Social-Aware Computing based Congestion Control in Delay Tolerant Networks

Liu, Yan; Wang, Kun; Guo, Hang; Lü, Qing; Sun, Yuqing

doi:10.1007/s11036-016-0759-8

Cited by 12 publications

(5 citation statements)

References 32 publications

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“…However, despite this exciting idea, its applicability is reduced to scenarios with nodes that produce data with high correlation. A socially aware congestion control algorithm (SACC) addresses the congestion problem using the perspective of socially aware computing for delay-tolerant networks (DTN) [ 25 ]. SACC uses the social features of a network and the congestion level of a node to build a social congestion metric (SCM) using a novel message-dropping mechanism.…”

Section: Related Workmentioning

confidence: 99%

Prioritization-Driven Congestion Control in Networks for the Internet of Medical Things: A Cross-Layer Proposal

Buenrostro-Mariscal

Santana-Mancilla

Montesinos‐López

et al. 2023

Sensors

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Real-life implementation of the Internet of Things (IoT) in healthcare requires sufficient quality of service (QoS) to transmit the collected data successfully. However, unsolved challenges in prioritization and congestion issues limit the functionality of IoT networks by increasing the likelihood of packet loss, latency, and high-power consumption in healthcare systems. This study proposes a priority-based cross-layer congestion control protocol called QCCP, which is managed by communication devices’ transport and medium access control (MAC) layers. Unlike existing methods, the novelty of QCCP is how it estimates and resolves wireless channel congestion because it does not generate control packets, operates in a distributed manner, and only has a one-bit overhead. Furthermore, at the same time, QCCP offers packet scheduling considering each packet’s network load and QoS. The results of the experiments demonstrated that with a 95% confidence level, QCCP achieves sufficient performance to support the QoS requirements for the transmission of health signals. Finally, the comparison study shows that QCCP outperforms other TCP protocols, with 64.31% higher throughput, 18.66% less packet loss, and 47.87% less latency.

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Section: Related Workmentioning

confidence: 99%

Prioritization-Driven Congestion Control in Networks for the Internet of Medical Things: A Cross-Layer Proposal

Buenrostro-Mariscal

Santana-Mancilla

Montesinos‐López

et al. 2023

Sensors

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“…To address the issue of congestion due to limited resources, the authors in Reference 27, presented an improved socially aware congestion control algorithm (SACC) where the node's congestion level and social features are used for construction. Social congestion metric (SCM) is sued for performing the forwarding process, where nodes having higher SCM values which are considered for forwarding messages.…”

Section: Related Workmentioning

confidence: 99%

Congestion aware reward based scheme based on delay tolerant networks for emergency evacuation in 6G‐based internet of things networks

Awan

Tariq

Qureshi

et al. 2023

Trans Emerging Tel Tech

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Internet of Things (IoT) networks are based on advanced augmented reality‐based applications for better services. These advanced networks are always at threat due to different disasters in an urban congested environment. Delay tolerant networks is one of the well‐known solutions with various features. However, due to heavy data traffic, it suffered from congestion and selfish behavior issues. The existing solutions endeavored to mitigate selfishness and enforce nodes to cooperate which leads to congestion. The information concerning other nodes in the network is needed and to be maintained, stored, and shared. In this article, the issue of the occurrence of congestion while mitigating the selfish behavior of nodes is taken into account, especially for augmented reality (AR) and 6 G‐based IoT networks. This article proposes a credit‐based congestion aware reward‐based scheme for enforcing nodes to cooperate to refrain from selfishness. The load‐sharing technique handles the congestion in 6G/AR‐based IoT networks where the messages are shifted to low or non‐congested nodes rather than dropping them. Simulation results affirm the efficacy of the proposed scheme in terms of data delivery ratio, network overhead, energy consumption, and latency and outperform compare to the state‐of‐the‐art schemes.

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“…Based on this assumption, Johari et al [18] developed a novel approach to address the issues of delay in DTN communication, this approach is called as Licklider transmission protocol convergence layer (LTPCL) which is developed with the help of several meta-heuristic approaches such as genetic algorithm and ant colony optimization along with the shortest path routing scheme. Liu et al [20] focused on the delay and congestion problems in the delay tolerant networking. In order to focus on this issue, an improved Socially Aware Congestion Control algorithm (SACC) approach is developed where a social congestion metric is formulated based on the social features and congestion level.…”

Section: Literature Reviewmentioning

confidence: 99%

Relay Selection Trust Management (RSTM) model for Delay Tolerant Networks

S¹

2019

IJATCSE

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Increased demand for wireless communication required efficient quality of communication. Nowadays, wireless communication ns where end-to-end connectivity from source to destination is a crucial task such as interplanetary networks, vehicular networks, underwater networks, etc…In order to address these issues, DTN (Delay Tolerant Networks) have been introduced which helps to enable the end-to-end connectivity between source and destination by using a store-and-forward mechanism. However, the connectivity and performance of conventional DTNs suffer from the issue of unreliable environments, high dynamics of nodes and power consumption. Moreover, security is also considered a challenging task in these networks. Thus, in this work we focus of these issues of DTN and introduce a novel hybrid approach which provides an efficient solution for relay selection, buffer and, trust management scheme, this scheme is called as Relay Selection Trust Management (RSTM) model for Delay Tolerant Networks. The performance of the proposed approach is compared with the existing techniques such as Epidemic routing, Game theory, and spray & waits approaches. The experimental results show that the performance of the proposed approach RSTM achieves better performance in terms of packet delivery, delay, communication.

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Social-Aware Computing based Congestion Control in Delay Tolerant Networks

Cited by 12 publications

References 32 publications

Prioritization-Driven Congestion Control in Networks for the Internet of Medical Things: A Cross-Layer Proposal

Prioritization-Driven Congestion Control in Networks for the Internet of Medical Things: A Cross-Layer Proposal

Congestion aware reward based scheme based on delay tolerant networks for emergency evacuation in 6G‐based internet of things networks

Relay Selection Trust Management (RSTM) model for Delay Tolerant Networks

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