Ns2 2015 2016 ieee project list-(v)_with abstract(S3 Infotech:9884848198)

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NS2 – IEEE 2015 PROJECT TITLES
S3NS2001 - Defending Against Collaborative Attacks by Malicious Nodes in
MANETs: A Cooperative Bait Detection Approach
In mobile ad hoc networks (MANETs), a primary requirement for the
establishment of communication among nodes is that nodes should cooperate with
each other. In the presence of malevolent nodes, this requirement may lead to
serious security concerns; for instance, suchnodes may disrupt the routing process.
In this context, preventing or detecting malicious nodes launching grayhole or
collaborative blackhole attacks is a challenge. This paper attempts to resolve this
issue by designing a dynamic source routing (DSR)-based routing mechanism,
which is referred to as the cooperative bait detection scheme (CBDS), that
integrates the advantages of both proactive and reactive defense architectures. Our
CBDS method implements a reverse tracing technique to help in achieving the
stated goal. Simulation results are provided, showing that in the presence of
malicious-node attacks, the CBDS outperforms the DSR, 2ACK, and best-effort
fault-tolerant routing (BFTR) protocols (chosen as benchmarks) in terms of packet
delivery ratio and routing overhead (chosen as performance metrics).
S3NS2002 - Enhanced ANTSEC framework with cluster based cooperative
caching in mobile ad hoc networks
In a mobile ad hoc network (MANET), communication between mobile
nodes occurs without centralized control. In this environment the mobility of a
node is unpredictable; this is considered as a characteristic of wireless networks.
Because of faulty or malicious nodes, the network is vulnerable to routing
misbehavior. The resource constrained characteristics of MANETs leads to
increased query delay at the time of data access. In this paper,
AntHocNet+Security (ANTSEC) framework is proposed that includes an enhanced
cooperative caching scheme embedded with artificial immune system. This
framework improves security by injecting immunity into the data packets,
improves the packet delivery ratio and reduces end-to-end delay using cross layer

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design. The issues of node failure and node malfunction are addressed in the cache
management.
S3NS2003 - Experimental Assessment of ABNO-Driven Multicast
Connectivity in Flexgrid Networks
The increasing demand of internet services is pushing cloud services
providers to increase the capacity of their data centers (DC) and create DC
federations, where two or more cloud providers interconnect their infrastructures.
As a result of the huge capacity required for the inter-DC network, the flexgrid
optical technology can be used. In such scenario, applications can run in DCs
placed in geographically distant locations, and hence, multicast-based
communication services among their components are required. In this paper, we
study two different approaches to provide multicast services in multilayer
scenarios assuming that the optical network is based on the flexgrid technology: 1)
establishing a point-to-multipoint optical connection (light-tree) for each multicast
request, and 2) using a multipurpose virtual network topology (VNT) to serve both
unicast and multicast connectivity requests. When that VNT is not able to serve an
incoming request as a result of lack of capacity, it is reconfigured to add more
resources. A control plane architecture based on the applications-based network
operations (ABNO) one, currently being standardized by the IETF, is presented;
workflows are proposed and PCEP extensions are studied for the considered
approaches. The experimental validation is carried-out on a testbed setup
connecting Telefonica, CNIT, and UPC premises.
S3NS2004 - Game Theoretic Max-logit Learning Approaches for Joint Base
Station Selection and Resource Allocation in Heterogeneous Networks
This paper investigates the problem of joint base station selection and
resource allocation in an orthogonal frequency division multiple access (OFDMA)
heterogeneous cellular network. The original throughput maximization problem is
NP-hard and we propose solving it by using game theoretic stochastic learning
approaches. To this end, we first transform the original problem into a tractable
form, which has a weighted utility function. Then we prove that an exact potential
game applies and it exists the best Nash equilibria which is a near optimal solution

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of the original problem when an efficient solution method of the weights is
employed. To obtain the optimal solution, we redesign the utility function by
leveraging a state space to formulate the original problem into an ordinal state
based potential game, which is proved that it exists a recurrent state equilibrium
point that maximizes system throughput. Furthermore, we propose two different
variants of Max-logit learning algorithm based on these two games respectively:
one is a simultaneous learning algorithm with less information exchange, which
achieves the best Nash equilibrium point of the exact potential game and the other
is an efficient learning algorithm for the ordinal state based potential game, which
can converge to the global optimization solution. Finally, numerical results are
given to validate those theoretical findings.
S3NS2005- A Scalable, Low-Latency, High-Throughput, Optical Interconnect
Architecture Based on Arrayed Waveguide Grating Routers
This paper proposes, simulates, and experimentally demonstrates an optical
interconnect architecture for large-scale computing systems. The proposed
architecture, Hierarchical Lightwave Optical Interconnect Network (H-LION),
leverages wavelength routing in arrayed waveguide grating routers (AWGRs), and
computing nodes (or servers) with embedded routers and wavelength-specific
optical I/Os. Within the racks and clusters, the interconnect topology is hierarchical
all-to-all exploiting passive AWGRs. For the intercluster communication, the
proposed architecture exploits a flat and distributed Thin-CLOS topology based on
AWGR-based optical switches. H-LION can scale beyond 100 000 nodes while
guaranteeing up to 1.83×saving in number of inter-rack cables, and up to
1.5×saving in number of inter-rack switches, when compared with a legacy three-
tier Fat Tree network. Network simulation results show a system-wide network
throughput reaching as high as 90% of the total possible capacity in case of
synthetic traffic with uniform random distribution. Experiments show 97% intra
cluster throughput for uniform random traffic, and error-free intercluster
communication at 10 Gb/s.
S3NS2006 - Analysis of system trustworthiness based on information flow
noninterference theory

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The trustworthiness analysis and evaluation are the bases of the trust chain
transfer. In this paper the formal method of trustworthiness analysis of a system
based on the noninterference (NI) theory of the information flow is studied. Firstly,
existing methods cannot analyze the impact of the system states on the
trustworthiness of software during the process of trust chain transfer. To solve this
problem, the impact of the system state on trustworthiness of software is
investigated, the run-time mutual interference behavior of software entities is
described and an interference model of the access control automaton of a system is
established. Secondly, based on the intransitive noninterference (INI) theory, a
formal analytic method of trustworthiness for trust chain transfer is proposed,
providing a theoretical basis for the analysis of dynamic trustworthiness of
software during the trust chain transfer process. Thirdly, a prototype system with
dynamic trustworthiness on a platform with dual core architecture is constructed
and a verification algorithm of the system trustworthiness is provided. Finally, the
monitor hypothesis is extended to the dynamic monitor hypothesis, a theorem of
static judgment rule of system trustworthiness is provided, which is useful to prove
dynamic trustworthiness of a system at the beginning of system construction.
Compared with previous work in this field, this research proposes not only a
formal analytic method for the determination of system trustworthiness, but also a
modeling method and an analysis algorithm that are feasible for practical
implementation.
S3NS2007- Mobile Sink based Adaptive Immune Energy-Efficient Clustering
Protocol for Improving the Lifetime and Stability Period of Wireless Sensor
Networks
Energy hole problem is a critical issue for data gathering in Wireless Sensor
Networks. Sensors near the static sink act as relays for far sensor and thus will
deplete their energy very quickly, resulting energy holes in the sensor field.
Exploiting the mobility of a sink has been widely accepted as an efficient way to
alleviate this problem. However, determining an optimal moving trajectory for a
mobile sink is an NP-hard problem. Thus, this paper proposed a Mobile Sink based
adaptive Immune Energy-Efficient clustering Protocol (MSIEEP) to alleviate the
energy holes. MSIEEP uses the Adaptive Immune Algorithm (AIA) to guide the

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mobile sink based on minimizing the total dissipated energy in communication and
overhead control packets. Moreover, AIA is used to find the optimum number of
Cluster Heads (CHs) to improve the lifetime and stability period of the network.
The performance of MSIEEP is compared with the previously published protocols;
namely LEACH, LEACHGA, A-LEACH, rendezvous and MIEEPB using Matlab.
Simulation results show that MSIEEP is more reliable and energy efficient as
compared to other protocols. Furthermore, it improves the lifetime, the stability
and the instability periods over the previous protocols, because it always selects
CHs from high energy nodes. Moreover, the mobile sink increases the ability of the
proposed protocol to deliver packets to the destination.
S3NS2008 - Joint Resource Allocation for Throughput Enhancement in
Cognitive Radio Femto cell Networks
In cognitive radio femto cell network (CRFN), secondary users (SUs)
cooperatively sense a spectrum band to decide the presence of primary network.
However, this sensing overhead generally degrades the throughput performance.
The prior work, to resolve this problem, proposed algorithms either to decrease the
time spent in sensing or to decrease the number of SUs participating in sensing. In
this paper, we propose a joint resource allocation (RA) strategy considering the
time and energy consumed for spectrum sensing to maximize the throughput while
satisfying the target detection performance in CRFN. Furthermore, to reduce the
resources used in spectrum sensing additionally, we also adopt the right censored
order statistics based cooperative spectrum sensing scheme, which produces the
criterion for deciding the set of reporting SUs. By so jointly designing the time and
energy for sensing, the proposed joint RA scheme provides the improvement of
spectral efficiency. Through simulation results, it is shown that the proposed joint
RA scheme exhibits the enhanced performance over the conventional ones in terms
of total throughput of secondary networks.
S3NS2009 - A survey on the privacy-preserving data aggregation in wireless
sensor networks
Wireless sensor networks (WSNs) consist of a great deal of sensor nodes
with limited power, computation, storage, sensing and communication capabilities.

S3 INFOTECH +91 988 48 48 198
Data aggregation is a very important technique, which is designed to substantially
reduce the communication overhead and energy expenditure of sensor node during
the process of data collection in a WSNs. However, privacy-preservation is more
challenging especially in data aggregation, where the aggregators need to perform
some aggregation operations on sensing data it received. We present a state-of-the
art survey of privacy-preserving data aggregation in WSNs. At first, we classify
the existing privacy- preserving data aggregation schemes into different categories
by the core privacy-preserving techniques used in each scheme. And then compare
and contrast different algorithms on the basis of performance measures such as the
privacy protection ability, communication consumption, power consumption and
data accuracy etc. Furthermore, based on the existing work, we also discuss a
number of open issues which may intrigue the interest of researchers for future
work.
S3NS20010 - Energy Detection Technique for Adaptive Spectrum Sensing
The increasing scarcity in the available spectrum for wireless
communication is one of the current bottlenecks impairing further deployment of
services and coverage. The proper exploitation of white spaces in the radio
spectrum requires fast, robust, and accurate methods for their detection. This paper
proposes a new strategy to detect adaptively white spaces in the radio spectrum.
Such strategy works in Cognitive Radio (CR) networks whose nodes perform
spectrum sensing based on energy detection in a cooperative way or not. The main
novelty of the proposal is the use of a cost-function that depends upon a single
parameter which, by itself, contains the aggregate information about the presence
or absence of primary users. The detection of white spaces based on this parameter
is able to improve significantly the deflection coefficient associated with the
detector, as compared to other state-of-the-art algorithms. In fact, simulation
results show that the proposed algorithm outperforms by far other competing
algorithms. For example, our proposal can yield a probability of miss-detection 20
times smaller than that of an optimal soft-combiner solution in a cooperative setup
with a predefined probability of false alarm of 0.1.

Ns2 2015 2016 ieee project list-(v)_with abstract(S3 Infotech:9884848198)

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