Hop Count Based Interest Selection and Content Forwarding Scheme for Vehicular Named Data Networks

International Journal of Computer Networks & Communications (IJCNC) Vol.15, No.6, November 2023
DOI: 10.5121/ijcnc.2023.15606 135
HOP COUNT BASED INTEREST SELECTION AND
CONTENT FORWARDING SCHEME FOR VEHICULAR
NAMED DATA NETWORKS
Nithin Rao R1
and Rinki Sharma2
1
Research Scholar, Department of Computer Science and Engineering, Ramaiah
University of Applied Sciences, India
2Professor, Department of Computer Science and Engineering, Ramaiah University of
Applied Sciences, India
ABSTRACT
Vehicular Named Data Networks (VNDN) face challenges in efficiently disseminating content due to high
mobility and intermittent connectivity. To address these challenges, a Hop Count based Interest Selection
and Content Forwarding (HISCF) scheme for VNDNs is proposed. The scheme focuses on mitigating
interest flooding, reducing data packet duplication, and alleviating network congestion. HISCF consists of
two components: interest selection and content forwarding. The selection process chooses a vehicle based
on hop count and Interest Satisfaction Ratio (ISR) to forward the interest packet. Content forwarding is
performed considering a hop count limit and pending interests, ensuring efficient content delivery. The
HISCF scheme is evaluated using extensive simulations in ns-3 with ndnSIM. Performance metrics such as
Data Packet Replication Count (DPRC), total number of interest packets forwarded, Interest Response
Time (IRT) and routing overhead are analysed. Results show that HISCF outperforms naïve VNDN,
reducing DPRC, minimizing interest packets forwarded, and decreasing average IRT. The findings
demonstrate that HISCF effectively mitigates interest broadcast storms, reduces data packet duplication,
and improves content delivery efficiency in VNDNs. This study contributes to VNDN research advancement
and provides insights for designing effective content forwarding mechanisms in vehicular networks.
KEYWORDS
Vehicular Named Data Networks, Content Dissemination, Interest Selection, Content Forwarding, Network
Performance.
1. INTRODUCTION
Over the past decade, Vehicular Ad-hoc Networks (VANETs) have gained significant attention
but have faced challenges in meeting vehicle network expectations, primarily due to the lack of
infrastructure support for global IP allocation [1]. VANET applications can be divided into
critical and non-critical data, and to address the needs of critical applications and safety, Wireless
Access in Vehicular Environment (WAVE) and Dedicated Short Range Communication (DSRC)
protocols are used. [2]. The use of standard IEEE 80.211-based protocols in VANETs introduces
TCP/IP overhead, which can be mitigated by leveraging DSRC for extended data exchange
services. However, the TCP/IP protocol encounters issues in the dynamic automotive
environment, including packet losses, session re-establishment, route recalculations, and
inconsistent connectivity [3].

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Named Data Networking (NDN) is an emerging architecture for the future of the internet, shifting
from host-centric to information-centric communication [4]. Vehicular Named Data Networks
(VNDNs) have been proposed as an exploration of NDN in VANETs [5]. In a typical VANET,
each node or vehicle has an IP address or node ID used for communication. However, in the
vehicular context, where nodes are mobile and communication lines and node IDs frequently
change, the NDN approach is considered more suitable as it focuses on retrieving data rather than
relying on host IDs and positions [6].
Despite being a relatively new field, VNDN faces fundamental challenges. For instance, the
broadcast nature of interest packets can lead to interest and data packet flooding, resulting in
reduced network performance [7]. To address this, efficient forwarding methods are necessary.
Additionally, while it is generally assumed that data packets follow the same path as interest
packets, recent studies have shown otherwise [8].
This paper aims to tackle both interest and content packet storms by proposing an interest
selection forwarder scheme based on multiple criteria, including hop count, Interest Satisfaction
Ratio (ISR), and matching content names, thereby mitigating interest broadcast storms.
Furthermore, a content forwarding scheme is proposed, considering hop count and Neighbour
Data List (NDL), to minimize data packet duplication and alleviate network congestion. The
research contributions of this paper are twofold: Proposal of an interest selection forwarder
scheme and proposition of a content forwarding scheme to reduce packet duplication and mitigate
network congestion.
2. RELATED WORK
This section highlights the related work in the field of forwarding schemes of VNDN.
The broadcast nature of NDN benefits the vehicular network environment, ensuring a fast
mechanism to disseminate data packets. However, in dense networks, uncontrolled broadcasting
leads to broadcast storms, resulting in redundant copies of interest and data packets flooding the
network. To address these issues, researchers have explored modification of the forwarding
plane's naive broadcasting nature, focusing on selection-based forwarding schemes. While
extensive research has been conducted on VNDN in recent years, literature on forwarding
techniques of VNDN is still in its early stages.
Several authors have classified various forwarding solutions based on criteria such as
transmission mode and working principle [9], [10], [11]. In [12], a location-based solution was
proposed to mitigate the broadcast problem. It involves maintaining a content location table by all
nodes, storing the location of content producers/providers. Other nodes in the network forward
interest packets to locations closer to potential providers/producers. However, this architecture
does not consider vehicle mobility, leading to interests being forwarded to the previously known
location of the producer instead of the current location.
A novel forwarding mechanism named COMPASS was proposed in [13]. Each node divides the
area into directional interfaces and selects a relay node based on performance metrics to transmit
the packets. If the driving direction changes, the Performance Information Table (PIT) and
Forwarding Information Base (FIB) values are updated, and interface re-mapping is performed.
However, the results show that the packets take a larger number of hops to reach the content
provider compared to conventional techniques.
In [14], a neighbour awareness-based forwarding scheme is proposed, divided into two stages. In
the first stage, vehicles share information with their neighbours, including hop count, metadata,

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and vehicle speed, which are maintained in a neighbour table. In the second stage, the node
selects only one neighbour as the forwarder based on entries in the neighbour table, reducing the
interest broadcast storm. However, the exchanged information metrics may not be sufficient for
efficient forwarder selection, and the mechanism is tested in a low-density vehicle scenario.
Similarly, [15] proposes a mechanism where each node maintains a neighbour list, including
velocity, distance, and neighbour IDs obtained through beacon exchanges. The forwarder is
selected based on the relative distances from the relay node to the consumer and provider nodes.
However, this mechanism experiences higher transmission delays, and the results are not
validated by comparing them with the naive VNDN architecture.
In [16], a counter-based forwarding approach is proposed, setting a limit on the maximum
number of hops an interest packet can take. The counter decreases by 1 for each hop, and when it
reaches zero, the node drops the packet, thereby reducing the interest broadcast storm. The
lifetime of entries in the PIT is calculated through an adaptive procedure to minimize packet loss,
triggering retransmission if the lifetime lapses. However, the hop count value may be affected
due to the lack of consideration for content mobility.
Authors in [17] propose a forwarder scheme based on link stability, where vehicles consider
information such as the provider/forwarder's velocity, direction, and location to calculate
connectivity time. The scheme selects the path with the highest stability, transmitting data
packets in the same path but in the opposite direction. The authors in [18] also propose the
transmission of interest packets based on priority. However, the efficiency of these schemes is
not validated in low-density scenarios.
In [19], a link stability-based scheme is proposed, improving upon previous methods by
incorporating a local threshold value. Vehicles calculate the link lifetime value based on motion
metrics and forward the interest packet only if the value exceeds the local threshold. If the value
falls below the threshold, the packet is dropped. Notably, this mechanism does not consider the
non-linear path during link lifetime calculation.
While existing research on content or interest forwarding mechanisms has focused on mitigating
interest broadcast storms or reducing packet duplication, this paper proposes a novel scheme that
addresses both issues. The proposed approach involves selecting a single node as the interest
forwarder, mitigating interest broadcast problems and reducing the duplication of data packets by
hop count value.
3. RESEARCH CONTRIBUTION
The research contribution of the proposed work can be summarized as follows:
A novel Hop Count based Interest Selection and Content Forwarding (HISCF) scheme for VNDN
is developed. The HISCF scheme aims to mitigate interest broadcast storm and reduce data
packet duplication by introducing improvements in interest selection procedure and content
dissemination process. Key metrics such as hop count and ISR are used in selection of interest
forwarder. Hop count limit and neighbour information are used in data forwarding decisions.
The HISCF scheme is evaluated by considering parameters such as Data Packet Replication
Count, total number of interest packets forwarded, Interest Retrieval Time (IRT) and routing
overhead. In addition, the HISCF scheme is compared against naïve VNDN to determine the
effectiveness of the proposed approach. The proposed scheme opens up numerous possibilities in
the field of data dissemination and content retrieval for VNDN.

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4. HOP COUNT BASED INTEREST SELECTION AND CONTENT FORWARDING
SCHEME
This section presents the proposed Hop Count based Interest Selection and Content Forwarding
(HISCF) mechanism for VNDN. In naïve VNDN approach, due to broadcast nature of interest
packets, redundant copies are generated. The neighbouring nodes which receive these interest
packets, reply with data packets if they are intended producer or have the data stored in cache.
This process further aggravates congestion in the network since packet size of content is larger
compared to requesting interest. To mitigate both these issues which are interdependent, HISCF
scheme aims to reduce interest flooding and avoid processing of redundant copies of data
packets, thereby reducing network congestion.
Interest forwarder selection and data forwarding constitute the elementary parts of the HISCF
mechanism. Hop count and ISR are the two criteria based on which a vehicle is assigned to
forward an interest packet. Beacon messages containing information related to CIT are
exchanged among neighbouring vehicles periodically. Vehicles which have satisfied contents in
the past 3 seconds update the name of the content along with vehicle IDs and their hop count. In
addition, ISR is an important metric which gives the ratio of number of satisfied interests to the
number of received interests. A vehicle is designated to forward the interest based on lower hop
count and higher ISR values obtained from CIT instead of broadcasting it to all the neighbouring
vehicles which leads to interest broadcast storms.
Figure 1. Interest Forwarder Selection in HISCF Scheme
The series of events that take place when a node receives an interest packet is listed in Algorithm
1. The node scans its Content Store (CS) data structure for matching content after receiving an
interest. The node responds with the data packet if the matching content is identified. The
Pending Interest Table (PIT) is examined next, if the requested content is not found in CS. The
FACE ID of the incoming interest request is appended to the PIT list and the interest is dropped
indicating a previous entry for the same content. If there is an absence of the PIT entry, the hop
count value in the interest packet is incremented by 1 and corresponding entry is made. The naïve
VNDN works in a similar way till this step and broadcasts the interest packet to all neighbouring
nodes after PIT entry. However, HISCF uses information in CIT to select the interest forwarder
instead of broadcasting. A sample CIT is shown in Table 1. The node checks if any one of the
neighbours have satisfied the requested interest and selects the node if there is an entry present.
The node selection criteria are used if there are multiple nodes in CIT which have satisfied the
interest. A node with least hop count value and higher ISR is selected to forward the interest
packet, and thereby increasing the likelihood of fetching the required content and reducing
broadcast storms.
Table 1. A Sample Content Information Table

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Content
Name
Vehicle
ID
Hop
Count
Interest
Satisfaction
Ratio (ISR)
C1 V1 1 50
C2 V1, V2,
V3,
1,3,6 50,70,80
C3 V3, V4 6,1 80,70
.
.
Cn V3, Vn 6,0 80
The series of events that take place when a node receives a data packet is listed in Algorithm 2.
Every node in the network maintains a Neighbour Data List (NDL) by periodically exchanging
control packets to facilitate the content forwarding in HISCF. Table 2 illustrates a sample NDL.
The node scans the PIT for an entry, whenever it receives a data packet. If an entry is not
identified, the data packet is discarded from the network since it has not reached the intended
receiver or forwarder. In addition, Hop Count Limit (HCL) value is examined by the node, if the
value is exhausted, the packet is discarded and prevented from further participation in the
network. In case the content entry is present in PIT and node ID matches the FACE ID, the data
packet has successfully reached the destination. Alternatively, if the FACE ID does not match,
the node examines the NDL and forwards the data packet to the node that has a corresponding
entry in PIT.
Table 2. A Sample Neighbour Data List
Vehicle ID Hop
Count
Pending
Interests
V1 3 I1, I2
V2 1 I1, I3
V3 5 I2,I4
.
.
.
Vn 3 I3,I1,I4
Figure 2. Content Forwarder Selection in HISCF mechanism

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ALGORITHM 1: WHEN INTEREST PACKET IS RECEIVED AT THE NODE
1 If content present in CS, then:
2 Prepare Data Packet using Name, Content, Meta Info etc…
3 Send Data Packet
4 Else:
5 If name present in PIT, then:
6 Include Face ID in PIT
7 Drop Interest
8 Else:
9 HC = HC +1
10 Update HC in PIT
11 Fetch CIT
12 If CN matches any content in CIT, then:
13 Fetch the Vid of matching CN
14 If HC of content matching Vid >1:
15 Select Vid with least HC
16 If HC of Vids are equal then:
17 Select Vid with highest ISR
18 Forward interest to selected Vid
19 Else:
21 Else:
23 Else:
24 Include Face ID in PIT
25 Drop Interest
HC: Hop Count
CIT: Content Information Table
Vid: Vehicle Identity
CN: Content Name
ALGORITHM 2: WHEN DATA PACKET IS RECEIVED AT THE NODE
1 If CN in PIT, then:
2 If Face matched with node then:
3 Cache the data; Data successfully delivered to requested node
4 Else:
5 If HCL ≥ 0 Then:
6 Fetch HCs of all Vni having Interest in PIT via NDL
7 While Interest is present in PIT fetched via NDL:
8 If HC of Vni >1 then:
9 Update HCL = HCL + HC
10 Send Data to Vni
11 Remove Vni entry from PIT
12 Else:
13 Update HCL = HCL -1
14 Send data to Vni
15 Remove Vni entry from PIT
16 Else:
17 Drop data packet
18 Else:
19 Drop data packet
HCL: Hop Count Limit

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HC: Hop Count
NDL: Neighbour Data List
Vni: ID of neighbouring vehicle from NDL
5. SIMULATION ENVIRONMENT
The simulation platform set up for analysing the proposed HISCF mechanism is outlined in this
section. Network Simulator (ns-3.30) is used as a simulation tool. The ndnSIM module is
integrated to facilitate modelling of data structures such as FIB, PIT and CS, which are essential
for NDN [20]. Traffic and mobility patterns are generated by SUMO (Simulation of Urban
Mobility) package. [21]
Each vehicle is set a transmission range of up to 500 meters. The average size of beacon
messages exchanged to maintain the CIT and NDL tables are 2 KB and preliminary analysis of
results indicate 8 beacons can be exchanged among vehicles per second. Since the sizes of CIT
and NDL are lesser than beacon size, these tables are eventually updated at rate of 8 times per
second. The critical simulation parameters used to analyse the performance of HISCF in varying
scenarios are summarized in Table 3.
Table 3. Simulation Parameters
Parameter Values
Network Simulator Ns-3.29
Simulation Area 2 Lane, two-way traffic
street of 4.8 Km
Simulation time 300s
Mobility Model Random Walk
Traffic Generator SUMO
Transmission Power 6.198mW
Frequency Band 5.9GHz
Number of vehicle nodes 60-120
Vehicle speed 60 km/hr -120 km/hr
Producer nodes 10% of the total nodes
Number of RSU 3
Packet Size 10 kb to 90 kb
Average beacon size 2 kb
6. PERFORMANCE EVALUATION
The performance evaluation aims to assess the effectiveness of the HISCF scheme in mitigating
the issues associated with naïve VNDN, such as data packet duplication and interest broadcast
storms. By comparing the performance metrics of HISCF with the traditional VNDN approach,
the improvements achieved by the proposed scheme can be determined.
The parameter DPRC provides insights into the reduction in data packet duplication achieved by
the HISCF scheme. A lower DPRC value indicates a more efficient forwarding mechanism, as
fewer redundant data packets are processed by the network. Additionally, the total number of
interest packets forwarded reflects the efficiency of the interest forwarding process. By analysing

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this metric, the effectiveness of the HISCF scheme in reducing unnecessary interest packet
dissemination can be assessed.
Another crucial performance metric is the average Interest Response Time (IRT), which
measures the time taken for an interest packet to be satisfied from the instance it is generated. A
lower IRT signifies faster content retrieval, indicating improved network efficiency and reduced
content delivery latency.
To gain a comprehensive understanding of the proposed HISCF scheme's performance, the
evaluation considers varying vehicle speeds and network densities. Vehicle speed plays a
significant role in the network's dynamics, influencing packet forwarding decisions and overall
content dissemination. Likewise, network density influences the intensity of packet interactions
and the potential for congestion. Analysing the performance under different scenarios allows for
the evaluation of the scheme's robustness and its ability to adapt to diverse vehicular network
conditions.
6.1. Data Packet Replication Count (DPRC)
The total number of data packet copies processed in the network for every satisfied interest is
determined by DPRC. An ideal network should have low DPRC, since high DPRC can contribute
for congestion. The proposed HISCF significantly reduces the DPRC as compared to the naïve
VNDN strategy in terms varying network size. The speed of vehicles is maintained a constant 70
km/hr and the number of vehicles is varied from 60 to 110 in step size of 10. It can be observed
from Fig. 1, that DPRC is directly proportional to network size. This can be attributed to the
increase in duplication of data packet copies with vehicle density. In the next scenario shown in
Fig. 2, the number of vehicles is maintained constant at 70, and the speed of vehicles is varied
from 60 to 110 km/hr. It can be observed that, although DPRC increases with speed, it is not very
significant and there is no clear corelation between them.
HISCF outperforms naïve VNDN in both the scenarios of varying vehicle speeds and network
size. This is mainly due to the modification of content forwarding scheme in HISCF, which does
not broadcast or reply to every incoming request. The scheme sends data packet to only a
potential forwarder by analysing the data from NDL table and also the respective HCL value.
These results validate the efficiency of the HISCF scheme in reducing the processing redundant
data packets, thereby reducing the chances of network congestion and improving the overall
efficiency.
Figure 3. DPRC vs Number of vehicles

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Figure 4. DPRC vs Vehicle speed
6.2. Total Number of Interest Packets Forwarded
A key measure of the effectiveness and performance of the forwarding schemes is the total
number of interests forwarded in the network. The Fig. 3 and Fig. 4, display the performance
comparison of naïve VNDN and HISCF against varying network size and vehicle speeds
respectively.
In the first scenario, the network density is increased and the other parameters such as vehicle
speed, packet sizes and number of chunks are kept constant. It can be observed from Fig. 3, that
the number of interest packet forwarded increases with network density for both naïve VNDN
and HISCF. However, from Fig. 4, it is evident that vehicle speeds do not have significant impact
on this metric.
The HISCF scheme reduces unnecessary forwarding of interest packets unlike naïve VNDN that
broadcasts interest packets to all the neighbouring nodes. The interest selection algorithm in
HISCF designates only a single vehicle to forward the interest in the network based on the
analysis of data from CIT such as matching content name, hop count and ISR. This substantially
lowers the interests forwarded in the network, furthermore mitigating the interest broadcast
storms and improving the overall network performance.
Figure 5. Number of Interest Packets forwarded Vs Number of vehicles

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Figure 6. Number of Interest Packets forwarded Vs Vehicle speed
6.3. Interest Response Time
The IRT is a critical metric that measures the amount of time the network takes to satisfy an
interest packet. Similar to DPRC and total number of interest packets forwarded in the network,
IRT is also analysed by varying the vehicle speeds and network density, to get a better insight of
the performance.
The results from Fig. 5 indicate that the delay in satisfying the interest also increases with
network density. The packets travel larger distance and processing time at each node contributes
to this additional delay. Similarly, from Fig. 6, it can be observed that, there is notable increase in
the delay with vehicle speeds. At high speeds, due to intermittent connectivity, the complete
packet transmission is not achievable. The packets have to be retransmitted in such scenarios and
thus there is delay in satisfying the interest packet.
However, the HISCF scheme performs better in both the scenarios as compared to the naïve
VNDN. Efficient content forwarding mechanism is one of the primary aspects that contributes to
this superior performance and thereby improving the overall performance of the network. In
addition, there is less chances of congestion due to mitigation of interest broadcast storms and
reduction of redundant data packets. These factors overall aid the interest packet in reaching the
producer soon and fetch the data packet.
Figure 7. IRT Vs Number of vehicles

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Figure 8. IRT Vs Vehicle speed
6.4. Routing overhead
The number of control packets required to successfully deliver one data packet is referred as
routing overhead. It is an important metric that quantifies the overhead introduced in the network
for routing the data packet efficiently. To analyse this parameter better, the network density and
vehicle mobility is varied.
A comparison of naïve VNDN approach and HISCF by varying the network density is shown in
Fig. 7. It is evident that, routing overhead increases with number of vehicles, since additional
control packets are required to maintain the routes. Similar behaviour can be observed form Fig.
8, where vehicle speed also has a direct corelation with routing overhead. At higher speeds, due
to intermittent connectivity, network may experience packet loss and transmission errors. In
addition, fading of signal, link failures occur at high speeds, resulting in packet loss. The number
of control packets required to recover from these situations and maintain routes is high, thus
contributing to increasing routing overhead.
Naïve VNDN outperforms the proposed HISCF mechanism in terms of routing overhead for both
the scenarios. Naïve VNDN approach is simple and straight forward. It does not generate
additional control packets to forward interest or data packets. Very minimal data structures such
as PIT, CS and FIB are used to facilitate the operations. However, HISCF approach maintains
two additional data structures NDL and CIT. Many control packets are required to maintain and
update these tables periodically. All these factors contribute to increased overhead of the HISCF
mechanism.
Figure 9. Routing overhead Vs Number of vehicles

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Figure 10. Routing overhead Vs Vehicle speed
The findings from the evaluation of all these metrics are summarized in Table 4.
Table 4. Summary of Simulation Results
Performance Metrics Results and Observations
Data Packet Replication Count
(DPRC)
Due to selective forwarding of interest and data packets
in proposed HISCF, redundant copies of data are
reduced significantly by an average of 90% in both
scenarios of varying network size and vehicle speeds.
Total number of interest
packets forwarded
HISCF forwards only selective interest based on ISR and
CIT, instead of broadcasting interests by naïve VNDN.
This has significant impact and reduces the interest
packets forwarded by an average of 84%.
Interest Response Time (IRT) The efficient forwarding technique of HISCF ensures
less delay in satisfying the interests. The response time is
reduced by an average of 18% in both the cases of
varying network size and vehicle speed.
Routing overhead HISCF scheme uses data from additional data structures
such as CIT, NDL and involves decision making
parameters such as ISR, hop count, hop count limit, thus
increasing the number of control packets involved in
data transmission process. The routing overhead as a
result increases by an average of 42% across both the
scenarios of varying network size and vehicle speed.
7. CONCLUSION
The proposed HISCF mechanism counters the challenges posed by naïve VNDN approach such
as interest flooding and processing of redundant data packets. HISCF approach consistently
outperformed the naïve VNDN across various scenarios and critical parameters such as DPRC,
average IRT and total number of interests forwarded.
The HISCF mechanism’s ability to reduce data packet duplication against varying network size
and vehicle speeds is evident through DPRC metric. The effectiveness of the interest forwarding
scheme was demonstrated by the significant reduction in the total number of interest packets
forwarded in the network as compared to naïve VNDN. Combined efficiency of both interest and
data forwarding schemes was noticeable through the reduction in the average response time for

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an interest packet in comparison with the naïve approach. However, the process of selecting the
interest forwarder, maintaining CIT, NDL and analysis of HCL generates additional control
packets, thus increasing the routing overhead. Other network parameters such as scalability,
bandwidth utilization and energy consumption might be impacted by increased overhead.
Overall, the analysis of results obtained from this work indicate the effectiveness of the
forwarding techniques of the proposed HISCF approach. These results support the realization of
intelligent transport systems and contributes to the scientific advancement of VNDN.
Future research directions include optimization of the developed HISCF scheme by considering
other network parameters such as content source mobility, network dynamics and scalability. In
addition, incorporating security and privacy related techniques to the HISCF mechanism can be
investigated.
CONFLICTS OF INTEREST
The authors declare no conflict of interest
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13.
AUTHORS
Nithin Rao R is currently working as an Assistant Professor in the Department of Computer
Science and Engineering, Ramaiah University of Applied Sciences, Bangalore. He is
currently pursuing Ph.D in the field of vehicle networks. He obtained his M.Tech degree from
Ramaiah University of Applied Sciences in 2016. He has over 7 years of work experience in
industry, teaching and research. He has published 8 papers in reputed conferences and
journals.
Dr. Rinki Sharma is presently working as a Professor in the Department of Computer
Science and Engineering, Ramaiah University of Applied Sciences, Bangalore. She obtained
her Ph.D from Coventry University, United Kingdom in the year 2015. The title of her
doctoral dissertation is Simulation studies on effects of dual polarization and directivity of
antennas on the performance of MANETs. She has over 16 years of work experience in industry, teaching
and research. Apart from teaching and research she has held other vital positions in the Ramaiah University
of Applied Sciences, Bangalore. She has been granted 5 international patents, has published 5 book
chapters, and 15 papers in reputed conferences and journals.

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