Hybrid-Vehcloud: An Obstacle Shadowing Approach for VANETs in Urban Environment

Routing of messages in Vehicular Ad-hoc Networks (VANETs) is challenging due to obstacle shadowing regions with high vehicle densities, which leads to frequent disconnection problems and blocks radio wave propagation between vehicles. Previous researchers used multi-hop, vehicular cloud or roadside infrastructures to solve the routing issue among the vehicles, but they suffer from significant packet delays and frequent packet losses arising from obstacle shadowing. We proposed a vehicular cloud based hybrid technique called Hybrid-Vehcloud to disseminate messages in obstacle shadowing regions, and multi-hop technique to disseminate messages in non-obstacle shadowing regions. The novelty of our approach lies in the fact that our proposed technique dynamically adapts between obstacle shadowing and non-obstacle shadowing regions. Simulation based performance analysis of Hybrid-Vehcloud showed improved performance over Cloud-assisted Message Downlink Dissemination Scheme (CMDS), Cross-Layer Broadcast Protocol (CLBP) and Cloud-VANET schemes at high vehicle densities

DFCV: A Novel Approach for Message Dissemination in Connected Vehicles using Dynamic Fog

Vehicular Ad-hoc Network (VANET) has emerged as a promising solution for enhancing road safety. Routing of messages in VANET is challenging due to packet delays arising from high mobility of vehicles, frequently changing topology, and high density of vehicles, leading to frequent route breakages and packet losses. Previous researchers have used either mobility in vehicular fog computing or cloud computing to solve the routing issue, but they suffer from large packet delays and frequent packet losses. We propose Dynamic Fog for Connected Vehicles (DFCV), a fog computing based scheme which dynamically creates, increments and destroys fog nodes depending on the communication needs. The novelty of DFCV lies in providing lower delays and guaranteed message delivery at high vehicular densities. Simulations were conducted using hybrid simulation consisting of ns-2, SUMO, and Cloudsim. Results show that DFCV ensures efficient resource utilization, lower packet delays and losses at high vehicle densities

Hybrid-Vehfog: A Robust Approach for Reliable Dissemination of Critical Messages in Connected Vehicles

Vehicular Ad-hoc Networks (VANET) enable efficient communication between vehicles with the aim of improving road safety. However, the growing number of vehicles in dense regions and obstacle shadowing regions like Manhattan and other downtown areas leads to frequent disconnection problems resulting in disrupted radio wave propagation between vehicles. To address this issue and to transmit critical messages between vehicles and drones deployed from service vehicles to overcome road incidents and obstacles, we proposed a hybrid technique based on fog computing called Hybrid-Vehfog to disseminate messages in obstacle shadowing regions, and multi-hop technique to disseminate messages in non-obstacle shadowing regions. Our proposed algorithm dynamically adapts to changes in an environment and benefits in efficiency with robust drone deployment capability as needed. Performance of Hybrid-Vehfog is carried out in Network Simulator (NS-2) and Simulation of Urban Mobility (SUMO) simulators. The results showed that Hybrid-Vehfog outperformed Cloud-assisted Message Downlink Dissemination Scheme (CMDS), Cross-Layer Broadcast Protocol (CLBP), PEer-to-Peer protocol for Allocated REsource (PrEPARE), Fog-Named Data Networking (NDN) with mobility, and flooding schemes at all vehicle densities and simulation times

HEER: Hybrid Energy Efficient Reactive Protocol for Wireless Sensor Networks

Wireless Sensor Networks (WSNs) consist of numerous sensors which send sensed data to base station. Energy conservation is an important issue for sensor nodes as they have limited power.Many routing protocols have been proposed earlier for energy efficiency of both homogeneous and heterogeneous environments. We can prolong our stability and network lifetime by reducing our energy consumption. In this research paper, we propose a protocol designed for the characteristics of a reactive homogeneous WSNs, HEER (Hybrid Energy Efficient Reactive) protocol. In HEER, Cluster Head(CH) selection is based on the ratio of residual energy of node and average energy of network. Moreover, to conserve more energy, we introduce Hard Threshold (HT) and Soft Threshold (ST). Finally, simulations show that our protocol has not only prolonged the network lifetime but also significantly increased stability period.Comment: 2nd IEEE Saudi International Electronics, Communications and Photonics Conference (SIECPC 13), 2013, Riyadh, Saudi Arabi

SIMPLE: Stable Increased-throughput Multi-hop Protocol for Link Efficiency in Wireless Body Area Networks

In this work, we propose a reliable, power efficient and high throughput routing protocol for Wireless Body Area Networks (WBANs). We use multi-hop topology to achieve minimum energy consumption and longer network lifetime. We propose a cost function to select parent node or forwarder. Proposed cost function selects a parent node which has high residual energy and minimum distance to sink. Residual energy parameter balances the energy consumption among the sensor nodes while distance parameter ensures successful packet delivery to sink. Simulation results show that our proposed protocol maximize the network stability period and nodes stay alive for longer period. Longer stability period contributes high packet delivery to sink which is major interest for continuous patient monitoring.Comment: IEEE 8th International Conference on Broadband and Wireless Computing, Communication and Applications (BWCCA'13), Compiegne, Franc

Approximating fixed points of nonexpansive type mappings

In a uniformly convex Banach space, the convergence of Ishikawa iterates to a unique fixed point is proved for nonexpansive type mappings under certain conditions

Association between Pus Cells and Semen Parameters in Infertile Pakistani Males

Objectives: This study evaluated the association between pus cells and semen parameters in infertile Pakistani males. Methods: A cross-sectional descriptive study was carried out in the Department of Reproductive Physiology/Health, National Institute of Health, Islamabad, Pakistan, from 2004 to 2009. A total of 1,521 subjects were analysed, along with 97 proven fathers as controls. Results: The mean of pus cells was 7.43 ± 0.43, 4.35 ± 0.34, and 4.26 ± 0.17 per high field in teratozoospermic, oligoasthenozoospermic, and asthenozoospermic groups, respectively, while it was 3.25 ± 0.26, 3.10 ± 0.19, and 2.98 ± 0.04 per high field in azoospermic, oligozoospermic and the proven father groups, respectively. The fewest pus cells were observed among proven fathers, which varied non-significantly (P >0.05) with all cases, except with teratozoospermic, oligozoospermic, and oligoasthenozoospermic cases. Pus cells showed an inverse relationship to sperm motility and count, except in azoospemia cases. Similarly, the fewest pus cells were observed among groups where normal forms where significantly more frequent (P <0.05). More pus cells were observed in cases where motility, and concentration or morphology was compromised. Similarly, low pus cell counts were seen in cases where sperm had the fewest head and neck defects. All kinds of sperm defects varied non-significantly (P >0.05) between proven fathers and normal concentration cases. Conclusion: High pus cell counts were observed in various subclasses of infertile patients. Ignorance of this pyospermic factor will make pyospermic patients to be misdiagnosed as normozoospermic. Therefore, the presence of pyospermia must be considered by physicians as a male infertility factor

Computational intelligent sensor-rank consolidation approach for Industrial Internet of Things (IIoT).

Continues field monitoring and searching sensor data remains an imminent element emphasizes the influence of the Internet of Things (IoT). Most of the existing systems are concede spatial coordinates or semantic keywords to retrieve the entail data, which are not comprehensive constraints because of sensor cohesion, unique localization haphazardness. To address this issue, we propose deep-learning-inspired sensor-rank consolidation (DLi-SRC) system that enables 3-set of algorithms. First, sensor cohesion algorithm based on Lyapunov approach to accelerate sensor stability. Second, sensor unique localization algorithm based on rank-inferior measurement index to avoid redundancy data and data loss. Third, a heuristic directive algorithm to improve entail data search efficiency, which returns appropriate ranked sensor results as per searching specifications. We examined thorough simulations to describe the DLi-SRC effectiveness. The outcomes reveal that our approach has significant performance gain, such as search efficiency, service quality, sensor existence rate enhancement by 91%, and sensor energy gain by 49% than benchmark standard approaches