scholarly journals Routing in Networks using Genetic Algorithm

2017 ◽  
Vol 6 (1) ◽  
pp. 88-98
Author(s):  
Meenakshi Moza ◽  
Suresh Kumar

With the increase in traffic, internet service providers are trying their best to provide maximum utilization of resources available. The current traffic load has to be taken into account for computation of paths in routing protocols. Network applications; require the shortest paths to be used for communication purposes. Addressing the selection of path, from a known source to destination is the basic aim of this paper. This paper proposes a method of calculating the shortest path for a network using a combination of Open shortest path first and Genetic Algorithm (OSGA). Genetic Algorithm is used in this paper for optimization of routing. It helps in enhancing the performance of the routers.

Author(s):  
Amandeep Kaur Sandhu ◽  
Jyoteesh Malhotra

This article describes how a rapid increase in usage of internet has emerged from last few years. This high usage of internet has occurred due to increase in popularity of multimedia applications. However, there is no guarantee of Quality of Service to the users. To fulfill the desired requirements, Internet Service Providers (ISPs) establish a service level agreement (SLA) with clients including specific parameters like bandwidth, reliability, cost, power consumption, etc. ISPs make maximum SLAs and decrease energy consumption to raise their profit. As a result, users do not get the desired services for which they pay. Virtual Software Defined Networks are flexible and manageable networks which can be used to achieve these goals. This article presents shortest path algorithm which improves the matrices like energy consumption, bandwidth usage, successful allocation of nodes in the network using VSDN approach. The results show a 40% increase in the performance of proposed algorithms with a respect to existing algorithms.


Author(s):  
A. A. Heidari ◽  
M. R. Delavar

In realistic network analysis, there are several uncertainties in the measurements and computation of the arcs and vertices. These uncertainties should also be considered in realizing the shortest path problem (SPP) due to the inherent fuzziness in the body of expert's knowledge. In this paper, we investigated the SPP under uncertainty to evaluate our modified genetic strategy. We improved the performance of genetic algorithm (GA) to investigate a class of shortest path problems on networks with vague arc weights. The solutions of the uncertain SPP with considering fuzzy path lengths are examined and compared in detail. As a robust metaheuristic, GA algorithm is modified and evaluated to tackle the fuzzy SPP (FSPP) with uncertain arcs. For this purpose, first, a dynamic operation is implemented to enrich the exploration/exploitation patterns of the conventional procedure and mitigate the premature convergence of GA technique. Then, the modified GA (MGA) strategy is used to resolve the FSPP. The attained results of the proposed strategy are compared to those of GA with regard to the cost, quality of paths and CPU times. Numerical instances are provided to demonstrate the success of the proposed MGA-FSPP strategy in comparison with GA. The simulations affirm that not only the proposed technique can outperform GA, but also the qualities of the paths are effectively improved. The results clarify that the competence of the proposed GA is preferred in view of quality quantities. The results also demonstrate that the proposed method can efficiently be utilized to handle FSPP in uncertain networks.


2014 ◽  
Vol 4 (4) ◽  
pp. 36-54 ◽  
Author(s):  
António Leitão ◽  
Adriano Vinhas ◽  
Penousal Machado ◽  
Francisco Câmara Pereira

Inverse Combinatorial Optimization has become a relevant research subject over the past decades. In graph theory, the Inverse Shortest Path Length problem becomes relevant when people don't have access to the real cost of the arcs and want to infer their value so that the system has a specific outcome, such as one or more shortest paths between nodes. Several approaches have been proposed to tackle this problem, relying on different methods, and several applications have been suggested. This study explores an innovative evolutionary approach relying on a genetic algorithm. Two scenarios and corresponding representations are presented and experiments are conducted to test how they react to different graph characteristics and parameters. Their behaviour and differences are thoroughly discussed. The outcome supports that evolutionary algorithms may be a viable venue to tackle Inverse Shortest Path problems.


Author(s):  
A. A. Heidari ◽  
M. R. Delavar

In realistic network analysis, there are several uncertainties in the measurements and computation of the arcs and vertices. These uncertainties should also be considered in realizing the shortest path problem (SPP) due to the inherent fuzziness in the body of expert's knowledge. In this paper, we investigated the SPP under uncertainty to evaluate our modified genetic strategy. We improved the performance of genetic algorithm (GA) to investigate a class of shortest path problems on networks with vague arc weights. The solutions of the uncertain SPP with considering fuzzy path lengths are examined and compared in detail. As a robust metaheuristic, GA algorithm is modified and evaluated to tackle the fuzzy SPP (FSPP) with uncertain arcs. For this purpose, first, a dynamic operation is implemented to enrich the exploration/exploitation patterns of the conventional procedure and mitigate the premature convergence of GA technique. Then, the modified GA (MGA) strategy is used to resolve the FSPP. The attained results of the proposed strategy are compared to those of GA with regard to the cost, quality of paths and CPU times. Numerical instances are provided to demonstrate the success of the proposed MGA-FSPP strategy in comparison with GA. The simulations affirm that not only the proposed technique can outperform GA, but also the qualities of the paths are effectively improved. The results clarify that the competence of the proposed GA is preferred in view of quality quantities. The results also demonstrate that the proposed method can efficiently be utilized to handle FSPP in uncertain networks.


2021 ◽  
Vol 5 (3) ◽  
pp. 244-259
Author(s):  
Satriyo Widhi Pamungkas

The problem of net neutrality has become a debate in many countries where the regulation on the net neutrality policy confirms that internet providers or Internet Service Providers (ISPs) are not allowed to make distinctions or be discriminatory in the selection of internet applications or content to be used by consumers or users. The purpose of this research is to analyze the application of network neutrality from the perspective of Indonesian law which specifically examines critically the applicable Information and Electronic Transactions Law. This research method is descriptive qualitative. The results show that the implementation of Net Neutrality in terms of the Information and Electronic Transactions Law is still not optimal because there are still network restrictions that are applied to certain Internet Network Providers. The results also show that there is a need for amendments to the ITE Law related to the enforcement of legal protection with the principle of forming a prohibition against the actions of Internet Service Provider (ISP) business actors that can disrupt the business climate.


2014 ◽  
Vol 2014 ◽  
pp. 1-11
Author(s):  
Yanjun Li ◽  
Guoqing Zhang ◽  
Guoqiang Zhang

Peer-to-peer (P2P) file distribution imposes increasingly heavy traffic burden on the Internet service providers (ISPs). The vast volume of traffic pushes up ISPs’ costs in routing and investment and degrades their networks performance. Building ISP-friendly P2P is therefore of critical importance for ISPs and P2P services. So far most efforts in this area focused on improving the locality-awareness of P2P applications, for example, to construct overlay networks with better knowledge of the underlying network topology. There is, however, growing recognition that data scheduling algorithms also play an effective role in P2P traffic reduction. In this paper, we introduce the advanced locality-aware network coding (ALANC) for P2P file distribution. This data scheduling algorithm completely avoids the transmission of linearly dependent data blocks, which is a notable problem of previous network coding algorithms. Our simulation results show that, in comparison to other algorithms, ALANC not only significantly reduces interdomain P2P traffic, but also remarkably improves both the application-level performance (for P2P services) and the network-level performance (for ISP networks). For example, ALANC is 30% faster in distributing data blocks and it reduces the average traffic load on the underlying links by 40%. We show that ALANC holds the above gains when the tit-for-tat incentive mechanism is introduced or the overlay topology changes dynamically.


2020 ◽  
Author(s):  
SEPTY NUR AULIA DARMANTYA

Internet service providers that are used today are growing rapidly with various advantages and disadvantages. Because of this, there are many criteria that can be used as basic internet service providers that are most suitable for use. In this study, the author raised several network providers namely Telkomsel and Indosat. To choose a good Internet service provider is by using an AHP (Analytical Hierarchy Process) method, with this method respondents are guided to make decisions based on two-level criteria. Level 1 criteria: data transfer speed, type of service, and type of card. While for level 2 there are three alternatives, namely Telkomsel and Indosat. From the results of the selection of internet service providers, Telkomsel is the best compared to Indosat.


ADALAH ◽  
2020 ◽  
Vol 4 (2) ◽  
Author(s):  
Munadhil Abdul Muqsith

Abstract:The internet developed for the first time in Indonesia in the early 1990s. Starting from the pagayuban network, it is now expanding without boundaries anywhere. A survey conducted by the Indonesian Internet Service Providers Association (APJII) said that the number of internet users in Indonesia in 2012 reached 63 million people or 24.23 percent of the country's total population. Next year, that figure is predicted to increase by close to 30 percent to 82 million users and continue to grow to 107 million in 2014 and 139 million or 50 percent of the total population in 2015. million people. This matter also results in political communication with the internet media, or is often said to be cyber politics. Cyber politics in Indonesia has faced growth in recent years. There are many facilities that support the growth of cyber politics, such as Facebook, Twitter, mailing list, YouTube, and others.Keywords: Cyberpolitik, Internet  Abstrak:Internet berkembang pertama kali di Indonesia pada awal tahun 1990-an. Diawali dari pagayuban network kini berkembang luas tanpa batas dimanapun juga. Suatu survei yang diselenggarakan Asosiasi Penyelenggara Jasa Internet Indonesia (APJII) mengatakan kalau jumlah pengguna internet di Indonesia tahun 2012 menggapai 63 juta orang ataupun 24,23 persen dari total populasi negeri ini. Tahun depan, angka itu diprediksi naik dekat 30 persen jadi 82 juta pengguna serta terus berkembang jadi 107 juta pada 2014 serta 139 juta ataupun 50 persen total populasi pada 2015. juta orang. Perihal ini pula berakibat pada komunikasi politik dengan media internet, ataupun kerap diucap dengan cyber politic. Cyber politic di Indonesia hadapi pertumbuhan sebagian tahun terakhir. Banyaknya fasilitas yang menunjang pertumbuhan cyber politic semacam terdapatnya facebook, Twitter, mailing list, youtobe, serta lain-lain.Kata Kunci: Cyberpolitik, Internet 


2012 ◽  
Vol 57 (3) ◽  
pp. 829-835 ◽  
Author(s):  
Z. Głowacz ◽  
J. Kozik

The paper describes a procedure for automatic selection of symptoms accompanying the break in the synchronous motor armature winding coils. This procedure, called the feature selection, leads to choosing from a full set of features describing the problem, such a subset that would allow the best distinguishing between healthy and damaged states. As the features the spectra components amplitudes of the motor current signals were used. The full spectra of current signals are considered as the multidimensional feature spaces and their subspaces are tested. Particular subspaces are chosen with the aid of genetic algorithm and their goodness is tested using Mahalanobis distance measure. The algorithm searches for such a subspaces for which this distance is the greatest. The algorithm is very efficient and, as it was confirmed by research, leads to good results. The proposed technique is successfully applied in many other fields of science and technology, including medical diagnostics.


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