An Energy-Balanced Joint Routing and Charging Framework in Wireless Rechargeable Sensor Networks for Mobile Multimedia

Liu, Fang; Lu, Hancheng; Wang, Ting; Liu, Yuanan

doi:10.1109/access.2019.2958268

Cited by 15 publications

(7 citation statements)

References 24 publications

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“…Moreover, the proposed charging procedure prefers towards the accusing mode of the best parity of the absolute vitality utilization of sensor hubs during one charging trip. Energy Aware and Adaptive Cross Layer Scheme (EAACLS) to forward multimedia information through sensor networks was presented [18]. with the goal that it chooses ideal video encoding boundaries at application layer as indicated by current remote channel state, and packet allocations as per its sort through a versatile need video line so less significant parcels are dropped if there should arise an occurrence of system congestion.…”

Section: Related Workmentioning

confidence: 99%

Cross Layer based Energy Aware and Packet Scheduling Algorithm for Wireless Multimedia Sensor Network

Jenila¹,

Canessane²

2023

INT J COMPUT COMMUN, Int. J. Comput. Commun. Control

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Video transmission using sensor networks plays a most significant role in industrial and surveillance applications. Multimedia transmission is also a challenging task in case of guaranteeing quality of service in conditions like limited bandwidth, high congestion, multi-hop routing, etc. Cross layer approach is carried out to handle multimedia transmission over sensor networks for improving network adaptivity. Cross layer based energy aware and packet scheduling algorithm is proposed here to reduce congestion ratio and to improve link quality between the routing nodes. Link quality estimation among nodes is done using Semi-Markov process. Node congestion rate is determined for identifying node’s data channel rate. Packet scheduling process determines the highly prioritized packets by using queue scheduler component thereby the active nodes are selected through link quality process and the packets are transmitted to sink based on prioritize level. Simulation analysis is carried out and the efficiency of the proposed mechanism is proved to be better while comparing with the conventional schemes.

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Section: Related Workmentioning

confidence: 99%

Cross Layer based Energy Aware and Packet Scheduling Algorithm for Wireless Multimedia Sensor Network

Jenila¹,

Canessane²

2023

INT J COMPUT COMMUN, Int. J. Comput. Commun. Control

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“…A model in which, in addition to the sink (base station), a mobile station will navigate through the WSN to collect data and charge sensor nodes is considered by Liu et al [ 150 ]. The paper suggests a joint routing and charging strategy.…”

Section: Routing For Data Gathering In Wsnmentioning

confidence: 99%

Data Gathering Techniques in WSN: A Cross-Layer View

Gurewitz

Shifrin

Dvir

2022

Sensors

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Wireless sensor networks (WSNs) have taken a giant leap in scale, expanding their applicability to a large variety of technological domains and applications, ranging from the Internet of things (IoT) for smart cities and smart homes to wearable technology healthcare applications, underwater, agricultural and environmental monitoring and many more. This expansion is rapidly growing every passing day in terms of the variety, heterogeneity and the number of devices which such applications support. Data collection is commonly the core application in WSN and IoT networks, which are typically composed of a large variety of devices, some constrained by their resources (e.g., processing, storage, energy) and some by highly diverse demands. Many challenges span all the conceptual communication layers, from the Physical to the Applicational. Many novel solutions devised in the past do not scale well with the exponential growth in the population of the devices and need to be adapted, revised, or new innovative solutions are required to comply with this massive growth. Furthermore, recent technological advances present new opportunities which can be leveraged in this context. This paper provides a cross-layer perspective and review of data gathering in WSN and IoT networks. We provide some background and essential milestones that have laid the foundation of many subsequent solutions suggested over the years. We mainly concentrate on recent state-of-the-art research, which facilitates the scalable, energy-efficient, cost-effective, and human-friendly functionality of WSNs and the novel applications in the years to come.

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“…, v { }. ese orders are determined by the ant colony algorithm [8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27]. e calculation is based on equations (18)-(20).…”

Section: Energy Consumption Predictionmentioning

confidence: 99%

“…In the study, a heuristic optimization algorithm is employed. A joint scheme for both charging and tour planning in a MS-based WSN is proposed in [18]. Energy consumption of each sensor is leveraged which in turn mitigates energy exhaustion.…”

Section: Introductionmentioning

confidence: 99%

Predictive Trajectory‐Based Mobile Data Gathering Scheme for Wireless Sensor Networks

Fan

Feng

et al. 2021

Complexity

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Tradition wireless sensor networks (WSNs) transmit data by single or multiple hops. However, some sensor nodes (SNs) close to a static base station forward data more frequently than others, which results in the problem of energy holes and makes networks fragile. One promising solution is to use a mobile node as a mobile sink (MS), which is especially useful in energy-constrained networks. In these applications, the tour planning of MS is a key to guarantee the network performance. In this paper, a novel strategy is proposed to reduce the latency of mobile data gathering in a WSN while the routing strategies and tour planning of MS are jointly optimized. First, the issue of network coverage is discussed before the appropriate number of clusters being calculated. A dynamic clustering scheme is then developed where a virtual cluster center is defined as the MS sojourn for data collection. Afterwards, a tour planning of MS based on prediction is proposed subject to minimizing the traveling distance to collect data. The proposed method is simulated in a MATLAB platform to show the overall performance of the developed system. Furthermore, the physical tests on a test rig are also carried out where a small WSN based on an unmanned aerial vehicle (UAV) is developed in our laboratory. The test results validate the feasibility and effectiveness of the method proposed.

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An Energy-Balanced Joint Routing and Charging Framework in Wireless Rechargeable Sensor Networks for Mobile Multimedia

Cited by 15 publications

References 24 publications

Cross Layer based Energy Aware and Packet Scheduling Algorithm for Wireless Multimedia Sensor Network

Cross Layer based Energy Aware and Packet Scheduling Algorithm for Wireless Multimedia Sensor Network

Data Gathering Techniques in WSN: A Cross-Layer View

Predictive Trajectory‐Based Mobile Data Gathering Scheme for Wireless Sensor Networks

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