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14 pages, 3606 KiB  
Article
Secure Cooperative Routing in Wireless Sensor Networks
by Rida Batool, Nargis Bibi, Samah Alhazmi and Nazeer Muhammad
Appl. Sci. 2024, 14(12), 5220; https://doi.org/10.3390/app14125220 - 16 Jun 2024
Cited by 1 | Viewed by 902
Abstract
In wireless sensor networks (WSNs), sensor nodes are randomly distributed to transmit sensed data packets to the base station periodically. These sensor nodes, because of constrained battery power and storage space, cannot utilize conventional security measures. The widely held challenging issues for the [...] Read more.
In wireless sensor networks (WSNs), sensor nodes are randomly distributed to transmit sensed data packets to the base station periodically. These sensor nodes, because of constrained battery power and storage space, cannot utilize conventional security measures. The widely held challenging issues for the network layer of WSNs are the packet-dropping attacks, mainly sinkhole and wormhole attacks, which focus on the routing pattern of the protocol. This thesis presents an improved version of the second level of the guard to the system, intrusion detection systems (IDSs), to limit the hostile impact of these attacks in a Low Energy Adaptive Clustering Hierarchy (LEACH) environment. The proposed system named multipath intrusion detection system (MIDS) integrates an IDs with ad hoc on-demand Multipath Distance Vector (AOMDV) protocol. The IDS agent uses the number of packets transmitted and received to calculate intrusion ratio (IR), which helps to mitigate sinkhole attacks and from AOMDV protocol round trip time (RTT) is computed by taking the difference between route request and route reply time to mitigate wormhole attack. MATLAB simulation results show that this cooperative model is an effective technique due to the higher packet delivery ratio (PDR), throughput, and detection accuracy. The proposed MIDS algorithm is proven to be more efficient when compared with an existing LEACH-based IDS system and MS-LEACH in terms of overall energy consumption, lifetime, and throughput of the network. Full article
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<p>WSN security trends [<a href="#B7-applsci-14-05220" class="html-bibr">7</a>].</p>
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<p>Anchor-based location estimation.</p>
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<p>FCM and optimal path selection. Each color shows distinct cluster. Triangle in each cluster is cluster head (CH). Purple triangle in the center is base station.</p>
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<p>Sinkhole/wormhole detection. Each color shows distinct cluster. Triangle in each cluster is cluster head (CH). purple triangle in the center is base station.</p>
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<p>Alive nodes of the network vs. rounds.</p>
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<p>Packet delivery ratio with rounds.</p>
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<p>Latency with rounds.</p>
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<p>Throughput with rounds.</p>
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<p>Residual energy during communication phase.</p>
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<p>Average energy consumption.</p>
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<p>Throughput of the network.</p>
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<p>Lifetime of the network.</p>
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15 pages, 1082 KiB  
Article
Arithmetic Optimization AOMDV Routing Protocol for FANETs
by Huamin Wang, Yongfu Li, Yubing Zhang, Tiancong Huang and Yang Jiang
Sensors 2023, 23(17), 7550; https://doi.org/10.3390/s23177550 - 31 Aug 2023
Cited by 2 | Viewed by 1684
Abstract
Flying ad hoc networks (FANETs), composed of small unmanned aerial vehicles (UAVs), possess characteristics of flexibility, cost-effectiveness, and rapid deployment, rendering them highly attractive for a wide range of civilian and military applications. FANETs are special mobile ad hoc networks (MANETs), FANETs have [...] Read more.
Flying ad hoc networks (FANETs), composed of small unmanned aerial vehicles (UAVs), possess characteristics of flexibility, cost-effectiveness, and rapid deployment, rendering them highly attractive for a wide range of civilian and military applications. FANETs are special mobile ad hoc networks (MANETs), FANETs have the characteristics of faster network topology changes and limited energy. Existing reactive routing protocols are unsuitable for the highly dynamic and limited energy of FANETs. For the lithium battery-powered UAV, flight endurance lasts from half an hour to two hours. The fast-moving UAV not only affects the packet delivery rate, average throughput, and end-to-end delay but also shortens the flight endurance. Therefore, research is urgently needed into a high-performance routing protocol with high energy efficiency. In this paper, we propose a novel routing protocol called AO-AOMDV, which utilizes arithmetic optimization (AO) to enhance the ad hoc on-demand multi-path distance vector (AOMDV) routing protocol. The AO-AOMDV utilizes a fitness function to calculate the fitness value of multiple paths and employs arithmetic optimization for selecting the optimal route for routing selection. Our experiments were conducted using NS3 with three evaluation metrics: the packet delivery ratio, network lifetime, and average end-to-end delay. We compare this algorithm to routing protocols including AOMDV and AODV. The results indicate that the proposed AO-AOMDV attained a higher packet delivery ratio, network lifetime, and lower average end-to-end delay. Full article
(This article belongs to the Section Vehicular Sensing)
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<p>AOMDV routing protocol.</p>
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<p>3D deployment of UAV nodes for simulation.</p>
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<p>PDR for varying UAV velocities.</p>
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<p>Average end-to-end delay for varying UAV velocities.</p>
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<p>Network lifetime for varying UAV velocities.</p>
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<p>PDR for varying node densities.</p>
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<p>Average E2E delay for varying node densities.</p>
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<p>Network lifetime for varying node densities.</p>
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21 pages, 3101 KiB  
Article
A Reliable Low-Latency Multipath Routing Algorithm for Urban Rail Transit Ad Hoc Networks
by Lei Suo, Liu Liu, Zhaoyang Su, Shiyuan Cai, Zijie Han, Haitao Han and Feng Bao
Sensors 2023, 23(12), 5576; https://doi.org/10.3390/s23125576 - 14 Jun 2023
Cited by 3 | Viewed by 1387
Abstract
With the advancement of urban rail transit towards intelligence, the demand for urban rail transit communication has increased significantly, but the traditional urban rail transit vehicle–ground communication system has been unable to meet the future vehicle–ground communication requirements. To improve the performance of [...] Read more.
With the advancement of urban rail transit towards intelligence, the demand for urban rail transit communication has increased significantly, but the traditional urban rail transit vehicle–ground communication system has been unable to meet the future vehicle–ground communication requirements. To improve the performance of vehicle–ground communication, the paper proposes a reliable low-latency multipath routing (RLLMR) algorithm for urban rail transit ad hoc networks. First, RLLMR combines the characteristics of urban rail transit ad hoc networks and uses node location information to configure a proactive multipath to reduce route discovery delay. Second, the number of transmission paths is adaptively adjusted according to the quality of service (QoS) requirements for vehicle–ground communication, and then the optimal path is selected based on the link cost function to improve transmission quality. Third, in order to enhance the reliability of communication, a routing maintenance scheme has been added, and the static node-based local repair scheme is used in routing maintenance to reduce the maintenance cost and time. The simulation results show that compared with traditional AODV and AOMDV protocols, the proposed RLLMR algorithm has good performance in improving latency and is slightly inferior to the AOMDV protocol in improving reliability. However, overall, the throughput of the RLLMR algorithm is better than that of the AOMDV. Full article
(This article belongs to the Section Sensor Networks)
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<p>The network topology of the train and trackside nodes.</p>
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<p>Vehicle–ground communication network architecture.</p>
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<p>Intra-cell routing repair.</p>
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<p>Inter-cell routing repair.</p>
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<p>RLLMR algorithm flowchart (<b>a</b>) Routing Selection process. (<b>b</b>) Routing repair process.</p>
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<p>The relationship of discovery latency with arrival rate.</p>
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<p>The relationship of discovery latency with mobile node location.</p>
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<p>The relationship of end-to-end latency with the arrival rate.</p>
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<p>Average end-to-end latency in a good network environment.</p>
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<p>Average end-to-end latency in a bad network environment.</p>
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<p>The relationship of packets loss rate with sent packets.</p>
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<p>Packets loss rate in a good network environment.</p>
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<p>Packets loss rate in a bad network environment.</p>
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<p>Throughput in a good network environment.</p>
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<p>Throughput in a bad network environment.</p>
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16 pages, 1730 KiB  
Article
Improving Efficiency of Large RFID Networks Using a Clustered Method: A Comparative Analysis
by M. Thurai Pandian, Kuldeep Chouhan, B. Muthu Kumar, Jatindra Kumar Dash, N. Z. Jhanjhi, Ashraf Osman Ibrahim and Anas W. Abulfaraj
Electronics 2022, 11(18), 2968; https://doi.org/10.3390/electronics11182968 - 19 Sep 2022
Cited by 6 | Viewed by 1770
Abstract
Radio Frequency Identification (RFID) is primarily used to resolve the problems of taking care of the majority of nodes perceived and tracking tags related to the items. Utilizing contactless radio frequency identification data can be communicated distantly using electromagnetic fields. In this paper, [...] Read more.
Radio Frequency Identification (RFID) is primarily used to resolve the problems of taking care of the majority of nodes perceived and tracking tags related to the items. Utilizing contactless radio frequency identification data can be communicated distantly using electromagnetic fields. In this paper, the comparison and analysis made between the Clustered RFID with existing protocols Ad hoc On-demand Multicast Distance Vector Secure Adjacent Position Trust Verification (AOMDV_SAPTV) and Optimal Distance-Based Clustering (ODBC) protocols based on the network attributes of accuracy, vulnerability and success rate, delay and throughput while handling the huge nodes of communication. In the RFID Network, the clustering mechanism was implemented to enhance the performance of the network when scaling nodes. Multicast routing was used to handle the large number of nodes involved in the transmission of particular network communication. While scaling up the network, existing methods may be compromised with their efficiency. However, the Clustered RFID method will give better performance without compromising efficiency. Here, Clustered RFID gives 93% performance, AOMDV_SAPTV can achieve 79%, and ODBC can reach 85% of performance. Clustered RFID gives 14% better performance than AOMDV_SAPTV and 8% better performance than ODBC for handling a huge range of nodes. Full article
(This article belongs to the Collection Smart Sensing RFID Tags)
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<p>Working methodology of Clustered RFID.</p>
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<p>(<b>a</b>) Accuracy of AOMDV_SAPTV (<b>b</b>) Success rate of AOMDV_SAPTV (<b>c</b>) Vulnerability of AOMDV_SAPTV (<b>d</b>) Delay of AOMDV_SAPTV (<b>e</b>) Throughput of AOMDV_SAPTV.</p>
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<p>(<b>a</b>) Accuracy of Clustered RFID (<b>b</b>) Success rate of Clustered RFID (<b>c</b>) Vulnerability of Clustered RFID (<b>d</b>) Delay of Clustered RFID (<b>e</b>) Throughput of Clustered RFID.</p>
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<p>(<b>a</b>) Accuracy of ODBC (<b>b</b>) Success rate of ODBC (<b>c</b>) Vulnerability of ODBC (<b>d</b>) Delay of ODBC (<b>e</b>) Throughput of ODBC.</p>
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<p>Comparison between AOMDV_SAPTV, ODBC with Clustered RFID.</p>
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14 pages, 1526 KiB  
Article
Wireless Body Area Routing Protocols Impact Analysis on Entity Mobility Models with Static Sink Node
by Sunny Singh, Devendra Prasad, Shalli Rani, Aman Singh, Fahd S. Alharithi and Jasem Almotiri
Appl. Sci. 2022, 12(11), 5655; https://doi.org/10.3390/app12115655 - 2 Jun 2022
Cited by 4 | Viewed by 2083
Abstract
The most important and emerging characteristic of Wireless Body Area Networks (WBANs), which differentiates them from other wired and wireless area networks, is mobility. Therefore, the routing protocols for WBAN are designed in such a way that they can deal with dynamic changes [...] Read more.
The most important and emerging characteristic of Wireless Body Area Networks (WBANs), which differentiates them from other wired and wireless area networks, is mobility. Therefore, the routing protocols for WBAN are designed in such a way that they can deal with dynamic changes in topology and provide maximum throughput, packet delivery ratio, average end-to-end delay, and minimum energy consumption. Thus, achieving optimal values for every performance parameter becomes a big challenge. This work investigates the performance of three separate path discovery protocols, such as Destination-Sequenced Distance-Vector Routing (DSDV), Ad Hoc On-demand Distance Vector (AODV), and Ad Hoc On-demand Multipath Distance Vector Routing protocol (AOMDV), for two different mobility models with a fixed-positioned sink. During experimentation, the AOMDV routing protocol achieves a high packet delivery ratio (PDR), average end-to-end delay, and throughput as compared to other routing protocols. Full article
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<p>General WBAN Architecture.</p>
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<p>Movement of Mobile Nodes in RWM (<b>Left</b>) and RDM (<b>Right</b>).</p>
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<p>The current working strategy of the proposed model.</p>
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<p>Performance analysis of RWM and RDM on various routing protocols in terms of PDR.</p>
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<p>Performance analysis of RWM and RDM on various routing protocols in terms of average end-to-end delay.</p>
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<p>Performance analysis of RWM and RDM on various routing protocols in terms of throughput.</p>
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38 pages, 3389 KiB  
Article
Intelligent Transport System Using Time Delay-Based Multipath Routing Protocol for Vehicular Ad Hoc Networks
by Yashar Ghaemi, Hosam El-Ocla, Nitin Ramesh Yadav, Manisha Reddy Madana, Dheeraj Kurugod Raju, Vignesh Dhanabal and Vishal Sheshadri
Sensors 2021, 21(22), 7706; https://doi.org/10.3390/s21227706 - 19 Nov 2021
Cited by 9 | Viewed by 2521
Abstract
During the last decade, the research on Intelligent Transportation System (ITS) has improved exponentially in real-life scenarios to provide optimized transport network performance. It is a matter of importance that alert messages are delivered promptly to prevent vehicular traffic problems. The fact is [...] Read more.
During the last decade, the research on Intelligent Transportation System (ITS) has improved exponentially in real-life scenarios to provide optimized transport network performance. It is a matter of importance that alert messages are delivered promptly to prevent vehicular traffic problems. The fact is an ITS system per se could be a part of a vehicular ad hoc network (VANET) which is an extension of a wireless network. In all sorts of wireless ad hoc networks, the network topology is subjected to change due to the mobility of network nodes; therefore, an existing explored route between two nodes could be demolished in a minor fraction of time. When it comes to the VANETs, the topology likely changes due to the high velocity of nodes. On the other hand, time is a crucial factor playing an important role in message handling between the network’s nodes. In this paper, we propose Time delay-based Multipath Routing (TMR) protocol that effectively identifies an optimized path for packet delivery to the destination vehicle with a minimal time delay. Our algorithm gives a higher priority to alert messages compared to normal messages. It also selects the routes with the short round-trip time (RTT) within the RTT threshold. As a result, our algorithm would realize two goals. Firstly, it would speed up the data transmission rate and deliver data packets, particularly warning messages, to the destination vehicle promptly and therefore avoid vehicular problems such as car accidents. Secondly, the TMR algorithm reduces the data traffic load, particularly of the normal messages, to alleviate the pressure on the network and therefore avoids network congestion and data collisions. This, in turn, lessens the packets’ retransmissions. To demonstrate the effectiveness of the proposed protocol, the TMR has been compared with the other protocols such as AOMDV, FF-AOMDV, EGSR, QMR, and ISR. Simulation results demonstrate that our proposed protocol proves its excellent performance compared to other protocols. Full article
(This article belongs to the Special Issue Artificial Intelligence Based Autonomous Vehicles)
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<p>Flow diagram of message handling.</p>
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<p>Flow diagram of packet forwarding at OBU.</p>
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<p>Normal packet format.</p>
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<p>Scenario 1: data communications in one road segment.</p>
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<p>Comparison of AOMDV, FF-AOMDV, EGSR, QMR, and proposed protocol TMR and TSR throughput with simulation time.</p>
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<p>Comparison of AOMDV, FF-AOMDV, EGSR, QMR, and proposed protocol TMR and TSR for PLR with simulation time.</p>
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<p>Comparison of FF-AOMDV, EGSR, QMR, and proposed protocol TMR for end-to-end delay with pause time.</p>
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<p>Comparison of FF-AOMDV, EGSR, QMR, and proposed protocol TMR for energy consumption with pause time.</p>
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<p>Comparison of FF-AOMDV, EGSR, QMR, and proposed protocol TMR for throughout with different packet sizes.</p>
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<p>Comparison of FF-AOMDV, EGSR, QMR, and proposed protocol TMR for energy consumption with different packet sizes.</p>
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<p>Comparison of FF-AOMDV, EGSR, QMR, and proposed protocol TMR for end-to-end delay with different packet sizes.</p>
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<p>Comparison of FF-AOMDV, EGSR, QMR, and proposed protocol TMR for throughput with faulty node.</p>
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<p>Comparison of FF-AOMDV, EGSR, QMR, and proposed protocol TMR for energy consumption with faulty node.</p>
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<p>Comparison of FF-AOMDV, EGSR, QMR, and proposed protocol TMR for throughput with number of nodes.</p>
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<p>Comparison of FF-AOMDV, EGSR, QMR, and proposed protocol TMR for end-to-end delay with number of nodes.</p>
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<p>Comparison of FF-AOMDV, EGSR, QMR, and proposed protocol TMR for PLR with number of nodes.</p>
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<p>Comparison of FF-AOMDV, EGSR, QMR, and proposed protocol TMR for energy consumption with number of nodes.</p>
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<p>Comparison of AOMDV, FF-AOMDV, EGSR, QMR, and proposed protocol TMR for throughput with mobility speed.</p>
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<p>Comparison of FF-AOMDV, EGSR, QMR, and proposed protocol TMR for PLR with mobility speed.</p>
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<p>Comparison of FF-AOMDV, EGSR, QMR, and proposed protocol TMR for energy consumption with mobility speed.</p>
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<p>Comparison of FF-AOMDV, EGSR, QMR, and proposed protocol TMR for routing overhead with mobility speed.</p>
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<p>Comparison of FF-AOMDV, EGSR, QMR, and proposed protocol TMR for routing overhead with mobility speed.</p>
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<p>Scenario 2: data communications in multiple road segments.</p>
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<p>Comparison of EGSR, ISR, and proposed protocol TMR for throughput with simulation time.</p>
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<p>Comparison of EGSR, ISR, and proposed protocol TMR for PLR with simulation time.</p>
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<p>Comparison of EGSR, ISR, and proposed protocol TMR for end-to-end delay with simulation time.</p>
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<p>Comparison of EGSR, ISR, and proposed protocol TMR for routing overhead with simulation time.</p>
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<p>Comparison of QMR, ISR, and proposed protocol TMR for throughput with mobility speed.</p>
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<p>Comparison of QMR, ISR, and proposed protocol TMR for PLR with mobility speed.</p>
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<p>Comparison of QMR, ISR, and proposed protocol TMR for end-to-end delay with mobility speed.</p>
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<p>Comparison of QMR, ISR, and proposed protocol TMR for routing overhead with mobility speed.</p>
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<p>Comparison of QMR, ISR, and proposed protocol TMR for throughput with number of nodes.</p>
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<p>Comparison of QMR, ISR, and proposed protocol TMR for PLR with number of nodes.</p>
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<p>Comparison of QMR, ISR, and proposed protocol TMR for end-to-end delay with number of nodes.</p>
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<p>Comparison of QMR, ISR, and proposed protocol TMR for routing overhead with number of nodes.</p>
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<p>Scenarios of time-complexity networks.</p>
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21 pages, 3934 KiB  
Communication
Energy Efficient Routing Protocol in Sensor Networks Using Genetic Algorithm
by Jatinkumar Patel and Hosam El-Ocla
Sensors 2021, 21(21), 7060; https://doi.org/10.3390/s21217060 - 25 Oct 2021
Cited by 20 | Viewed by 2856
Abstract
In this paper, we examine routing protocols with the shortest path in sensor networks. In doing this, we propose a genetic algorithm (GA)-based Ad Hoc On-Demand Multipath Distance Vector routing protocol (GA-AOMDV). We utilize a fitness function that optimizes routes based on the [...] Read more.
In this paper, we examine routing protocols with the shortest path in sensor networks. In doing this, we propose a genetic algorithm (GA)-based Ad Hoc On-Demand Multipath Distance Vector routing protocol (GA-AOMDV). We utilize a fitness function that optimizes routes based on the energy consumption in their nodes. We compare this algorithm with other existing ad hoc routing protocols including LEACH-GA, GA-AODV, AODV, DSR, EPAR, EBAR_BFS. Results prove that our protocol enhances the network performance in terms of packet delivery ratio, throughput, round trip time and energy consumption. GA-AOMDV protocol achieves average gain that is 7 to 22% over other protocols. Therefore, our protocol extends the network lifetime for data communications. Full article
(This article belongs to the Special Issue Distributed Algorithms for Wireless Sensor Networks)
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<p>Wireless sensor network.</p>
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<p>GA-AOMDV flowchart.</p>
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<p>Network topology.</p>
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<p>E2E vs. No of Nodes.</p>
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<p>Energy consumption vs. No of Nodes.</p>
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<p>Throughput vs. No of Nodes.</p>
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<p>Packet delivery ratio vs. No of Nodes.</p>
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<p>E2E vs. mobility speed.</p>
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<p>Energy consumption vs. mobility speed.</p>
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<p>Throughput vs. mobility speed.</p>
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<p>Packet delivery ratio vs. mobility speed.</p>
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<p>Energy Consumption vs. No of Nodes.</p>
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<p>Packet Delivery Ratio vs. No of Nodes.</p>
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<p>RTT vs. No of Nodes.</p>
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<p>Packet Delivery Ratio vs. Average Bandwidth.</p>
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<p>Energy Consumption vs. Average Bandwidth.</p>
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<p>RTT vs. Bandwidth.</p>
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<p>Throughput vs. Bandwidth.</p>
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<p>Energy Consumption vs. mobility speed.</p>
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<p>RTT vs. Speed of nodes.</p>
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15 pages, 692 KiB  
Article
An Optimized Framework for WSN Routing in the Context of Industry 4.0
by Shalli Rani, Deepika Koundal, Kavita, Muhammad Fazal Ijaz, Mohamed Elhoseny and Mohammed I. Alghamdi
Sensors 2021, 21(19), 6474; https://doi.org/10.3390/s21196474 - 28 Sep 2021
Cited by 93 | Viewed by 2917
Abstract
The advancements in Industry 4.0 have opened up new ways for the structural deployment of Smart Grids (SGs) to face the endlessly rising challenges of the 21st century. SGs for Industry 4.0 can be better managed by optimized routing techniques. In Mobile Ad [...] Read more.
The advancements in Industry 4.0 have opened up new ways for the structural deployment of Smart Grids (SGs) to face the endlessly rising challenges of the 21st century. SGs for Industry 4.0 can be better managed by optimized routing techniques. In Mobile Ad hoc Networks (MANETs), the topology is not fixed and can be encountered by interference, mobility of nodes, propagation of multi-paths, and path loss. To extenuate these concerns for SGs, in this paper, we have presented a new version of the standard Optimized Link State Routing (OLSR) protocol for SGs to improve the management of control intervals that enhance the efficiency of the standard OLSR protocol without affecting its reliability. The adapted fault tolerant approach makes the proposed protocol more reliable for industrial applications. The process of grouping of nodes supports managing the total network cost by reducing severe flooding and evaluating an optimized head of clusters. The head of the unit is nominated according to the first defined expectation factor. With a sequence of rigorous performance evaluations under simulation parameters, the simulation results show that the proposed version of OLSR has proliferated Quality of Service (QoS) metrics when it is compared against the state-of-the-art-based conventional protocols, namely, standard OLSR, DSDV, AOMDV and hybrid routing technique. Full article
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<p>Design overview of the routing scheme.</p>
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<p>Distance measurements of mobile nodes.</p>
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<p>Network setup.</p>
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<p>Comparison of delay in data reception.</p>
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<p>Comparison of packet delivery.</p>
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<p>Comparison of hello message sent.</p>
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<p>Comparison of existing and proposed techniques in transmitted control messages.</p>
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<p>Comparison of existing and proposed techniques in average throughput.</p>
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19 pages, 939 KiB  
Article
Energy-Balanced Routing Algorithm Based on Ant Colony Optimization for Mobile Ad Hoc Networks
by Dong Yang, Hongxing Xia, Erfei Xu, Dongliang Jing and Hailin Zhang
Sensors 2018, 18(11), 3657; https://doi.org/10.3390/s18113657 - 28 Oct 2018
Cited by 25 | Viewed by 3587
Abstract
The mobile ad hoc network (MANET) is a multi-hop, non-central network composed of mobile terminals with self-organizing features. Aiming at the problem of extra energy consumption caused by node motion in MANETs, this paper proposes an improved energy and mobility ant colony optimization [...] Read more.
The mobile ad hoc network (MANET) is a multi-hop, non-central network composed of mobile terminals with self-organizing features. Aiming at the problem of extra energy consumption caused by node motion in MANETs, this paper proposes an improved energy and mobility ant colony optimization (IEMACO) routing algorithm. Firstly, the algorithm accelerates the convergence speed of the routing algorithm and reduces the number of route discovery packets by introducing an offset coefficient of the transition probability. Then, based on the energy consumption rate, the remaining lifetime of nodes (RLTn) is considered. The position and velocity information predicts the remaining lifetime of the link (RLTl). The algorithm combines RLTn and RLTl to design the pheromone generation method, which selects the better quality path according to the transition probability to ensure continuous data transmission. As a result, the energy consumption in the network is balanced. The simulation results show that compared to the Ad Hoc on-demand multipath distance vector (AOMDV) algorithm with multipath routing and the Ant Hoc Max-Min-Path (AntHocMMP) algorithm in consideration of node energy consumption and mobility, the IEMACO algorithm can reduce the frequency of route discovery and has lower end-to-end delay as well as packet loss rate especially when nodes move, and can extend the network lifetime. Full article
(This article belongs to the Section Sensor Networks)
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<p>Flow of the route discovery.</p>
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<p>Routing performance with varying <span class="html-italic">offset coefficient</span> <math display="inline"><semantics> <mi>θ</mi> </semantics></math>.</p>
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<p>Comparison of convergence performance.</p>
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<p>Average end-to-end delay versus node moving speed.</p>
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<p>Packet delivery rate versus node moving speed.</p>
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<p>First node death time versus node moving speed.</p>
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<p>Number of dead nodes versus node moving speed.</p>
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<p>Average end-to-end delay versus node packet rate.</p>
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<p>Packet delivery rate versus node packet rate.</p>
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<p>First node death time versus node packet rate.</p>
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<p>Number of dead nodes versus node packet rate.</p>
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20 pages, 11315 KiB  
Article
Energy Reduction Multipath Routing Protocol for MANET Using Recoil Technique
by Rakesh Kumar Sahu and Narendra S. Chaudhari
Electronics 2018, 7(5), 56; https://doi.org/10.3390/electronics7050056 - 25 Apr 2018
Cited by 15 | Viewed by 6332
Abstract
In Mobile Ad-hoc networks (MANET), power conservation and utilization is an acute problem and has received significant attention from academics and industry in recent years. Nodes in MANET function on battery power, which is a rare and limited energy resource. Hence, its conservation [...] Read more.
In Mobile Ad-hoc networks (MANET), power conservation and utilization is an acute problem and has received significant attention from academics and industry in recent years. Nodes in MANET function on battery power, which is a rare and limited energy resource. Hence, its conservation and utilization should be done judiciously for the effective functioning of the network. In this paper, a novel protocol namely Energy Reduction Multipath Routing Protocol for MANET using Recoil Technique (AOMDV-ER) is proposed, which conserves the energy along with optimal network lifetime, routing overhead, packet delivery ratio and throughput. It performs better than any other AODV based algorithms, as in AOMDV-ER the nodes transmit packets to their destination smartly by using a varying recoil off time technique based on their geographical location. This concept reduces the number of transmissions, which results in the improvement of network lifetime. In addition, the local level route maintenance reduces the additional routing overhead. Lastly, the prediction based link lifetime of each node is estimated which helps in reducing the packet loss in the network. This protocol has three subparts: an optimal route discovery algorithm amalgamation with the residual energy and distance mechanism; a coordinated recoiled nodes algorithm which eliminates the number of transmissions in order to reduces the data redundancy, traffic redundant, routing overhead, end to end delay and enhance the network lifetime; and a last link reckoning and route maintenance algorithm to improve the packet delivery ratio and link stability in the network. The experimental results show that the AOMDV-ER protocol save at least 16% energy consumption, 12% reduction in routing overhead, significant achievement in network lifetime and packet delivery ratio than Ad hoc on demand multipath distance vector routing protocol (AOMDV), Ad hoc on demand multipath distance vector routing protocol life maximization (AOMR-LM) and Source routing-based multicast protocol (SRMP) algorithms. Hence, the AOMDV-ER algorithm performs better than these recently developed algorithms. Full article
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<p>Illustrates the application of MANET in tactical network.</p>
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<p>(<b>a</b>) Min-power route; (<b>b</b>) Max-Min Energy Distance Path.</p>
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<p>Minimum distance from SD line.</p>
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<p>Recoil technique with recoiled nodes.</p>
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<p>(<b>a</b>) Recoiled off time distribution to nodes 1, 2 and 3; (<b>b</b>) Recoiled off time calculation; (<b>c</b>) Recoiled off time calculation for an arbitrary node N.</p>
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<p>(<b>a</b>) Node mobility; (<b>b</b>) Mobility estimation.</p>
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<p>(<b>a</b>) Illustrates the route maintenance between nodes A and D; (<b>b</b>) Packet transmission from S to D and table entry with route request in network; (<b>c</b>) Illustrates.</p>
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<p>(<b>a</b>) Illustrates the route maintenance between nodes A and D; (<b>b</b>) Packet transmission from S to D and table entry with route request in network; (<b>c</b>) Illustrates.</p>
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<p>Simulation tool snap shot.</p>
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<p>(<b>a</b>) Overhead vs. Node Speed; (<b>b</b>) Overhead vs. Packet Size; (<b>c</b>) Overhead vs. Sim. time.</p>
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<p>(<b>a</b>) N Lifetime vs. Node Speed; (<b>b</b>) N. Lifetime vs. Packet Size; (<b>c</b>) N. Lifetime vs. Sim. time.</p>
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<p>(<b>a</b>) Energy consumption with time; (<b>b</b>) Exh. nodes with time; (<b>c</b>) PDR with time x.</p>
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<p>(<b>a</b>) PDR vs. Node Speed; (<b>b</b>) PDR vs. Packet Size; (<b>c</b>) PDR vs. Sim. time.</p>
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<p>(<b>a</b>) Throughput vs. Node Speed; (<b>b</b>) Throughput vs. Packet Size; (<b>c</b>) Throughput vs. Sim. time.</p>
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<p>(<b>a</b>) Best fit line on AODV-ER; (<b>b</b>) Best fit line on AODV-ER; (<b>c</b>) Best fit line on AODV-ER.</p>
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<p>(<b>a</b>) Energy cons. vs. Node speed; (<b>b</b>) Energy cons. vs. Pack. Size; (<b>c</b>) Energy cons. vs. time.</p>
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2811 KiB  
Conference Report
A Smart Sensor Grid to Enhance Irrigation Techniques in Jordan Using a Novel Event-Based Routing Protocol
by Maher Ali Al Rantisi, Glenford Mapp and Orhan Gemikonakli
Multimodal Technol. Interact. 2017, 1(2), 9; https://doi.org/10.3390/mti1020009 - 16 May 2017
Viewed by 4828
Abstract
Due to rapid changes in climatic conditions worldwide, environmental monitoring has become one of the greatest concerns in the last few years. With the advancement in wireless sensing technology, it is now possible to monitor and track fine-grained changes in harsh outdoor environments. [...] Read more.
Due to rapid changes in climatic conditions worldwide, environmental monitoring has become one of the greatest concerns in the last few years. With the advancement in wireless sensing technology, it is now possible to monitor and track fine-grained changes in harsh outdoor environments. Wireless sensor networks (WSN) provide very high quality and accurate analysis for monitoring of both spatial and temporal data, thus providing the opportunity to monitor harsh outdoor environments. However, to deploy and maintain a WSN in such harsh environments is a great challenge for researchers and scientists. Several routing protocols exist for data dissemination and power management but they suffer from various disadvantages. In our case study, there are very limited water resources in the Middle East, hence soil moisture measurements must be taken into account to manage irrigation and аgriculturаl projects. In order to meet these challenges, a Smart Grid that supports a robust, reactive, event-based routing protocol is developed using Ad hoc On-Demand Multipath Distance Vector (AOMDV) as a starting point. A prototype WSN network of 5 nodes is built and a detailed simulation of 30 nodes is also developed to test the scalability of the new system. Full article
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<p>Sensor Network forming mesh.</p>
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<p>Routing decisions made based on external events.</p>
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<p>Waspmote Sensor Node.</p>
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<p>XBee RF Module and USB PC Gateway.</p>
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<p>Watermark Soil Moisture Sensor and Weather Station having Rainfall Sensor.</p>
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<p>Five Node wireless sensor network (WSN) Test Bed Setup.</p>
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<p>30-Nodes Simulation Setup.</p>
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<p>The throughput differences between light rain, heavy and very heavy rain, on node 1.</p>
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<p>Transmission Energy Consumption in mA.</p>
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<p>Received Energy Consumption in mA.</p>
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<p>Energy consumed by nodes before and during rainfall.</p>
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Article
LBMR: Load-Balanced Multipath Routing for Wireless Data-Intensive Transmission in Real-Time Medical Monitoring
by Chinyang Henry Tseng
Int. J. Environ. Res. Public Health 2016, 13(6), 547; https://doi.org/10.3390/ijerph13060547 - 31 May 2016
Cited by 3 | Viewed by 4145
Abstract
In wireless networks, low-power Zigbee is an excellent network solution for wireless medical monitoring systems. Medical monitoring generally involves transmission of a large amount of data and easily causes bottleneck problems. Although Zigbee’s AODV mesh routing provides extensible multi-hop data transmission to extend [...] Read more.
In wireless networks, low-power Zigbee is an excellent network solution for wireless medical monitoring systems. Medical monitoring generally involves transmission of a large amount of data and easily causes bottleneck problems. Although Zigbee’s AODV mesh routing provides extensible multi-hop data transmission to extend network coverage, it originally does not, and needs to support some form of load balancing mechanism to avoid bottlenecks. To guarantee a more reliable multi-hop data transmission for life-critical medical applications, we have developed a multipath solution, called Load-Balanced Multipath Routing (LBMR) to replace Zigbee’s routing mechanism. LBMR consists of three main parts: Layer Routing Construction (LRC), a Load Estimation Algorithm (LEA), and a Route Maintenance (RM) mechanism. LRC assigns nodes into different layers based on the node’s distance to the medical data gateway. Nodes can have multiple next-hops delivering medical data toward the gateway. All neighboring layer-nodes exchange flow information containing current load, which is the used by the LEA to estimate future load of next-hops to the gateway. With LBMR, nodes can choose the neighbors with the least load as the next-hops and thus can achieve load balancing and avoid bottlenecks. Furthermore, RM can detect route failures in real-time and perform route redirection to ensure routing robustness. Since LRC and LEA prevent bottlenecks while RM ensures routing fault tolerance, LBMR provides a highly reliable routing service for medical monitoring. To evaluate these accomplishments, we compare LBMR with Zigbee’s AODV and another multipath protocol, AOMDV. The simulation results demonstrate LBMR achieves better load balancing, less unreachable nodes, and better packet delivery ratio than either AODV or AOMDV. Full article
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<p>Example scenario of LBMR routing for real-time medical monitoring.</p>
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<p>LBMR routing in a Zigbee stack.</p>
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<p>Layer routing in LBMR.</p>
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<p>Routing table and neighbor table in LBMR.</p>
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<p>Flow variance of each layer. (<b>a</b>) Grid topology; (<b>b</b>) Random topology.</p>
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<p>Load distribution in gird topology (total node is 85). (<b>a</b>) AOMDV; (<b>b</b>) LBMR.</p>
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<p>Load distribution in random topology (total node is 100). (<b>a</b>) AOMDV; (<b>b</b>) LBMR.</p>
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<p>Route maintenance. (<b>a</b>) Grid topology (total nodes is 85); (<b>b</b>) Random topology (total nodes is 100).</p>
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<p>Packet delivery ratio. (<b>a</b>) Grid topology; (<b>b</b>) Random topology.</p>
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321 KiB  
Article
WEAMR — A Weighted Energy Aware Multipath Reliable Routing Mechanism for Hotline-Based WSNs
by Ali Tufail, Arslan Qamar, Adil Mehmood Khan, Waleed Akram Baig and Ki-Hyung Kim
Sensors 2013, 13(5), 6295-6318; https://doi.org/10.3390/s130506295 - 13 May 2013
Cited by 9 | Viewed by 7346
Abstract
Reliable source to sink communication is the most important factor for an efficient routing protocol especially in domains of military, healthcare and disaster recovery applications. We present weighted energy aware multipath reliable routing (WEAMR), a novel energy aware multipath routing protocol which utilizes [...] Read more.
Reliable source to sink communication is the most important factor for an efficient routing protocol especially in domains of military, healthcare and disaster recovery applications. We present weighted energy aware multipath reliable routing (WEAMR), a novel energy aware multipath routing protocol which utilizes hotline-assisted routing to meet such requirements for mission critical applications. The protocol reduces the number of average hops from source to destination and provides unmatched reliability as compared to well known reactive ad hoc protocols i.e., AODV and AOMDV. Our protocol makes efficient use of network paths based on weighted cost calculation and intelligently selects the best possible paths for data transmissions. The path cost calculation considers end to end number of hops, latency and minimum energy node value in the path. In case of path failure path recalculation is done efficiently with minimum latency and control packets overhead. Our evaluation shows that our proposal provides better end-to-end delivery with less routing overhead and higher packet delivery success ratio compared to AODV and AOMDV. The use of multipath also increases overall life time of WSN network using optimum energy available paths between sender and receiver in WDNs. Full article
(This article belongs to the Section Sensor Networks)
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<p>WSN with sink node.</p>
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<p>WSN with Hotlines Architecture.</p>
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<p>Proposed RREQ message format.</p>
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<p>Proposed RREP message format.</p>
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<p>Overview of the multipath discovery process</p>
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<p>Algorithm to send data packet.</p>
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<p>Overall procedure for the sender node to send data packet.</p>
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<p>Algorithm to receive data packet.</p>
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<p>Overall procedure for intermediate node to receive data packet.</p>
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