Performance Modeling of Communication Networks with Markov Chains

Mo, Jeonghoon

doi:10.2200/s00269ed1v01y201004cnt005

Cited by 14 publications

(12 citation statements)

References 16 publications

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“…A discrete time energy harvesting model [ 23 ] is adopted in this scheme. We assume that RS is equipped with a battery, which has finite capacity

and is discretized into

levels.…”

Section: Analysis Of Outage Performancementioning

confidence: 99%

“…Let

represent the quantization level defined by

where

is l th energy level of the battery. Therefore, we model RS’s charging and discharging behavior by adopting a Markov chain (MC) with

states [ 23 ] and obtain further state transition probabilities.

denotes a current energy level of RS and

represents the transition probability from state

to state

.…”

Section: Analysis Of Outage Performancementioning

confidence: 99%

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Performance Analysis and Optimization of a Cooperative Transmission Protocol in NOMA-Assisted Cognitive Radio Networks with Discrete Energy Harvesting

Wang

Shi

Tang

et al. 2021

Entropy

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In this paper, we propose a spectrum-sharing protocol for a cooperative cognitive radio network based on non-orthogonal multiple access technology, where the base station (BS) transmits the superimposed signal to the primary user and secondary user with/without the assistance of a relay station (RS) by adopting the decode-and-forward technique. RS performs discrete-time energy harvesting for opportunistically cooperative transmission. If the RS harvests sufficient energy, the system performs cooperative transmission; otherwise, the system performs direct transmission. Moreover, the outage probabilities and outage capacities of both primary and secondary systems are analyzed, and the corresponding closed-form expressions are derived. In addition, one optimization problem is formulated, where our objective is to maximize the energy efficiency of the secondary system while ensuring that of the primary system exceeds or equals a threshold value. A joint optimization algorithm of power allocation at BS and RS is considered to solve the optimization problem and to realize a mutual improvement in the performance of energy efficiency for both the primary and secondary systems. The simulation results demonstrate the validity of the analysis results and prove that the proposed transmission scheme has a higher energy efficiency than the direct transmission scheme and the transmission scheme with simultaneous wireless information and power transfer technology.

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“…A discrete time energy harvesting model [ 23 ] is adopted in this scheme. We assume that RS is equipped with a battery, which has finite capacity

and is discretized into

levels.…”

Section: Analysis Of Outage Performancementioning

confidence: 99%

“…Let

represent the quantization level defined by

where

is l th energy level of the battery. Therefore, we model RS’s charging and discharging behavior by adopting a Markov chain (MC) with

states [ 23 ] and obtain further state transition probabilities.

denotes a current energy level of RS and

represents the transition probability from state

to state

.…”

Section: Analysis Of Outage Performancementioning

confidence: 99%

Performance Analysis and Optimization of a Cooperative Transmission Protocol in NOMA-Assisted Cognitive Radio Networks with Discrete Energy Harvesting

Wang

Shi

Tang

et al. 2021

Entropy

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“…As mentioned, in this paper, we review the literature that paid attention to queuing theory for modeling of cloud environments. Queuing models are classified into two categories: (1) single‐queue models, such as M/M/1, G/M/1, and M/M/k, and (2) queuing network models, such as a Jackson network and an open/closed network . Based on the literature review, some queuing models are shown in Figure .…”

Section: Background and Related Surveysmentioning

confidence: 99%

Applying queue theory for modeling of cloud computing: A systematic review

Ghomi

Rahmani

Qader

2019

Concurrency and Computation

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The cloud computing paradigm is an important service in the Internet for sharing and providing resources in a cost-efficient way. Modeling of a cloud system is not an easy task because of the complexity and large scale of such systems. Cloud reliability could be improved by modeling the various aspects of cloud systems, including scheduling, service time, wait time, and hardware and software failures. The aim of this study is to survey research studies done on the modeling of cloud computing using the queuing system in order to identify where more emphasis should be placed in both current and future research directions. This paper follows the goal by investigating the articles published between 2008 and January 2017 in journals and conferences. A systematic mapping study combined with a systematic literature review was performed to find the related literature, and 71 articles were selected as primary studies that were classified in relation to the focus, research type, and contribution type. We classified the modeling techniques of cloud computing using the queuing theory in seven categories based on their focus area: (1) performance, (2) quality of service, (3) workflow scheduling, (4) energy savings, (5) resource management, (6) priority-based servicing, and (7) reliability. A majority of the primary articles focus on performance (37%), 15% of them focus on resource management, 14% of them focus on quality of service, 13% of them focus on workflow scheduling, 13% of them focus on energy savings, 4% of them focus on priority-based servicing for requests, and 4% of them focus on reliability. This work summarizes and classifies the research efforts conducted on applying queue theory for modeling of cloud computing (AQTMCC), providing a good starting point for further research in this area. KEYWORDScloud computing, cloud modeling, queuing systems, queuing theory, systematic review INTRODUCTIONCloud computing is the recent evolution in the information technology and is growing very fast due to the extensive use of mobile devices, such as PDAs, cell phones, and tablets. 1 To emphasize the goals of cloud computing, we refer to the definition of NIST (National Institute of Standards and Technology); a cloud model is composed of five characteristics, three service models, and four deployment models. 2 Service models of cloud computing are as follows: (1) Software as a Service (SaaS), such as CRM (Customer Relationship Management), virtual desktop, communications, and games; (2) Platform as a Service (PaaS), such as databases, web servers, and deployment tools; and (3) Infrastructure as a Service (IaaS), such as virtual machines (VMs), storages, servers, and load balancers. Deployment models include private clouds, public clouds, community clouds, and hybrid clouds. The characteristics of a cloud are on-demand self-servicing, elasticity, broad network access, resource pooling, and measured service. 1 A data center in cloud computing consists of several servers that are organized in racks and connected through communicati...

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“…The following are the assumptions [9] [10] made while developing model: i. Off-Board integrators which comply with IEEE 1547 standards for charging or discharging. ii.…”

Section: Stochastic Modeling Of Evpl Occupancymentioning

confidence: 99%

Markov chain based stochastic model of electric vehicle parking lot occupancy in vehicle-to-grid

Kumar

Udaykumar

2015

2015 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC)

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The concept of connecting group of electric vehicles (EVs) to the grid for power transaction is known as Vehicle-to-Grid (V2G). The EVs can be connected to the grid through V2G integrators and charging slots. The arrival of EVs in parking lot is time varying and random in nature and facilitating them to participate in power transaction is challenging and aggregator's responsibility. In this paper, development of Markov chain based stochastic model of Electric Vehicle Parking Lot (EVPL) occupancy is proposed. A developed model is simulated using MATLAB and the results are presented.

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Performance Modeling of Communication Networks with Markov Chains

Cited by 14 publications

References 16 publications

Performance Analysis and Optimization of a Cooperative Transmission Protocol in NOMA-Assisted Cognitive Radio Networks with Discrete Energy Harvesting

Performance Analysis and Optimization of a Cooperative Transmission Protocol in NOMA-Assisted Cognitive Radio Networks with Discrete Energy Harvesting

Applying queue theory for modeling of cloud computing: A systematic review

Markov chain based stochastic model of electric vehicle parking lot occupancy in vehicle-to-grid

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