An AHP-Based Flexible Relay Node Selection Scheme for WBANs

Kim, Beomseok; Cho, Jinsung; Jeon, Seokhee; Liu, Ben

doi:10.1007/s11277-016-3284-y

Cited by 23 publications

(12 citation statements)

References 15 publications

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“…A number of studies have proposed new mathematical models, including optimization theory [16], game theory [17], machine learning [18] and an analytic hierarchy process (AHP) [19], to capture the user perceived QoS for enabling network performance analytics [20], [21] for network resource allocation. In order to solve the network resource allocation problem, in [22], the authors proposed a solution to the problem of assigning services with heterogeneous and noninterchangeable resource demands to the multiple network interfaces of an IoT device.…”

Section: Related Workmentioning

confidence: 99%

Resource Allocation for Ultra-Reliable and Enhanced Mobile Broadband IoT Applications in Fog Network

Abedin

Alam

Kazmi

et al. 2019

IEEE Trans. Commun.

117

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In recent years, in order to provide a better quality of service (QoS) to Internet of Things (IoT) devices, the cloud computing paradigm has shifted toward the edge. However, the resource capacity (e.g., bandwidth) in fog network technology is limited and it is essential to efficiently bind the IoT applications with stringent QoS requirements with the available network infrastructure. In this paper, we formulate a joint user association and resource allocation problem in the downlink of the fog network, considering the evergrowing demand of QoS requirements imposed by the ultra-reliable low latency communications and enhanced mobile broadband services. First, we determine the priority of different QoS requirements of heterogeneous IoT applications at the fog network by enforcing the analytical framework using an analytic hierarchy process (AHP). Using the AHP, we then formulate a two-sided matching game to initiate stable association between the fog network infrastructure (i.e., fog devices) and IoT devices. Subsequently, we consider the externalities in the matching game that occurs due to job delay and solve the network resource allocation problem by applying the "best-fit" resource allocation strategy during matching. The simulation results illustrate the stability of the user association and efficiency of resource allocation with higher utility gain.

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Section: Related Workmentioning

confidence: 99%

Resource Allocation for Ultra-Reliable and Enhanced Mobile Broadband IoT Applications in Fog Network

Abedin

Alam

Kazmi

et al. 2019

IEEE Trans. Commun.

117

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show abstract

“…Some multi-attribute decision-making methods assign equal weights (α = β) to attributes, this will lead to the ranking results being affected by human factors, which is not scientific and unreasonable. There are many methods to compute the weights, such as Analytic Hierarchy Process (AHP) method, Delphi method, principle element analysis and entropy technology [38]- [40]. Here, we choose entropy technology to calculate the weights of I D (i) and I C (i) for its excellent performance [41].…”

Section: The Proposed Centralitymentioning

confidence: 99%

A Novel Centrality of Influential Nodes Identification in Complex Networks

et al. 2020

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Influential nodes identification in complex networks is vital for understanding and controlling the propagation process in complex networks. Some existing centrality measures ignore the impacts of neighbor node. It is well-known that degree is a famous centrality measure for influential nodes identification, and the contributions of neighbors also should be taken into consideration. Furthermore, topological connections among neighbors will affect nodes' spreading ability, that is, the denser the connections among neighbors, the greater the chance of infection. In this paper, we propose a novel centrality, called DCC, to identify influential nodes by comprehensively considering degree and clustering coefficient as well as neighbors. The weights of degree and clustering coefficient are calculated by entropy technology. To verify the feasibility and effectiveness of DCC, the comparisons between DCC and other centrality measures in four aspects are conducted based on four real networks. The experimental results demonstrate that DCC is more effective in identifying influential nodes. INDEX TERMS Complex networks, influential nodes, degree centrality, neighbor node, clustering coefficient.

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“…The current techniques vary on the criteria for the selection of the relay node. For multi‐hop, Kim et al [3] used AHP MCDM techniques for a relay node selection. This system uses only three criteria and provides high communication reliability and low power consumption.…”

Section: Related Workmentioning

confidence: 99%

AHP–neutrosophic decision model for selection of relay node in wireless body area network

Bilandi¹,

Verma²,

Dhir³

2020

CAAI trans. intell. technol.

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The medical health systems empowered by wireless body area networks (WBANs) are becoming a reliable technology with unmatched facilities for personalised health monitoring and managing real‐time health issues. A WBAN is primarily composed of a miniature, and smart devices called sensors that are worn in, on, or around the human body. In recent years, research has been mainly centred towards the reduction of the energy consumption and stability of the network. The selection of the relay node is one of the foremost issues for balancing the energy consumption in WBAN. To overcome this issue, the authors propose a hybrid analytic hierarchy process–neutrosophic method for making the decision of the relay node selection, in which the analytic hierarchy process (AHP) technique calculates the weights for different criteria and forwards them to the neutrosophic technique which finds out the best alternative solution or choice which is closest to the ideal solution. A detailed analysis is carried out on multi‐criteria decision‐making techniques by comparing the proposed AHP–neutrosophic and AHP techniques taking into account various criteria and alternatives. The experimental outcomes of this research indicate a significant reduction in terms of energy consumption and enhanced overall network‐stability.

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An AHP-Based Flexible Relay Node Selection Scheme for WBANs

Cited by 23 publications

References 15 publications

Resource Allocation for Ultra-Reliable and Enhanced Mobile Broadband IoT Applications in Fog Network

Resource Allocation for Ultra-Reliable and Enhanced Mobile Broadband IoT Applications in Fog Network

A Novel Centrality of Influential Nodes Identification in Complex Networks

AHP–neutrosophic decision model for selection of relay node in wireless body area network

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