scholarly journals Modeling of Wireless Traffic Load in Next Generation Wireless Networks

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Sohaib Manzoor ◽  
Khalid Bashir Bajwa ◽  
Muhammad Sajid ◽  
Hira Manzoor ◽  
Mahak Manzoor ◽  
...  
Keyword(s):  
Markov Chain Model ◽  
Search Tree ◽  
Base Stations ◽  
Traffic Load ◽  
Binary Search Tree ◽  
Chain Model ◽  
New Paradigm ◽  
Wifi Networks ◽  
Whale Optimization ◽  
Handover Mechanism

Software defined WiFi network (SD-WiFi) is a new paradigm that addresses issues such as mobility management, load management, route policies, link discovery, and access selection in traditional WiFi networks. Due to the rapid growth of wireless devices, uneven load distribution among the network resources still remains a challenging issue in SD-WiFi. In this paper, we design a novel four-tier software defined WiFi edge architecture (FT-SDWE) to manage load imbalance through an improved handover mechanism, enhanced authentication technique, and upgraded migration approach. In the first tier, the handover mechanism is improved by using a simple AND operator and by shifting the association control to WAPs. Unauthorized user load is mitigated in the second tier, with the help of base stations (BSs) which act as edge nodes (ENs), using elliptic ElGamal digital signature algorithm (EEDSA). In the third tier, the load is balanced in the data plane among the OpenFlow enabled switches by using the whale optimization algorithm (WOA). Moreover, the load in the fourth tier is balanced among the multiple controllers. The global controller (GC) predicts the load states of local controllers (LCs) from the Markov chain model (MCM) and allocates packets to LCs for processing through a binary search tree (BST). The performance evaluation of FT-SDWE is demonstrated using extensive OMNeT++ simulations. The proposed framework shows effectiveness in terms of bandwidth, jitter, response time, throughput, and migration time in comparison to SD-WiFi, EASM, GAME-SM, and load information strategy schemes.

scholarly journals Analytical Models and Performance Evaluation of Vehicular-to-Infrastructure Networks With Optimal Retransmission Number

2021 ◽  
Author(s):  
Aytül Bozkurt
Keyword(s):  
Vehicular Networks ◽  
Markov Chain Model ◽  
Arrival Rate ◽  
High Rate ◽  
Traffic Load ◽  
Analytical Models ◽  
Traffic Model ◽  
Chain Model ◽  
Queuing Model ◽  
The Impact

Abstract Vehicle-to-infrastructure and vehicle-to-vehicle communications has been introduced to provide high rate Internet connectivity to vehicles to meet the ubiquitous coverage and increasing high-data rate internet and multimedia demands by utilizing the 802.11 access points (APs). In order to evaluate the performance of vehicular networks over WLAN, in this paper, we investigate the transmisison and network performance of vehicles that pass through AP by considering contention nature of vehicles over 802.11 WLANs. Firstly, we derived an analytical traffic model to obtain the number of vehicles under transmision range of an AP. Then, incorporating vehicle traffic model with Markov chain model and for arrival packets, M/G/1/K queuing system, we developed a model evaluating the performance of DCF mechanism with an optimal retransmission number. We also derived the probability of mean arrival rate l to AP. A distinctive aspect of our proposed model is that it incorporates both vehicular traffic model and backoff procedure with M/G/1/K queuing model to investigate the impact of various traffic load conditions and system parameters on the vehicular network system. Based on our model, we show that the delay and througput performance of the system reduces with the increasing vehicle velocity due to optimal retransmision number m, which is adaptively adjusted in the network with vehicle mobility.

scholarly journals A QoS-aware Scheduling with Node Grouping for IEEE 802.11ah

2021 ◽  
Author(s):  
Nurzaman Ahmed ◽  
Iftekhar Hussain
Keyword(s):  
Large Scale ◽  
Network Reliability ◽  
Markov Chain Model ◽  
Traffic Load ◽  
Chain Model ◽  
Medium Access ◽  
Traffic Scheduling ◽  
Scheduling Scheme ◽  
Ieee 802.11Ah ◽  
Critical Traffic

Abstract The recent IEEE 802.11ah amendment has proven to be suitable for supporting large-scale devices in Internet of Things (IoT). It is essential to provide a minimum level of Quality of Service (QoS) for critical applications such as industrial automaton and healthcare. In this paper, we propose a QoSaware Medium Access Control (MAC) layer solution to enhance network reliability and reduce critical traffic latency by an adaptive station grouping and a priority traffic scheduling scheme. The proposed grouping scheme calculates the current traffic load and distributes among different RAW groups considering different requirements of the stations. The RAW scheduling scheme further provides priority slot access using a novel backoff scheme. Markov-chain model is developed to study the throughput and latency behaviours for the traffic generated from the critical application. The proposed protocol shows significant delay improvement for priority traffic. The overall throughput performance improves up to 12.7% over the existing RAW grouping scheme.

Type II Sleep Mode Operation for IEEE 802.16e Based WiMAX

2011 ◽  
Vol 128-129 ◽  
pp. 343-349
Author(s):  
Jian Bin Xue ◽  
Song Bai Li ◽  
Ting Zhang ◽  
Wen Hua Wang
Keyword(s):  
Energy Efficiency ◽  
Energy Saving ◽  
Markov Chain Model ◽  
Broad Band ◽  
Traffic Load ◽  
Sleep Mode ◽  
Chain Model ◽  
Ieee 802.16E ◽  
Mode Operation ◽  
Set Up

To overcome the flaw of energy efficiency drop in broad band wireless communication with the short time sleep, the energy-saving mechanism of the sleep mode operation was researched in IEEE 802.16e. In this paper we propose a dynamic algorithm to tune the ratio of the sleep windows and receive windows according to the traffic load. Then, a Markov chain model was set up to analyze the energy efficiency and mean access delay. NS2 simulation results show that the proposed algorithm can achieve marked gain in energy efficiency compared to the traditional energy saving mechanism.

An Efficient Markov Chain Model for the Simulation of Heterogeneous Soil Structure

2004 ◽  
Vol 68 (2) ◽  
pp. 346 ◽  
Author(s):  
Keijan Wu ◽  
Naoise Nunan ◽  
John W. Crawford ◽  
Iain M. Young ◽  
Karl Ritz
Keyword(s):  
Markov Chain ◽  
Soil Structure ◽  
Markov Chain Model ◽  
Chain Model ◽  
Heterogeneous Soil

Data Mining Technique Applied To DNA Sequencing

2015 ◽  
Vol 2 (7) ◽  
pp. 18
Author(s):  
R. Jamuna
Keyword(s):  
Data Mining ◽  
Dna Methylation ◽  
Markov Chain ◽  
Human Genome ◽  
Transition Probabilities ◽  
Markov Chain Model ◽  
Effective Means ◽  
Cpg Islands ◽  
Chain Model ◽  
The Given

CpG islands (CGIs) play a vital role in genome analysis as genomic markers.  Identification of the CpG pair has contributed not only to the prediction of promoters but also to the understanding of the epigenetic causes of cancer. In the human genome [1] wherever the dinucleotides CG occurs the C nucleotide (cytosine) undergoes chemical modifications. There is a relatively high probability of this modification that mutates C into a T. For biologically important reasons the mutation modification process is suppressed in short stretches of the genome, such as ‘start’ regions. In these regions [2] predominant CpG dinucleotides are found than elsewhere. Such regions are called CpG islands. DNA methylation is an effective means by which gene expression is silenced. In normal cells, DNA methylation functions to prevent the expression of imprinted and inactive X chromosome genes. In cancerous cells, DNA methylation inactivates tumor-suppressor genes, as well as DNA repair genes, can disrupt cell-cycle regulation. The most current methods for identifying CGIs suffered from various limitations and involved a lot of human interventions. This paper gives an easy searching technique with data mining of Markov Chain in genes. Markov chain model has been applied to study the probability of occurrence of C-G pair in the given   gene sequence. Maximum Likelihood estimators for the transition probabilities for each model and analgously for the  model has been developed and log odds ratio that is calculated estimates the presence or absence of CpG is lands in the given gene which brings in many  facts for the cancer detection in human genome.

Requirements Prioritization Techniques for Global Software Engineering

2017 ◽  
Vol 6 (1) ◽  
Author(s):  
Samina Saghir ◽  
Tasleem Mustafa
Keyword(s):  
Software Engineering ◽  
Requirements Engineering ◽  
Search Tree ◽  
Software Requirements ◽  
Binary Search Tree ◽  
Time Zone ◽  
Analytic Hierarchy ◽  
Requirements Prioritization ◽  
Global Software Engineering ◽  
Hierarchy Process

<p>Increase in globalization of the industry of software requires an exploration of requirements engineering (RE) in software development institutes at multiple locations. Requirements engineering task is very complicated when it is performed at single site, but it becomes too much complex when stakeholder groups define well-designed requirements under language, time zone and cultural limits. Requirements prioritization (RP) is considered as an imperative part of software requirements engineering in which requirements are ranked to develop best-quality software. In this research, a comparative study of the requirements prioritization techniques was done to overcome the challenges initiated by the corporal distribution of stakeholders within the organization at multiple locations. The objective of this study was to make a comparison between five techniques for prioritizing software requirements and to discuss the results for global software engineering. The selected techniques were Analytic Hierarchy Process (AHP), Cumulative Voting (CV), Value Oriented Prioritization (VOP), Binary Search Tree (BST), and Numerical Assignment Technique (NAT). At the end of the research a framework for Global Software Engineering (GSE) was proposed to prioritize the requirements for stakeholders at distributed locations.<strong></strong></p>

scholarly journals Bloom Filter-Based Parallel Architecture for Accelerating Equi-Join Operation on FPGA

Electronics ◽  
2021 ◽  
Vol 10 (15) ◽  
pp. 1778
Author(s):  
Binhao He ◽  
Meiting Xue ◽  
Shubiao Liu ◽  
Wei Luo
Keyword(s):  
Relational Databases ◽  
Parallel Architecture ◽  
Operation Time ◽  
Bloom Filter ◽  
Search Tree ◽  
Binary Search Tree ◽  
Maximum Acceleration ◽  
Data Intensive ◽  
Match Rate ◽  
Field Programmable

As one of the most important operations in relational databases, the join is data-intensive and time-consuming. Thus, offloading this operation using field-programmable gate arrays (FPGAs) has attracted much interest and has been broadly researched in recent years. However, the available SRAM-based join architectures are often resource-intensive, power-consuming, or low-throughput. Besides, a lower match rate does not lead to a shorter operation time. To address these issues, a Bloom filter (BF)-based parallel join architecture is presented in this paper. This architecture first leverages the BF to discard the tuples that are not in the join result and classifies the remaining tuples into different channels. Second, a binary search tree is used to reduce the number of comparisons. The proposed method was implemented on a Xilinx FPGA, and the experimental results show that under a match rate of 50%, our architecture achieved a high join throughput of 145.8 million tuples per second and a maximum acceleration factor of 2.3 compared to the existing SRAM-based join architectures.

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