A Future Network Architecture for Resource Sharing and Service Diversity

2010 ◽  
Author(s):  
Rui Li ◽  
Jianya Chen ◽  
Yunjie Liu ◽  
Tao Huang
Keyword(s):  
Resource Sharing ◽  
Network Architecture

scholarly journals A Game for Energy-Aware Allocation of Virtualized Network Functions

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Roberto Bruschi ◽  
Alessandro Carrega ◽  
Franco Davoli
Keyword(s):  
Resource Sharing ◽  
Network Architecture ◽  
Building Blocks ◽  
Energy Aware ◽  
Network Nodes ◽  
Physical Network ◽  
Network Flexibility ◽  
Unique Nash Equilibrium ◽  
Network Functions ◽  
Network Functionality

Network Functions Virtualization (NFV) is a network architecture concept where network functionality is virtualized and separated into multiple building blocks that may connect or be chained together to implement the required services. The main advantages consist of an increase in network flexibility and scalability. Indeed, each part of the service chain can be allocated and reallocated at runtime depending on demand. In this paper, we present and evaluate an energy-aware Game-Theory-based solution for resource allocation of Virtualized Network Functions (VNFs) within NFV environments. We consider each VNF as a player of the problem that competes for the physical network node capacity pool, seeking the minimization of individual cost functions. The physical network nodes dynamically adjust their processing capacity according to the incoming workload, by means of an Adaptive Rate (AR) strategy that aims at minimizing the product of energy consumption and processing delay. On the basis of the result of the nodes’ AR strategy, the VNFs’ resource sharing costs assume a polynomial form in the workflows, which admits a unique Nash Equilibrium (NE). We examine the effect of different (unconstrained and constrained) forms of the nodes’ optimization problem on the equilibrium and compare the power consumption and delay achieved with energy-aware and non-energy-aware strategy profiles.

scholarly journals A Survey of Search Algorithms for Peer-to-Peer File Sharing Applications in Mobile Computing Infrastructure

2021 ◽  
Author(s):  
Ajay Arunachalam ◽  
vinayakumar R
Keyword(s):  
Resource Sharing ◽  
Network Architecture ◽  
Mobile Ad Hoc Network ◽  
Distributed Storage ◽  
File Sharing ◽  
Resource Discovery ◽  
Peer To Peer ◽  
Future Research ◽  
File Transfer ◽  
Content Sharing

Peer-to-Peer (P2P) Networking have a lot of practical applicability’s over the years. File storage and resource sharing are few key areas among the others where such peered network architecture is widely successful. The common building block for P2P networking is to store or locate an identifiable resource, for which there are basically 3 approaches namely (1) local storage/broadcast search (2) global storage/local search (3) distributed storage/distributed search. With the development of mobile hardware and wireless technology, it further became feasible to use mobile devices in these P2P networks. This computing architecture is widely used in Mobile Ad-hoc Network (MANET) for building content sharing applications. Search algorithm and file transfer schemes are the basic components of such content sharing systems. In this article, we provide a brief overview of the resource discovery approaches for peer-to-peer file sharing applications over MANET. We analyze and classify the search techniques into 4 broad schemes, mainly the flooding-based schemes, Distributed Hash Table (DHT) based schemes, advertisement-based schemes, and social network-based schemes. The pros and cons of each technique is summarized. Further, a one-to-one comparison is done across the classes for quick interpretation. We also outline the various issues, and complications that should be taken into consideration while designing any resource discovery algorithm. Further, we briefly discuss the security threats, and present state-of-the-art countermeasures for it. Also, we highlight some important guidelines that need to be focused while designing efficient file sharing applications and services in Mobile Edge Computing (MEC) enabled networks. Comprehensive and in-depth assessments of the related approaches are presented providing clear insights for the future research directions.

scholarly journals A Survey of Search Algorithms for Peer-to-Peer File Sharing Applications in Mobile Computing Infrastructure

2021 ◽  
Author(s):  
Ajay Arunachalam ◽  
vinayakumar R
Keyword(s):  
Resource Sharing ◽  
Network Architecture ◽  
Mobile Ad Hoc Network ◽  
Distributed Storage ◽  
File Sharing ◽  
Resource Discovery ◽  
Peer To Peer ◽  
Future Research ◽  
File Transfer ◽  
Content Sharing

Peer-to-Peer (P2P) Networking have a lot of practical applicability’s over the years. File storage and resource sharing are few key areas among the others where such peered network architecture is widely successful. The common building block for P2P networking is to store or locate an identifiable resource, for which there are basically 3 approaches namely (1) local storage/broadcast search (2) global storage/local search (3) distributed storage/distributed search. With the development of mobile hardware and wireless technology, it further became feasible to use mobile devices in these P2P networks. This computing architecture is widely used in Mobile Ad-hoc Network (MANET) for building content sharing applications. Search algorithm and file transfer schemes are the basic components of such content sharing systems. In this article, we provide a brief overview of the resource discovery approaches for peer-to-peer file sharing applications over MANET. We analyze and classify the search techniques into 4 broad schemes, mainly the flooding-based schemes, Distributed Hash Table (DHT) based schemes, advertisement-based schemes, and social network-based schemes. The pros and cons of each technique is summarized. Further, a one-to-one comparison is done across the classes for quick interpretation. We also outline the various issues, and complications that should be taken into consideration while designing any resource discovery algorithm. Further, we briefly discuss the security threats, and present state-of-the-art countermeasures for it. Also, we highlight some important guidelines that need to be focused while designing efficient file sharing applications and services in Mobile Edge Computing (MEC) enabled networks. Comprehensive and in-depth assessments of the related approaches are presented providing clear insights for the future research directions.

scholarly journals Distributed Optimization for Mobile Robots under Mobile Edge Computing Environment

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Hui Luo ◽  
Quan Yin
Keyword(s):  
Mobile Robots ◽  
Resource Sharing ◽  
Network Architecture ◽  
Distributed Optimization ◽  
Optimization Technique ◽  
Infinite Horizon ◽  
Base Station ◽  
Edge Computing ◽  
Mobile Edge Computing ◽  
Reliable Communication

Driven by the development of the Internet industry, mobile robots (MRs) technology has become increasingly mature and widely used in all walks of life. Since MRs are densely distributed in the network system, how to establish a reliable communication architecture to achieve good cooperation and resource sharing between MRs has become a research hotspot. In this respect, mobile edge computing (MEC) technology and millimeter wave (mmW) technology can provide powerful support. This paper proposes a mmW communication network architecture for distributed MRs in MEC environment. The mmW base station provides reliable communication services for MRs under the coverage of information cloud (IC). We design a joint resource and power allocation strategy aimed at minimizing network energy consumption. First, we use the Lyapunov optimization technique to transform the original infinite horizon Markov decision process (MDP) problem. Then, a semidistributed algorithm is introduced to solve the distributed optimization problem in the mmW network. By improving the autonomous decision-making ability of the mmW base station, the signaling overheads caused by information interaction are reduced, and information leakage is effectively avoided. Finally, the global optimal solution is obtained. Simulation results demonstrate the superiority of the proposed strategy.

Forgetting within the time-based resource-sharing model

2006 ◽  
Author(s):  
Valerie Camos ◽  
Pierre Barrouillet
Keyword(s):  
Resource Sharing

SCORING MODELING BASED ON NEURAL NETWORKS FOR DETERMINING A BANK BORROWER'S RATING

2020 ◽  
Vol 2020 (10) ◽  
pp. 54-62
Author(s):  
Oleksii VASYLIEV ◽  
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Network Architecture ◽  
Statistical Data ◽  
Activation Function ◽  
Decision Making Process ◽  
Neural Network Architecture ◽  
Acceptable Accuracy ◽  
The Neural Network ◽  
Sigmoid Activation Function

The problem of applying neural networks to calculate ratings used in banking in the decision-making process on granting or not granting loans to borrowers is considered. The task is to determine the rating function of the borrower based on a set of statistical data on the effectiveness of loans provided by the bank. When constructing a regression model to calculate the rating function, it is necessary to know its general form. If so, the task is to calculate the parameters that are included in the expression for the rating function. In contrast to this approach, in the case of using neural networks, there is no need to specify the general form for the rating function. Instead, certain neural network architecture is chosen and parameters are calculated for it on the basis of statistical data. Importantly, the same neural network architecture can be used to process different sets of statistical data. The disadvantages of using neural networks include the need to calculate a large number of parameters. There is also no universal algorithm that would determine the optimal neural network architecture. As an example of the use of neural networks to determine the borrower's rating, a model system is considered, in which the borrower's rating is determined by a known non-analytical rating function. A neural network with two inner layers, which contain, respectively, three and two neurons and have a sigmoid activation function, is used for modeling. It is shown that the use of the neural network allows restoring the borrower's rating function with quite acceptable accuracy.

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