A review on rendezvous based data acquisition methods in wireless sensor networks with mobile sink

Wireless Networks - Solutions for energy hole problem in wireless sensor networks (WSNs) have been excessively explored using mobile sink (MS). Although, MS provides a considerable amount of energy...     

A Survey on Path Planning Techniques for Mobile Sink in IoT-Enabled Wireless Sensor Networks

Wireless Personal Communications - Recently, the Internet of Things (IoT) had emerged very rapidly and became the most important technology in today’s era. In an IoT-based environment, every...     

Nodal congestion price estimation in spot power market using artificial neural network

In the world wide increasing trend of restructured power system, open access in transmission system and competition in generation and distribution have introduced a frequently occurring problem of congestion. To establish a proficient price-based congestion management procedure, the nodal pricing strategy is found to be appropriate. From congestion management point of view, the optimal nodal prices are comprised of two basic components. First component is locational marginal price, that is marginal cost of generation to supply load and transmission losses both. Second component is nodal congestion price (NCP), that is the charges to maintain network security. Levenberg-Marquardt algorithm based neural network (LMANN) for estimating NCPs in spot power market by dividing the whole power system into various congestion zones is presented. Euclidian distance based clustering technique has been applied for feature selection before employing LMANN. The purpose of using artificial neural network (ANN) based approach for NCP estimation in spot power market is to exploit the tolerance for any missing or partially corrupted data to achieve tractability, robustness and very fast solution. The proposed ANN method also handles the congestion price volatility by taking continuously varying load and constrained transmission into account. The information provided by the proposed method regarding the formation of different congestion zones and the severity of congestion within a zone instructs both the market participants as well as independent system operator in making effective decisions. The proposed method has been examined for an RTS 24-bus system and is found to be quite promising.     

A Novel Technique for Gateway Selection in Hybrid MANET Using Genetic Algorithm

Integration of Mobile Ad hoc NETworks (MANETs) with the Internet has been paid immense attention in the field of heterogeneous networks. In MANET some intermediate nodes called Internet Gateways (IGs) are responsible for sending the data traffic of source nodes towards the fixed nodes in the Internet. The key issue considered while selecting IG nodes is its optimised throughput with the reduced delay in resource constraint mobile nodes. In this paper, a genetic algorithm inspired Delay Sensitive Gateway Selection (DSGS) scheme is proposed considering the issue of network delay by minimising the total distance travelled by the source nodes to the gateway. The performance of the proposed GA-based DSGS scheme is studied using a comparative approach. The simulation results demonstrate that the proposed scheme significantly outperforms the conventional schemes and is capable of achieving higher network throughput while minimising the end-to-end delay.

     

Gateway load balancing using multiple QoS parameters in a hybrid MANET

A Mobile ad hoc network (MANET) is a self configurable wireless network in which mobile nodes communicate with each other in a multihop fashion without any pre-installed infrastructure. A MANET can be considered to be a standalone network. To enhance the connectivity of a MANET it can be connected to the fixed network, thus forming a heterogeneous network. The integration of MANET and the Internet is called a hybrid MANET which is facilitated by special nodes called Internet gateway nodes. Load balancing among gateways is a challenging task when a MANET is connected to Internet. Gateway nodes with higher loads will lead to disconnected networks and depletes the node’s resources which include their batteries, memory and bandwidth quickly. Gateway selection based on the shortest path may increase traffic concentration on one particular gateway which leads to congestion and increases delay in the network. In this paper a QoS based load balancing mechanism has been proposed among multiple gateway nodes that provide communication between mobile nodes and fixed nodes in the Internet to select lightly loaded gateways so that more packets will be delivered to the fixed host in the Internet. The proposed QoS based scheme selects four QoS parameters that are (1) connecting degree, (2) interface queue length, (3) routing table entries and (4) hop count. A weight based method is used to select the gateway which combines all four QoS metrics. Simulation results demonstrate that when compared with individual parameter, the average ETE delay, queue size and traffic load of gateway generated by proposed algorithm is decreased by 17, 25 and 15 % respectively and when compared with existing schemes, the average ETE delay, queue size and traffic load of gateway is decreased by 25, 25 and 16 % respectively.     

Light weight security protocol for communications in vehicular networks

Increasing demand in user-friendly, computationally efficient and sophisticated vehicles led automobile industries to manufacture them with efficient onboard sensors, communication devices, resource rich hardware. Vehicular resources provide infotainment on-the-go. In mere future, every vehicle is a resource full machine. The vehicular resources which include computing power, storage and internet connectivity can be shared among the vehicles or can be lend over the internet to various customers. Vehicles can comprehensively make use of the resources available with road-side units (RSU’s) to communicate with other vehicles and RSU’s. Vehicular communications are useful especially in situations of accidents (or) natural calamities. Vehicles can update the RSU’s with information regarding such events. This information can then be broadcasted to the vehicles in that area or path. The proposed scheme ensures secure and efficient communications among nodes in a hierarchy consisting of vehicles, RSU’s, RSU co-ordinators and Trusted authority. The approach outlined in the paper can be used to decrease the overhead involved in secure transfer of information during communication.     

RSS Fingerprints Based Distributed Semi-Supervised Locally Linear Embedding (DSSLLE) Location Estimation System for Indoor WLAN

An important requirement for many novel location based services, is to determine the locations of people, equipment, animals, etc. The accuracy and response time of estimation are critical issues in location estimation system. Most of the location estimation system suffers with the problem of scalability and unavailability of all the access points at all the location for large site. In this paper, we have proposed a distributed semi-supervised location estimation method, which divide the location estimation system into subsystems. Our method partition the input signal space and output location space into clusters on the basis of visibility of access points at various locations of the site area. Each cluster of input signal space together with output location subspace is used to learn the association between Received Signal Strength fingerprint and their respective location in a subsystem. Previous methods for location estimation in indoor wireless networks require a large amount of labeled data for learning the radio map. However, labeled instances are often difficult, expensive, or time consuming to obtain, as they require great efforts, meanwhile unlabeled data may be relatively easy to collect. So, the use of semi-supervised learning is more feasible. On each subsystem at first, we use Locally Linear Embedding to reduce the dimensions of data, and then we use semi-supervised learning algorithm to learn the radio map. The algorithm performs nonlinear mapping between the received signal strengths from nearby access points and the user’s location. It is shown that the proposed Distributed Semi-Supervised Locally Linear Embedding scheme has the advantage of robustness, scalability, useful in large site application and is easy in training and implementation. We have compared our results with Distributed Subtract on Negative Add on Positive (DSNAP) and benchmark method RADAR. Experimental results show that our method provide better results in terms of accuracy and response time in comparison to centralized systems, in which a single system is used for large site as well as with DSNAP and benchmark method RADAR.     

Effect of Coating of Ammonium Perchlorate with Fluorocarbon on Ballistic and Sensitivity Properties of AP/Al/HTPB Propellant

Fluorocarbon polymers are used to enhance thermal stability and electrostatic protection of composite propellant compositions. A precipitation technique has been developed to coat ammonium perchlorate (AP) using a copolymer of hexafluoropropylene and vinylidene fluoride (HFP‐VF) with the help of solvent‐counter solvent method. The coated AP has been used to prepare propellant compositions in different ratio based on hydroxyl terminated polybutadiene (HTPB), aluminium powder along with uncoated AP and studied for viscosity build‐up and visco‐elastic behaviour as well as mechanical, ballistic, thermal and sensitivity properties keeping 86% solid loading. The data on viscosity build‐up indicate that as the percentage of viton coated AP increases end of mix viscosity and viscosity build‐up increase accordingly. The mechanical properties data reveal that tensile strength and percentage elongation are found in increasing order. The burn rate of the composition also increases on higher percentage of HFP‐VF coated AP. The thermal stability of composition increases as the percentage of HFP‐VF coated AP increases. The data on sensitivity indicate that impact sensitivity decreases on increasing the percentage of HFP‐VF coated AP while no change is observed in friction sensitivity value.     

Performance Analysis of Received Signal Strength Fingerprinting Based Distributed Location Estimation System for Indoor WLAN

Location Estimation has become important for many applications of indoor wireless networks. Received Signal Strength (RSS) fingerprinting methods have been widely used for location estimation. Most of the location estimation system suffers with the problem of scalability and unavailability of all the access points at all the location for large site. The accuracy and response time of estimation are critical issues in location estimation system for large sites. In this paper, we have proposed a distributed location estimation method, which divide the location estimation system into subsystems. Our method partitions the input signal space and output location space into clusters on the basis of visibility of access points at various locations of the site area. Each cluster of input signal space together with output location subspace is used to learn the association between RSS fingerprint and their respective location in a subsystem. We have performed experimentation on two RSS dataset, which are gathered on different testbeds, and compared our results with benchmark RADAR method. Experimental results show that our method provide better results in terms of accuracy and response time in comparison to centralized systems, in which a single system is used for large site.