User‐optimized data transmission scheduling based on edge community service in opportunistic social network

Wang, Ziqi; Jin, Ying; Wu, Jia

doi:10.1049/cmu2.12437

Cited by 7 publications

(3 citation statements)

References 40 publications

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“…This method selects the optimal relay node for transmission based on channel coefficients. Ziqi Wang et al [30] proposed a user-optimized data transmission scheduling method based on the edge community service, called ECSUO. This method constructs an edge community service model by introducing mobile edge computing into an opportunistic social network.…”

Section: Related Workmentioning

confidence: 99%

An effective data communication community establishment scheme in opportunistic networks

Hao

Gou

2023

IET Communications

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The network transmission speed has been greatly improved, thanks to the power of 5G technology. The millisecond‐level communication delay has made a qualitative leap in communication quality. However, the sharp increase in the number of nodes connected to the internet has resulted in an explosion of traffic. Ensuring stable network transmission in the face of large data volumes has become an urgent problem to be solved. Existing research mainly optimizes for low data volumes of nodes, and cannot dynamically adapt to node transmission load to cope with explosive growth. This is because the node's cache is always at a high level, which causes community communication to be blocked. To address this issue, the authors have designed an effective data communication community establishment scheme. By adding a data information flow (DIF) attribute to each user and using the dynamic feedback adjustment (DFA) mechanism, the authors can combine the entire communication community and control the user's data information flow concentration at a relatively low level. This degree of optimization ensures that the user node maintains a relatively stable state for fast communication. The authors design an effective data communication community establishment scheme. By adding a data information flow (DIF) attribute to each user, using the dynamic feedback adjustment mechanism and combining the entire communication community, the user's data information flow concentration is controlled at a relatively low level.

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Section: Related Workmentioning

confidence: 99%

An effective data communication community establishment scheme in opportunistic networks

Hao

Gou

2023

IET Communications

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“…Use the opportunistic network environment simulator (ONE) to perform simulation tests to evaluate the performance of CMCT. Compare with the other three algorithms: ETNS (an effective transmission strategy based on node socialization) [37], ICPP (Interest Characteristic Probability Predicted Method) [38], Spray and Wait routing algorithm [39]. (1) ETNS: This algorithm is a transmission strategy based on node socialization.…”

Section: System Model Designmentioning

confidence: 99%

A user cache management and cooperative transmission mechanism based on edge community computing in opportunistic social networks

et al. 2022

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With the advent of the 5G era, people's demand for information and bandwidth is increasing. The signal source will mainly be high-frequency radio waves with high bandwidth. However, the coverage of high-frequency radio waves is very limited, which leads to the emergence of micro base stations. Opportunistic social networks are just suitable for this new transmission method, it is easy for users to simultaneously request content with high popularity in a short time, which will cause a heavy load on the micro base station and a high transmission delay. This paper establishes the community mechanism and proposes a user cache management and cooperative transmission mechanism (CMCT) based on edge community computing by using the predictability of users' requests for popular content. The free user equipment space is used to manage cache distribution through the edge community computing to perform cooperative transmission, thereby reducing the content delivery delay and the load of the micro base station. Simulation experiments show that the CMCT algorithm can reduce end-to-end delay and overhead, and improve data transmission efficiency.

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“…Of the vast quantity of data, frequently less than 20 of them are considered usable [ 19 ]. The rest of the redundant images not only slow down the progress of judgment, but also sometimes mislead doctors to a certain extent [ 20 ]. In addition, considering that the diagnosis of MRI images is highly subjective and mostly depends on the experience and professional knowledge of doctors, the lack of talents in this field is also a major reason for the low efficiency of diagnoses [ 21 ].…”

Section: Introductionmentioning

confidence: 99%

AI-Assisted Diagnosis and Decision-Making Method in Developing Countries for Osteosarcoma

Tang

Huang

et al. 2022

Healthcare

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Osteosarcoma is a malignant tumor derived from primitive osteogenic mesenchymal cells, which is extremely harmful to the human body and has a high mortality rate. Early diagnosis and treatment of this disease is necessary to improve the survival rate of patients, and MRI is an effective tool for detecting osteosarcoma. However, due to the complex structure and variable location of osteosarcoma, cancer cells are highly heterogeneous and prone to aggregation and overlap, making it easy for doctors to inaccurately predict the area of the lesion. In addition, in developing countries lacking professional medical systems, doctors need to examine mass of osteosarcoma MRI images of patients, which is time-consuming and inefficient, and may result in misjudgment and omission. For the sake of reducing labor cost and improve detection efficiency, this paper proposes an Attention Condenser-based MRI image segmentation system for osteosarcoma (OMSAS), which can help physicians quickly locate the lesion area and achieve accurate segmentation of the osteosarcoma tumor region. Using the idea of AttendSeg, we constructed an Attention Condenser-based residual structure network (ACRNet), which greatly reduces the complexity of the structure and enables smaller hardware requirements while ensuring the accuracy of image segmentation. The model was tested on more than 4000 samples from two hospitals in China. The experimental results demonstrate that our model has higher efficiency, higher accuracy and lighter structure for osteosarcoma MRI image segmentation compared to other existing models.

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User‐optimized data transmission scheduling based on edge community service in opportunistic social network

Cited by 7 publications

References 40 publications

An effective data communication community establishment scheme in opportunistic networks

An effective data communication community establishment scheme in opportunistic networks

A user cache management and cooperative transmission mechanism based on edge community computing in opportunistic social networks

AI-Assisted Diagnosis and Decision-Making Method in Developing Countries for Osteosarcoma

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