BEST FINAL YEAR PROJECT IEEE 2015 BY SPECTRUM SOLUTIONS PONDICHERRY

2
IEEE 2015 PROJECTS
CSE/IT/IS/ECE/E&I/EEE/MECHANICAL DEPARTMENT
SPECTRUM SOLUTIONS
COMPANY DETAIL:
SPECTRUM SOLUTIONS is a Pondicherry based R&D firm which always looks forward in the field
of science and technology to provide best technical support for the final year students. SPECTRUM has a great
team of technical experts for the design development of Electronic and software Systems using Embedded,
MATLAB, Java, Dot Net Technology.
SPECTRUM SOLUTIONS always concentrate us to provide quality products for various institutions
and students. We offer the projects in all domains for the students of Diploma, B.Tech/B.E
,M.Tech/M.E,MS,BCA,MCA etc. Our major concern is in the field of technical education to bridge the gap
between Industry and Academics. We are always in the good eyes of the Educational Institutions in India to
provide training & projects in Embedded Systems MATLAB and software technologies. We also provide
interview training for free of cost. We never stop in going that extra mile ahead in providing greater value to
own ideas of students, may it be in terms of providing adequate workforce proficient in highly application cost
oriented Embedded Systems or Software Systems.
EDUCATIONAL PARTNER:
International Journal of Research in Engineering and Advanced Technology (IJREAT)

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OUR FEATURES FOR STUDENTS:
1. 10 Days technical Project classes with practical.
2. 5 Days personality development classes.
3. Paper presentation guidance.
4. Individual Certificates.
5. Weekend Classes.
6. Students help with their job search queries.
7. Lower project cost without hampering the quality.
8. Project delivery on time.
POJECTS FOR - B.Tech/B.E, M.Tech/M.E,M.S,DIPLOMA,BCA,MCA
MAIL ID : spectrumpondichery@gmail.com
WEBSITE : www.spectrumpondicherry.blogspot.in/
FACEBOOK : https://www.facebook.com/pages/Spectrum-Solutions/548721691855495?ref=hl
LANDLINE NO : 0413-2618850
MOBILE NO : 9381775781
ADDRESS : SPECTRUM SOLUTIONS
E-Mail: spectrumpondicherry@gmail.com
Contact: 0413-2618850, 9381775781
No-66,1st Floor
Near Rogini Nagar Govt Hospital
Poornankuppam
Pondicherry-07

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Appendix
Department Technology Page Number
1. CSE/IT/IS JAVA 5-22
2. CSE/IT/IS NS-2 22-30
3. ECE/EEE/MECHANICAL EMBEDDED 32-40
4. ECE/CSE MATLAB (Command) 42-64
5. EEE/ECE MATLAB (Simulink) 66-72
6. TRAINING PAMPHLET EMBEDDED,MATLAB,NETWORKING
NETWORK SECURITY,PCB
DESIGNING
72-END

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APPENDIX:
D DotNet
J Java
IP Image Processing
DM DataMining
NS Network Security
NW Networking
MC Mobile Computing
SC Service Computing
PD Parallel distribution
CC Cloud Computing
S.No Code Title Year Abstract
1 JCCZ-01 AuditFree
Cloud Storage
via Deniable
Attribute
based
Encryption
IEEE-2015 Cloud storage services have become increasingly popular.
Because of the importance of privacy, many cloud storage
encryption schemes have been proposed to protect data from
those who do not have access. All such schemes assumed that
cloud storage providers are safe and cannot be hacked;
however, in practice, some authorities (i.e., coercers) may
force cloud storage providers to reveal user secrets or
confidential data on the cloud, thus altogether circumventing
storage encryption schemes. In this paper, we present our
design for a new cloud storage encryption scheme that
enables cloud storage providers to create convincing fake
user secrets to protect user privacy. Since coercers cannot
tell if obtained secrets are true or not, the cloud storage
providers ensure that user privacy is still securely protected.

6
2 JCCZ-02 CHARM A
Cost efficient
Multi cloud
Data Hosting
Scheme with
High
Availability
IEEE-2015 Nowadays, more and more enterprises and organizations are
hosting their data into the cloud, in order to reduce the IT
maintenance cost and enhance the data reliability. However,
facing the numerous cloud vendors as well as their
heterogenous pricing policies, customers may well be
perplexed with which cloud(s) are suitable for storing their
data and what hosting strategy is cheaper. The general status
quo is that customers usually put their data into a single
cloud (which is subject to the vendor lock-in risk) and then
simply trust to luck. Based on comprehensive analysis of
various state-of-the-art cloud vendors, this paper proposes a
novel data hosting scheme (named CHARM) which
integrates two key functions desired. The first is selecting
several suitable clouds and an appropriate redundancy
strategy to store data with minimized monetary cost and
guaranteed availability. The second is triggering a transition
process to re-distribute data according to the variations of
data access pattern and pricing of clouds. We evaluate the
performance of CHARM using both trace-driven
simulations and prototype experiments. The results show
that compared with the major existing schemes, CHARM
not only saves around 20% of monetary cost but also
exhibits sound adaptability to data and price adjustments.
Index Terms—Multi-cloud; data hosting; cloud storage.
3 JCCZ-03 Enabling
Cloud
Storage
Auditing with
Key
Exposure
Resistance
IEEE-2015 Cloud storage auditing is viewed as an important service to
verify the integrity of the data in public cloud. Current
auditing protocols are all based on the assumption that the
client’s secret key for auditing is absolutely secure. However,
such assumption may not always be held, due to the possibly
weak sense of security and/or low security settings at the
client. If such a secret key for auditing is exposed, most of
the current auditing protocols would inevitably become
unable to work. In this paper, we focus on this new aspect of
cloud storage auditing. We investigate how to reduce the
damage of the client’s key exposure in cloud storage
auditing, and give the first practical solution for this new
problem setting. We formalize the definition and the security
model of auditing protocol with key-exposure resilience and
propose such a protocol. In our design, we employ the binary
tree structure and the pre-order traversal technique to
update the secret keys for the client. We also develop a novel
authenticator construction to support the forward security
and the property of blockless verifiability. The security proof
and the performance analysis show that our proposed
protocol is secure and efficient.

7
4 JCCZ-04 MobiContext_
Cloud
IEEE-2015 In recent years, recommendation systems have seen
significant evolution in the field of knowledge engineering.
Most of the existing recommendation systems based their
models on collaborative filtering approaches that make them
simple to implement. However, performance of most of the
existing collaborative filtering based recommendation system
suffers due to the challenges, such as: (a) cold start, (b) data
sparseness, and (c) scalability. Moreover, recommendation
problem is often characterized by the presence of many
conflicting objectives or decision variables, such as users’
preferences and venue closeness. In this paper, we proposed
MobiContext, a hybrid cloud based Bi Objective
Recommendation Framework (BORF) for mobile social
networks. The MobiContext utilizes multi objective
optimization techniques to generate personalized
recommendations. To address the issues pertaining to cold
start and data sparseness, the BORF performs data
preprocessing by using the Hub Average (HA) inference
model. Moreover, the Weighted Sum Approach (WSA) is
implemented for scalar optimization and an evolutionary
algorithm (NSGAII) is applied for vector optimization to
provide optimal suggestions to the users about a venue.
5 JCCZ-05 OPoR
Enabling Proof
of
Retrievability
in Cloud
Computing
with Resource
Constrained
Devices
IEEE-2015 Cloud Computing moves the application software and
databases to the centralized large data centers, where the
management of the data and services may not be fully
trustworthy. In this work, we study the problem of ensuring
the integrity of data storage in Cloud Computing. To reduce
the computational cost at user side during the integrity
verification of their data, the notion of public verifiability
has been proposed. However, the challenge is that the
computational burden is too huge for the users with
resource-constrained devices to compute the public
authentication tags of file blocks. To tackle the challenge, we
propose OPoR, a new cloud storage scheme involving a cloud
storage server and a cloud audit server, where the latter is
assumed to be semi-honest. In particular, we consider the
task of allowing the cloud audit server, on behalf of the cloud
users, to pre-process the data before uploading to the cloud
storage server and later verifying the data integrity. OPoR
outsources the heavy computation of the tag generation to
the cloud audit server and eliminates the involvement of user
in the auditing and in the preprocessing phases.
Furthermore, we strengthen the Proof of Retrievabiliy (PoR)
model to support dynamic data operations, as well as ensure
security against reset attacks launched by the cloud storage
server in the upload phase.

8
6 JCCZ-06 Privacy-
Preserving
Public
Auditing for
IEEE-2015 To protect outsourced data in cloud storage against
corruptions, adding fault tolerance to cloud storage together
with data integrity checking and failure reparation becomes
critical. Recently, regenerating codes have gained popularity
due to their lower repair bandwidth while providing fault
tolerance. Existing remote checking methods for
regenerating-coded data only provide private auditing,
requiring data owners to always stay online and handle
auditing, as well as repairing, which is sometimes
impractical. In this paper, we propose a public auditing
scheme for the regenerating-code-based cloud storage. To
solve the regeneration problem of failed authenticators in the
absence of data owners, we introduce a proxy, which is
privileged to regenerate the authenticators, into the
traditional public auditing system model. Moreover, we
design a novel public verifiable authenticator, which is
generated by a couple of keys and can be regenerated using
partial keys. Thus, our scheme can completely release data
owners from online burden. In addition, we randomize the
encode coefficients with a pseudorandom function to
preserve data privacy. Extensive security analysis shows that
our scheme is provable secure under random oracle model
and experimental evaluation indicates that our scheme is
highly efficient .
7 JCCZ-07 Profit
Maximization
Scheme
IEEE-2015 As an effective and efficient way to provide computing
resources and services to customers on demand, cloud
computing has become more and more popular. From cloud
service providers’ perspective, profit is one of the most
important considerations, and it is mainly determined by the
configuration of a cloud service platform under given
market demand. However, a single long-term renting scheme
is usually adopted to configure a cloud platform, which
cannot guarantee the service quality but leads to serious
resource waste. In this paper, a double resource renting
scheme is designed firstly in which short-term renting and
long-term renting are combined aiming at the existing issues.
This double renting scheme can effectively guarantee the
quality of service of all requests and reduce the resource
waste greatly. Secondly, a service system is considered as an
M/M/m+D queuing model and the performance indicators
that affect the profit of our double renting scheme are
analyzed, e.g., the average charge, the ratio of requests that
need temporary servers, and so forth. Thirdly, a profit
maximization problem is formulated for the double renting
scheme and the optimized configuration of a cloud platform
is obtained by solving the profit maximization problem.

9
8 JCCZ-08 Reactive
Resource
Provisioning
Heuristics for
IEEE-2015 The need for low latency analysis over high-velocity data
streams motivates the need for distributed continuous
dataflow systems. Contemporary stream processing systems
use simple techniques to scale on elastic cloud resources to
handle variable data rates. However, application QoS is also
impacted by variability in resource performance exhibited
by clouds and hence necessitates ―dynamic dataflows‖ which
utilize alternate tasks as additional control over the
dataflow’s cost and QoS. Further, we formalize an
optimization problem to represent deployment and runtime
resource provisioning that allows us to balance the
application’s QoS, value, and the resource cost. We propose
two greedy heuristics, centralized and sharded, based on the
variable-sized bin packing algorithm and compare against a
Genetic Algorithm (GA) based heuristic that gives a near-
optimal solution. A large-scale simulation study, using the
Linear Road Benchmark and VM performance traces from
the AWS public cloud, shows that while GA-based heuristic
provides a better quality schedule, the greedy heuristics are
more practical, and can intelligently utilize cloud elasticity to
mitigate the effect of variability, both in input data rates and
cloud resource performance, to meet the QoS of fast data
applications.
9 JCCZ-09 SAE Toward
Efficient Cloud
Data Analysis
IEEE-2015 Social network analysis is used to extract features of human
communities and proves to be very instrumental in a variety
of scientific domains. The dataset of a social network is often
so large that a cloud data analysis service, in which the
computation is performed on a parallel platform in the
could, becomes a good choice for researchers not
experienced in parallel programming. In the cloud, a
primary challenge to efficient data analysis is the
computation and communication skew (i.e., load imbalance)
among computers caused by humanity’s group behavior
(e.g., bandwagon effect). Traditional load balancing
techniques either require significant effort to re-balance
loads on the nodes, or cannot well cope with stragglers. In
this paper, we propose a general straggler-aware execution
approach, SAE, to support the analysis service in the cloud.
It offers a novel computational decomposition method that
factors straggling feature extraction processes into more
fine-grained sub-processes, which are then distributed over
clusters of computers for parallel execution. Experimental
results show that SAE can speed up the analysis by up to
1.77 times compared with state-of-the-art solutions.

10
10 JCCZ-10 Service
Operatorawar
e Trust
Scheme for
Resource
IEEE-2015 This paper proposes a service operator-aware trust scheme
(SOTS) for resource matchmaking across multiple clouds.
Through analyzing the built-in relationship between the
users, the broker, and the service resources, this paper
proposes a middleware framework of trust management that
can effectively reduce user burden and improve system
dependability. Based on multi-dimensional resource service
operators, we model the problem of trust evaluation as a
process of multi-attribute decision-making, and develop an
adaptive trust evaluation approach based on information
entropy theory. This adaptive approach can overcome the
limitations of traditional trust schemes, whereby the trusted
operators are weighted manually or subjectively. As a result,
using SOTS, the broker can efficiently and accurately
prepare the most trusted resources in advance, and thus
provide more dependable resources to users. Our
experiments yield interesting and meaningful observations
that can facilitate the effective utilization of SOTS in a large-
scale multi-cloud environment.
11 JCCZ-11 Towards
Optimized
Fine Grained
Pricing of
IEEE-2015 Although many pricing schemes in IaaS platform are
already proposed with pay-as-you-go and subscription/spot
market policy to guarantee service level agreement, it is still
inevitable to suffer from wasteful payment because of
coarsegrained pricing scheme. In this paper, we investigate
an optimized fine-grained and fair pricing scheme. Two
tough issues are addressed: (1) the profits of resource
providers and customers often contradict mutually; (2) VM-
maintenance overhead like startup cost is often too huge to
be neglected. Not only can we derive an optimal price in the
acceptable price range that satisfies both customers and
providers simultaneously, but we also find a best-fit billing
cycle to maximize social welfare (i.e., the sum of the cost
reductions for all customers and the revenue gained by the
provider). We carefully evaluate the proposed optimized
fine-grained pricing scheme with two large-scale real-world
production traces (one from Grid Workload Archive and the
other from Google data center). We compare the new
scheme to classic coarse-grained hourly pricing scheme in
experiments and find that customers and providers can both
benefit from our new approach. The maximum social
welfare can be increased up to 72:98% and 48:15% with
respect to DAS-2 trace and Google trace respectively.

11
12 JCCZ-12 Understanding
the
Performance
and
IEEE-2015 Commercial clouds bring a great opportunity to the
scientific computing area. Scientific applications usually
require significant resources, however not all scientists have
access to sufficien high end computing systems. Cloud
computing has gained the attention of scientists as a
competitive resource to run HPC applications at a
potentially lower cost. But as DIfferent infrastructure, it is
unclear whether clouds are capable of running scientific
applications with a reasonable performance per money
spent. This work provides a comprehensive evaluation of
EC2 cloud in different aspects. We first analyze the
potentials of the cloud by evaluating the raw performance of
different services of AWS such as compute, memory,
network and I /O. Based on the findings on the raw
performance, we then evaluate the performance of the
scientific applications running in the cloud. Finally, we
compare the performance of AWS with a private cloud, in
order to find the root cause of its limitations while running
scientific applications. This paper aims to assess the ability of
the cloud to perform well, as well as to evaluate the cost of
the cloud in terms of both raw performance and scientific
applications performance Furthermore, we evaluate other
services including S3, EBS and DynamoDB among many
AWS services in order to assess the abilities of those to be
used by scientific applications and frameworks. We also
evaluate a real scientific compng application through the
Swift parallel scripting System at scale.
13 JDMZ-13 Anonymizing
Collections of
Tree Struct
Data- Data
Engg
IEEE-2015 Collections of real-world data usually have implicit or
explicit structural relations. For example, databases link
records through foreign keys, and XML documents express
associations between different values through syntax.
Privacy preservation, until now, has focused either on data
with a very simple structure, e.g. relational tables, or on data
with very complex structure e.g. social network graphs, but
has ignored intermediate cases, which are the most frequent
in practice. In this work, we focus on tree structured data.
Such data stem from various applications, even when the
structure is not directly reflected in the syntax, e.g. XML
documents. A characteristic case is a database where
information about a single person is scattered amongst
different tables that are associated through foreign keys. The
paper defines k(m;n)-anonymity, which provides protection
against identity disclosure and proposes a greedy
anonymization heuristic that is able to sanitize large
datasets. The algorithm and the quality of the anonymization
are evaluated experimentally.

12
14 JDMZ-14 FOCS Fast
Overlapped
Community
Search
IEEE-2015 However, most of the existing algorithms that detect
overlapping communities assume that the communities are
denser than their surrounding regions and falsely identify
overlaps as communities. Further, many of these algorithms
are computationally demanding and thus, do not scale
reasonably with varying network sizes. In this article, we
propose FOCS (Fast Overlapped Community Search), an
algorithm that accounts for local connectedness in order to
identify overlapped communities. FOCS is shown to be
linear in number of edges and nodes. It additionally gains in
speed via simultaneous selection of multiple near-best
communities rather than merely the best, at each iteration.
FOCS outperforms some popular overlapped community
finding algorithms in terms of
15 JDMZ-15 Making Digital
Artifacts_Data
Engg
IEEE-2015 The current Web has no general mechanisms to make digital
artifacts — such as datasets, code, texts, and images —
verifiable and permanent. For digital artifacts that are
supposed to be immutable, there is moreover no commonly
accepted method to enforce this immutability. These
shortcomings have a serious negative impact on the ability to
reproduce the results of processes that rely onWeb
resources, which in turn heavily impacts areas such as
science where reproducibility is important. To solve this
problem, we propose trusty URIs containing cryptographic
hash values. We show how trusty URIs can be used for the
verification of digital artifacts, in a manner that is
independent of the serialization format in the case of
structured data files such as nano publications.
16 JDMZ-16 Privacy Policy
Inference of
User-Uploaded
IEEE-2015 With the increasing volume of images users share through
social sites, maintaining privacy has become a major
problem, as demonstrated by a recent wave of publicized
incidents where users inadvertently shared personal
information. In light of these incidents, the need of tools to
help users control access to their shared content is apparent.
Toward addressing this need, we propose an Adaptive
Privacy Policy Prediction (A3P) system to help users
compose privacy settings for their images. We propose a
two-level framework which according to the user’s available
history on the site, determines the best available privacy
policy for the user’s images being uploaded. Our solution
relies on an image classification framework for image
categories which may be associated with similar policies, and
on a policy prediction algorithm to automatically generate a
policy for each newly uploaded image, also according to
users’ social features.

13
17 JDMZ-17 RRW - A
Robust and
Reversible
Watermarking
IEEE-2015 Advancement in information technology is playing an
increasing role in the use of information systems comprising
relational databases. These databases are used effectively in
collaborative environments for information extraction;
consequently, they are vulnerable to security threats
concerning ownership rights and data tampering.
Watermarking is advocated to enforce ownership rights over
shared relational data and for providing a means for
tackling data tampering. When ownership rights are
enforced using watermarking, the underlying data
undergoes certain modifications; as a result of which, the
data quality gets compromised. Reversible watermarking is
employed to ensure data quality along-with data recovery.
However, such techniques are usually not robust against
malicious attacks and do not provide any mechanism to
selectively watermark a particular attribute by taking into
account its role in knowledge discovery. Therefore,
reversible watermarking is required that ensures; (i)
watermark encoding and decoding by accounting for the role
of all the features in knowledge discovery; and, (ii) original
data recovery in the presence of active malicious attacks.
18 JDMZ-18 Sparsity
Learning
Formulations
for Mining
IEEE-2015 Traditional clustering and feature selection methods
consider the data matrix as static. However, the data
matrices evolve smoothly over time in many applications. A
simple approach to learn from these time-evolving data
matrices is to analyze them separately. Such strategy ignores
the time-dependent nature of the underlying data. In this
paper, we propose two formulations for evolutionary co-
clustering and feature selection based on the fused Lasso
regularization. The evolutionary co-clustering formulation is
able to identify smoothly varying hidden block structures
embedded into the matrices along the temporal dimension.
Our formulation is very flexible and allows for imposing
smoothness constraints over only one dimension of the data
matrices. The evolutionary feature selection formulation can
uncover shared features in clustering from time-evolving
data matrices. We show that the optimization problems
involved are non-convex, non-smooth and non-separable. To
compute the solutions efficiently, we develop a two-step
procedure that optimizes the objective function iteratively.
We evaluate the proposed formulations using the Allen
Developing Mouse Brain Atlas data. Results show that our
formulations consistently outperform prior methods.

14
19 JDMZ-19 Structured
Learning_Kno
wledge
Discovery
IEEE-2015 Social identity linkage across different social media
platforms is of critical importance to business intelligence by
gaining from social data a deeper understanding and more
accurate profiling of users. In this paper, we propose a
solution framework, HYDRA, which consists of three key
steps: (I) we model heterogeneous behavior by long-term
topical distribution analysis and multi-resolution temporal
behavior matching against high noise and information
missing, and the behavior similarity are described by multi-
dimensional similarity vector for each user pair; (II) we
build structure consistency models to maximize the structure
and behavior consistency on users’ core social structure
across different platforms, thus the task of identity linkage
can be performed on groups of users, which is beyond the
individual level linkage in previous study; and (III) we
propose a normalized-margin-based linkage function
formulation, and learn the linkage function by multi-
objective optimization where both supervised pair-wise
linkage function learning and structure consistency
maximization are conducted towards a unified Pareto
optimal solution. The model is able to deal with drastic
information missing, and avoid the curse-of-dimensionality
in handling high dimensional sparse representation.
20 JDMZ-20 Subgraph
Matching with
Set Similarity
IEEE-2015 In real-world graphs such as social networks, Semantic Web
and biological networks, each vertex usually contains rich
information, which can be modeled by a set of tokens or
elements. In this paper, we study a subgraph matching with
set similarity (SMS2) query over a large graph database,
which retrieves subgraphs that are structurally isomorphic
to the query graph, and meanwhile satisfy the condition of
vertex pair matching with the (dynamic) weighted set
similarity. To efficiently process the SMS2 query, this paper
designs a novel lattice-based index for data graph, and
lightweight signatures for both query vertices and data
vertices. Based on the index and signatures, we propose an
efficient two-phase pruning strategy including set similarity
pruning and structure-based pruning, which exploits the
unique features of both (dynamic) weighted set similarity
and graph topology. We also propose an efficient
dominating-set-based subgraph matching algorithm guided
by a dominating set selection algorithm to achieve better
query performance. Extensive experiments on both real and
synthetic datasets demonstrate that our method outperforms
state-of-the-art methods by an order of magnitude.

15
21 JDMZ-21 The Impact of
View Histories
on Edit
Recommendati
ons
IEEE-2015 Recommendation systems are intended to increase developer
productivity by recommending files to edit. These systems
mine association rules in software revision histories.
However, mining coarse grained rules using only edit
histories produces recommendations with low accuracy, and
can only produce recommendations after a developer edits a
file. In this work, we explore the use of finer grained
association rules, based on the insight that view histories
help characterize the contexts of files to edit. To leverage this
additional context and fine grained association rules, we
have developed MI, a recommendation system extending
ROSE, an existing edit based recommendation system. We
then conducted a comparative simulation of ROSE and MI
using the interaction histories stored in the Eclipse Bugzilla
system. The simulation demonstrates that MI predicts the
files to edit with significantly higher recommendation
accuracy than ROSE (about 63% over 35%), and makes
recommendations earlier, often before developers begin
editing. Our results clearly demonstrate the value of
considering both views and edits in systems to recommend
files to edit, and results in more accurate, earlier, and more
flexible recommendations.
22 JDMZ-22 Towards
Effective Bug
Triage with
Software Data
Reduction
Techniques
IEEE-2015 Software companies spend over 45 percent of cost in dealing
with software bugs. An inevitable step of fixing bugs is bug
triage, which aims to correctly assign a developer to a new
bug. To decrease the time cost in manual work, text
classification techniques are applied to conduct automatic
bug triage. In this paper, we address the problem of data
reduction for bug triage, i.e., how to reduce the scale and
improve the quality of bug data. We combine instance
selection with feature selection to simultaneously reduce data
scale on the bug dimension and the word dimension. To
determine the order of applying instance selection and
feature selection, we extract attributes from historical bug
data sets and build a predictive model for a new bug data set.
We empirically investigate the performance of data
reduction on totally 600,000 bug reports of two large open
source projects, namely Eclipse and Mozilla. The results
show that our data reduction can effectively reduce the data
scale and improve the accuracy of bug triage. Our work
provides an approach to leveraging techniques on data
processing to form reduced and high-quality bug data in
software development and maintenance.

16
23 JIPZ-23 Multiview
Alignment
Hashing for
Efficient Image
IEEE-2015 Hashing is a popular and efficient method for nearest
neighbor search in large-scale data spaces, by embedding
high-dimensional feature descriptors into a similarity
preserving Hamming space with a low dimension. For most
hashing methods, the performance of retrieval heavily
depends on the choice of the high-dimensional feature
descriptor. Furthermore, a single type of feature cannot be
descriptive enough for different images when it is used for
hashing. Thus, how to combine multiple representations for
learning effective hashing functions is an imminent task. In
this paper, we present a novel unsupervised Multiview
Alignment Hashing (MAH) approach based on Regularized
Kernel Nonnegative Matrix Factorization (RKNMF),
24 JIPZ-24 YouTube
Video
Promotion by
Cross-network
IEEE-2015 The emergence and rapid proliferation of various social
media networks have reshaped the way how video contents
are generated, distributed and consumed in traditional video
sharing portals. Nowadays, online videos can be accessed
from far beyond the internal mechanisms of the video
sharing portals, such as internal search and front page
highlight. Recent studies have found that external referrers,
such as external search engines and other social media
websites, arise to be the new and important portals to Lead
users to online videos. In this paper, we introduce a novel
cross-network collaborative application to help drive the
online traffic for given videos in traditional video portal
YouTube by leveraging the high propagation efficiency of
the popular Twitter followees.
25 JMCZ-01 Modelling and
Analysis_Mob
Comp
IEEE-2015 —In opportunistic networks, direct communication between
mobile devices is used to extend the set of services accessible
through cellular or WiFi networks. Mobility patterns and
their impact in such networks have been extensively studied.
In contrast, this has not been the case with communication
traffic patterns, where homogeneous traffic between all
nodes is usually assumed. This assumption is generally not
true, as node mobility and social characteristics can
significantly affect the end-to-end traffic demand between
them. To this end, in this paper we explore the joint effect of
traffic patterns and node mobility on the performance of
popular forwarding mechanisms, both analytically and
through simulations. Among the different insights stemming
from our analysis, we identify conditions under which
heterogeneity renders the added value of using extra relays
more/less useful. Furthermore, we confirm the intuition that
an increasing amount of heterogeneity closes the
performance gap between different forwarding policies,
making endto- end routing more challenging in some cases.

17
26 JMCZ-02 Towards
Information
Diffusion in
Mobile Social
IEEE-2015 The emerging of mobile social networks opens opportunities
for viral marketing. However, before fully utilizing mobile
social networks as a platform for viral marketing, many
challenges have to be addressed. In this paper, we address
the problem of identifying a small number of individuals
through whom the information can be diffused to the
network as soon as possible, referred to as the diffusion
minimization problem. Diffusion minimization under the
probabilistic diffusion model can be formulated as an
asymmetric k- center problem which is NP-hard, and the
best known approximation algorithm for the asymmetric k-
center problem has approximation ratio of log_ n and time
complexity O(n5). Clearly, the performance and the time
complexity of the approximation algorithm are not
satisfiable in large-scale mobile social networks.
27 JMMZ-01 Color
imaging_Multi
media
IEEE-2015 Multimedia data with associated semantics is omnipresent in
today’s social online platforms in the form of keywords, user
comments, and so forth. This article presents a statistical
framework designed to infer knowledge in the imaging
domain from the semantic domain. Note that this is the
reverse direction of common computer vision applications.
The framework relates keywords to image characteristics
using a statistical significance test. It scales to millions of
images and hundreds of thousands of keywords. We
demonstrate the usefulness of the statistical framework with
three color imaging applications: 1) semantic image
enhancement: re-render an image in order to adapt it to its
semantic context; 2) color naming: find the color triplet for a
given color name; and 3) color palettes: find a palette of
colors that best represents a given arbitrary semantic
context and that satisfies established harmony constraints.
28 JPDZ-01 Secure
Distributed
Deduplication
Systems with
Improved
Reliability -01-
Secure
Distributed
Deduplication
Systems with
Improved
Reliability
IEEE-2015 Data deduplication is a technique for eliminating duplicate
copies of data, and has been widely used in cloud storage to
reduce storage space and upload bandwidth. However, there
is only one copy for each file stored in cloud even if such a
file is owned by a huge number of users. As a result,
deduplication system improves storage utilization while
reducing reliability. Furthermore, the challenge of privacy
for sensitive data also arises when they are outsourced by
users to cloud. Aiming to address the above security
challenges, this paper makes the first attempt to formalize
the notion of distributed reliable deduplication system. We
propose new distributed deduplication systems with higher
reliability in which the data chunks are distributed across
multiple cloud servers.

18
29 JPDZ-02 Service
Operatorawar
e Trust
Scheme for
Resource
IEEE-2015 This paper proposes a service operator-aware trust scheme
(SOTS) for resource matchmaking across multiple clouds.
Through analyzing the built-in relationship between the
users, the broker, and the service resources, this paper
proposes a middleware framework of trust management that
can effectively reduce user burden and improve system
dependability. Based on multi-dimensional resource service
operators, we model the problem of trust evaluation as a
process of multi-attribute decision-making, and develop an
adaptive trust evaluation approach based on information
entropy theory. This adaptive approach can overcome the
limitations of traditional trust schemes, whereby the trusted
operators are weighted manually or subjectively. As a result,
using SOTS, the broker can efficiently and accurately
prepare the most trusted resources in advance, and thus
provide more dependable resources to users. Our
experiments yield interesting and meaningful observations
that can facilitate the effective utilization of SOTS in a large-
scale multi-cloud environment.
30 JSCZ-01 A Trust-Aware
Service
Brokering
Scheme
IEEE-2015 Oriented by requirement of trust management in multiple
cloud environment, this paper presents T-broker, a
trustaware service brokering scheme for efficient matching
cloud services (or resources) to satisfy various user requests.
First, a trusted third party-based service brokering
architecture is proposed for multiple cloud environment, in
which the T-broker acts as a middleware for cloud trust
management and service matching. Then, T-broker uses a
hybrid and adaptive trust model to compute the overall trust
degree of service resources, in which trust is defined as a
fusion evaluation result from adaptively combining the
direct monitored evidence with the social feedback of the
service resources. More importantly, T-broker uses the
maximizing deviation method to compute the direct
experience based on multiple key trusted attributes of
service resources, which can overcome the limitations of
traditional trust schemes, in which the trusted attributes are
weighted manually or subjectively. Finally, T-broker uses a
lightweight feedback mechanism, which can effectively
reduce networking risk and improve system efficiency. The
experimental results show that, compared with the existing
approaches, our T-broker yields very good results in many
typical cases, and the proposed system is robust to deal with
various numbers of dynamic service behavior from multiple
cloud sites.

19
31 JSCZ-02 Collusion-
Tolerable
Privacy-
Preserving
Sum and
IEEE-2015 Much research has been conducted to securely outsource
multiple parties’ data aggregation to an untrusted
aggregator without disclosing each individual’s privately
owned data, or to enable multiple parties to jointly aggregate
their data while preserving privacy. However, those works
either require secure pair-wise communication channels or
suffer from high complexity. In this paper, we consider how
an external aggregator or multiple parties can learn some
algebraic statistics (e.g., sum, product) over participants’
privately owned data while preserving the data privacy. We
assume all channels are subject to eavesdropping attacks,
and all the communications throughout the aggregation are
open to others. We first propose several protocols that
successfully guarantee data privacy under semi-honest
model, and then present advanced protocols which tolerate
up to k passive adversaries who do not try to tamper the
computation. Under this weak assumption, we limit both the
communication and computation complexity of each
participant to a small constant. At the end, we present
applications which solve several interesting problems via our
protocols.
32 JSCZ-03 Control Cloud
Data Access
Privilege and
Anonymity
With Fully
Anonymous
Attribute-
Based
Encryption
IEEE-2015 Cloud computing is a revolutionary computing paradigm,
which enables flexible, on-demand, and low-cost usage of
computing resources, but the data is outsourced to some
cloud servers, and various privacy concerns emerge from it.
Various schemes based on the attribute-based encryption
have been proposed to secure the cloud storage. However,
most work focuses on the data contents privacy and the
access control, while less attention is paid to the privilege
control and the identity privacy. In this paper, we present a
semi anonymous privilege control scheme Anony Control to
address not only the data privacy, but also the user identity
privacy in existing access control schemes. Anony Control
decentralizes the central authority to limit the identity
leakage and thus achieves semi anonymity. Besides, it also
generalizes the file access control to the privilege control, by
which privileges of all operations on the cloud data can be
managed in a fine-grained manner. Subsequently, we present
the Anony Control-F, which fully prevents the identity
leakage and achieve the full anonymity. Our security
analysis shows that both Anony Control and Anony Control-
F are secure under the decisional bilinear Diffie–Hellman
assumption, and our performance evaluation exhibits the
feasibility of our schemes.

20
33 JSCZ-04 Data Lineage
in Malicious
Environments
IEEE-2015 Intentional or unintentional leakage of confidential data is
undoubtedly one of the most severe security threats that
organizations face in the digital era. The threat now extends
to our personal lives: a plethora of personal information is
available to social networks and smartphone providers and
is indirectly transferred to untrustworthy third party and
fourth party applications. In this work, we present a generic
data lineage framework LIME for data flow across multiple
entities that take two characteristic, principal roles (i.e.,
owner and consumer). We define the exact security
guarantees required by such a data lineage mechanism
toward identification of a guilty entity, and identify the
simplifying non-repudiation and honesty assumptions. We
then develop and analyze a novel accountable data transfer
protocol between two entities within a malicious
environment by building upon oblivious transfer, robust
watermarking, and signature primitives. Finally, we perform
an experimental evaluation to demonstrate the practicality of
our protocol and apply our framework to the important data
leakage scenarios of data outsourcing and social networks. In
general, we consider LIME , our lineage framework for data
transfer, to be an key step towards achieving accountability
by design.
34 JSCZ-05 Enabling
Cloud Storage
Auditing with
IEEE-2015 Cloud storage auditing is viewed as an important service to
verify the integrity of the data in public cloud. Current
auditing protocols are all based on the assumption that the
client’s secret key for auditing is absolutely secure. However,
such assumption may not always be held, due to the possibly
weak sense of security and/or low security settings at the
client. If such a secret key for auditing is exposed, most of
the current auditing protocols would inevitably become
unable to work. In this paper, we focus on this new aspect of
cloud storage auditing. We investigate how to reduce the
damage of the client’s key exposure in cloud storage
auditing, and give the first practical solution for this new
problem setting. We formalize the definition and the security
model of auditing protocol with key-exposure resilience and
propose such a protocol. In our design, we employ the binary
tree structure and the pre-order traversal technique to
update the secret keys for the client. We also develop a novel
authenticator construction to support the forward security
and the property of blockless verifiability. The security proof
and the performance analysis show that our proposed
protocol is secure and efficient.

21
35 JSCZ-06 Formalization
and
Verification_C
ybernetics
IEEE-2015 Group behavior interactions, such as multirobot teamwork
and group communications in social networks, are widely
seen in both natural, social, and artificial behavior related
applications. Behavior interactions in a group are often
associated with varying coupling relationships, for instance,
conjunction or disjunction. Such coupling relationships
challenge existing behavior representation methods, because
they involve multiple behaviors from different actors,
constraints on the interactions, and behavior evolution. In
addition, the quality of behavior interactions are not checked
through verification techniques. In this paper, we propose an
ontology-based behavior modeling and checking system
(OntoB for short) to explicitly represent and verify complex
behavior relationships, aggregations, and constraints. The
OntoB system provides both a visual behavior model and an
abstract behavior tuple to capture behavioral elements, as
well as building blocks. It formalizes various intra-coupled
interactions (behaviors conducted by the same actor) via
transition systems (TSs), and inter-coupled behavior
aggregations (behaviors conducted by different actors) from
temporal, inferential, and party-based perspectives.
36 JSCZ-07 Group Key
Agreement
with Local
Connectivity
IEEE-2015 In this paper, we study a group key agreement problem
where a user is only aware of his neighbors while the
connectivity graph is arbitrary. In our problem, there is no
centralized initialization for users. A group key agreement
with these features is very suitable for social networks.
Under our setting, we construct two efficient protocols with
passive security. We obtain lower bounds on the round
complexity for this type of protocol, which demonstrates that
our constructions are round efficient. Finally, we construct
an actively secure protocol from a passively secure one.
37 JSCZ-08 Privacy-
Preserving
Public
Auditing for
IEEE-2015 To protect outsourced data in cloud storage against
corruptions, adding fault tolerance to cloud storage together
with data integrity checking and failure reparation becomes
critical. Recently, regenerating codes have gained popularity
due to their lower repair bandwidth while providing fault
tolerance. Existing remote checking methods for
regenerating-coded data only provide private auditing,
requiring data owners to always stay online and handle
auditing, as well as repairing, which is sometimes impractical.
In this paper, we propose a public auditing scheme for the
regenerating-code-based cloud storage. To solve the
regeneration problem of failed authenticators in the absence
of data owners, we introduce a proxy, which is privileged to
regenerate the authenticators, into the traditional public
auditing system model.

22
38 JSEZ-01 Impact of
view_DM
IEEE-2015 Recommendation systems are intended to increase developer
productivity by recommending files to edit. These systems
mine association rules in software revision histories.
However, mining coarse-grained rules using only edit
histories produces recommendations with low accuracy, and
can only produce recommendations after a developer edits a
file. In this work, we explore the use of fine-grained
association rules, based on the insight that view histories
help characterize the contexts of files to edit. To leverage this
additional context and fine-grained association rules, we
have developed MI, a recommendation system extending
ROSE, an existing edit based recommendation system. We
then conducted a comparative simulation of ROSE and MI
using the interaction histories stored in the Eclipse Bugzilla
system. The simulation demonstrates that MI predicts the
files to edit with significantly higher recommendation
accuracy than ROSE (about 63% over 35%), and makes
recommendations earlier, often before developers begin
editing. Our results clearly demonstrate the value of
considering both views and edits in systems to recommend
files to edit, and results in more accurate, earlier, and more
flexible recommendations.
NS-2
39 NSZ-01 A Distributed
Fault-Tolerant
Topology
Control
Algorithm for
Heterogeneous
Wireless
Sensor
Networks
IEEE-2015 This paper introduces a distributed fault-tolerant topology
control algorithm, called the Disjoint Path Vector (DPV), for
heterogeneous wireless sensor networks composed of a large
number of sensor nodes with limited energy and computing
capability and several supernodes with unlimited energy
resources. The DPV algorithm addresses the k-degree
Anycast Topology Control problem where the main objective
is to assign each sensor’s transmission range such that each
has at least k-vertex-disjoint paths to supernodes and the
total power consumption is minimum. The resulting
topologies are tolerant to k _ 1 node failures in the worst
case. We prove the correctness of our approach by showing
that topologies generated by DPV are guaranteed to satisfy
k-vertex supernode connectivity. Our simulations show that
the DPV algorithm achieves up to 4-fold reduction in total
transmission power required in the network and 2-fold
reduction in maximum transmission power required in a
node compared to existing solutions.

23
40 NSZ-02 Adaptive
Algorithms for
Diagnosing
Large-Scale
Failures in
Computer
Networks
IEEE-2015 We propose a greedy algorithm, Cluster-MAX-COVERAGE
(CMC), to efficiently diagnose large-scale clustered failures.
We primarily address the challenge of determining faults
with incomplete symptoms. CMC makes novel use of both
positive and negative symptoms to output a hypothesis list
with a low number of false negatives and false positives
quickly. CMC requires reports from about half as many
nodes as other existing algorithms to determine failures with
100 percent accuracy. Moreover, CMC accomplishes this
gain significantly faster (sometimes by two orders of
magnitude) than an algorithm that matches its accuracy.
When there are fewer positive and negative symptoms at a
reporting node, CMC performs much better than existing
algorithms. We also propose an adaptive algorithm called
Adaptive-MAX-COVERAGE (AMC) that performs
efficiently during both independent and clustered failures.
During a series of failures that include both independent and
clustered, AMC results in a reduced number of false
negatives and false positives.
41 NSZ-03 Delay
Optimization
and Cross-
Layer Design
in Multihop
Wireless
Networks With
Network
Coding and
Successive
Interference
Cancelation
IEEE-2015 Network coding (NC) and multipacket reception with
successive interference cancelation (SIC) have been shown to
improve the performance of multihop wireless networks
(MWNs). However, previous work emphasized maximization
of network throughput without considering quality of service
(QoS) requirements, which may lead to high packet delays in
the network. The objective of this work is minimization of
packet delay in a TDMA-based MWN that is jointly utilizing
NC and SIC techniques for a given traffic demand matrix.
We assume conflictfree scheduling and allow multipath
routing. We formulate a cross-layer optimization that
assigns time slots to links in a way that the average packet
delay is minimized. The problem formulation results in a
difficult mixed integer nonlinear programming (MINLP)
that the state-of-art software can only solve for very small-
sized networks. For large networks, we develop a heuristic
approach that iteratively determines the optimal solution.
We present numerical results, which show that the average
packet delay and traffic handling capacity of a network,
using w/o NC+SIC, NC, SIC and NC+SIC schemes, improves
from left to right. The traffic capacity of NC+SIC is double
of the w/o NC+SIC. Thus, combined utilization of NC and
SIC techniques results in significant performance
improvement.

24
42 NSZ-04 Distributed
denial of
service attacks
in software-
defined
networking
with cloud
computing
IEEE-2015 Although software-defined networking (SDN) brings
numerous benefits by decoupling the control plane from the
data plane, there is a contradictory relationship between
SDN and distributed denial-of-service (DDoS) attacks. On
one hand, the capabilities of SDN make it easy to detect and
to react to DDoS attacks. On the other hand, the separation
of the control plane from the data plane of SDN introduces
new attacks. Consequently, SDN itself may be a target of
DDoS attacks. In this paper, we first discuss the new trends
and characteristics of DDoS attacks in cloud computing
environments. We show that SDN brings us a new chance to
defeat DDoS attacks in cloud computing environments, and
we summarize good features of SDN in defeating DDoS
attacks. Then we review the studies about launching DDoS
attacks on SDN and the methods against DDoS attacks in
SDN.In addition, we discuss a number of challenges that
need to be addressed to mitigate DDoS attached in SDN with
cloud computing. This work can help understand how to
make full use of SDN’s advantages to defeat DDoS attacks in
cloud computing environments and how to prevent SDN
itself from becoming a victim of DDoSattacks.
43 NSZ-05 Dynamic
Openflow-
Controlled
Optical Packet
Switching
Network
IEEE-2015 This paper presents and experimentally demonstrates the
generalized architecture of Open flow-controlled optical
packet switching (OPS) network. Open flow control is
enabled by introducing The Openflow/OPS agent into the
OPS network, which realizes the Openflow protocol
translation and message exchange between the Openflow
control plane and the underlying OPS nodes. With software-
defined networking (SDN) and Openflow technique, the
complex control functions of the conventional OPS network
can offloaded into a centralized and flexible control plane,
while promoted control and operations can be provided due
to centralized coordination of network resources.
Furthermore, a contentionaware routing/rerouting strategy
as well as a fast network adjustment mechanism is proposed
and demonstrated for the first time as advanced Openflow
control to route traffic and handle the network dynamics.
With centralized SDN/Openflow control, the OPS network
has the potential to have better resource utilization and
enhanced network resilience at lower cost and less node
complexity. Our work will accelerate the development of
both OPS and SDN evolution.

25
44 NSZ-06 Game-
Theoretic
Topology
Controlfor
Opportunistic
Localizationin
Sparse
Underwater
Sensor
Networks
IEEE-2015 In this paper, we propose a localization scheme named
Opportunistic Localization by Topology Control (OLTC),
specifically for sparse Underwater Sensor Networks
(UWSNs). In a UWSN, an unlocalized sensor node finds its
location by utilizing the spatio-temporal relation with the
reference nodes. Generally, UWSNs are sparsely deployed
because of the high implementation cost, and unfortunately,
the network topology experiences partitioning due to the
effect of passive node mobility. Consequently, most of the
underwater sensor nodes lack the required number of
reference nodes for localization in underwater environments.
The existing literature is deficient in addressing the problem
of node localization in the above mentioned scenario.
Antagonistically, however, we promote that even in such
sparse UWSN context, it is possible to localize the nodes by
exploiting their available opportunities.
45 NSZ-07 Improving
Physical-Layer
Security in
Wireless
Communicatio
ns Using
Diversity
Techniques
IEEE-2015 Due to the broadcast nature of radio propagation, wireless
transmission can be readily overheard by unauthorized users
for interception purposes and is thus highly vulnerable to
eavesdropping attacks. To this end, physical-layer security is
emerging as a promising paradigm to protect the wireless
communications against eavesdropping attacks by exploiting
the physical characteristics of wireless channels. This article
is focused on the investigation of diversity techniques to
improve physical-layer security differently from the
conventional artificial noise generation and beamforming
techniques, which typically consume additional power for
generating artificial noise and exhibit high implementation
complexity for beamformer design. We present several
diversity approaches to improve wireless physical-layer
security, including multiple-input multiple-output (MIMO),
multiuser diversity, and cooperative diversity. To illustrate
the security improvement through diversity, we propose a
case study
46 NSZ-08 Interference-
Based
Topology
Control
Algorithm for
Delay-
Constrained
Mobile Ad Hoc
Networks
IEEE-2015 As the foundation of routing, topology control should
minimize the interference among nodes, and increase the
network capacity. With the development of mobile ad hoc
networks (MANETs), there is a growing requirement of
quality of service (QoS) in terms of delay. In order to meet
the delay requirement, it is important to consider topology
control in delay constrained environment, which is
contradictory to the objective of minimizing interference. In
this paper, we focus on the delay-constrained topology
control problem, and take into account delay and
interference jointly.

26
47 NSZ-09 Joint Optimal
Data Rate and
Power
Allocation in
Lossy Mobile
Ad Hoc
Networks with
Delay-
Constrained
Traffics
IEEE-2015 In this paper, we consider lossy mobile ad hoc networks
where the data rate of a given flow becomes lower and lower
along its routing path. One of the main challenges in lossy
mobile ad hoc networks is how to achieve the conflicting goal
of increased network utility and reduced power
consumption, while without following the instantaneous state
of a fading channel. To address this problem, we propose a
cross-layer rate-effective network utility maximization
(RENUM) framework by taking into account the lossy
nature of wireless links and the constraints of rate outage
probability and average delay. In the proposed framework,
the utility is associated with the effective rate received at the
destination node of each flow instead of the injection rate at
the source of the flow. We then present a distributed joint
transmission rate, link power and average delay control
algorithm, in which explicit broadcast message passing is
required for power allocation algorithm.
48 NSZ-10 Max
Contribution
An Online
Approximation
of Optimal
Resource
Allocation in
Delay Tolerant
Networks
IEEE-2015 In this paper, a joint optimization of link scheduling, routing
and replication for delay-tolerant networks (DTNs) has been
studied. The optimization problems for resource allocation
in DTNs are typically solved using dynamic programming
which requires knowledge of future events such as meeting
schedules and durations. This paper defines a new notion of
approximation to the optimality for DTNs, called snapshot
approximation where nodes are not clairvoyant, i.e., not
looking ahead into future events, and thus decisions are
made using only contemporarily available knowledges.
Unfortunately, the snapshot approximation still requires
solving an NP-hard problem of maximum weighted
independent set (MWIS) and a global knowledge of who
currently owns a copy and what their delivery probabilities
are. This paper proposes an algorithm, Max-Contribution
(MC) that approximates MWIS problem with a greedy
method and its distributed online approximation algorithm,
Distributed Max-Contribution (DMC).

27
49 NSZ-11 Neighbor
Similarity
Trust against
Sybil Attack in
P2P E-
Commerce
IEEE-2015 Peer to peer (P2P) e-commerce applications exist at the edge
of the Internet with vulnerabilities to passive and active
attacks. These attacks have pushed away potential business
firms and individuals whose aim is to get the best benefit in
e-commerce with minimal losses. The attacks occur during
interactions between the trading peers as a transaction takes
place. In this paper, we propose how to address Sybil attack,
an active attack, in which peers can have bogus and multiple
identities to fake their owns. Most existing work, which
concentrates on social networks and trusted certification, has
not been able to prevent Sybil attack peers from doing
transactions. Our work exploits the neighbor similarity trust
relationship to address Sybil attack. In our approach,
duplicated Sybil attack peers can be identified as the
neighbor peers become acquainted and hence more trusted
to each other. Security and performance analysis shows that
Sybil attack can be minimized by our proposed neighbor
similarity trust.
50 NSZ-12 Power Control
and Soft
Topology
Adaptations in
Multihop
Cellular
Networks With
Multi-Point
Connectivity
IEEE-2015 The LTE standards account for the use of relays to enhance
coverage near the cell edge. In a traditional topology, a
mobile can either establish a direct link to the base station
(BS) or a link to the relay, but not both. In this paper, we
consider the benefit of multipoint connectivity in allowing
user equipment (UEs) to split their transmit power over
simultaneous links to the BS and the relay, in effect
transmitting two parallel flows. We model decisions by the
UEs as to: (i) which point of access to attach to (either a relay
or a relay and the BS or only the BS); and (ii) how to allocate
transmit power over these links so as to maximize their total
rate. We show that this flexibility in the selection of points of
access leads to substantial network capacity increase against
when nodes operate in a fixed network topology. Individual
adaptations by UEs, in terms of both point of access and
transmit power, are interdependent due to interference and
to the possibility of over-loading of the backhaul links.

28
51 NSZ-13 Privacy-
Preserving
Detection of
Privacy-
Preserving
Detection of
Sensitive Data
Exposure
IEEE-2015 Statistics from security firms, research institutions and
government organizations show that the number of data-leak
instances have grown rapidly in recent years. Among various
data-leak cases, human mistakes are one of the main causes
of data loss. There exist solutions detecting inadvertent
sensitive data leaks caused by human mistakes and to
provide alerts for organizations. A common approach is to
screen content in storage and transmission for exposed
sensitive information. Such an approach usually requires the
detection operation to be conducted in secrecy. However, this
secrecy requirement is challenging to satisfy in practice, as
detection servers may be compromised or outsourced. In this
paper, we present a privacypreserving data-leak detection
(DLD) solution to solve the issue where a special set of
sensitive data digests is used in detection. The advantage of
our method is that it enables the data owner to safely
delegate the detection operation to a semihonest provider
without revealing the sensitive data to the provider. We
describe how Internet service providers can offer their
customers DLD as an add-on service with strong privacy
guarantees. The evaluation results show that our method can
support accurate detection with very small number of false
alarms under various data-leak scenarios.
52 NSZ-14 Security-
Aware
Relaying
Scheme for
Cooperative
Networks With
Untrusted
Relay Nodes
IEEE-2015 This paper studies the problem of secure transmission in
dual-hop cooperative networks with untrusted relays, where
each relay acts as both a potential helper and an
eavesdropper. A security-aware relaying scheme is proposed,
which employs the alternate jamming and secrecy-enhanced
relay selection to prevent the confidential message from
being eavesdropped by the untrusted relays. To evaluate the
performance of the proposed strategies, we derive the lower
bound of the achievable ergodic secrecy rate (ESR), and
conduct the asymptotic analysis to examine how the ESR
scales as the number of relays increases.

29
53 NSZ-15 Self-
Organizing
Resource
Management
Framework in
OFDMA
Femtocells
IEEE-2015 Next generation wireless networks (i.e., WiMAX, LTE)
provide higher bandwidth and spectrum efficiency
leveraging smaller (femto) cells with orthogonal frequency
division multiple access (OFDMA). The uncoordinated,
dense deployments of femtocells however, pose several
unique challenges relating to interference and resource
management in OFDMA femtocell networks. Towards
addressing these challenges, we propose RADION, a
distributed resource management framework that effectively
manages interference across femtocells. RADION’s core
building blocks enable femtocells to opportunistically
determine the available resources in a completely distributed
and efficient manner. Further, RADION’s modular nature
paves the way for different resource management solutions
to be incorporated in the framework. We implement
RADION on a real WiMAX femtocell testbed deployed in a
typical indoor setting. Two distributed solutions are enabled
through RADION and their performance is studied to
highlight their quick self-organization into efficient resource
allocations.
54 NSZ-16 Statistical
Dissemination
Control in
Large
Machine-to-
Machine
Communicatio
n Networks
IEEE-2015 Cloud based machine-to-machine (M2M) communications
have emerged to achieve ubiquitous and autonomous data
transportation for future daily life in the cyber-physical
world. In light of the need of network characterizations, we
analyze the connected M2M network in the machine swarm
of geometric random graph topology, including degree
distribution, network diameter, and average distance (i.e.,
hops). Without the need of end-to-end information to escape
catastrophic complexity, information dissemination appears
an effective way in machine swarm. To fully understand
practical data transportation, G/G/1 queuing network model
is exploited to obtain average end-to-end delay and
maximum achievable system throughput. Furthermore, as
real applications may require dependable networking
performance across the swarm, quality of service (QoS)
along with large network diameter creates a new intellectual
challenge.

30
55 NSZ-17 Toward
Transparent
Coexistence for
Multihop
Secondary
Cognitive
Radio
Networks
IEEE-2015 The dominate spectrum sharing paradigm of today is
interference avoidance, where a secondary network can use
the spectrum only when such a use is not interfering with the
primary network. However, with the advances of physical-
layer technologies, the mindset of this paradigm is being
challenged. This paper explores a new paradigm called
―transparent coexistence‖ for spectrum sharing between
primary and secondary nodes in a multihop network
environment. Under this paradigm, the secondary network is
allowed to use the same spectrum simultaneously with the
primary network as long as their activities are ―transparent‖
(or ―invisible‖) to the primary network. Such transparency
is accomplished through a systematic interference
cancelation (IC) by the secondary nodes without any impact
on the primary network. Although such a paradigm has been
studied in the information theory (IT) and communications
(COMM) communities, it is not well understood in the
wireless networking community, particularly for multihop
networks.

32
S.No Code Title Year Abstract
56 EST-01 A Cooperative Train
Control Model for
Energy Saving
IEEE-2015 Increasing attention is being paid to energy efficiency in
subway systems to reduce operational cost and carbon
emissions. Optimization of the driving strategy and efficient
utilization of regenerative energy are two effective methods
to reduce the energy consumption for electric subway
systems. Based on a common scenario that an accelerating
train can reuse the regenerative energy from a braking train
on the opposite track, this paper proposes a cooperative train
control model to minimize the practical energy consumption,
i.e., the difference between traction energy and the reused
regenerative energy. First, we design a numerical algorithm to
calculate the optimal driving strategy with the given trip time,
in which the variable traction force, braking force, speed
limits, and gradients are considered.
57 EST-02 A High Reliability
Wearable Device for
Elderly Fall Detection
IEEE-2015 Falls are critical events among elderly people that requires
timely rescue. In this paper we propose a fall detection system
consisting of an inertial unit that includes triaxial
accelerometer, gyroscope and magnetometer with efficient
data fusion and fall detection algorithms. Starting from the
raw data, the implemented orientation filter provides the
correct orientation of the subject in terms of Yaw, Pitch and
Roll angles. The system is tested according to experimental
protocols, engaging volunteers who performed simulated falls,
simulated falls with recovery and Activities of Daily Living
(ADL). By placing our wearable sensor on the waist of the
subject, the unit is able to achieve fall detection performance
above those of similar systems proposed in literature.
58 EST-03 A Method for
Uncertainty
Assessment of
Passive Sun -Induced
Chlorophyll
Fluorescence
Retrieval by Using an
Infrared Reference
Light
IEEE-2015 Measurements of sun-induced chlorophyll fluorescence (SIF)
over plant canopies provide a proxy for plant photosynthetic
capacity and are of high interest for plant research. Together
with spectral reflectance, SIF has the potential to act as a non-
invasive approach to quantify photosynthetic plant traits from
field to air- and spaceborne scales. But SIF is a small signal
contribution to the reflected sunlight and often not
distinguishable from sensor noise. SIF estimation is, therefore,
affected by an unquantified uncertainty, making it difficult to
estimate accurately how much SIF is truly emitted from the
plant. To investigate and overcome this, we designed a device
based on a spectrometer covering the visible range and
equipped it with an LED emitting at the wavelength of SIF.
Using this as a reference and applying thorough calibrations,
we present consistent evidence of the instrument’s capability
of SIF retrieval and accuracy estimations. The LED’s intensity
was measured under sunlight with 1.27 ± 0.27 mW×sr-1m-
2nm-1 stable over the day. The large increase of SIF due to the

33
Kautsky effect was measured spectrally and temporally
proving the biophysical origin of the signal. We propose
rigorous tests for instruments intended to measure SIF and
show ways to further improve the presented methods.
59 EST-04 A Runtime Integrity
Monitoring
Framework for Real-
Time Relative
Positioning Systems
Based on GPS and
DSRC
IEEE-2015 This paper provides a three-layered framework to monitor the
positioning performance requirements of real-time relative
positioning (RRP) systems of the Cooperative Intelligent
Transport Systems that support cooperative collision warning
(CCW) applications. These applications exploit state data of
surrounding vehicles obtained solely from the Global
Positioning System (GPS) and dedicated short-range
communications (DSRC) units without using other sensors. To
this end, this paper argues the need for the GPS/DSRC-based
RRP systems to have an autonomous monitoring mechanism,
since the operation of CCW applications is meant to augment
safety on roads. The advantages of autonomous integrity
monitoring are essential and integral to any safety-of-life
system. The autonomous integrity monitoring framework
proposed necessitates the RRP systems to detect/predict the
unavailability of their subsystems and of the integrity
monitoring module itself and, if available, to account for
effects of data link delays and breakages of DSRC links, as well
as of faulty measurement sources of GPS and/or integrated
augmentation positioning systems, before the information
used for safety warnings/alarms becomes unavailable,
unreliable, inaccurate, or misleading.
60 EST-05 A Self-Sustainable
Power Management
System for Reliable
Power Scaling Up of
Sediment Microbial
Fuel Cells
IEEE-2015 Sediment microbial fuel cells (SMFCs) are considered a
promising renewable power source for remote monitoring
Applications. However, existing SMFCs can only produce
several mill watts of power, and the output power is not
scaled linearly with the size of SMFCs. An effective alternative
method to increase the output power is to independently
operate multiple SMFCs, each of which has an optimal size for
maximum power density. Independently operated SMFCs
have electrically isolated electrodes (anodes/cathodes), which
complicates the design of a suitable power management
system (PMS). This paper describes the challenges in designing
a PMS that can harvest energy from multiple independently
operated (mio) SMFCs and accordingly proposes a design
solution. From experimental results, the proposed PMS
demonstrates reliable output power scaling up of mio-SMFC.
The proposed PMS is self-sustainable because it is powered
entirely from harvested energy without requiring additional
external power sources.

34
61 EST-06 A Single- Stage
Photovoltaic System
for a Dual-Inverter-
Fed Open- End
Winding Induction
Motor Drive for
Pumping
Applications
IEEE-2015 This paper presents an integrated solution for a photovoltaic
(PV)-fed water-pump drive system, which uses an openend
winding induction motor (OEWIM). The dual-inverter-fed
OEWIM drive achieves the functionality of a three-level
inverter and requires low value dc-bus voltage. This helps in
an optimal arrangement of PV modules, which could avoid
large strings and Helps in improving the PV performance with
wide bandwidth of operating voltage. It also reduces the
voltage rating of the dc-link capacitors and switching devices
used in the system. The proposed control strategy achieves an
integration of both maximum power point tracking and V/f
control for the efficient utilization of the PV panels and the
motor. The proposed control scheme requires the sensing of
PV voltage and current only. Thus, the system requires less
number of sensors. All the analytical, simulation, and
experimental results of this work under different
environmental conditions are presented in this paper.
62 EST-07 A Smart Sensor
Network for Sea
Water Quality
Monitoring
IEEE-2015 Measurement of chlorophyll concentration is gaining more-
and-more importance in evaluating the status of the marine
ecosystem. For wide areas monitoring a reliable architecture
of wireless sensors network is required. In this paper, we
present a network of smart sensors, based on ISO/IEC/IEEE
21451 suite of standards, for in situ and in continuous space–
time monitoring of surface water bodies, in particular for
seawater. The system is meant to be an important tool for
evaluating water quality and a valid support to strategic
decisions concerning critical environment issues. The aim of
the proposed system is to capture possible extreme events
and collect long-term periods of data.
63 EST-08 A Train Localization
Algorithm for Train
Protection Systems
of the Future
IEEE-2015 This paper describes an algorithm that enables a railway
vehicle to determine its position in a track network. The
system is based solely on onboard sensors such as a velocity
sensor and a Global Navigation Satellite System (GNSS) sensor
and does not require trackside infrastructure such as axle
counters or balises. The paper derives a probabilistic modeling
of the localization task and develops a sensor fusion approach
to fuse the inputs of the GNSS sensor and the velocity sensor
with the digital track map. We describe how we can treat
ambiguities and stochastic uncertainty adequately. Moreover,
we introduce the concept of virtual balises that can be used to
replace balises on the track and evaluate the approach
experimentally. This paper focuses on an accurate modeling of
sensor and estimation uncertainties, which is relevant for
safety critical applications.

35
64 EST-09 Alleviation of
Electromagnetic
Interference Noise
Using a Resonant
Shunt for Balanced
Converters
IEEE-2015 Balanced converter is an effective way to reduce the CM
noise. However, the parasitic capacitance between the switch
and heat sink leads to resonant problems, resulting in high
noise in certain frequency range. This paper proposes a novel
coupled inductor structure based on the balanced technique
for the Boost converter to further reduce the CM noise at
certain frequency range. A shunt resonant path is adopted to
offer a maximum suppression. The analytical estimation for
shunt winding’s performance is provided for better design.
Some simulation and experimental results of this new
technique are presented to validate its effectiveness. The
experiments about the capacitance unbalance, different load
current, and reduction of the CM inductor size are also
discussed for better understanding of this technique.
65 EST-10 An Approach of
Reliable Data
Transmission With
Random Redundancy
for Wireless Sensors
in
Structural Health
Monitoring
IEEE-2015 Lossy transmission is a common problem suffered from
monitoring systems based on wireless sensors. Though
extensive works have been done to enhance the reliability of
data communication in computer networks, few of the
existing methods are well tailored for the wireless sensors for
structural health monitoring (SHM). These methods are
generally unsuitable for resource-limited wireless sensor
nodes and intensive data SHM applications. In this paper, a
new data coding and transmission method is proposed that is
specifically targeted at the wireless SHM systems deployed on
large civil infrastructures. The proposed method includes two
coding stages: 1) a source coding stage to compress the
natural redundant information inherent in SHM signals and 2)
a redundant coding stage to inject artificial redundancy into
wireless transmission to enhance the transmission reliability.
Methods with light memory and computational overheads are
adopted in the coding process to meet the resource
constraints of wireless sensor nodes. In particular, the lossless
entropy compression method is implemented for
datacompression, and a simple random matrix projection is
proposed for redundant transformation. After coding, a
wireless sensor node transmits the same payload of coded
data instead of the original sensor data to the base station.
Some data loss may occur during the transmission of the
coded data. However, the complete original data can be
reconstructed losslessly on the base station from the
incomplete coded data given that the data loss ratio is
reasonably low. The proposed method is implemented into
the Imote2 smart sensor platform and tested in a series of
communication experiments on a cable-stayed bridge.

36
66 EST-11 Automated Health
Alerts Using In-Home
Sensor
Data for Embedded
Health Assessment
IEEE-2015 We present an example of unobtrusive, continuous
monitoring in the home for the purpose of assessing early
health changes. Sensors embedded in the environment
capture behavior and activity patterns. Changes in patterns
are detected as potential signs of changing health. We _rst
present results of a preliminary study investigating 22 features
extracted from in-home sensor data. A 1-D alert algorithm was
then implemented to generate health alerts to clinicians in a
senior housing facility. Clinicians analyze each alert and
provide a rating on the clinical relevance. These ratings are
then used as ground truth for training and testing classi_ers.
Here, we present the methodology for four classi_cation
approaches that fuse multisensory data. Results are shown
using embedded sensor data and health alert ratings collected
on 21 seniors over nine months. The best results show similar
performance for two techniques, where one approach uses
only domain knowledge and the second uses supervised
learning for training. Finally, we propose a health change
detection model based on these results and clinical expertise.
The system of in-home sensors and algorithms for automated
health alerts provides a method for detecting health problems
very early so that early treatment is possible. This method of
passive in-home sensing alleviates compliance issues.
67 EST-12 Compact Personal
Distributed
Wearable
Exposimeter
IEEE-2015 A compact wearable Personal Distributed Exposimeter is
proposed, sensing the power density of incident radio-
frequency (RF) fields on the body of a human. In contrast to
current commercial exposimeters, our Personal Distributed
Exposimeter, being composed of multiple compact personal
wearable RF exposimeter sensor modules, minimizes
uncertainties caused by the proximity of the body, the specific
antenna used and the exact position of the exposimeter. For
unobtrusive deployment inside a jacket, each individual
exposimeter sensor module is specifically implemented on the
feedplane of a textile patch antenna. The new wearable
sensor module’s high-resolution logarithmic detector logs RF
signal levels. Next, on-board flash memory records minimum,
maximum and average exposure data over a time span of
more than two weeks, at a one-second sample period.
Sample-level synchronization of each individual exposimeter
sensor module enables combining of measurements collected
by different nodes. The system is first calibrated in an
anechoic chamber, and then compared to a commercially
available single-unit exposimeter.

37
68 EST-13 Intra-Vehicle
Networks: A Review
IEEE-2015 Automotive electronics is a rapidly expanding area With an
increasing number of safety, driver assistance, and
infotainment devices becoming standard in new vehicles.
Current vehicles generally employ a number of different
networking protocols to integrate these systems into the
vehicle. The introduction of large numbers of sensors to
provide driver assistance applications and the associated high-
bandwidth requirements of these sensors have accelerated
the demand for faster and more flexible network
communication technologies within the vehicle. This paper
Presents a comprehensive overview of current research on
advanced intra-vehicle networks and identifies outstanding
research questions for the future.
69 EST-14 Multirobot Control
Using Time-Varying
Density Functions
IEEE-2015 An approach is presented for influencing teams of robots by
means of time-varying density functions, representing rough
references for where the robots should be located. A
continuous-time coverage algorithm is proposed and
distributed approximations are given whereby the robots
only need to access information from adjacent robots. Robotic
experiments show that the proposed algorithms work in
practice, as well as in theory.
70 EST-15 Optimization-Based
Motion Planning in
Joint Space
for Walking
Assistance With
Wearable Robot
IEEE-2015 In this paper, we propose an alternative motion planning
method for a wearable robot with a variable stride length and
walking speed. Trajectories are planned in a joint space rather
than a workspace to avoid an ill-posed problem with no
solution in inverse kinematics, and to consider the joint’s
range of motion, maximum velocity, foot clearance, and
backward balance. The joint trajectories are represented by
minimum jerk trajectories. Two via-points are assigned, and
the parameters (angle and angular velocity) at the via-points
are determined by applying an inverted pendulum model or
optimization to satisfy the constraints. The fastest gait pattern
generated by the proposed algorithm was twice as fast as the
pattern generated by the workspace-based planning method.
We confirmed that the fastest walking pattern of 0.36 m/s
was feasible on a tread mill, and a walking pattern of 0.27 m/s
was found for walking across the floor with a walker.
Furthermore, the proposed method required approximately
65% of the electric power for the workspace-based method for
the same walking speed and stride length. These results
suggest that the proposed motion planning method is
effective at generating a high-speed and efficient gait pattern
for a wearable robot.

38
71 EST-16 Path Following Using
Dynamic Transverse
Feedback
Linearization for Car-
Like Robots
IEEE-2015 This paper presents an approach for designing path following
controllers for the kinematic model of car-like mobile robots
using transverse feedback linearization with dynamic
extension.This approach is applicable to a large class of paths
and its effectiveness is experimentally demonstrated on a
Chameleon R100 Ackermann steering robot. Transverse
feedback linearization makes the desired path attractive and
invariant, while the dynamic extension allows the closed-loop
system to achieve the desired motion along the path.
72 EST-17 Recent Advances in
Wearable Sensors
for Health
Monitoring
IEEE-2015 Wearable sensor technology continues to advance and
provide significant opportunities for improving personalized
Health care. In recent years, advances in flexible electronics,
Smart materials and low-power computing and networking
have reduced barriers to technology accessibility, integration,
and cost, unleashing the potential for ubiquitous monitoring.
This paper discusses recent advances in wearable sensors and
systems that monitor movement, physiology, and
environment, with a focus on applications for Parkinson’s
disease, stroke, and head and neck injuries.
73 EST-18 Road Edge
Recognition Using
the Stripe Hough
Transform From
Millimeter-Wave
Radar Images
IEEE-2015 Millimeter-wave (MMW) radar, which is used for road feature
recognition, has performance that is superior to optical
cameras in terms of robustness in different weather and
lighting conditions, as well as providing ranging capabilities.
However, the signatures of road features in MMW radar
images are different from that of optical images, and even
physically continuous features, such as road edges, will be
presented as a set of bright points or spots distributed along
the roadside. Therefore, discrimination of the radar features is
of paramount importance in automotive imaging systems. To
tackle this problem, an approach called the stripe Hough
transform (HT) is introduced in this paper, allowing enhanced
extraction of the geometry of the road path. The performance
of the approach is demonstrated by comparison of extracted
features from MMW images with the real geometry of the
road and with the results of processing by classical HT.
74 EST-19 Scanning the Issue
and Beyond:
Transportation and
Mobility
Transformation for
Smart Cities
IEEE-2015 THE OVERALL performance and current status of IEEE
TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(T-ITS) have been reported and discussed in the first Executive
Committee (ExCom) meeting of the IEEE Intelligent
Transportation Systems Society (ITSS) this year, held in
beautiful Saint Thomas, U.S. Virgin Islands. I am glad to inform
you that the state of our journal is like the sunny blue sky,
white clouds, and lovely beach of the Virgin Islands: bright and
Pleasant. The ExCom has decided to establish a new platform

39
for ITSS social media presence; thus, our future abstracts will
be distributed through the new social media platform. This
issue starts with three survey papers on technology and
security for intelligent vehicles. I will go beyond smart cars and
share my thinking and view on issues of transportation and
mobility transformation for smart living in smart communities
and cities.
75 EST-20 Smart Lighting
System
ISO/IEC/IEEE 21451
Compatible
IEEE-2015 Smart lighting systems go far beyond merely replacing lamps.
These modern systems are now able to reproduce arbitrary
spectra, color temperatures, and intensities and pivot on
smart sensors and actuators incorporating information and
communication technologies. This paper presents an
interoperable smart lighting solution that combines
heterogeneous lighting technologies enabling intelligent
functions. The system can shift light intensity to increase
visual comfort, and it is oriented toward human centric
lighting studies. Moreover, this system follows the guidelines
defined by the ISO/IEC/IEEE 21451 standards and ZigBee Light
Link and also, it includes an additional transducer signal
treatment service for artificial intelligence algorithms. Finally,
a representational state transfer application allows us to test
the interoperability and visualize energy savings in an office
room.
76 EST-21 Wearable Sensors
for Human Activity
Monitoring: A
Review
IEEE-2015 An increase in world population along with a significant aging
portion is forcing rapid rises in healthcare costs. The
healthcare system is going through a transformation in which
continuous monitoring of inhabitants is possible even without
hospitalization. The advancement of sensing technologies,
embedded systems, wireless communication technologies,
nano technologies, and miniaturization makes it possible to
develop smart systems to monitor activities of human beings
continuously. Wearable sensors detect abnormal and/or
unforeseen situations by monitoring physiological parameters
along with other symptoms. Therefore, necessary help can be
provided in times of dire need. This paper reviews the latest
reported systems on activity monitoring of humans based on
wearable sensors and issues to be addressed to tackle the
challenges.
77 EST-22 Design of a Mobile
Charging Service for
Electric Vehicles in
an Urban
Environment
IEEE-2015 This paper presents a novel approach to providing a service for
electric-vehicle (EV) battery charge replenishment. This is an
alternate system in which the charge replenishment is
provided by mobile chargers (MCs). These chargers could have
two possible configurations: a mobile plug-in charger (MP) or
a mobile battery-swapping station (MS). A queuing-based

40
analytical approach is used to determine the appropriate
range of design parameters for such a mobile charging system.
An analytical analysis is first developed for an idealized system
with a nearest-job-next (NJN) service strategy explored for
such a system. In a NJN service strategy, the MC services the
next spatially closest EV when it is finished with its current
request. An urban environment approximated by Singapore is
then analyzed through simulation. Charging requests are
simulated through a trip generation model based on
Singapore. In such a realistic environment, an updated
practical NJN service strategy is proposed. For an MP system
in an urban environment such as Singapore, there exists an
optimal battery capacity with a threshold battery charge rate.
Similarly, the battery swap capacity of an MS system does not
need to be large for the system to perform.
78 EST-23 Comparison of
Charge Estimation
Methods
in Partial Discharge
Cable Measurements
IEEE-2015 The aim of this paper is to compare different partial discharge
(PD) charge estimation methods for PD cable measurements.
The paper covers the mathematical foundation behind the
different presented methods, and explores the limits of each
method regarding the associated maximum charge estimation
errors in PD cable measurements. The results are focused on
long cables where large PD pulse distortions are present and
therefore, the measured pulses differ significantly from the
calibrator ones. Each proposed method is analyzed, and
finally, limitations of each method are discussed.
79 EST-24 Hierarchical and
Networked Vehicle
Surveillance in ITS: A
Survey
IEEE-2015 Traffic surveillance has become an important topic in
intelligent transportation systems (ITSs), which is aimed at
monitoring and managing traffic flow. With the progress in
computer vision, video-based surveillance systems have made
great advances on traffic surveillance in ITSs. However, the
performance of most existing surveillance systems is
susceptible to challenging complex traffic scenes (e.g., object
occlusion, pose variation, and cluttered background).
Moreover, existing related research is mainly on a single video
sensor node, which is incapable of addressing the surveillance
of traffic road networks. Accordingly, we present a review of
the literature on the video-based vehicle surveillance systems
in ITSs.We analyze the existing challenges in video-based
surveillance systems for the vehicle and present a general
architecture for video surveillance systems, i.e., the
hierarchical and networked vehicle surveillance, to survey the
different existing and potential techniques.

42
M-MATLAB IP-Image Processing CM-Communication VP-Video Processing AP-Audio Processing
MATLAB IMAGE PROCESSING
S.NO CODE TITLE YEAR ABSTRACT
80 MIPST-01 Bayesian Fusion of
Multi-Band
Images
IEEE-2015 This paper presents a Bayesian fusion technique for
remotely sensed multi-band images is presented. The
observed images are related to the high spectral and
high spatial resolution image to be recovered through
physical degradations, e.g., spatial and spectral blurring
and/or subsampling defined by the sensor
characteristics. The fusion problem is formulated within
a Bayesian estimation framework. An appropriate prior
distribution exploiting geometrical consideration is
introduced. To compute the Bayesian estimator of the
scene of interest from its posterior distribution, a
Markov chain Monte Carlo algorithm is designed to
generate samples asymptotically distributed according to
the target distribution. To efficiently sample from this
high-dimension distribution, a Hamiltonian Monte Carlo
step is introduced in the Gibbs sampling strategy. The
efficiency of the proposed fusion method is evaluated
with respect to several state-of-the-art fusion
techniques.
81 MIPST-02 Registration of
Images With N-
Fold Dihedral Blur
IEEE-2015 In this paper, we extend our recent registration method
designed specifically for registering blurred images. The
original method works for unknown blurs, assuming the
blurring point-spread function (PSF) exhibits an N-fold
rotational symmetry. Here, we also generalize the theory
to the case of dihedrally symmetric blurs, which are
produced by the PSFs having both rotational and axial
symmetries .Such kind of blurs are often found in
unfocused images acquired by digital cameras, as in out
of focus shots the PSF typically mimics the shape of the
shutter aperture. This makes our registration algorithm
particularly well-suited in applications where blurred
image registration must be used as a preprocess step of
an image fusion algorithm, and where common
registration methods fail, due to the amount of blur. We
demonstrate that the proposed method leads to an
improvement of the registration performance, and we
show it to real images by providing successful examples
of blurred image registration followed by depth-of-field
extension and multichannel blind deconvolution.

43
82 MIPST-03 A Novel SURE-
Based Criterion for
Parametric PSF
Estimation
IEEE-2015 We propose an unbiased estimate of a filtered version of
the mean squared error—the blur-SURE (Stein’s
unbiased risk estimate)—as a novel criterion for
estimating an unknown point spread function (PSF) from
the degraded image only. The PSF is obtained by
minimizing this new objective functional over a family of
Wiener processing. Based on this estimated blur kernel,
we then perform nonblind deconvolution using our
recently developed algorithm. The SURE-based
framework is exemplified with a number of parametric
PSF, involving a scaling factor that controls the blur size.
A typical example of such parametrization is the
Gaussian kernel. The experimental results demonstrate
that minimizing the blur-SURE yields highly accurate
estimates of the PSF parameters, which also result in a
restoration quality that is very similar to the one
obtained with the exact PSF, when plugged into our
recent multi-Wiener SURE-LET deconvolution algorithm.
The highly competitive results obtained outline the great
potential of developing more powerful blind
deconvolution algorithms based on SURE-like estimates.
83 MIPST-04 Histogram-Based
Locality-
Preserving
Contrast
Enhancement
IEEE-2015 Histogram equalization (HE), a simple contrast
enhancement (CE) method, tends to show excessive
enhancement and gives unnatural artifacts on images
with high peaks in their histograms. Histogram-based CE
methods have been proposed in order to overcome the
drawback of HE, however, they do not always give good
enhancement results. In this letter, a histogram-based
locality-preserving CE method is proposed. The proposed
method is formulated as an optimization problem to
preserve localities of the histogram for performing image
CE. The locality-preserving property makes the histogram
shape of the enhanced image to be similar to that of the
original image. Experimental results show that the
proposed histogram-based method gives output images
with graceful CE on which existing methods give
unnatural results.
84 MIPST-05 An Efficient MRF
Embedded Level
Set Method for
Image
Segmentation
IEEE-2015 This paper presents a fast and robust level set method
for image segmentation. To enhance the robustness
against noise, we embed a Markov random field (MRF)
energy function to the conventional level set energy
function. This MRF energy function builds the correlation
of a pixel with its neighbors and encourages them to fall
into the same region. To obtain a fast implementation of

44
the MRF embedded level set model, we explore algebraic
multigrid (AMG) and sparse field method (SFM) to
increase the time step and decrease the computation
domain ,respectively. Both AMG and SFM can be
conducted in a parallel fashion, which facilitates the
processing of our method for big image databases. By
comparing the proposed fast and robust level set
method with the standard level set method and its
popular variants on noisy synthetic images, synthetic
aperture radar (SAR) images, medical images, and
natural images, we comprehensively demonstrate the
new method is robust against various kinds of noises. In
particular, the new level set method can segment an
image of size 500 × 500 within 3 s on MATLAB R2010b
installed in a computer with 3.30-GHz CPU and 4-GB
memory.
85 MIPST-06 Robust Clutter
Suppression and
Moving Target
Imaging Approach
for Multichannel
in Azimuth
High-Resolution
and Wide-Swath
Synthetic
Aperture Radar
IEEE-2015 This paper describes a clutter suppression approach
and the corresponding moving target imaging algorithm
for a multichannel in azimuth high-resolution and wide-
swath (MC-HRWS) synthetic aperture radar (SAR)
system. Incorporated with digital beaforming processing,
MC-HRWS SAR systems are able to suppress the Doppler
ambiguities to allow for HRWS SAR imaging and null the
clutter directions to suppress clutter for ground moving
target indication. In this paper, the degrees of freedom in
azimuth for the multichannel SAR systems are employed
to implement clutter suppression. First, the clutter and
moving target echoes are transformed into the range
compression and azimuth chirp Fourier transform
frequency domain, i.e., coarse-focused images
formation, when the clutter echoes are with azimuth
Doppler ambiguity. Considering that moving targets are
sparse in the imaging scene and that there is a difference
between clutter and a moving target in the spatial
domain, a series of spatial domain filters are constructed
to extract moving target echoes. Then, using an
extracted moving target echo, two groups of signals are
formed, and slant-range velocity of a moving target can
be estimated based on baseband Doppler centroid
estimation algorithm and multilook cross-correlation
Doppler centroid ambiguity number resolving approach.
After the linear range cellmigration correction and
azimuth focus processing, a well-focused moving target
image can be obtained.

BEST FINAL YEAR PROJECT IEEE 2015 BY SPECTRUM SOLUTIONS PONDICHERRY

BEST FINAL YEAR PROJECT IEEE 2015 BY SPECTRUM SOLUTIONS PONDICHERRY

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