Erlang Based Buffer Management and Routing in Opportunistic Networks

Derakhshanfard, Nahideh

doi:10.1007/s11277-019-06835-8

Cited by 4 publications

(4 citation statements)

References 15 publications

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“…In [13] the proposed algorithm has considered the probability of message delivery, buffer status, and message delivery time concurrently in selecting the relay node and in allocation the tokens sent to the node.…”

Section: Related Workmentioning

confidence: 99%

BMRTD: Buffer Management policy based on Remaining Time to encounter nodes with the Destination node in delay tolerant networks

Karami

Derakhshanfard

2023

Preprint

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Delay Tolerant Network (DTN) is a kind of network that there is no continuous network connectivity among nodes. There are no end-to-end and constant connection paths from source nodes to destination nodes due to the mobility nature of nodes. In such networks there exists an inevitable long delivery delay. DTN is designed to perform properly over intermittent connections among nodes. Because of mobile nature of nodes, routing in DTN is based on store-carry-forward patterns to forward messages. Store-carry-forward is based on appropriateness of next node to deliver the message. Improving performance of such networks depends on both routing protocol and buffer management policy when nodes have limited buffer space. However, by sending multiple messages to a node, the number of received messages may exceed the capacity of the nodes and cause a buffer overflow. In order to increase performance, we have to drop some messages and receive some new one. Dropping appropriate message is a challenging problem. Deleting an appropriate message and replacing with a message with better condition can leads to increasing delivery ratio and decreasing delivery delay. Recognizing message with better condition is another challenge. So an efficient buffer management is very important to improving routing performance. Most buffer management policies are mainly for routing protocols. In this paper, we propose a buffer management policy for RPRTD routing protocol in delay tolerant network. This approach is based on Remaining Time to encounter nodes with the Destination node of messages (RTD). This algorithm determines which of the messages should be transmitted, which of the nodes should be considered as sender and which of the messages should be dropped when the buffer is full. Simulation results show that proposed algorithm has improved the delivery ratio and delay in delivering messages compared to the state of the art.

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Section: Related Workmentioning

confidence: 99%

BMRTD: Buffer Management policy based on Remaining Time to encounter nodes with the Destination node in delay tolerant networks

Karami

Derakhshanfard

2023

Preprint

Self Cite

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“…A designated node, called a supernode, takes a packet from one cell to another towards the destination cell, 26 controlling message flooding. Relay Erlang selects an appropriate relay node, taking into account the nodes' delivery probability, buffer state, and delivery time 27 . The advantages of the flooding and forwarding approaches are integrated to implement a hybrid routing algorithm that satisfies the QOS of heterogeneous networks 28 .…”

Section: Related Workmentioning

confidence: 99%

“…Relay Erlang selects an appropriate relay node, taking into account the nodes' delivery probability, buffer state, and delivery time. 27 The advantages of the flooding and forwarding approaches are integrated to implement a hybrid routing algorithm that satisfies the QOS of heterogeneous networks. 28 Hajer et al 29 propose an energy-efficient opportunistic routing paradigm that provides a tradeoff between energy consumption and network lifetime, using static and dynamic utility factors.…”

Section: Multi-copy Based Routing Algorithmmentioning

confidence: 99%

Regular routine aware routing in opportunistic mobile social networks

Syed Rabiya,

Ramalakshmi,

Naskath

2023

Trans Emerging Tel Tech

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Due to intermittent connectivity, routing protocols in opportunistic mobile social networks (OMSN) forward messages through opportunistic contacts. Previous opportunistic routing protocols focus on the past contact history of nodes to make a forwarding decision. It was found that predicting temporally evolving contacts and communities according to different times of the day would improve the accuracy of the prediction. In this paper, a routing paradigm called RRoutine is proposed that allows message holders to exchange multiple copies of the message based on the predicted number of communities. This distribution continues until the remaining copies of the message become one. Each message holder applies either inter or intra‐community forwarding and selects a set of potential forwarders based on the prediction of future encounters in the community and an expected remaining duration between two nodes (ERIMD). The estimation of ERIMD takes into account the sequence of daily activities, the time scale of current activities, and the return time to regular meetings of the nodes. Also, unlike traditional routing, where a single forwarder is selected, a set of potential candidates is selected and prioritized according to their contact prediction, with the most likely candidate receiving the highest priority. Simulation results obtained from synthetic and real mobility data show that the proposed paper improves the performance of the system in terms of message delivery rate, throughput, and latency.

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“…It dynamically controls the sleep time and wake-up time to ensure that nodes will not miss possible communication opportunities. In order to improve the delivery rate of the spray and wait algorithm, Derakhshanfard 14 proposed an Erlang-based buffer management and routing algorithm, which considered the probability of message delivery and buffer when selecting relay nodes and allocating tokens sent to nodes status and message delivery time. Also, taking into account the difference in node forwarding capabilities, Wu et al 15 proposed a spray strategy based on social circles.…”

Section: Routing Algorithm Based On Opportunistic Forwardingmentioning

confidence: 99%

Activity-based routing algorithm in opportunistic mobile social networks

Zhang

Liu

Chen³

et al. 2021

International Journal of Distributed Sensor Networks

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In opportunistic mobile social networks, nodes are clustered according to their interests or hobbies and take part in different activities regularly. We delve into the temporal and spatial mobility characteristics of network nodes and put forward an activity-based message opportunistic forwarding algorithm. The main idea of the algorithm is that we choose different message forwarding methods according to the situation of nodes participating in activities. If the source node and the destination node are both attend in the same activities, we select the best relay node which has the biggest delivery probability. While the source node and the destination node are not in the same activities at the same time, we need to find the optimal path which owns highest indirect delivery probability, and messages will be transmitted through the optimal path. The simulation results show that the proposed routing algorithm can not only improve the successful delivery ratio of messages but also reduce the network delay and the network overhead obviously, in comparison with the classical opportunistic routing algorithms, such as community-aware message opportunistic transmission algorithm, community-based message transmission scheme algorithm, PRoPHET, Epidemic algorithm, and interest characteristic probability prediction algorithm.

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Erlang Based Buffer Management and Routing in Opportunistic Networks

Cited by 4 publications

References 15 publications

BMRTD: Buffer Management policy based on Remaining Time to encounter nodes with the Destination node in delay tolerant networks

BMRTD: Buffer Management policy based on Remaining Time to encounter nodes with the Destination node in delay tolerant networks

Regular routine aware routing in opportunistic mobile social networks

Activity-based routing algorithm in opportunistic mobile social networks

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