis (NG
) (Al-
berti et al., 2014; de Oliveira et al., 2015), a conver-
gent information model that covers information ex-
changing, processing, and storage. In this paper, we
address IoT, big data, cloud computing, and software-
defined (McKeown et al., 2008) technologies’ con-
vergence under the perspective of NovaGenesis. In
addition, we specify a set of NovaGenesis services
to publish sensor device’s data in distributed hash ta-
bles (DHTs) employing self-verifying names (SVNs)
Alberti, A., Reis, E., Righi, R., Muñoz, V. and Chang, V.
Converging Future Internet, “Things”, and Big Data: A Specification Following NovaGenesis Model.
DOI: 10.5220/0005890600730081
In Proceedings of the International Conference on Internet of Things and Big Data (IoTBD 2016), pages 73-81
ISBN: 978-989-758-183-0
2016 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved
and contract-based trust network formation. In other
words, we specify the data path form devices to the
cloud, employing NovaGenesis emerging paradigms,
like SVNs and contract-based service composition.
IoT devices capabilities and configurations are ex-
posed to software-controllers, which control their op-
erational parameters following the model in (Alberti
et al., 2014). Finally, we specify how the “things”
sensed information are subscribed by a big data ser-
vice (BDS) and injected in Spark big data platform.
This allows NovaGenesis services to subscribe data
analytics generated by Spark.
The remaining of this paper is structured as fol-
lows. Section 2 provides an overview of FIWARE
IoT + big data + cloud computing integration pro-
posal. The section also covers the requirements for
“clean slate” FI architectures that can improve the
state-of-the-art while converging these aspects. Sec-
tion 3 presents NovaGenesis and its current imple-
mentation. Section 4 specifies a set of new services
for converging IoT, big data, cloud computing, and
software-controllers. A sequence diagram is provided
to clarify new services joint functioning. The section
also provides a discussion on how these services in-
teract one another, ranging from “things” raw data
to big data analytics results. The main contribution
of the paper is on integrating future Internet services
with already established big data technologies and
software-controlled devices and gateways, advancing
IoT architectures towards SDN and SOA. Section 5
provides a discussion on how the proposed model can
help on addressing some open challenges in IoT and
big data integration. Section 6 finishes the paper.
The amount of future Internet (FI), IoT, cloud com-
puting, and big data convergent scenarios is immense.
The amount of technologies that support such sce-
narios is also impressive. One example of initiative
aimed at this convergence is the European project FI-
WARE (Ramparany et al., 2014). Figure 1 illustrates
a simplified overview of FIWARE architectural com-
ponents for IoT, which include: (i) IoT broker; (ii)
backend device management (BDM); (iii) context-
broker (CB); (iv) big data analysis (BDA); and (v)
complex event processing (CEP). Before describing
them, it is important to notice that three kinds of
“things” are supported: (a) devices that are compati-
ble with next generation service interface (NGSI) ver-
sion 9/10; (b) devices that are not compatible with
NGSI 9/10, however the gateways are; and (c) devices
and gateways that are not compatible with NGSI-
9/10. The IoT broker recovers, collects and pro-
cesses information from “things” exposing devices
as RESTful application programming interface (API)
resources. The BDM exposes legacy technologies
(standardized or proprietary) as resources to the CB
via NGSI-9/10. IoT agents are instantiated to handle,
configure and monitor non NGSI devices and gate-
ways. The CB provides a publish/subscribe context
broker service via NGSI-9/10 interface. Contexts can
be registered, updated, queried, notified, subscribed,
etc. For example, a native NGSI-9/10 device can
create a context that carries the current value of the
temperature in a certain room. BDA is an extended
version of hadoop (Hu et al., 2014) from Telefonica
(called Cosmos). Finally, CEP is an IBM generic en-
abler (as FIWARE names its components) to correlate
real time events according to programmed rules. The
data generated either by CEP or BDA is published on
CB. BDA is fed by CB and processed data from CEP.
Therefore, FIWARE allows near real time map/reduce
operations over large amounts of data from IoT.
Figure 1: FIWARE scenario for converging future Internet,
Internet of “things”, big data, and cloud computing.
Considering the perspective of clean slate archi-
tectures for the future Internet (Pan et al., 2011), the
convergence provided by the FIWARE project — that
is supported by current Internet and web technologies
— could be improved in the following aspects
Security - The current Internet approach of us-
ing natural language names (NLNs) to name uniform
resource locators (URLs), hosts (IP addresses) and
transport layer ports (in sockets) is human-friendly,
but the intrinsic binding to physical world entities de-
pends on the correct and unambiguous understand-
ing of these names. Information centric networking
(ICN) proposes self-verifying names (SVNs) as an al-
ternative to NLNs (Ahlgren et al., 2012), so making
possible to check the relationship between the named
Many other aspects can be considered. However, due
to limited space we decided to concentrate on these three.
IoTBD 2016 - International Conference on Internet of Things and Big Data
entity and the name at any time. Furthermore, Gh-
odsi et al. (Ghodsi et al., 2011) argue that SVNs have
better security, scalability, and flexibility than NLNs.
SVNs can also support provenance, non repudiation,
and integrity of IoT data and its sources. FIWARE ar-
chitecture is based on the current Internet/Web design
and therefore do not support SVNs.
Contract-based Composition - Web services can
support contract-based services composition, e.g. us-
ing constrained application protocol (CoAP) observ-
able resources. This enables services to form a
trust networks, increasing security and privacy. Who
would like to have your IoT services publishing pri-
vate data to low trust services you do not know? The
RESTFul interfaces (e.g. NGSI-9/10) are dynamic
and allow a service to establish service level agree-
ments (SLAs) with other instantiated services. How-
ever, contract-based operation is typically not oblig-
atory. For instance, in FIWARE generic enablers are
not required to establish SLAs one another. SLAs are
employed to deal with cloud infrastructure.
Software-Defined Control - The role of software
is increasing in emerging information and commu-
nication technologies (ICT) architectures. Software-
defined networking (SDN) consists on decoupling
control and data planes in networking equipment
(McKeown et al., 2008). Unfortunately, current
open SDN standards are concerned only with traf-
fic forwarding, e.g. OpenFlow. There exists a huge
potential behind software-controlling IoT and cloud
devices/infrastructure. Controllers can be extended
to deal with many other functions, like proxying,
fire-walling, interconnection, etc. FIWARE’s back-
end device management is an example of software-
controlling IoT devices. These software controllers
can be exposed as services to other applications. An-
other example is the FIWARE’s protocol translation
software that can be software-controlled. In short,
FIWARE project already perceived the potential of
software-controlling the IoT/cloud devices. However,
what is missing is contract-based dynamic composi-
tion with exposed controllers-as-a-service (CaaS).
FIWARE and SmartSantander meet the software-
defined control requirement, but lack on supporting
SLAs among their services as well as on supporting
SVNs and its name resolution. SENSEI does not meet
any of these requirements. (Pan et al., 2011) surveys
many future Internet architectures, including “clean
slate” ones. Some of them individually support these
requirements, but they are not focused on IoT.
3 NovaGenesis
NovaGenesis (NG) project started in 2008 with this
question in mind: imagine there is no Internet archi-
tecture right now, how could we design it using the
best contemporary technologies? However, we real-
ized that emerging architectures should embrace not
only networking aspects, but also computing, stor-
age, and visualization. Thus, NG aims for redesign-
ing both communication mechanisms and protocols
for enabling a program running anywhere to address
messages to programs anywhere else with acceptable
performance and portability levels. Also, it looks
for the convergence of computing and communica-
tions, merging technologies like cloud and mobile
computing, Internet of things (IoT), service frame-
works, software-defined networking (SDN), network
function virtualization (NFV) and distributed systems
(Alberti, 2012; Alberti, 2013).
3.1 Foundational Concepts
Figure 2 illustrates key ingredients we tried to con-
verge in NG. We started from naming, name resolu-
tion, and life-cycling of contents and services. There-
after, we included exposition, control and gateway for
“things”. The idea was to create a generic framework
that could deal with naming, life-cycling, persistent
identification, location-independency, joint content,
services, and “things” coordination (orchestration).
3.1.1 Existences
The physical world in the Earth is full of physical en-
tities, e.g. cars, houses, etc. Furthermore, the human
mind is capable of creating virtual realities, full of vir-
tual entities, e.g. computer programs, files. Adopting
these definitions, a convergent information architec-
ture can be seen as the combination of physical and
virtual existences aimed at dealing with information
in a universal scale. An “individual” existence is any-
thing that can be classified as independent or sepa-
rated from others.
3.1.2 Binding Natural and
Hash-Function-Generated Names
Names are symbols used to denote one or more in-
dividual existences. In this case, to denote means to
represent something by signals. By definition, names
denote meaning and sense. However, there are names
that are almost randomly generated, having weak se-
mantics, e.g. the plate of your car. Consider the bi-
nary word obtained at the output of a hashing algo-
rithm. This binary word (also called hash code) can
Converging Future Internet, “Things”, and Big Data: A Specification Following NovaGenesis Model
be used as a name a self-verifying name (SVN). In
this case, the binary input of the hash function can
be the existence itself (e.g. computer program ex-
ecutable, source code, or information files) or other
binary input related to the entity being named (e.g.
entities’ immutable attributes). In the first case, the
name is said to be self-certifiable, because at any time
the existence’s binary words can be hashed again to
get exactly the same name. In the second case, the
perennial physical existence attributes can be digital-
ized again to certificate the name.
IoT means that any “thing” will be part of the
Internet, therefore architectures should accommo-
date/recognize “things” names. Our approach em-
ploys an unlimited number of namespaces, that are
linked by means of name bindings. A name binding is
a mapping among two or more names. A name bind-
ing (NB) can relate a name to an object or a name to
other names. NovaGenesis allows any naming struc-
ture and generalized name resolution as a service.
3.1.3 Names as Identifiers or Locators
There is no novelty on using names as identifiers or
locators. This is intrinsic to ICT technologies. How-
ever, the adoption of SCNs as identifiers is more re-
cent. NovaGenesis borrowed this idea from other
FIAs, specially NetInf (Dannewitz, 2009) and XIA
(Han et al., 2012). A locator should provide a notion
of distance among existences in some space. As one
can expect, it is not possible to derive such distance
notion from SVNs they are flat. Then, NG pro-
vides such distance notion by using SVN-bindings.
3.1.4 Contents, Services, and Contracts
A content can be defined as a piece of information,
composed by chunks of binary data. For example, a
textual file. A service is a data (or information) pro-
cessor. Thus, a textual file can be the input or the
output of a word processor service. In addition, a net-
working information processor, such as a frame for-
warder, is a service like any other, since it receives
information at the input, adds some control data, and
forwards the processed information as an output. In
this context, a process that is instantiated in an op-
erating system provides in essence information pro-
cessing, which in turn can be defined as a service.
Therefore, in this paper we propose the following def-
inition: a service is an existence aimed at process-
ing, exchanging, or storing information. Services ne-
gotiate their job using contracts, which are contents
that describe service requirements, clauses to be re-
spected, evaluation, and finalization criteria, among
other data. All the information required to describe
Self-*, Context
Name Resolution
Internet of Things
Exposition, Orchestration
Protocol Development
ID/Loc Splitting
Mngt. and Control
Figure 2: Key ingredients for Future Internet.
and regulate a service offer can be included in a con-
tract. In service-oriented architecture (SOA) a con-
tract is usually called service-level agreement (SLA).
3.1.5 Distributed Publishing and Subscribing of
Name-bindings and Content
Names and NBs are central in NG. Thus, an impor-
tant design choice was to decide how they are going
to be stored and exchanged. Instead of a traditional
communication model, such as a “receiver accepts
all model”, it was selected a loosely coupled, asyn-
chronous, receiver select” model a pub/sub ap-
proach. In summary, services can publish name bind-
ings or content to other services. For example, the
binding of an operating system name to a host name
can be published by a service that represents the OS.
Another OS representative service can subscribe this
binding (assuming it is public) to discover that there
is a name relation between those two existences.
3.1.6 Name-based Life-cycling
The life-cycling of substrate resources, services, and
content (including names) is populated by a dense
entanglement of existential relationships. Operating
systems inhabit hosts. Services are instantiated, com-
bined in runtime, and removed from operating sys-
tems. Contents are created, exchanged, processed,
and removed from services. To deal with this hier-
archical life-cycling requirement, name bindings are
categorized. There are NBs exclusive for: (i) physical
world entities; (ii) software entities; (iii) contents; (iv)
other names, e.g. a process ID in a Linux OS. There
are also NBs to link names among physical-virtual,
virtual-physical, etc.
IoTBD 2016 - International Conference on Internet of Things and Big Data
T 2
Figure 3: NovaGenesis current prototype.
3.2 Proof-of-concept Implementation
In 2012, we implemented a C++ prototype of No-
vaGenesis (NG) to run at user space of Linux Kernel
as illustrated on Figure 3. This 40k line codes proto-
type already runs without TCP/IP, using a raw socket
directly over Ethernet or Wi-Fi. In the figure, Host 1
is connected by Ethernet, while the remaining hosts
use Wi-Fi. A proxy/gateway service (PGS) encapsu-
lates NG messages over link layer technologies.
NovaGenesis web of names is build of distributed
stored name bindings. NBs are published and sub-
scribed by services. This is the most innovative aspect
of NovaGenesis a distributed, highly scalable, pub-
lish/subscribe, name binding and content storage ser-
vice. NBs and content are published by any services
through sending a message to an instance of a pub-
lish/subscribe service (PSS). The PSS stores which
services are pre-authorized to access the published
data. Also, it records a time to live (TTL) for any
published data. There is also a notification function-
ality that enables PSS to inform other services about
new publications or NB updating. However, the PSS
does not store the data published. It forwards them
to a generic indirection resolution service (GIRS),
which selects a hash table service (HTS) to store it.
Thus, published NBs and content are forwarded by
the GIRS to an HTS instance, where they are stored
behind a hash table data structure.
User services (or applications — App) can expose
its NBs and content to other services via PSS. Thus,
other services can subscribe a services’ NBs and con-
tent. The PSS does the rendezvous between publish-
ers and subscribers, enabling them to discover how
published names are related each other in a secure
way. Eventually, services can successively subscribe
NBs to identify and locate other existences, storing
these NBs in local data structures, and routing infor-
mation based on them.
GIRS and HTS instances form a distributed
hash table (DHT). This DHT was designed from
the scratch to support named-based and contract-
oriented operation. Current DHTs do not employ self-
certifying names to identify the DHT nodes. In addi-
tion, they relay on TCP/IP stack for communication.
Our GIRS/HTS approach relays on NovaGenesis ser-
vices to forward and route the data among DHT in-
stances. This explains why we decided on a “clean
slate” DHT design.
In this section, we specify an extension to NovaGe-
nesis services that can provide similar support for
converging IoT, FI, big data and cloud as FIWARE
provides. However, our proposal meets the require-
ments presented in Section 2 to advance conver-
gence towards more secure, trustable, contract-based,
software-controlled architectures. Figure 4 illustrates
how these new services interact one other by us-
ing NovaGenesis PSS/GIRS/HTS, which can be seen
as a distributed name resolution system (NRS) with
cache capabilities. All these services use a pub-
lish/subscribe (pub/sub) application programming in-
terface (API), which has five primitives: (i) publishes
a NB (and a content, if any); (ii) subscribes a NB (and
content, if any); (iii) notifies peer services about NB
(and content) published; (iv) revokes a publication;
and (v) delivers name bindings and related contents.
This interface is used alternatively to the NGSI-9/10
adopted on FI-WARE. In terms of components, the
proxy/gateway/controllerservice (PGCS) is similar to
the IoT broker, even tough it includes some of the
FI-WARE’s BDM functions, like resource exposition,
monitor, etc. NovaGenesis big data service (BDM)
role is different from FI-WARE’s BDA. It provides
an application level gateway to the big data solutions,
such as Spark, while the BDA implements the hadoop
distributed system. In addition, NG relays on a new
name resolution system (NRS), while FI-WARE is
Figure 4: New NovaGenesis services for converging future
Internet, Internet of “things”, big data, and cloud.
Converging Future Internet, “Things”, and Big Data: A Specification Following NovaGenesis Model
NG Layer
NG Layer
NG Layer
App Layer
NG Layer
App Layer
App Layer
Figure 5: Layer stack for NG and Spark big data plus IoT.
based on DNS.
Figure 5 illustrates the protocol stack behind our
approach. The NG layer employs a blank page mes-
saging service implemented using SVNs. NG mes-
sages are encapsulated over IEEE 802.15.4 (to be im-
plemented) or Ethernet/Wi-Fi (already implemented).
The NovaGenesis pub/sub API can be seen as a ser-
vice access point (SAP) between NG Layer and NG
application layer. Observe that the original PGS pre-
sented in Figure 3 is modified not only to run em-
bedded (EPGS), but also to include software-control
capabilities (PGCS). To the best of our knowledge,
the EPGS is the first future Internet gateway that:
(i) employs SVNs, instead of “human readable” ad-
dresses; (ii) exposes hardware resources to services
using a contract-based approach; and (iii) receives
control commands from a software-controller(PGCS)
using named-data paradigm.
4.1 Embedded Proxy/Gateway Service
This service is a minimal NG implementation to run
embedded. It generates nodes’ self-verifiable names
as well as a descriptor of the hardware features and
functionalities, storing them in a local hash table (HT)
component. Also, it sends a periodic “hello” mes-
sage that exposes its names as well as its MAC ad-
dress (proxy function)
to possible peers (Figure 6 il-
lustrates this procedure). The “hello” step is shown
as transaction a in this figure. Since a PGCS receives
this “hello”, it answers back with its names and PSS’s
names, enabling the EPGS to publish data on the NG
NRS (Transaction b). Then, the EPGS publishes its
name bindings, descriptors, and a service offer to the
NRS via the discovered PGCS (c). The NRS noti-
fies the PGCS (d), which subscribes the service of-
fer (f,g). The service offer exposes device features,
names, and capabilities to the PGCS. The PGCS pub-
lishes a service contract acceptance object (h) to the
NRS. The NRS notifies the EPGS about the accep-
tance (i), which subscribes it (not shown in figure).
After contracting a PGCS the hello message can be
suppressed to save energy
The EPGS is able to encapsulate NG messages
over a link layer technology (gateway function) that
is compatible with a PGCS (IEEE 802.15.4 as shown
in Figure 5). The EPGS publishes its status, configu-
ration, and raw data (measures) to the NRS (p), noti-
fying other services interested in the raw data (BDS)
or status/configuration (PGCS).
4.2 Proxy/Gateway/Controller Service
The PGCS has gateway, proxy, and controller func-
tionalities. Similarly to the EPGS, it generates node’s
SVNs and descriptors and store them in a local HT. It
also sends a periodic “hello” message with its names
and MAC address
to other PGCS (a,b in Figure 6).
The PGCS is an IoT gateway for one or more sensors
and/or actuators nodes. The PGCS has the respon-
sibility to disclosure PSS names, so the EPGS(es)
can use NRS API (b). The PGCS is able to encap-
sulate message to the its contracted EPGS(es), using
their link layer technologies, e.g. IEEE 802.15.4. Fi-
nally, the PGCS acts as a software-controller of the
EPGS’s represented devices, i.e. the PGCS can pub-
lish control messages to the EPGSes in its trust net-
work, changing their configurations. For example, a
PGCS can publish a control message ordering a con-
trolled device to change its IEEE 802.15.4 channel.
4.3 Management and Control Service
This service is responsible to manage and control the
infrastructure and it is implemented as an applica-
tion that uses NG pub/sub API. It exposes its func-
tionalities, which can cover the classical five man-
agement areas: fault, configuration, accounting, per-
formance, security (FCAPS). It maintains a trust net-
work (via SLAs) with many PGCSes. This model en-
ables to propagate policies and rules in a distributed
way to many software-controllers, keeping consis-
tency, since configurations/rules/policies are all pub-
lished in the NRS using SVNs. It addresses the
load balancing and controller consistency problems
of OpenFlow. In summary, the MCS performs gate-
way/proxy/controller management and control. De-
pending on the amount of ctrl. and manag. opera-
tions, this service can be fragmented.
4.4 Big Data Service
This service is a gateway to interoperate to Spark (Za-
haria et al., 2010) — a popular big data implementa-
tion. The BDS exposes big data platforms as a service
to other NG services/applications via pub/sub API.
IoTBD 2016 - International Conference on Internet of Things and Big Data
Its aim is similar to FIWARE’s Cosmos generic en-
abler even though Cosmos is based on Hadoop
(Hu et al., 2014). NovaGenesis is a pub/sub envi-
ronment, therefore the BDS will need to translate this
communication model to request/reply, which is the
typical model to access current big data implemen-
tations. Also, NG is implemented in C++ language,
which makes interoperation with big data approaches
complex, since typically there is no native support for
injection/querying in C/C++. In this context, to in-
teroperate NG with Spark the BDS will keep a se-
cure socket shell (SSH) connection to the Spark con-
sole (Figure 5) using TCP/IP. Using this interface, the
BDS will be able to send Hive structured query lan-
guage (SQL) queries to the Spark cloud. Also, the
BDS will be able to: (i) inject data subscribed at No-
vaGenesis side on Spark; and (ii) publish the obtained
results on NovaGenesis NRS. Thus, data series from
NovaGenesis distributed hash service will be injected
into Spark, analyzed, and retrieved via BDS.
In Figure 6, the BDS searches for PGCSes that can
provide useful data for analytics. It subscribes rele-
vant NLN (e.g. “PGCS”, “gateway”, etc) from local
NRS (transaction i). The NRS returns knownPGCSes
(j). The BDS publishes a service offer to a PGCS (k)
that can provided the raw data for big data analysis.
The PGCS subscribes the service offer (l,m). After
analyzing the offer, the PGCS publishes a service of-
fer acceptance object to the BDS (n), which is notified
by the NRS. The BDS subscribes the acceptance ob-
ject (o). Finally, the raw data provided by the EPGS
is published to the BDS (p), which subscribes it (q).
The subscribed raw data is injected by BDS on Spark
via SSH. The BDS can now perform queries on Spark
(s) and publish resulting analytics on NG NRS (t).
Since there will be thousands of devices to be con-
nected (in ideal situations), it is a huge task is to mon-
itor, control and manage all network traffics and de-
vices (mobiles, routers, sensors etc). This is highly
important for all IoT and BD architectures. Factors
affecting such performance will include latency, size
of data and network speed (Chang and Wills, 2015).
The proposed N:1 device control/management model
based on software-controllers (PGCSes) is highly
scalable, since more PGCSes can be elastically al-
located when required. The proper selection of ser-
vices’ hosts can decrease latency.
Current security and privacy methods are lag-
ging behind sophisticated hacking techniques and
just one single solution is far not enough. A
Figure 6: Sequence diagram for NG and Spark big data,
including EPGS and laptop PGCS “hello” (a,b), exposition
and service offering (c,d,f,g), service contracting (h) and ac-
ceptance (i). A similar discovery, negotiation, and contract
establishment procedure is performed by the laptop PGCS
and BDS pair (i,j,k,l,m,n,o). Raw data is published by the
EPGS (p), notified and subscribed by NRS (q), and injected
on Spark (r). Results are published by BDS on NG NRS (t).
multi-layered security solution can reduce the risk
of unauthorized access and the use of back-end
non-SQL databases should be implemented in core
servers/clusters for IoT and BD architectures (Chang
et al., 2016). NovaGenesis self-verifying names,
pub/sub, and contract-based operation enhances secu-
rity, privacy, and trust. Name resolution is very impor-
tant to provide a multi-layered security solution.
Since a lot of data can be generated, smart means
to recover data at any instance with advanced tech-
niques to meet performance, accuracy and reliability
are required. All sites should have the facility to per-
form multi-purpose and multi-site recovery to ensure
business continuity (Chang, 2015). The distributed
nature of NG model can help on maintaining coher-
ence in case of disaster. Name resolution can be ex-
plored to find out alternatives to access some data or
network. Name rebind is an important tool.
Converging Future Internet, “Things”, and Big Data: A Specification Following NovaGenesis Model
This work has proposed the concept and reported the
specification of a model to integrate big data, cloud
computing, IoT device-control-as-a-service, and IoT
services. The proposed model is based on NovaGe-
nesis, a “clean slate” FI proposal. A big data ser-
vice was proposed to interoperate NG name resolu-
tion service (based on pub/sub and distributed hash
tables) with Spark big data. The proposed specifi-
cation also introduces embedded proxy/gateway ser-
vices that encapsulate IoT devices traffic towards NG
pub/sub, as well as represent IoT device’s in the ser-
vice tier. Software-defined IoT devices are controlled
by proxy/gateway/controller services (Alberti et al.,
2014). A domain level management and control ser-
vice (MCS) was also specified to implement in a logi-
cal centralized way the classical areas of management
and coordinate PGCSes activities. The architecture
advances state-of-the-art by converging data, control,
and management planes for FI with big data and IoT.
Future work includes: (i) implementation and per-
formance evaluation of the convergent architecture
specified in this paper; (ii) elasticity and scalability
tests of the proposed control/management model in-
cluding cloud computing resources; (iii) evaluated la-
tency and efficiency of proposed control/management
model; (iv) to monitor and evaluate service repu-
tation; (v) explore security advantages of proposed
model; (vi) implement and evaluate NG benefits for
disaster recovery scenarios; and (vii) evaluate NG in-
tegration to other big data platforms besides Spark.
This work was partially supported by Finep/Funttel
Grant No. 01.14.0231.00, under the Radiocommu-
nication Reference Center (Centro de Referˆencia em
Radicomunicac¸˜oes - CRR) project of the National In-
stitute of Telecommunications (Instituto Nacional de
Telecomunicac¸˜oes), Brazil.
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Converging Future Internet, “Things”, and Big Data: A Specification Following NovaGenesis Model