Multihop data gathering in wireless sensor networks with a mobile sink

Tashtarian, Farzad; Sohraby, K.; Varasteh, Amir

doi:10.1002/dac.3264

Cited by 10 publications

(7 citation statements)

References 43 publications

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“…The result reveals that the method outperforms existing algorithms. In another work by Tashtarian et al, an approach was proposed to determine the ideal trajectory of a given MS without considering any RPs [72]. The proposed approach was compared with existing state-of-the-art approach and a scenario that utilizes RPs for routing.…”

Section: Volume 4 2016mentioning

confidence: 99%

Data Collection in Sensor Cloud: Recent Advances, Taxonomy, Use Cases and Open Challenges

Ali¹

2020

Preprint

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<div>In recent years, Wireless Sensor Networks (WSNs) technologies are used in many important</div><div>areas, including weather forecasting, security, environmental monitoring, health care, and industry.</div><div>Nonetheless, due to the constraints of WSNs in terms of energy, processing, connectivity, computation and</div><div>data integrity. An important issue in this research field is the efficient management of the large number</div><div>of WSN’s data. Therefore, there is a need for strong and scalable high-performance computing and large</div><div>storage infrastructure for real-time processing and storage of WSN’s data. This article attempts to discuss</div><div>data collection methods in WSNs, sensor cloud, and IoT. Also, in this context, a general overview of</div><div>WSNs and sensor cloud platforms, including their definitions, architectures, and applications are given.</div><div>We investigate, highlight and report recent advances in data collection technology by categorizing and</div><div>classifying data collection methods in WSNs, sensor cloud, IoT and developing a taxonomy based on</div><div>these classifications. Furthermore, the analysis and synthesis of existing works in this research domain</div><div>is highlighted. The identification of key research challenges for future work and use case in this research</div><div>domain were also highlighted and discussed.</div>

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Section: Volume 4 2016mentioning

confidence: 99%

Data Collection in Sensor Cloud: Recent Advances, Taxonomy, Use Cases and Open Challenges

Ali¹

2020

Preprint

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“…The energy consumed during WSN operation directly affects the performance of the network and degrades the network lifetime. Various techniques are used to decrease the energy consumption, reduce the total amount of data through methods of aggregation or compression [6], design efficient routing protocols, and activate sleep mode for unneeded nodes in the network. Diverse routing protocols [7] have been developed to ensure the communication in WSNs, and these protocols can be categorized into three families [8]: data-centric, hierarchical [9][10][11], and locationbased [12,13] protocols.…”

Section: Introductionmentioning

confidence: 99%

A Heuristic Algorithm of Cooperative Agents Communication for Enhanced GAF Routing Protocol in WSNs

Aznaoui

Raghay

Ouakrim

et al. 2019

Wireless Communications and Mobile Computing

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Rapid progress in technologies has led to the development of small sensor nodes. A wireless sensor network (WSN) is an interconnected collection of a large number of these small sensor nodes that is used to monitor and record the physical environment. WSNs have applications in diverse scenarios. They play an important role in tracking and monitoring in different domains, such as environmental research, military, and health care. In most of these applications, the WSN is composed of a large number of nodes deployed in an area of interest, and not all nodes are directly connected to the base station (BS). In some cases, batteries of nodes cannot be recharged or changed. For that, the most solution required to overcome these problems is to optimize energy consumed during communication. Data transmission in networks is maintained by routing protocols, which are responsible for discovering the required paths. This paper presents an improvement of the Geographic Adaptive Fidelity (GAF) routing protocol created on a smart actives node selection. The routing process works on cooperative agents communication where another node is activated in the same grid if the data collected are considered as important data, and a heuristic method is used to find an optimal path in terms of energy to transmit data collected until reaching the BS. Simulation results prove that the cooperative agents GAF (CAGAF) routing protocol proposed is more efficient compared to the basic version in terms of considering important data, energy consumed, and dead nodes.

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“…The ubiquitous objects provide many daily tasks to make human life easier by sensing the environment and applying knowledge [2]. They affect many domains including wireless sensors [3], mobile ad hoc networks [4], smart cities, unmanned airplanes, smart transport, and smart homes, to name a few [5]. The smart objects need to interact with each other to exchange information about their environment or to communicate with the cloud [6].…”

Section: Introductionmentioning

confidence: 99%

Hybrid Zoning Algorithm to Optimize Overhead in Smart Mobile Communication

Souidi

Habbani

Berradi

2019

JSAN

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With the increase of mobile terminals, routing protocols in wireless communications must provide better quality of service to meet bandwidth and reliability requirements. In networks without infrastructure, such as ad hoc and sensor networks, where a device performs as both a terminal and a router to forward data of other nodes, maintaining the network topology consumes considerable resources in terms of energy and bandwidth. These parameters need to be considered when designing routing protocols for wireless networks. To reduce the cost of the protocol overhead, some algorithms act on the forwarders, while others act on the transmission of messages. Finally, the hybrid ones are a combination of both. In this paper, we propose a new algorithm with two zoning strategies to enhance the performance of mobile network. The first strategy helps to select dispersive forwarders in order to reduce the collision in radio channel. The second strategy aims to reduce the transmission of redundant messages. Both strategies are based on the location information of nodes. We implemented our algorithm in the optimized link state routing protocol, the most used protocol in mobile ad hoc networks. We showed by simulations that our solution reduces drastically the cost of the overhead with no hindrance to the network topology.

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Multihop data gathering in wireless sensor networks with a mobile sink

Cited by 10 publications

References 43 publications

Data Collection in Sensor Cloud: Recent Advances, Taxonomy, Use Cases and Open Challenges

Data Collection in Sensor Cloud: Recent Advances, Taxonomy, Use Cases and Open Challenges

A Heuristic Algorithm of Cooperative Agents Communication for Enhanced GAF Routing Protocol in WSNs

Hybrid Zoning Algorithm to Optimize Overhead in Smart Mobile Communication

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