An energy efficient interference-aware routing protocol for underwater WSNs

Interference-aware routing protocol design for underwater wireless sensor networks (UWSNs) is one of the key strategies in reducing packet loss in the highly hostile underwater environment. The reduced interference causes efficient utilization of the limited battery power of the sensor nodes that, in consequence, prolongs the entire network lifetime. In this paper, we propose an energy-efficient interference-aware routing (EEIAR) protocol for UWSNs. A sender node selects the best relay node in its neighborhood with the lowest depth and the least number of neighbors. Combination of the two routing metrics ensures that data packets are forwarded along the least interference paths to reach the final destination. The proposed work is unique in that it does not require the full dimensional localization information of sensor nodes and the network total depth is segmented to identify source, relay and neighbor nodes. Simulation results reveal better performance of the scheme than the counterparts DBR and EEDBR techniques in terms of energy efficiency, packet delivery ratio and end-to-end delay

A trust model using edge nodes and cuckoo filter for securing vanet under nlos conditions

Trust, as a key element of security, has a vital role in securing vehicular ad-hoc networks (VANETs). Malicious and selfish nodes by generating inaccurate information, have undesirable impacts on the trustworthiness of the VANET environment. Obstacles also have a negative impact on data trustworthiness by restricting direct communication between nodes. In this study, a trust model based on plausibility, experience, and type of vehicle is presented to cope with inaccurate, incomplete and uncertainty data under both line of sight (LoS) and none-line of sight (NLoS) conditions. In addition, a model using the k-nearest neighbor (kNN) classification algorithm based on feature similarity and symmetry is developed to detect the NLoS condition. Radio signal strength indicator (RSSI), packet reception rate (PDR) and the distance between two vehicle nodes are the features used in the proposed kNN algorithm. Moreover, due to the big data generated in VANET, secure communication between vehicle and edge node is designed using the Cuckoo filter. All obtained results are validated through well-known evaluation measures such as precision, recall, overall accuracy, and communication overhead. The results indicate that the proposed trust model has a better performance as compared to the attack-resistant trust management (ART) scheme and weighted voting (WV) approach. Additionally, the proposed trust model outperforms both ART and WV approaches under diffierent patterns of attack such as a simple attack, opinion tampering attack, and cunning attack. Monte-Carlo simulation results also prove validity of the proposed trust model

A Novel RSSI Prediction Using Imperialist Competition Algorithm (ICA), Radial Basis Function (RBF) and Firefly Algorithm (FFA) in Wireless Networks

This study aims to design a vertical handover prediction method to minimize unnecessary handovers for a mobile node (MN) during the vertical handover process. This relies on a novel method for the prediction of a received signal strength indicator (RSSI) referred to as IRBF-FFA, which is designed by utilizing the imperialist competition algorithm (ICA) to train the radial basis function (RBF), and by hybridizing with the firefly algorithm (FFA) to predict the optimal solution. The prediction accuracy of the proposed IRBF–FFA model was validated by comparing it to support vector machines (SVMs) and multilayer perceptron (MLP) models. In order to assess the model’s performance, we measured the coefficient of determination (R2), correlation coefficient (r), root mean square error (RMSE) and mean absolute percentage error (MAPE). The achieved results indicate that the IRBF–FFA model provides more precise predictions compared to different ANNs, namely, support vector machines (SVMs) and multilayer perceptron (MLP). The performance of the proposed model is analyzed through simulated and real-time RSSI measurements. The results also suggest that the IRBF–FFA model can be applied as an efficient technique for the accurate prediction of vertical handover

Distance-Based and Low Energy Adaptive Clustering Protocol for Wireless Sensor Networks

A wireless sensor network (WSN) comprises small sensor nodes with limited energy capabilities. The power constraints of WSNs necessitate efficient energy utilization to extend the overall network lifetime of these networks. We propose a distance-based and low-energy adaptive clustering (DISCPLN) protocol to streamline the green issue of efficient energy utilization in WSNs. We also enhance our proposed protocol into the multi-hop-DISCPLN protocol to increase the lifetime of the network in terms of high throughput with minimum delay time and packet loss. We also propose the mobile-DISCPLN protocol to maintain the stability of the network. The modelling and comparison of these protocols with their corresponding benchmarks exhibit promising results

Evaluation of object-based and ontology-based models in context-aware systems

Today, context-aware systems are discussed as one of the key subjects in ubiquitous computing systems. In this area, researchers have been trying to find some techniques for context information modeling. So that attaining general and efficient model for managing, storing and retrieving data and contextual information is a necessary aspect. In this regard and in order to achieving this goal, several methods already have been proposed. In our research and in this paper, object-based models and ontology-based models are introduced as two most famous models for modeling the context information along with some novel approaches that are based on these models. In continuation, the key requirements of an effective model will be introduced and finally the proposed models will be evaluated as for these requirements

Energy-efficient data reporting for navigation in position-free hybrid wireless sensor networks

Hybrid wireless sensor network (HWSN) consists of static and mobile sensor nodes that work together for sensing and data collection in a region of interest. The static sensors detect events and send in situ notifications to the mobile node to come closer to the event to collect the data. It is challenging to the static nodes to send data packets to mobile nodes in position-free HWSN. The flood-based mechanism is commonly used in reporting data packets and supporting mobile node navigation. However, it causes energy consumption and minimizes lifetime of sensor network. In this paper, an energy-efficient packet reporting (EPR) scheme is proposed to report event packets in an energy-efficient manner. It aims at supporting mobile node navigation in position-free HWSN. EPR uses multi-metric energy-efficient-based relay node selection to send data downstream. Then, it uses transmission power adjustment strategy on the upstream sending nodes to reduce their energy consumption. In the case of multiple nodes detecting event around the same vicinity, a clustering strategy is used to send an aggregated data packet. Extensive simulations show that EPR provides superior improvements over the existing schemes

A double cystic duct with a single gallbladder successfully treated with laparoscopic cholecystectomy: A challenge to laparoscopic surgeons

Although the cystic duct has diverse variations, a double cystic duct is rarely found. Only 20 cases had been reported until late 2017. In the present study, we describe a 58-year-old woman with a double cystic duct who initially presented with a passed stone and pancreatitis concomitant with a gallbladder containing microlithiasis. The double cystic duct was not detected in preoperative endoscopic ultrasonography; and the anomaly was an incidental finding during laparoscopic cholecystectomy. The patient had no postoperative complications and was discharged uneventfully. Postoperative magnetic resonance cholangiography showed a normal biliary tree structure. © 2020, Shiraz University of Medical Sciences. All rights reserved

Comparison between hybridized algorithm of GA–SA and ABC, GA, DE and PSO for vertical-handover in heterogeneous wireless networks

Genetic algorithms (GAs) and simulated annealing (SA) have emerged as leading methods for search and optimization problems in heterogeneous wireless networks. In this paradigm, various access technologies need to be interconnected; thus, vertical handovers are necessary for seamless mobility. In this paper, the hybrid algorithm for real-time vertical handover using different objective functions has been presented to find the optimal network to connect with a good quality of service in accordance with the user’s preferences. As it is, the characteristics of the current mobile devices recommend using fast and efficient algorithms to provide solutions near to real-time. These constraints have moved us to develop intelligent algorithms that avoid slow and massive computations. This was to, specifically, solve two major problems in GA optimization, i.e. premature convergence and slow convergence rate, and the facilitation of simulated annealing in the merging populations phase of the search. The hybrid algorithm was expected to improve on the pure GA in two ways, i.e., improved solutions for a given number of evaluations, and more stability over many runs. This paper compares the formulation and results of four recent optimization algorithms: artificial bee colony (ABC), genetic algorithm (GA), differential evolution (DE), and particle swarm optimization (PSO). Moreover, a cost function is used to sustain the desired QoS during the transition between networks, which is measured in terms of the bandwidth, BER, ABR, SNR, and monetary cost. Simulation results indicated that choosing the SA rules would minimize the cost function and the GA–SA algorithm could decrease the number of unnecessary handovers, and thereby prevent the ‘Ping-Pong’ effect

Energy harvesting and battery power based routing in wireless sensor networks

Wireless sensor networks (WSNs) are a collection of several small and inexpensive battery-powered nodes, commonly used to monitor regions of interests and to collect data from the environment. Several issues exist in routing data packets through WSN, but the most crucial problem is energy. There are a number of routing approaches in WSNs that address the issue of energy by the use of different energy-efficient methods. This paper, presents a brief summary of routing and related issues in WSNs. The most recent energy-efficient data routing approaches are reviewed and categorized based on their aims and methodologies. The traditional battery based energy sources for sensor nodes and the conventional energy harvesting mechanisms that are widely used to in energy replenishment in WSN are reviewed. Then a new emerging energy harvesting technology that uses piezoelectric nanogenerators to supply power to nanosensor; the type of sensors that cannot be charged by conventional energy harvesters are explained. The energy consumption reduction routing strategies in WSN are also discussed. Furthermore, comparisons of the variety of energy harvesting mechanisms and battery power routing protocols that have been discussed are presented, eliciting their advantages, disadvantages and their specific feature. Finally, a highlight of the challenges and future works in this research domain is presented

An authentication and plausibility model for big data analytic under LOS and NLOS conditions in 5G-VANET

The exchange of correct and reliable data among legitimate nodes is one of the most important challenges in vehicular ad hoc networks (VANETs). Malicious nodes and obstacles, by generating inaccurate information, have a negative impact on the security of 5G-VANET. The big data generated in the vehicular network is also an issue in the security of VANET. To this end, a security model based on authentication and plausibility is proposed to improve the safety of network named ‘AFPM’. In the first layer, an authentication mechanism using edge nodes along with 5G is proposed to deal with the illegitimate nodes who enter the network and broadcast wrong information. In the authentication mechanism, because of the growth of the connected vehicles to the edge nodes that lead to generating big data and hence the inappropriateness of the traditional data structures, cuckoo filter, as a space-efficient probabilistic data structure, is used. In the second layer, a plausibility model by performing fuzzy logic is presented to cope with inaccurate information. The plausibility model is based on detection of inconsistent data involved in the event message. The plausibility model not only tackles with inaccurate, incomplete, and inaccuracy data but also deals with misbehaviour nodes under both line-of-sight (LOS) and non-line-of-sight (NLOS) conditions. All obtained results are validated through well-known evaluation measures such as F-measure and communication overhead. The results presented in this paper demonstrate that the proposed security model possesses a better performance in comparison with the existing studies