Modeling Radio Resource Allocation Scheme with Fixed Transmission Zones for Multiservice M2M Communications in Wireless IoT Infrastructure

Shorgin, Sergey; Samouylov, Konstantin; Gaidamaka, Yuliya; Chukarin, A.; Buturlin, Ivan A.; Begishev, Vyacheslav

doi:10.1007/978-3-319-15705-4_46

Cited by 5 publications

(3 citation statements)

References 13 publications

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“…The D2D users get the resources according to the wireless network channel gain, which balances the system workload and enhances the system performance. An analytical model for heterogeneous traffic of M2M devices has been proposed in [48], that used fixed transmission nodes for M2M devices according to the user's requirements to achieve QoS constraints. An optimization protocol has been proposed in [19], which is based on the consensus algorithm for robust and efficient resource allocation in the heterogeneous IoT networks.…”

Section: Qos-aware Iot Resource Allocationmentioning

confidence: 99%

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Resource Management Techniques for Cloud-Based IoT Environment

Ali

Ansari

Alam

2020

Internet of Things (IoT)

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Internet of Things (IoT) is an Internet-based environment of connected devices and applications. IoT creates an environment where physical de-vices and sensors are flawlessly combined into information nodes to deliver innovative and smart services for human-being to make their life easier and more efficient. The main objective of the IoT devices-network is to generate data, which are converted into useful information by the data analysis process, it also provides useful resources to the end-users. IoT resource management is a key challenge to ensure the quality of end-user's experience. Many IoT smart devices and technologies like sensors, actuators, RFID, UMTS, 3G, and GSM etc. are used to develop IoT networks. Cloud Computing plays an important role in these net-works deployment by providing physical resources as virtualized resources consist of memory, computation power, network bandwidth, virtualized system and device drivers in secure and pay as per use basis. One of the major concerns of Cloud-based IoT environment is resource management, which ensures efficient resource utilization, load balancing, reduce SLA violation, and improve the system performance by reducing operational cost and energy consumption. Many researchers have been proposed IoT based resource management techniques. The focus of this paper is to investigate these proposed resource allocation techniques and finds which parameters must be considered for improvement in resource allocation for IoT networks. Further, this paper also uncovered challenges and issues of Cloud-based resource allocation for IoT environment.

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Section: Qos-aware Iot Resource Allocationmentioning

confidence: 99%

“…QoS-based resource allocation methods with features and limitations are described in Table 4. The intrusion among the communication channel has been reduced and enhanced the system performance Practical implementation is missing Radio Resource Allocation scheme [48] The traffic among the M2M devices has been reduced…”

Section: Qos-aware Iot Resource Allocationmentioning

confidence: 99%

Resource Management Techniques for Cloud-Based IoT Environment

Ali

Ansari

Alam

2020

Internet of Things (IoT)

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“…In the case of high network traffic access delay increases significantly, and this can be critical in various emergency situations [7]. Some other features of M2 M traffic transmission were considered in [10][11][12][13][14][15][16][17][18][19] taking into account problems of optimal radio resources allocation [11][12][13][14][15], overload control mechanisms based on Access Class Barring (ACB) schemes [10,14] and other congestion control problems [16,17].…”

Section: Introductionmentioning

confidence: 99%

Baseline Analytical Model for Machine-Type Communications Over 3GPP RACH in LTE-Advanced Networks

Samouylov

Gaidamaka

Gudkova

et al. 2016

Communications in Computer and Information Science

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Machine-type communication (MTC) is a new service defined by the 3rd Generation Partnership Project (3GPP) to provide machines to interact to each other over future wireless networks. One of the main problems in LTE-advanced networks is the distribution of a limited number of radio resources among enormously increasing number of MTC devices with different traffic characteristics. The radio resources allocation scheme for MTC traffic transmission in LTE networks is also standardized by 3GPP and implements the Random Access Channel (RACH) mechanism for transmitting data units from a plurality of MTC devices. Until now, there is a number of problems with the congestion in radio access network, as evidenced by a series of articles calling attention to the fact that more research is required, and even modification of the RACH mechanism in order to address drawbacks, exhibiting for example when a large number of devices are trying to access simultaneously. However, not many results have been obtained for the analysis, which allows to explore a variety of performance metrics of RACH mechanism on a qualitative level. In this paper the mathematical model in a form of the discrete Markov chain is built taking into account the features of the access procedure under congestion conditions and collisions. This baseline model allows to obtain the solution for key performance measures of RACH mechanism, such as the access success probability and the average access delay, in an analytical closed-form. Based on the proposed baseline model it is possible to obtain new results for the analysis of some modifications of RACH mechanism such as ACB (Access Class Baring).

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Efficient Algorithm for Evaluating the Required Volume of Resource in Wireless Communication Systems under Joint Servicing of Heterogeneous Traffic for the Internet of Things

Stepanov

2019

Autom Remote Control

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Modeling Radio Resource Allocation Scheme with Fixed Transmission Zones for Multiservice M2M Communications in Wireless IoT Infrastructure

Cited by 5 publications

References 13 publications

Resource Management Techniques for Cloud-Based IoT Environment

Resource Management Techniques for Cloud-Based IoT Environment

Baseline Analytical Model for Machine-Type Communications Over 3GPP RACH in LTE-Advanced Networks

Efficient Algorithm for Evaluating the Required Volume of Resource in Wireless Communication Systems under Joint Servicing of Heterogeneous Traffic for the Internet of Things

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