Energy Efficient Forwarding Algorithm in Opportunistic Networks

Zhao, Feng; Wang, Xiaoming; Jiang, Liping; Zhang, Lichen

doi:10.1049/cje.2016.08.035

Cited by 7 publications

(4 citation statements)

References 13 publications

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“…E2FA [52] 2016 Delivery predictability of nodes and buffer utility are used for choosing forwarders. CoSim [73] 2018 Cosine similarity of the data packets between nodes are used to find the similarity of the nodes which in turn are used to forward messages.…”

Section: R3 [33] 2011mentioning

confidence: 99%

Evaluating Forwarding Protocols in Opportunistic Networks: Trends, Advances, Challenges and Best Practices

et al. 2019

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A variety of applications and forwarding protocols have been proposed for opportunistic networks (OppNets) in the literature. However, the methodology of evaluation, testing and comparing these forwarding protocols are not standardized yet, which leads to large levels of ambiguity in performance evaluation studies. Performance results depend largely on the evaluation environment, and on the used parameters and models. More comparability in evaluation scenarios and methodologies would largely improve also the availability of protocols and the repeatability of studies, and thus would accelerate the development of this research topic. In this survey paper, we focus our attention on how various OppNets data forwarding protocols are evaluated rather than what they actually achieve. We explore the models, parameters and the evaluation environments and make observations about their scalability, realism and comparability. Finally, we deduce some best practices on how to achieve the largest impact of future evaluation studies of OppNets data dissemination/forwarding protocols.

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Section: R3 [33] 2011mentioning

confidence: 99%

Evaluating Forwarding Protocols in Opportunistic Networks: Trends, Advances, Challenges and Best Practices

et al. 2019

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“…Thus, the delivery ratio of the opportunistic network is reduced, and also the performance of the routing algorithm is deeply affected. Zhang et al proposed an energy‐aware congestion control (EACC) scheme for opportunistic networks to enhance energy utilization through reducing packet replacements under congestion conditions. Nodes dynamically update their residual energy level and query the residual energy level of their neighbors in current local environment and adjust their threshold ratio using the learning automata principle while moving around.…”

Section: Related Workmentioning

confidence: 99%

A controllable multi‐replica routing approach for opportunistic networks

Zhao

Wang

Lin

et al. 2017

IEEJ Transactions Elec Engng

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Opportunistic networks take full advantage of opportunistic encounters among nodes to transfer packets. According to the characteristics of the limited energy of nodes and the frequent link variation in opportunistic networks, we introduce a novel routing metric that comprehensively takes into consideration the energy consumption of nodes, the probability of relay nodes meeting their destination, the time-to-live of the packet, and the approximate number of packet copies. Based on this metric, we propose a controllable multi-replica routing approach in which a single-branch diffusion strategy is applied to achieve the goal of dynamically controlling the number of replicas of packets. Our simulation results show that the proposed approach can avoid excessive load on individual nodes, guarantee the energy fairness among nodes, prolong the network lifetime, and effectively improve the delivery ratio of packets.Correspondingly, our design focuses on two challenges: (i) how to maintain the energy fairness among nodes in an opportunistic network to prolong the network lifetime while achieving a high delivery ratio, and (ii) how to dynamically control the number of copies of packets in an opportunistic network without affecting the packet delivery ratio. Our main contributions are summarized as follows:

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“…Liu [ 4 ] achieved urban traffic monitoring in the urban area by tracking the mobile phone usage and trajectory of passengers on some platforms. These characteristics make the sparse mobile crowdsensing task distribution model based on subway transportation have a higher distribution rate and transmission quality than the traditional opportunistic network [ 5 ] distribution model.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Multi‐Task Allocation Method for Passenger Diffusion in Mobile Crowd Sensing

Jiang

Sijian

2021

Chinese J of Electronics

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This paper aims to solve the problem of low efficiency, high cost and instability in opportunistic network transmission in the process of mobile group intelligence perception task allocation. Two multi‐task dynamic distribution methods based on Lowest cost Participant selection algorithm (LC‐PSA) based on user incentive cost and Least number Participant selection algorithm (LN‐PSA) based on number of users are proposed respectively. Through these two algorithms, the goal of minimizing the number of people and moving distance required for the task and reducing the system's incentive cost is achieved. Simulation experiments show that compared with similar algorithms, the number of participants in the task distribution scheme selected by the LN‐PSA algorithm is reduced by 24.0%, and the system resource consumption is lower, which can provide stable services for the system when users are insufficient in emergencies. Compared with the traditional greedy heuristics algorithm, the LC‐PSA algorithm reduces the total system cost by 37.74% and has better overall performance in the comparison experiment.

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Energy Efficient Forwarding Algorithm in Opportunistic Networks

Cited by 7 publications

References 13 publications

Evaluating Forwarding Protocols in Opportunistic Networks: Trends, Advances, Challenges and Best Practices

Evaluating Forwarding Protocols in Opportunistic Networks: Trends, Advances, Challenges and Best Practices

A controllable multi‐replica routing approach for opportunistic networks

Dynamic Multi‐Task Allocation Method for Passenger Diffusion in Mobile Crowd Sensing

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