Mobility based call admission control and resource estimation in mobile multimedia networks using artificial neural networks

Kumar, Sanjeev; Kumar, Krishan; Kumar, Prabhat

doi:10.1109/ngct.2015.7375240

Cited by 19 publications

(5 citation statements)

References 13 publications

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“…4(b). The simulation results of NFCAC model is compared with efficient resource allocation based CAC (ERCAC) schemes as given in [39], the FL based CAC (FLCAC) policy given in [18][19], the neural network based CAC (NNCAC) as developed in [25][26] and the radial basis function-based CAC (RBFCAC) scheme in terms of cell loss ratio (CLR), channel utilization, call dropping probability (CDP) and call blocking probability (CBP) under the constraint of QoS guarantee. Fig.…”

Section: Simulation Results and Discussionmentioning

confidence: 99%

“…In [25], the author proposed mobility based CAC using an artificial neural network, in this the mobility of user is found with the previous and present user mobility history by using error back propagation model and base on the user mobility the allocation of the resource are made by queuing model. Here the neural network model trained to estimate the required bandwidth to accept voice and data calls in different QoS requirements.…”

Section: Previous Workmentioning

confidence: 99%

“…2, the output of one node is connected to the input of another node with its associated weight. Each node calculates the sum of the input weights and produces output through a predefined activation function [25].…”

Section: Neuro-fuzzy Call Admission Controller (Nfcac)mentioning

confidence: 99%

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Neuro-Fuzzy based Call Admission Control for next Generation Mobile Multimedia Networks

2019

ijeat

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As the demand of the mobile users are increasing day by day, wireless/mobile multimedia networks still need advancement in terms of, reliable traffic performance, link availability, efficient bandwidth utilization, and user mobility, that can attain extremely consistent wireless communication and data transmission over the networks. Due to the emerging demand of multimedia services a high-speed network and call admission control (CAC) scheme is required, which not only guarantees the quality of services (QoS) for new and handoff calls but also results in optimum resource utilization in bursty traffic network environments. The main objective of this integrated neural fuzzy based CAC scheme is to improve QoS with decent resource allocation, such that it minimizes the probability of call dropping and call blocking in mobile multimedia networks. The proposed neural fuzzy CAC scheme is a hybrid approach that integrates the semantic rule ability of fuzzy logic (FL) controller and self-training capability of a neural network (NN) which is further enhanced to construct an efficient computational model for traffic control and fair radio resources allocation for new calls and handoff calls. The simulation results conclude that a neural fuzzy based CAC can achieve minimal call dropping probabilities and maximum resource utilization in high-speed networks as compared to fuzzy logic based CAC and conventional CAC or existing CAC schemes

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Section: Simulation Results and Discussionmentioning

confidence: 99%

Section: Previous Workmentioning

confidence: 99%

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Neuro-Fuzzy based Call Admission Control for next Generation Mobile Multimedia Networks

2019

ijeat

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“…Point transformation occurs amid DNA replication so that there is a change inside a quality (twofold numbers) in which one base combine in the DNA grouping is adjusted. We play out this single point transformation when we get the information originating from hybrid segment [11], [12], [14].…”

Section: B Single Point Mutationmentioning

confidence: 99%

A Hybrid Soft Computing Approach on Security Algorithm of Cryptography

Sagar¹

2017

IJRASET

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Cryptography is a security mechanism to secure data from unauthorized access during the data transmission over the public channels. Ubiquitous use of internet over public channel makes easy to data retrieval from data transmission. Many algorithms are already exited as such RSA, DES, BLOWFISH and many more. In this paper we will proposed and implement an effective cryptography security method based on soft -computing techniques (neural network and Genetic). So the result is going to be additional correct then previously implemented methods. In depth experiments demonstrate that our new proposed method achieves fascinating performance on real-life events over other methods. Proposed system our main aim to find an easy and fast solution for users to send data with a more secure and trusted way over the public channels. So that their personal information not captured by any unauthorized entity. Keywords: Cryptography, Symmetric key, Asymmetric key, RSA, DES, Neural Network. I. INTRODUCTIONSecurity is a simple need in human environment in all perspective. These days the vast majority conveys over open channel and there, they transmit data that is extremely delicate and individual. So plainly security is extremely and essential worry in present time. Cryptography is a route by which we can secure our information from unapproved get to or illicit passage of obscure substance. In cryptography we utilize some numerical technique that progressions the first information so it cannot be perused without a key. The primary target of this paper is to applying the neural system in cryptography for secure information correspondence and to enhance the proficiency of cryptographic calculation. Essentially neural system used to take care of the intricate issue like: predication, self association, self learning, irregular number and so forth. The principle qualities of neural system are system structure, adaptation to non-critical failure, aggregate arrangement, learning capacity, parallel handling, and conveyed memory. Here with the utilization of neural system we propose another successful cryptographic calculation for secure information correspondence.

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“…According to [2], to offer good Quality of service (QoS), GSM network operators strive to effectively utilize their available resources and these calls for effectual network design and network planning. Call blocking probability, which defines the prospect of network services being deprived of to subscriber due to the nonavailability of radio resources, is the principal factor employed for efficient network design and network planning.…”

Section: Introductionmentioning

confidence: 99%

Multivariate Probabilistic Synthesis of Cellular Networks Teletraffic Blocking with Poissonian Distribution Arrival Rates

Nyangaresi¹,

Abeka²,

Rodrigues³

2018

IJWMT

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Cellular networks are characterized by mobility in which subscribers move freely within the coverage area. Since the radio spectrum is a scarce resource, the available bandwidth is divided by using a combination of Time-and Frequency-Division Multiple Access (TDMA) Code Division Multiple Access (CDMA) and Frequency Division Multiple Access (FDMA). For communication process to succeed, the subscriber must be allocated some frequency band (FDMA), a time slot (TDMA) or pseudorandom binary sequence that modulates the carrier (CDMA). With the increasing number of users, these resources may become unavailable, leading to new call blocking or handover call blocking. Erlang B and Erlang C have been used in the past to model teletraffic blocking in Public Switched Telephone Network (PSTN). Unfortunately, Erlang B is only ideal when subscribers do not perform call re-attempts after their initial calls are blocked. On the other hand, Erlang C model is applicable only in networks where queuing is applied and can easily lead to higher blocking rates when the number of users is high. This is because it takes into consideration the number of instances in the queue as well as the resources under use. In this paper, teletraffic blocking probabilities that take into account additional cellular network concepts such as the number of mobile stations, call retries, channels reservation, overlays and underlays, user velocity, relative mobility, call priority, call arrival rates and signal to interference plus noise ratio (SINR) were synthesized. The simulation results showed that the developed teletraffic blocking probabilities were superior to the conventional Erlang B and Erlang C as they consider new concepts that exist in cellular networks that were not envisioned in traditional PSTN.Index Terms: Blocking probability, grade of service, quality of service, teletraffic. 15 Blocking with Poissonian Distribution Arrival Rates Vincent O. Nyangaresi, Bsc (TIT), Msc (IT Sec. & Audit) is a researcher in areas of data communication and computer networks, network design and administration, distributed systems and information systems security. He is currently pursuing his PhD in Information Security and Audit. He has published numerous research articles covering areas such as communication systems, secure network communications, information systems acceptance modeling, TCP architecture and design, radio wave propagation, virtualization and cloud computing, among others. In addition, he lecturers in the fields of computer networks, digital forensics, software engineering, digital electronics and applied computer science. ). He has lectured in a number of universities and is currently a director, directorate of information and communications technology of Jaramogi Oginga Odinga University of science and technology. His research interests include scientific computation, approximation theory, modeling, informatics policy among others.

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Mobility based call admission control and resource estimation in mobile multimedia networks using artificial neural networks

Cited by 19 publications

References 13 publications

Neuro-Fuzzy based Call Admission Control for next Generation Mobile Multimedia Networks

Neuro-Fuzzy based Call Admission Control for next Generation Mobile Multimedia Networks

A Hybrid Soft Computing Approach on Security Algorithm of Cryptography

Multivariate Probabilistic Synthesis of Cellular Networks Teletraffic Blocking with Poissonian Distribution Arrival Rates

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