APMD: A fast data transmission protocol with reliability guarantee for pervasive sensing data communication

Liu, Yuxin; Li, Yuxuan; Li, Zhetao; Choi, Young‐June; Sekiya, Hiroo; Li, Jie

doi:10.1016/j.pmcj.2017.03.012

Cited by 38 publications

(30 citation statements)

References 23 publications

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“…In such kind of application scenarios, sensory data are valid only when they reach the sink within the specified time threshold. In particular, alarm information obtained by sensor nodes need to be delivered as soon as possible; otherwise, it will cause great damage and disaster to industrial manufacturing [4,6,24,29,32,36,[38][39][40][41]. Therefore, there are lots of research trying to reduce delay [2].…”

Section: Related Workmentioning

confidence: 99%

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Learning-based synchronous approach from forwarding nodes to reduce the delay for Industrial Internet of Things

Xiao

et al. 2018

J Wireless Com Network

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The Industrial Internet of Things (IIoTs) is creating a new world which incorporates machine learning, sensor data, and machine-to-machine (M2M) communications. In IIoTs, the length of the transmission delay is one of the pivotal performance because dilatory communication will cause heavy losses to industrial applications. In this paper, a learning-based synchronous (LS) approach from forwarding nodes is proposed to reduce the delay for IIoTs. In an asynchronous Media Access Control protocol, when senders need to send data, they always require to wait for their corresponding receiver to wake up. Thus, the delay here is greater than in the synchronous network. However, the synchronization cost of the whole network is enormous, and it is difficult to maintain. Therefore, LS mechanism uses a partial synchronization approach to reduce synchronization costs while effectively reducing delay. In LS approach, instead of synchronizing the nodes in the entire network, only sender nodes and part of the nodes in their forwarding node set are synchronized by self-learning methods, and accurate synchronization is not required here. Thus, the delay can be effectively reduced under the low cost. Secondly, the nodes near sink maintain the original duty cycle, while the nodes in the regions away from the sink use their remaining energy and perform synchronization operations, so as not to damage the network lifetime. Finally, because the synchronization in this paper is based on different synchronization periods among different nodes, it can improve the network performance by reducing the conflict between simultaneous data transmission. The theoretical analysis results show that compared with the previous approach FFSC, LS approach can reduce the end-to-end delay by 5. 13-11.64% and increase the energy efficiency by 14.29-17.53% under the same lifetime with a more balanced energy utilization.

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Section: Related Workmentioning

confidence: 99%

“…Therefore, it is important to quickly send the perceived information to the sink. So it is very important to study how to reduce the delay effectively for IIoTs, edge network, and society network as well as cloud computing [33][34][35], and there are also some related research work [4,6,24,29,32,[36][37][38].…”

Section: Introductionmentioning

confidence: 99%

Learning-based synchronous approach from forwarding nodes to reduce the delay for Industrial Internet of Things

Xiao

et al. 2018

J Wireless Com Network

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“…Conventional cloud computing system is an infrastructure as a Service (IaaS) mode. A customer can get service from a full computer infrastructure through the Internet . In this mode, services based on the Internet (such as storage and databases) are part of the IaaS.…”

Section: Related Workmentioning

confidence: 99%

Key parameters decision for cloud computing: Insights from a multiple game model

Wang

Liu

Zhang

2017

Concurrency and Computation

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Summary In service‐oriented cloud computing systems (CCSs), the aim of cloud service organizers (CSOs) is to achieve maximum profit by collecting metadata with low cost from big data reporters (BDRs) and to provide advanced services to customers at a high price. In these systems, BDRs receive payoffs by reporting metadata to CSOs and exchanging metadata with other BDRs, and customers expect to get high‐quality services at a low price. However, because the missing of a critical parameters decision model in such service‐oriented CCSs, it is difficult to measure key parameters in CCSs such as price and quality of services in the competitive market. In this paper, we propose a multiple game (MG) model to formulate the critical parameters decision process. In the MG model, there are multiple games: games among BDRs and games among CSOs under the rule of “survival of the fittest,” games between BDRs and CSOs under the rule of “the highest payoff first,” and games between customers and CSOs under the rule of “the lowest price and the highest quality of service (QoS) first.” With the proposed multiple game (MG) model, the optimal key parameters can be obtained and the Pareto‐optimal equilibrium point can be achieved. Extensive simulation results demonstrate the effectiveness and efficiency of the proposed MG model in dynamically deciding key parameters in CCSs.

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“…The typical solutions are Automatic Repeat-reQuest (ARQ) protocol and multi-path routing. 8,[12][13][14] In the ARQ, the data transmission reliability is guaranteed by retransmitting the lost data. In the multi-path routing, data packets are transmitted by multiple paths 1 to achieve reliable data transmission.…”

Section: Introductionmentioning

confidence: 99%

A fuzzy-rule-based packet reproduction routing for sensor networks

Zhang

Liu

et al. 2018

International Journal of Distributed Sensor Networks

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It is a major challenge to transfer target sensing data efficiently to sink in Internet of things. The low-efficiency data transmission can cause low quality of service. To realize the emergent detection and periodic data gathering, the sensed data should be transferred to the sink efficiently and quickly. Recently, there are many related studies. However, there are few researches taking energy efficiency, transport delay, and network reliability into comprehensive consideration. In this article, a novel adaptive green and reliable routing scheme based on a fuzzy logic system is proposed in consideration of energy efficiency, end-to-end transport delay, and network transmission reliability. The key idea of the proposed scheme is to generate different number of renewed packet copies after certain steps according to the fuzzy inference. The fuzzy inference reflects the knowledge that the nodes in the region far to the sink and with more remaining energy initiate and transmit more packet copies concurrently by multiple routing paths to ensure the success rate of data transmission, whereas less. Thus, the high energy efficiency and low latency are obtained for data collection. Our analysis and simulation results show that adaptive green and reliable routing is more superior than the existing scheme.

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APMD: A fast data transmission protocol with reliability guarantee for pervasive sensing data communication

Cited by 38 publications

References 23 publications

Learning-based synchronous approach from forwarding nodes to reduce the delay for Industrial Internet of Things

Learning-based synchronous approach from forwarding nodes to reduce the delay for Industrial Internet of Things

Key parameters decision for cloud computing: Insights from a multiple game model

A fuzzy-rule-based packet reproduction routing for sensor networks

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