Performance Comparison of Geographic DTN Routing Algorithms

Seki, Misako; Ogura, Kazumine; Yamasaki, Yoshio; Ohsaki, Hiroyuki

doi:10.1109/compsac.2015.148

Cited by 8 publications

(3 citation statements)

References 3 publications

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“…The duty-cycle scheduling method tries to make applications last longer by letting nodes sleep for as long as possible and waking them up when a packet is sent to them. In the study field of low duty-cycle networks [16][17][18][19][20][21], the researchers did a thorough analysis of how long it takes for data to travel from a node to a sink in networks where nodes work at different times. And some researchers say that the best choice is to use dynamic forwarding, which takes both the sleeping latency and the link quality into account and always sends the packet to the node with the desired metric [22].…”

Section: Duty-cycled Wsnsmentioning

confidence: 99%

Efficient Geographic Routing for High-Speed Data in Wireless Multimedia Sensor Networks

Pandith,

Ramaswamy,

Srikantaswamy

et al. 2023

JESA

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In recent eras, a large amount of data has been transferred through wireless networks in fifth-generation communication using a two-phase geography greedy forwarding (TPGF) routing algorithm with reconfigurable routing metrics represented by RrTPGF in random duty-cycled wireless multilevel multimedia sensor networks (WMSNs). The proposed method reduces the sleep delay in geographic routing networks. the systematically forwarded node in the geographic routing network to identify the significant neighboring nodes. The proposed algorithm is efficient in identifying the geographical distance of the neighboring node and identifying the sleeping delay of the nodes during the communication process. The proposed algorithm efficiently differentiates the worked node from the unworked node on the basis that it identifies the optimal single routing path with a low sleeping delay time at geographic routing. As per the simulation result, the performance of the proposed method shows better results as compared to the conventional methods when considering the scenario size of 750mm × 450mm and 250 nodes with respect to the average delay of the proposed method, which is reduced to 0.6%, and the average hop counts, which are reduced to 0.56% as compared to the conventional method.

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Section: Duty-cycled Wsnsmentioning

confidence: 99%

Efficient Geographic Routing for High-Speed Data in Wireless Multimedia Sensor Networks

Pandith,

Ramaswamy,

Srikantaswamy

et al. 2023

JESA

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“…Then, when the spray stage is finished, the protocol shifts to the waiting stage. In the waiting stage, every node keeps its message in the buffer until reaching its destination [32]. The advantage of the Spray & Wait protocol is lowering the overhead and buffer overflow by reducing the excessive packet forwarding in networks that exists in the flooding routing protocol like Epidemic.…”

Section: Description Of Dtns Routing Protocolsmentioning

confidence: 99%

Performance Analysis of the Impact of Time to Leave on Different Drop Policies for Delay Tolerant Networks

Hasan¹,

Al-Bayatti²,

Khan³

et al. 2022

Preprint

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Delay Tolerant Networks (DTNs) are intermittently connected networks, where there is no guaranteed end-to-end connectivity between the source and destination. The link between the pair of nodes in the DTNs environments is frequently disrupted, due to the fast mobility of nodes, dissemination nature, and power outages. Due to the absence of contemporaneous paths between the nodes, the opportunities for message forwarding in DTNs usually are limited. To obtain high data delivery, the DTNs use innovation of the Store-Carry and Forward (SCF) technique which allows data transmission to successfully proceed despite the absence of continuous end-to-end paths. However, the SCF approach arises various issues such as buffer congestion and message drop which are caused due to growing number of carried messages in restricted network resources. Therefore, buffer management techniques are required to manage the buffer capacity of the nodes by deciding how to effectively drop the messages and how to schedule the messages in the node’s buffer in a perfect way. This paper evaluates the performance of six buffer management techniques, namely First-In-FirstOut, Last In First Out, Drop Largest, Drop Youngest, Evict Shortest Lifetime First and Evict Most Forwarded First, with MaxProp and Spray and Wait routing protocols under variable message’s Time-To-Live values (60 to 300 minutes with step-change 60 minutes). In addition, this study uses an Opportunistic Network Environment (ONE) simulator that is utilized for evaluating the performance of the dropping policies techniques, where it is considering five performance metrics (delivery ratio, overhead ratio, average latency, hop count, and message drop). The evaluation results of each buffer management policy are explained by these metrics briefly.

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“…Routing design is a hot research topic, as a well-performing routing algorithm can deliver messages to the destination node in a short time with minimal overhead. Designing an efficient routing algorithm is a key and challenging problem in DTN [13].…”

Section: Introductionmentioning

confidence: 99%

Multi-Copy Relay Node Selection Strategy Based on Reinforcement Learning

Yang

Zhang

2023

Sensors

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Delay tolerant networks (DTNs), are characterized by their difficulty in establishing end-to-end paths and and large message propagation delays. To control network overhead costs, reduce message delays, and improve delivery rates in DTNs, it is essential to not only delete messages that have reached their destination but also to more precisely determine appropriate relay nodes. Based on the above goals, this paper constructs a multi-copy relay node selection router algorithm based on Q-lambda reinforcement learning with reference to the idea of community division (QLCR). In community division, if a node has the highestdegree, it is considered the core node, and nodes with similar interests and structural properties are divided into a community. Node degree refers to the number of nodes associated with the node, indicating its importance in the network. Structural similarity determines the distance between nodes. The selection of relay nodes considers node degree, interests, and structural similarity. The Q-lambda reinforcement learning algorithm enables each node to learn from the entire network, setting corresponding reward values based on encountered nodes meeting the specified conditions. Through iterative processes, the node with the most cumulative reward value is chosen as the final relay node. Experimental results demonstrate that the proposed algorithm achieves a high delivery rate while maintaining low network overhead and delay.

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Performance Comparison of Geographic DTN Routing Algorithms

Cited by 8 publications

References 3 publications

Efficient Geographic Routing for High-Speed Data in Wireless Multimedia Sensor Networks

Efficient Geographic Routing for High-Speed Data in Wireless Multimedia Sensor Networks

Performance Analysis of the Impact of Time to Leave on Different Drop Policies for Delay Tolerant Networks

Multi-Copy Relay Node Selection Strategy Based on Reinforcement Learning

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