scholarly journals Relay-Assisted D2D Transmission for Mobile Health Applications

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4417 ◽  
Author(s):  
Hongcheng Huang ◽  
Wei Xiang ◽  
Yang Tao ◽  
Biao Liu ◽  
Min Hu
Keyword(s):  
Energy Consumption ◽  
Mobile Health ◽  
Data Transmission ◽  
Transmission Rate ◽  
Relay Node ◽  
Medical Data ◽  
Spectrum Efficiency ◽  
D2d Communication ◽  
Relay Nodes ◽  
Relay Communication

Relay-assisted Device-to-Device (D2D) communication, one of the important transmission modes in mobile health systems, can provide high transmission quality for servicing users at the edge of system coverage. However, the quality of the D2D relay communication is largely limited by the relay nodes. When a poor node is selected to assist the source node in the data transmission, it is likely to result in the loss of medical data and inaccurate transmission. Therefore, this paper focuses on how to select relay modes and relay nodes to improve the reliability of medical data transmission. Firstly, in order to eliminate the relay nodes with low energy or poor willingness, the acceptable energy consumption metric of relay nodes is proposed in this paper. The relay mode of each relay node is determined by the acceptable energy consumption metric, which can ensure the physical reliability of the relay communication links. Then a trust metric is proposed to measure the social reliability of each relay link, further excluding the malicious relay nodes. Finally, this paper proposes a relay selection algorithm based on compromise factors (RSCF). With the help of the proposed algorithm, the reliability of the relay communication can be guaranteed, and the spectrum efficiency can be promoted greatly. The simulation results show that the relay nodes selected by RSCF algorithm can greatly improve transmission rate and reliability compared with the traditional relay-assisted D2D communication schemes.

A Relay Selection Algorithm Based on User Trust Degree for D2D Communications

2021 ◽  
Author(s):  
Xiaobin Li ◽  
Haoran Liu
Keyword(s):  
Success Rate ◽  
Social Relationship ◽  
Relay Node ◽  
D2d Communications ◽  
Relay Nodes ◽  
Trust Degree ◽  
Relay Communication ◽  
Relay Selection Algorithm ◽  
User Trust

Abstract The emergence of 5G has promoted the rapid development of the Internet of Things(IOT), the dramatic increasing of mobile equipment has led to the increasing shortage of spectrum resources, D2D(Device-to-Device) communication technology is widely concerned for its ability to improve the utilization of spectrum resources. In order to expand the communication scope, relay nodes are introduced into D2D communications, as the third party of D2D relay communication, the quality of relay nodes directly affects the quality of communication process. In order to make more users willing to participate in relay communication, social relationship is introduced into D2D relay communication, However, as an explicit relationship between people, the function of social relationship in D2D communication is limited by the mobility of users and the variability of communication scenarios. In order to find a more reli­able relay node and upgrade the connection success rate of D2D relay communication, implicit social relationship between the users need to be mined. Aiming at that, user trust degree (UTD) is established in this paper. By combining the explicit relationship which is called the social connectivity degree with the implicit social relationship called the interest similarity degree, and considering the user’s movement, a relay selection algorithm is presented to help sender find a relay node with a deeper user trust, which can increase the user’s willingness to participate in D2D relay communication and upgrade the success rate of communication connection, so this algorithm can ensure the security of the relay node and can improve the throughput performance. Simulation results show that this algorithm can increase the success rate of connection, improve the overall throughput of the system and improve the user's communication expe­rience.

Meta-Heuristic MOALO Algorithm for Energy-Aware Clustering in the Internet of Things

2021 ◽  
Vol 12 (2) ◽  
pp. 74-93
Author(s):  
Ravi Kumar Poluru ◽  
R. Lokeshkumar
Keyword(s):  
Energy Consumption ◽  
Data Transmission ◽  
Transmission Rate ◽  
Fitness Function ◽  
Shortest Paths ◽  
Cluster Head ◽  
Energy Aware ◽  
Energy Efficient Routing ◽  
Multi Objective ◽  
Data Transmission Rate

Boosting data transmission rate in IoT with minimized energy is the research issue under consideration in recent days. The main motive of this paper is to transmit the data in the shortest paths to decrease energy consumption and increase throughput in the IoT network. Thus, in this paper, the authors consider delay, traffic rate, and density in designing a multi-objective energy-efficient routing protocol to reduce energy consumption via the shortest paths. First, the authors propose a cluster head picking approach that elects optimal CH. It increases the effective usage of nodes energy and eventually results in prolonged network lifetime with enhanced throughput. The data transmission rate is posed as a fitness function in the multi-objective ant lion optimizer algorithm (MOALOA). The performance of the proposed algorithm is investigated using MATLAB and achieved high convergence, extended lifetime, as well as throughput when compared to representative approaches like E-LEACH, mACO, MFO-ALO, and ALOC.

A non-linear mathematical model-based routing protocol for WBAN-based health-care systems

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ch Rajendra Prasad ◽  
Polaiah Bojja
Keyword(s):  
Mathematical Model ◽  
Health Care ◽  
Energy Consumption ◽  
Routing Protocol ◽  
Data Transmission ◽  
Transmission Rate ◽  
Content Type ◽  
Data Transmission Rate ◽  
Model Based ◽  
Non Linear

Purpose This paper aims to present a non-linear mathematical model-based routing protocol for wireless body area networks (WBANs). Two non-linear mathematical models for WBANs are used in the proposed protocols Model 1 and Model 2. Model 1 intends to improve the data transmission rate and Model 2 intends to reduce energy consumption in the WBANs. These models are simulated for fixed deployment and priority-based data transmission, and performance of the network is analyzed under four constraints on WBANs. Design/methodology/approach Advancements in wireless technology play a vital role in several applications such as electronic health care, entertainment and games. Though WBANs are widely used in digital health care, they have restricted battery capacity which affects network stability and data transmission. Therefore, several research studies focused on reducing energy consumption and maximizing the data transmission rate in WBANs. Findings Simulation results of the proposed protocol exhibit superior performance in terms of four network constraints such as residual energy, the stability of the network, path loss and data transmission rate in contrast with conventional routing protocols. The performance improvement of these parameters confirms that the proposed algorithm is more reliable and consumes less energy than traditional algorithms. Originality/value The Model 1 of the proposed work provides maximum data extraction, which ensures reliable data transmission in WBANs. The Model 2 allocates minimal hop count path between the sink and the sensor nodes, which minimizes energy consumption in the WBANs.

scholarly journals ACTS: An Ant Colony Based Transmission Scheduling Approach for Cloud Network Collaboration Environment

Symmetry ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 2109
Author(s):  
Ruiying Cheng ◽  
Pan Zhang ◽  
Lei Xie ◽  
Yongqi Ai ◽  
Peng Xu
Keyword(s):  
Data Transmission ◽  
Ant Colony Algorithm ◽  
Relay Node ◽  
Ant Colony ◽  
Local Optimum ◽  
Transmission Scheduling ◽  
Cloud Platform ◽  
Network Resources ◽  
Relay Nodes ◽  
Cloud Network

In traditional cloud computing research, it is often considered that the network resources between edge devices and cloud platform are sufficient, and the symmetry between the upward link from edge devices to the cloud platform and the downward link from cloud platform to edge devices is definite. However, in many application scenarios, the network resources between edge devices and cloud platform might be limited, and the link symmetry may not be guaranteed. To solve this problem, network relay nodes are introduced to realize the data transmission between edge devices and the cloud platform. The environment in which network relay nodes that can cooperate with the cloud platform is called cloud network collaborative environment (CNCE). In CNCE, how to optimize data transmission from edge devices to cloud platform through relay nodes has become one of the most important research topics. In this paper, we focus on the following two influencing factors that previous studies ignored: (1) the multi-link and multi-constraint transmission process; and (2) the timely resource state of the relay node. Taking these factors into consideration, we design a novel data transmission scheduling algorithm, called ant colony based transmission scheduling approach (ACTS). First, we propose a multi-link optimization mechanism to optimize the constraint limits. This mechanism divides the transmission into two links called the downlink relay link and uplink relay link. For the downlink relay link, we use the store-and-forward method for the optimization. For the uplink relay link, we use the min–min method for the optimization. We use the ant colony algorithm for the overall optimization of the two links. Finally, we improve the pheromone update rule of the ant colony algorithm to avoid the algorithm from falling into a local optimum. Extensive experiments demonstrate that our proposed approach has better results in transmission efficiency than other advanced algorithms.

scholarly journals Multiparametric Monitoring in Equatorian Tomato Greenhouses (II): Energy Consumption Dynamics

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2556 ◽  
Author(s):  
Mayra Erazo-Rodas ◽  
Mary Sandoval-Moreno ◽  
Sergio Muñoz-Romero ◽  
Mónica Huerta ◽  
David Rivas-Lalaleo ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Data Transmission ◽  
Energy Demand ◽  
Transmission Rate ◽  
Process Analysis ◽  
Average Energy ◽  
Optimization Techniques ◽  
Star Topology ◽  
Zigbee Network ◽  
Consumption Dynamics

Tomato greenhouses are a crucial element in the Equadorian economy. Wireless sensor networks (WSNs) have received much attention in recent years in specialized applications such as precision farming. The energy consumption in WSNs is relevant nowadays for their adequate operation, and attention is being paid to analyzing the affecting factors, energy optimization techniques working on the network hardware or software, and characterizing the consumption in the nodes (especially in the ZigBee standard). However, limited information exists on the analysis of the consumption dynamics in each node, across different network technologies and communication topologies, or on the incidence of data transmission speed. The present study aims to provide a detailed analysis of the dynamics of the energy consumption for tomato greenhouse monitoring in Ecuador, in three types of WSNs, namely, ZigBee with star topology, ZigBee with mesh topology (referred to here as DigiMesh), and WiFi with access point topology. The networks were installed and maintained in operation with a line of sight between nodes and a 2-m length, whereas the energy consumption measurements of each node were acquired and stored in the laboratory. Each experiment was repeated ten times, and consumption measurements were taken every ten milliseconds at a rate of fifty thousand samples for each realization. The dynamics were scrutinized by analyzing the recorded time series using stochastic-process analysis methods, including amplitude probability functions and temporal autocorrelation, as well as bootstrap resampling techniques and representations of various embodiments with the so-called M-mode plots. Our results show that the energy consumption of each network strongly depends on the type of sensors installed in the nodes and on the network topology. Specifically, the CO2 sensor has the highest power consumption because its chemical composition requires preheating to start logging measurements. The ZigBee network is more efficient in energy saving independently of the transmission rate, since the communication modules have lower average consumption in data transmission, in contrast to the DigiMesh network, whose consumption is high due to its topology. Results also show that the average energy consumption in WiFi networks is the highest, given that the coordinator node is a Meshlium™ router with larger energy demand. The transmission duration in the ZigBee network is lower than in the other two networks. In conclusion, the ZigBee network with star topology is the most energy-suitable one when designing wireless monitoring systems in greenhouses. The proposed methodology for consumption dynamics analysis in tomato greenhouse WSNs can be applied to other scenarios where the practical choice of an energy-efficient network is necessary due to energy constrains in the sensor and coordinator nodes.

scholarly journals Relay Selection Joint Consecutive Packet Routing Scheme to Improve Performance for Wake-Up Radio-Enabled WSNs

2020 ◽  
Vol 2020 ◽  
pp. 1-32 ◽  
Author(s):  
Mengyu Peng ◽  
Wei Liu ◽  
Tian Wang ◽  
Zhiwen Zeng
Keyword(s):  
Energy Consumption ◽  
Relay Selection ◽  
Relay Node ◽  
Residual Energy ◽  
Packet Transmission ◽  
Network Throughput ◽  
Packet Routing ◽  
Relay Nodes ◽  
Data Packets ◽  
End To End Delay

Reducing energy consumption, increasing network throughput, and reducing delay are the pivot issues for wake-up radio- (WuR-) enabled wireless sensor networks (WSNs). In this paper, a relay selection joint consecutive packet routing (RS-CPR) scheme is proposed to reduce channel competition conflicts and energy consumption, increase network throughput, and then reduce end-to-end delay in data transmission for WuR-enabled WSNs. The main innovations of the RS-CPR scheme are as follows: (1) Relay selection: when selecting a relay node for routing, the sender will select the node with the highest evaluation weight from its forwarding node set (FNS). The weight of the node is weighted by the distance from the node to sink, the number of packets in the queue, and the residual energy of the node. (2) The node sends consecutive packets once it accesses the channel successfully, and it gives up the channel after sending all packets. Nodes that fail the competition sleep during the consecutive packet transmission of the winner to reduce collisions and energy consumption. (3) Every node sets two thresholds: the packet queue length threshold Nt and the packet maximum waiting time threshold Tt. When the corresponding value of the node is greater than the threshold, the node begins to contend for the channel. Besides, to make full use of energy and reduce delay, the threshold of nodes which are far from sink is small while that of nodes which are close to sink is large. In such a way, nodes in RS-CPR scheme will select those with much residual energy, a large number of packets, and a short distance from sink as relay nodes. As a result, the probability that a node with no packets to transmit becomes a relay is very small, and the probability that a node with many data packets in the queue becomes a relay is large. In this strategy, only a few nodes in routing need to contend for the channel to send packets, thereby reducing channel contention conflicts. Since the relay node has a large number of data packets, it can send many packets continuously after a successful competition. It also reduces the spending of channel competition and improves the network throughput. In summary, RS-CPR scheme combines the selection of relay nodes with consecutive packet routing strategy, which greatly improves the performance of the network. As is shown in our theoretical analysis and experimental results, compared with the receiver-initiated consecutive packet transmission WuR (RI-CPT-WuR) scheme and RI-WuR protocol, the RS-CPR scheme reduces end-to-end delay by 45.92% and 65.99%, respectively, and reduces channel collisions by 51.92% and 76.41%. Besides, it reduces energy consumption by 61.24% and 70.40%. At the same time, RS-CPR scheme improves network throughput by 47.37% and 75.02%.

Energy Efficient Clustering and Routing Algorithm for WSN

2019 ◽  
Vol 12 ◽  
Author(s):  
Mohit Kumar ◽  
Sonu Mittal ◽  
Md. Amir Khusru Akhtar
Keyword(s):  
Energy Consumption ◽  
Network Lifetime ◽  
Energy Efficient ◽  
Hot Spot ◽  
Routing Algorithm ◽  
Relay Node ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Efficient Clustering ◽  
Hot Spot Problem

Background: This paper presents a novel Energy Efficient Clustering and Routing Algorithm (EECRA) for WSN. It is a clustering-based algorithm that minimizes energy dissipation in wireless sensor networks. The proposed algorithm takes into consideration energy conservation of the nodes through its inherent architecture and load balancing technique. In the proposed algorithm the role of inter-cluster transmission is not performed by gateways instead a chosen member node of respective cluster is responsible for data forwarding to another cluster or directly to the sink. Our algorithm eases out the load of the gateways by distributing the transmission load among chosen sensor node which acts as a relay node for inter-cluster communication for that round. Grievous simulations show that EECRA is better than PBCA and other algorithms in terms of energy consumption per round and network lifetime. Objective: The objective of this research lies in its inherent architecture and load balancing technique. The sole purpose of this clustering-based algorithm is that it minimizes energy dissipation in wireless sensor networks. Method: This algorithm is tested with 100 sensor nodes and 10 gateways deployed in the target area of 300m × 300m. The round assumed in this simulation is same as in LEACH. The performance metrics used for comparisons are (a) network lifetime of gateways and (b) energy consumption per round by gateways. Our algorithm gives superior result compared to LBC, EELBCA and PBCA. Fig 6 and Fig 7 shows the comparison between the algorithms. Results: The simulation was performed on MATLAB version R2012b. The performance of EECRA is compared with some existing algorithms like PBCA, EELBCA and LBCA. The comparative analysis shows that the proposed algorithm outperforms the other existing algorithms in terms of network lifetime and energy consumption. Conclusion: The novelty of this algorithm lies in the fact that the gateways are not responsible for inter-cluster forwarding, instead some sensor nodes are chosen in every cluster based on some cost function and they act as a relay node for data forwarding. Note the algorithm does not address the hot-spot problem. Our next endeavor will be to design an algorithm with consideration of hot-spot problem.

scholarly journals Stable routing and energy-conserved data transmission over wireless sensor networks

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Suzan Shukry
Keyword(s):  
Energy Consumption ◽  
Routing Protocol ◽  
Data Transmission ◽  
Source Node ◽  
Wireless Sensor ◽  
Dominant Factor ◽  
Communication Overhead ◽  
Forwarding Node ◽  
Stable Path ◽  
Stable Routing

AbstractStable routing and energy conservation over a wireless sensor network (WSN) is a major issue in Internet of Things applications. The network lifetime can be increased when studying this issue with interest. Data transmission is a dominant factor in IoT networks for communication overhead and energy consumption. A proposed efficient node stable routing ($$ENSR$$ ENSR ) protocol is introduced to guarantee the stability of transmission data between the source and destination nodes, in a dynamic WSN conditions. $$ENSR$$ ENSR minimizes energy consumption and selects more stable nodes for packets forwarding. Stability becomes the most important factor that qualifies the node's centrality. A node’s stability is characterized by residual energy, link quality, and number of hops needed to reach the destination from the node. To calculate node's stability, an enhanced centrality concept, known as stable betweenness centrality ($$SBC$$ SBC ) is introduced. In $$ENSR$$ ENSR , at first, some nodes will be selected as the stable forwarding nodes, usually with maximum $$SBC$$ SBC between their neighbors within a limited communication radio range of a particular region. Furthermore, each stable forwarding node then broadcasts its identity, including $$SBC$$ SBC , to the source node separately. The source node can compute a stable path to forward packets to the corresponding stable forwarding node, based on a proper designed stable path routing metric ($$SPRM$$ SPRM ). Then, the stable forwarding node will behave as a new source node and start another stable path routing process until the packets are forwarded and reached to the destination node. In addition, the change of stable nodes over time balances and conserves node energy consumption, thereby mitigating “hot spots”. The proposed routing protocol is validated through simulation. The numerical results show that the proposed protocol outperforms the existing algorithms, global and local reliability-based routing ($$GLRR$$ GLRR ) and reliable energy-aware routing protocol $$(RER)$$ ( R E R ) , in terms of network efficiency and reliability.

scholarly journals Routing Algorithm Based on User Adaptive Data Transmission Scheme in Opportunistic Social Networks

Electronics ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 1138
Author(s):  
Yu Lu ◽  
Liu Chang ◽  
Jingwen Luo ◽  
Jia Wu
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Data Transmission ◽  
Routing Algorithm ◽  
Relay Node ◽  
Network Routing ◽  
Transmission Factor ◽  
Transmission Scheme ◽  
Network Delay ◽  
Significant Burden

With the rapid popularization of 5G communication and internet of things technologies, the amount of information has increased significantly in opportunistic social networks, and the types of messages have become more and more complex. More and more mobile devices join the network as nodes, making the network scale increase sharply, and the tremendous amount of datatransmission brings a more significant burden to the network. Traditional opportunistic social network routing algorithms lack effective message copy management and relay node selection methods, which will cause problems such as high network delay and insufficient cache space. Thus, we propose an opportunistic social network routing algorithm based on user-adaptive data transmission. The algorithm will combine the similarity factor, communication factor, and transmission factor of the nodes in the opportunistic social network and use information entropy theory to adaptively assign the weights of decision feature attributes in response to network changes. Also, edge nodes are effectively used, and the nodes are divided into multiple communities to reconstruct the community structure. The simulation results show that the algorithm demonstrates good performance in improving the information transmission’s success rate, reducing network delay, and caching overhead.

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