Abstract: In a real world scenario, the viability of the sensor networks has been proved by standardizing the technologies. Wireless sensor networks are vulnerable to both electronic and physical security breaches because of their deployment in remote, distributed, and inaccessible locations. The compromised sensor nodes send malicious data to the base station, and thus, the total network effectiveness will possibly be compromised. To detect and seclude the Route modifiers, a neural network based Pattern Learning predictor (PLP) is presented. This algorithm senses data at any node on present and previous patterns obtained from the en-route nodes. The eminence of any node is upgraded by their predicted and reported patterns. This paper propounds a solution not only to detect the route modifiers, but also to seclude the malevolent nodes from the network. The simulation result proves the effective performance of the network by the presented methodology in terms of energy level, routing and various network conditions.
Abstract: Co-channel interference is one of the major problems in wireless systems. The effects of co-channel interference in a Nakagami fading channel on the ABER (Average Bit Error Rate) with static nodes are well analyzed. In this paper, we derive the ABER with the presence of mobile nodes. ABER is also derived for mobile systems in the presence of co-channel interference.
Abstract: The mobile cloud computing (MCC) with wireless sensor networks (WSNs) technology gets more attraction by research scholars because its combines the sensors data gathering ability with the cloud data processing capacity. This approach overcomes the limitation of data storage capacity and computational ability of sensor nodes. Finally, the stored data are sent to the mobile users when the user sends the request. The most of the integrated sensor-cloud schemes fail to observe the following criteria: 1) The mobile users request the specific data to the cloud based on their present location. 2) Power consumption since most of them are equipped with non-rechargeable batteries. Mostly, the sensors are deployed in hazardous and remote areas. This paper focuses on above observations and introduces an approach known as collaborative location-based sleep scheduling (CLSS) scheme. Both awake and asleep status of each sensor node is dynamically devised by schedulers and the scheduling is done purely based on the of mobile users’ current location; in this manner, large amount of energy consumption is minimized at WSN. CLSS work depends on two different methods; CLSS1 scheme provides lower energy consumption and CLSS2 provides the scalability and robustness of the integrated WSN.
Abstract: Predicting links that may occur in the future and missing links in social networks is an attractive problem in social network analysis. Granular computing can help us to model the relationships between human-based system and social sciences in this field. In this paper, we present a model based on granular computing approach and Type-2 fuzzy logic to predict links regarding nodes’ activity and the relationship between two nodes. Our model is tested on collaboration networks. It is found that the accuracy of prediction is significantly higher than the Type-1 fuzzy and crisp approach.
Abstract: In wireless sensor networks, locality and positioning information can be captured using Global Positioning System (GPS). This message can be congregated initially from spot to identify the system. Users can retrieve information of interest from a wireless sensor network (WSN) by injecting queries and gathering results from the mobile sink nodes. Routing is the progression of choosing optimal path in a mobile network. Intermediate node employs permutation of device nodes into teams and generating cluster heads that gather the data from entity cluster’s node and encourage the collective data to base station. WSNs are widely used for gathering data. Since sensors are power-constrained devices, it is quite vital for them to reduce the power utilization. A tree-based data fusion clustering routing algorithm (TBDFC) is used to reduce energy consumption in wireless device networks. Here, the nodes in a tree use the cluster formation, whereas the elevation of the tree is decided based on the distance of the member nodes to the cluster-head. Network simulation shows that this scheme improves the power utilization by the nodes, and thus considerably improves the lifetime.
Abstract: Mobile Ad-hoc Network (MANET) is an infrastructure-less network of mobile devices, also known as nodes. These nodes heavily rely on each other’s resources such as memory, computing power, and energy. Thus, some nodes may become selective in forwarding packets so as to conserve their resources. These nodes are called misleading nodes. Several reputation-based techniques (e.g. CORE, CONFIDANT, LARS, SORI, OCEAN) and acknowledgment-based techniques (e.g. TWOACK, S-TWOACK, EAACK) have been proposed to detect such nodes. These techniques do not appropriately punish misleading nodes. Hence, this paper addresses the limitations of these techniques using a system called MINDRA.
Abstract: With the increasing use and application of Wireless Sensor Networks (WSN), need has arisen to explore them in more effective and efficient manner. An important area which can bring efficiency to WSNs is the localization process, which refers to the estimation of the position of wireless sensor nodes in an ad hoc network setting, in reference to a coordinate system that may be internal or external to the network. In this paper, we have done comparison and analysed Sigmoidal Feedforward Artificial Neural Networks (SFFANNs) and Radial Basis Function (RBF) networks for developing localization framework in WSNs. The presented work utilizes the Received Signal Strength Indicator (RSSI), measured by static node on 100 x 100 m2 grid from three anchor nodes. The comprehensive evaluation of these approaches is done using MATLAB software. The simulation results effectively demonstrate that FFANNs based sensor motes will show better localization accuracy as compared to RBF.
Abstract: Wireless Sensor Networks (WSNs) have many advantages. Their deployment is easier and faster than wired sensor networks or other wireless networks, as they do not need fixed infrastructure. Nodes are partitioned into many small groups named clusters to aggregate data through network organization. WSN clustering guarantees performance achievement of sensor nodes. Sensor nodes energy consumption is reduced by eliminating redundant energy use and balancing energy sensor nodes use over a network. The aim of such clustering protocols is to prolong network life. Low Energy Adaptive Clustering Hierarchy (LEACH) is a popular protocol in WSN. LEACH is a clustering protocol in which the random rotations of local cluster heads are utilized in order to distribute energy load among all sensor nodes in the network. This paper proposes Connected Dominant Set (CDS) based cluster formation. CDS aggregates data in a promising approach for reducing routing overhead since messages are transmitted only within virtual backbone by means of CDS and also data aggregating lowers the ratio of responding hosts to the hosts existing in virtual backbones. CDS tries to increase networks lifetime considering such parameters as sensors lifetime, remaining and consumption energies in order to have an almost optimal data aggregation within networks. Experimental results proved CDS outperformed LEACH regarding number of cluster formations, average packet loss rate, average end to end delay, life computation, and remaining energy computation.
Abstract: Energy has a prominent role for development of
nations. Countries which have energy resources also have strategic
power in the international trade of energy since it is essential for all
stages of production in the economy. Thus, it is important for
countries to analyze the weaknesses and strength of the system. On
the other side, international trade is one of the fields that are analyzed
as a complex network via network analysis. Complex network is one
of the tools to analyze complex systems with heterogeneous agents
and interaction between them. A complex network consists of nodes
and the interactions between these nodes. Total properties which
emerge as a result of these interactions are distinct from the sum of
small parts (more or less) in complex systems. Thus, standard
approaches to international trade are superficial to analyze these
systems. Network analysis provides a new approach to analyze
international trade as a network. In this network, countries constitute
nodes and trade relations (export or import) constitute edges. It
becomes possible to analyze international trade network in terms of
high degree indicators which are specific to complex networks such
as connectivity, clustering, assortativity/disassortativity, centrality,
etc. In this analysis, international trade of crude oil and coal which
are types of fossil fuel has been analyzed from 2005 to 2014 via
network analysis. First, it has been analyzed in terms of some
topological parameters such as density, transitivity, clustering etc.
Afterwards, fitness to Pareto distribution has been analyzed via
Kolmogorov-Smirnov test. Finally, weighted HITS algorithm has
been applied to the data as a centrality measure to determine the real
prominence of countries in these trade networks. Weighted HITS
algorithm is a strong tool to analyze the network by ranking countries
with regards to prominence of their trade partners. We have
calculated both an export centrality and an import centrality by
applying w-HITS algorithm to the data. As a result, impacts of the
trading countries have been presented in terms of high-degree
indicators.
Abstract: Opportunistic Routing (OR) increases the
transmission reliability and network throughput. Traditional routing
protocols preselects one or more predetermined nodes before
transmission starts and uses a predetermined neighbor to forward a
packet in each hop. The opportunistic routing overcomes the
drawback of unreliable wireless transmission by broadcasting one
transmission can be overheard by manifold neighbors. The first
cooperation-optimal protocol for Multirate OR (COMO) used to
achieve social efficiency and prevent the selfish behavior of the
nodes. The novel link-correlation-aware OR improves the
performance by exploiting the miscellaneous low correlated forward
links. Context aware Adaptive OR (CAOR) uses active suppression
mechanism to reduce packet duplication. The Context-aware OR
(COR) can provide efficient routing in mobile networks. By using
Cooperative Opportunistic Routing in Mobile Ad hoc Networks
(CORMAN), the problem of opportunistic data transfer can be
tackled. While comparing to all the protocols, COMO is the best as it
achieves social efficiency and prevents the selfish behavior of the
nodes.
Abstract: This paper presents a case study of using STATCOM to enhance the performance of Al-Qatraneh 33-kV transmission line. The location of the STATCOM was identified by maintaining minimum voltage drops at the 110 load nodes. The transmission line and the 110 load nodes have been modeled by MATLAB/Simulink. The suggested STATCOM and its location will increase the transmission capability of this transmission line and overcome the overload expected in the year 2020. The annual percentage loading rise has been considered as 14.35%. A graphical representation of the line-to-line voltages and the voltage drops at different load nodes is illustrated.
Abstract: Wireless Sensor Networks (WSNs) enable new
applications and need non-conventional paradigms for the protocol
because of energy and bandwidth constraints, In WSN, sensor node’s
life is a critical parameter. Research on life extension is based on
Low-Energy Adaptive Clustering Hierarchy (LEACH) scheme,
which rotates Cluster Head (CH) among sensor nodes to distribute
energy consumption over all network nodes. CH selection in WSN
affects network energy efficiency greatly. This study proposes an
improved CH selection for efficient data aggregation in sensor
networks. This new algorithm is based on Bacterial Foraging
Optimization (BFO) incorporated in LEACH.
Abstract: Geographical routing protocol requires node physical
location information to make forwarding decision. Geographical
routing uses location service or position service to obtain the position
of a node. The geographical information is a geographic coordinates
or can be obtained through reference points on some fixed coordinate
system. Link can be formed between two nodes. Link lifetime plays a
crucial role in MANET. Link lifetime represent how long the link is
stable without any failure between the nodes. Link failure may occur
due to mobility and because of link failure energy of nodes can be
drained. Thus this paper proposes survey about link lifetime
prediction using geographical information.
Abstract: Designing cost-efficient, secure network protocols for
Wireless Sensor Networks (WSNs) is a challenging problem because
sensors are resource-limited wireless devices. Security services such
as authentication and improved pairwise key establishment are
critical to high efficient networks with sensor nodes. For sensor
nodes to correspond securely with each other efficiently, usage of
cryptographic techniques is necessary. In this paper, two key
predistribution schemes that enable a mobile sink to establish a
secure data-communication link, on the fly, with any sensor nodes.
The intermediate nodes along the path to the sink are able to verify
the authenticity and integrity of the incoming packets using a
predicted value of the key generated by the sender’s essential power.
The proposed schemes are based on the pairwise key with the mobile
sink, our analytical results clearly show that our schemes perform
better in terms of network resilience to node capture than existing
schemes if used in wireless sensor networks with mobile sinks.
Abstract: The main function of Medium Access Control (MAC) is to share the channel efficiently between all nodes. In the real-time scenario, there will be certain amount of wastage in bandwidth due to back-off periods. More bandwidth will be wasted in idle state if the back-off period is very high and collision may occur if the back-off period is small. So, an optimization is needed for this problem. The main objective of the work is to reduce delay due to back-off period thereby reducing collision and increasing throughput. Here a method, called the virtual back-off algorithm (VBA) is used to optimize the back-off period and thereby it increases throughput and reduces collisions. The main idea is to optimize the number of transmission for every node. A counter is introduced at each node to implement this idea. Here counter value represents the sequence number. VBA is classified into two types VBA with counter sharing (VBA-CS) and VBA with no counter sharing (VBA-NCS). These two classifications of VBA are compared for various parameters. Simulation is done in NS-2 environment. The results obtained are found to be promising.
Abstract: This paper presents a novel algorithm for secure,
reliable and flexible transmission of big data in two hop wireless
networks using cooperative jamming scheme. Two hop wireless
networks consist of source, relay and destination nodes. Big data has
to transmit from source to relay and from relay to destination by
deploying security in physical layer. Cooperative jamming scheme
determines transmission of big data in more secure manner by
protecting it from eavesdroppers and malicious nodes of unknown
location. The novel algorithm that ensures secure and energy balance
transmission of big data, includes selection of data transmitting
region, segmenting the selected region, determining probability ratio
for each node (capture node, non-capture and eavesdropper node) in
every segment, evaluating the probability using binary based
evaluation. If it is secure transmission resume with the two- hop
transmission of big data, otherwise prevent the attackers by
cooperative jamming scheme and transmit the data in two-hop
transmission.
Abstract: In this paper we propose a novel methodology for
extracting a road network and its nodes from satellite images of
Algeria country.
This developed technique is a progress of our previous research
works. It is founded on the information theory and the mathematical
morphology; the information theory and the mathematical
morphology are combined together to extract and link the road
segments to form a road network and its nodes.
We therefore have to define objects as sets of pixels and to study
the shape of these objects and the relations that exist between them.
In this approach, geometric and radiometric features of roads are
integrated by a cost function and a set of selected points of a crossing
road. Its performances were tested on satellite images of Algeria
country.
Abstract: This paper presents an optimal broadcast algorithm
for the hypercube networks. The main focus of the paper is the
effectiveness of the algorithm in the presence of many node faults.
For the optimal solution, our algorithm builds with spanning tree
connecting the all nodes of the networks, through which messages
are propagated from source node to remaining nodes. At any given
time, maximum n − 1 nodes may fail due to crashing. We show
that the hypercube networks are strongly fault-tolerant. Simulation
results analyze to accomplish algorithm characteristics under many
node faults. We have compared our simulation results between our
proposed method and the Fu’s method. Fu’s approach cannot tolerate
n − 1 faulty nodes in the worst case, but our approach can tolerate
n − 1 faulty nodes.
Abstract: In urban context, urban nodes such as amenity or
hazard will certainly affect house price, while classic hedonic analysis
will employ distance variables measured from each urban nodes.
However, effects from distances to facilities on house prices generally
do not represent the true price of the property. Distance variables
measured on the same surface are suffering a problem called
multicollinearity, which is usually presented as magnitude variance
and mean value in regression, errors caused by instability. In this paper,
we provided a theoretical framework to identify and gather the data
with less bias, and also provided specific sampling method on locating
the sample region to avoid the spatial multicollinerity problem in three
distance variable’s case.
Abstract: Nature is the immense gifted source for solving
complex problems. It always helps to find the optimal solution to
solve the problem. Mobile Ad Hoc NETwork (MANET) is a wide
research area of networks which has set of independent nodes. The
characteristics involved in MANET’s are Dynamic, does not depend
on any fixed infrastructure or centralized networks, High mobility.
The Bio-Inspired algorithms are mimics the nature for solving
optimization problems opening a new era in MANET. The typical
Swarm Intelligence (SI) algorithms are Ant Colony Optimization
(ACO), Artificial Bee Colony (ABC), Particle Swarm Optimization
(PSO), Modified Termite Algorithm, Bat Algorithm (BA), Wolf
Search Algorithm (WSA) and so on. This work mainly concentrated
on nature of MANET and behavior of nodes. Also it analyses various
performance metrics such as throughput, QoS and End-to-End delay
etc.