Optimized on-demand data streaming from sensor nodes

2017 ◽  
Author(s):  
Jonas Traub ◽  
Sebastian Breß ◽  
Tilmann Rabl ◽  
Asterios Katsifodimos ◽  
Volker Markl
Keyword(s):  
Sensor Nodes ◽  
Data Streaming ◽  
On Demand

scholarly journals Intelligent On-Demand Connectivity Restoration for Wireless Sensor Networks

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Khalid Mahmood ◽  
Muhammad Amir Khan ◽  
Mahmood ul Hassan ◽  
Ansar Munir Shah ◽  
Shahzad Ali ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Connectivity ◽  
Energy Utilization ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
On Demand ◽  
Connectivity Restoration ◽  
Restoration Technique ◽  
Near Future

Wireless sensor networks are envisioned to play a very important role in the Internet of Things in near future and therefore the challenges associated with wireless sensor networks have attracted researchers from all around the globe. A common issue which is well studied is how to restore network connectivity in case of failure of single or multiple nodes. Energy being a scarce resource in sensor networks drives all the proposed solutions to connectivity restoration to be energy efficient. In this paper we introduce an intelligent on-demand connectivity restoration technique for wireless sensor networks to address the connectivity restoration problem, where nodes utilize their transmission range to ensure the connectivity and the replacement of failed nodes with their redundant nodes. The proposed technique helps us to keep track of system topology and can respond to node failures effectively. Thus our system can better handle the issue of node failure by introducing less overhead on sensor node, more efficient energy utilization, better coverage, and connectivity without moving the sensor nodes.

scholarly journals Energy Efficient Hybrid Optimization based K-means Clustering and Load balancing using Optimized Ad-hoc on-demand Distance Vector Routing for WSN

2019 ◽  
Vol 8 (9) ◽  
pp. 946-952
Keyword(s):  
Ad Hoc ◽  
Cluster Head ◽  
Region Of Interest ◽  
Base Station ◽  
Sensor Nodes ◽  
Hybrid Technique ◽  
On Demand ◽  
Distance Vector ◽  
Selection For ◽  
Ch Selection

Nowadays, Wireless Sensor Networks (WSN) play a key role in data transmission depends on the locations of nodes. WSN contains Base Station (BS) with several Sensor Nodes (SNs) and these nodes are randomly arranged inside the region. The BS used to give the commands and direction to the sensor node. Energy is a major issue in WSN as after some transmissions the nodes drain their energy when the information is passed inside the region of interest. According to the distance between the sensor nodes, the energy can be used during the Cluster Head (CH). The energy consumption (EC) is abridged by implementing the protocols of clustering and routing which is used to augment the Network Lifetime (NL). The optimal CH selection for finding the shortest path among the CHs is improved by developing the hybrid K-means with Particle Swarm Optimization (PSO) based hybrid Ad-hoc On-demand Distance Vector (AODV) channeling algorithms. The alive nodes, total packet sending time, throughput and NL are increased by using this hybrid technique, whereas dead nodes and EC are minimized in a network.

scholarly journals From the Eye of the Storm: An IoT Ecosystem Made of Sensors, Smartphones and UAVs

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3814 ◽  
Author(s):  
Milan Erdelj ◽  
Borey Uk ◽  
David Konam ◽  
Enrico Natalizio
Keyword(s):  
Remote Control ◽  
Unmanned Aerial Vehicles ◽  
System Architecture ◽  
Multimedia Communications ◽  
Data Streaming ◽  
On Demand ◽  
Communication Environment ◽  
Aerial Vehicles ◽  
Network Communications ◽  
Multi Uav

The development of Unmanned Aerial Vehicles (UAV) along with the ubiquity of Internet of Things (IoT) enables the creation of systems that, leveraging 5G enhancements, can provide real-time multimedia communications and data streaming. However, the usage of the UAVs introduces new constraints, such as unstable network communications and security pitfalls. In this work, the experience of implementing a system architecture for data and multimedia transmission using a multi-UAV system is presented. The system aims at creating an IoT ecosystem to bridge UAVs and other types of devices, such as smartphones and sensors, while coping with the fallback in an unstable communication environment. Furthermore, this work proposes a detailed description of a system architecture designed for remote drone fleet control. The proposed system provides an efficient, reliable and secure system for multi-UAV remote control that will offer the on-demand usage of available sensors, smartphones and unmanned vehicle infrastructure.

Load-Balance Energy Aware Ad-Hoc On Demand Multipath Distance Vector Routing Protocol (LBEA-AOMDV) for WSN

2018 ◽  
Vol 7 (2) ◽  
pp. 38-58 ◽  
Author(s):  
Amany Sarhan ◽  
Nawal A. El-Fishawy ◽  
Mahmoud M. Shawara
Keyword(s):  
Routing Protocol ◽  
Load Balance ◽  
Ad Hoc ◽  
Sensor Nodes ◽  
Energy Aware ◽  
On Demand ◽  
Network Load ◽  
Balance Energy ◽  
Distance Vector ◽  
Priority Levels

Nowadays, WSNs have received great importance because they are the best solutions that can be used in harsh environments. The main limitation in WSNs is the node power because the sensor node is battery powered and charging or replacing this battery is not applicable. Moreover, in mission-critical applications, sensor nodes can sense important data and the packet carrying this data must be given higher priority from the routing protocol. Most of the current routing protocols consider the node power but do not consider different paths for different priority data which may cause them to be delayed. This article proposes a load-balance energy aware ad-hoc on demand multipath distance vector (LBEA-AOMDV) protocol for wireless sensor networks, which is a multipath routing protocol, based on the original AOMDV. The proposed protocol shows that the paths are alternatively discovered on basis of an energy metric and instead of using only one path in data transmission, the network load is distributed through different paths. LBEA-AOMDV also uses a priority-based technique in which packets are assigned different priority levels and guided to different paths. The overall simulation results show that LBEA-AOMDV gives better performance when compared with AOMDV in terms of average consumed energy, end-to-end delay, number of dropped packets, average throughput and normalized routing load.

scholarly journals Distributed Software-Attestation Defense against Sensor Worm Propagation

2015 ◽  
Vol 2015 ◽  
pp. 1-6 ◽  
Author(s):  
Jun-Won Ho
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Defense Mechanisms ◽  
Main Idea ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Worm Propagation ◽  
On Demand ◽  
Software Diversity ◽  
Worm Attacks

Wireless sensor networks are vulnerable to sensor worm attacks in which the attacker compromises a few nodes and makes these compromised nodes initiate worm spread over the network, targeting the worm infection of the whole nodes in the network. Several defense mechanisms have been proposed to prevent worm propagation in wireless sensor networks. Although these proposed schemes use software diversity technique for worm propagation prevention under the belief that different software versions do not have common vulnerability, they have fundamental drawback in which it is difficult to realize the aforementioned belief in sensor motes. To resolve this problem, we propose on-demand software-attestation based scheme to defend against worm propagation in sensor network. The main idea of our proposed scheme is to perform software attestations against sensor nodes in on-demand manner and detect the infected nodes by worm, resulting in worm propagation block in the network. Through analysis, we show that our proposed scheme defends against worm propagation in efficient and robust manner. Through simulation, we demonstrate that our proposed scheme stops worm propagation at the reasonable overhead while preventing a majority of sensor nodes from being infected by worm.

scholarly journals An On-Demand Charging for Connected Target Coverage in WRSNs Using Fuzzy Logic and Q-Learning

Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5520
Author(s):  
Phi Le Nguyen ◽  
Van Quan La ◽  
Anh Duy Nguyen ◽  
Thanh Hung Nguyen ◽  
Kien Nguyen
Keyword(s):  
Fuzzy Logic ◽  
Network Lifetime ◽  
Sensor Nodes ◽  
Target Number ◽  
Q Learning ◽  
On Demand ◽  
Charging Time ◽  
Sufficient Power ◽  
Wireless Rechargeable Sensor Networks ◽  
Wireless Medium

In wireless rechargeable sensor networks (WRSNs), a mobile charger (MC) moves around to compensate for sensor nodes’ energy via a wireless medium. In such a context, designing a charging strategy that optimally prolongs the network lifetime is challenging. This work aims to solve the challenges by introducing a novel, on-demand charging algorithm for MC that attempts to maximize the network lifetime, where the term “network lifetime” is defined by the interval from when the network starts till the first target is not monitored by any sensor. The algorithm, named Fuzzy Q-charging, optimizes both the time and location in which the MC performs its charging tasks. Fuzzy Q-charging uses Fuzzy logic to determine the optimal charging-energy amounts for sensors. From that, we propose a method to find the optimal charging time at each charging location. Fuzzy Q-charging leverages Q-learning to determine the next charging location for maximizing the network lifetime. To this end, Q-charging prioritizes the sensor nodes following their roles and selects a suitable charging location where MC provides sufficient power for the prioritized sensors. We have extensively evaluated the effectiveness of Fuzzy Q-charging in comparison to the related works. The evaluation results show that Fuzzy Q-charging outperforms the others. First, Fuzzy Q-charging can guarantee an infinite lifetime in the WSRNs, which have a sufficient large sensor number or a commensurate target number. Second, in other cases, Fuzzy Q-charging can extend the time until the first target is not monitored by 6.8 times on average and 33.9 times in the best case, compared to existing algorithms.

scholarly journals Collaborative Wireless Power Transfer in Wireless Rechargeable Sensor Networks

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Azka Amin ◽  
Xi-Hua Liu ◽  
Muhammad Asim Saleem ◽  
Shagufta Henna ◽  
Taseer-ul Islam ◽  
...  
Keyword(s):  
Sensor Networks ◽  
Network Lifetime ◽  
Wireless Power Transfer ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Power Transfer ◽  
Wireless Power ◽  
Transfer Energy ◽  
On Demand ◽  
Wireless Rechargeable Sensor Networks

Wireless power transfer techniques to transfer energy have been widely adopted by wireless rechargeable sensor networks (WRSNs). These techniques are aimed at increasing network lifetime by transferring power to end devices. Under these wireless techniques, the incurred charging latency to replenish the sensor nodes is considered as one of the major issues in wireless sensor networks (WSNs). Existing recharging schemes rely on rigid recharging schedules to recharge a WSN deployment using a single global charger. Although these schemes charge devices, they are not on-demand and incur higher charging latency affecting the lifetime of a WSN. This paper proposes a collaborative recharging technique to offload recharging workload to local chargers. Experiment results reveal that the proposed scheme maximizes average network lifetime and has better average charging throughput and charging latency compared to a global charger-based recharging.

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