Demand of Wireless Network and Security in Current Research

2015 ◽  
Vol 14 (6) ◽  
pp. 5809-5813
Author(s):  
Abhishek Prabhakar ◽  
Amod Tiwari ◽  
Vinay Kumar Pathak
Keyword(s):  
Wireless Networks ◽  
Quality Of Service ◽  
Wireless Network ◽  
Network Performance ◽  
Wireless Security ◽  
Human Intervention ◽  
Unauthorized Access ◽  
Quality Of Service Parameters ◽  
Wireless Infrastructure

Wireless security is the prevention of unauthorized access to computers using wireless networks .The trends in wireless networks over the last few years is same as growth of internet. Wireless networks have reduced the human intervention for accessing data at various sites .It is achieved by replacing wired infrastructure with wireless infrastructure. Some of the key challenges in wireless networks are Signal weakening, movement, increase data rate, minimizing size and cost, security of user and QoS (Quality of service) parameters... The goal of this paper is to minimize challenges that are in way of our understanding of wireless network and wireless network performance.

Simulation and Emulation Tools for Fog Computing

2020 ◽  
Vol 13 ◽  
Author(s):  
Simar Preet Singh ◽  
Rajesh Kumar ◽  
Anju Sharma ◽  
S. Raji Reddy ◽  
Priyanka Vashisht
Keyword(s):  
Quality Of Service ◽  
Programming Languages ◽  
Traffic Management ◽  
Fog Computing ◽  
Research Work ◽  
Research Experience ◽  
Computing Paradigm ◽  
Quality Of Service Parameters ◽  
User Friendly

Background: Fog computing paradigm has recently emerged and gained higher attention in present era of Internet of Things. The growth of large number of devices all around, leads to the situation of flow of packets everywhere on the Internet. To overcome this situation and to provide computations at network edge, fog computing is the need of present time that enhances traffic management and avoids critical situations of jam, congestion etc. Methods: For research purposes, there are many methods to implement the scenarios of fog computing i.e. real-time implementation, implementation using emulators, implementation using simulators etc. The present study aims to describe the various simulation and emulation tools for implementing fog computing scenarios. Results: Review shows that iFogSim is the simulator that most of the researchers use in their research work. Among emulators, EmuFog is being used at higher pace than other available emulators. This might be due to ease of implementation and user-friendly nature of these tools and language these tools are based upon. The use of such tools enhance better research experience and leads to improved quality of service parameters (like bandwidth, network, security etc.). Conclusion: There are many fog computing simulators/emulators based on many different platforms that uses different programming languages. The paper concludes that the two main simulation and emulation tools in the area of fog computing are iFogSim and EmuFog. Accessibility of these simulation/emulation tools enhance better research experience and leads to improved quality of service parameters along with the ease of their usage.

scholarly journals Analisa Perbandingan Quality of Service Voice Over IP dengan Pengujian Codec Menggunakan Algoritma Low Latency Queuing

2017 ◽  
Vol 3 (2) ◽  
pp. 249-254
Author(s):  
Darmawan Darmawan ◽  
Yayan Syafriyatno
Keyword(s):  
Quality Of Service ◽  
Packet Loss ◽  
Packet Switching ◽  
Voice Over Ip ◽  
Low Latency ◽  
Delay Jitter

Voice over IP (VoIP) adalah solusi komunikasi suara yang murah karena menggunakan jaringan IP dibanding penggunaan telephone analog yang banyak memakan biaya. Dalam penerapannya, VoIP mengalami permasalahan karena menggunakan teknologi packet switching yang mana penggunaannya bersamaan dengan paket data sehingga timbul delay, jitter, dan packet loss.  Pada penelitian ini, algoritma Low Latency Queuing (LLQ) diterapkan pada router cisco. Algoritma LLQ merupakan gabungan dari algoritma Priority Queuing (PQ) dan Class Based Weight Fair Queuing (CBWFQ) sehingga dapat memprioritaskan paket suara disamping paket data. Algoritma LLQ ini diujikan menggunakan codec GSM FR, G722, dan G711 A-law. Hasil pengujian didapatkan nilai parameter yang tidak jauh berbeda dan memenuhi standar ITU-T.G1010. Nilai delay rata - rata terendah yaitu ketika menggunakan codec G722 sebesar 20,019 ms tetapi G722 memiliki rata - rata jitter yang terbesar yaitu 0,986 ms.  Codec dengan jitter rata – rata terkecil adalah G711 A-law sebesar 0,838 ms. Packet loss untuk semua codec yang diujikan adalah 0%.  Throughput pada paket data terbesar saat menggunakan codec GSM FR yaitu 18,139 kbps. Codec yang direkomendasikan adalah G711 A-law karena lebih stabil dari segi jitter dan codec GSM FR cocok diimplementasikan pada jaringan yang memiliki bandwitdh kecil.

scholarly journals IMPACT OF QUEUING DISCIPLINES ON THE PERFORMANCE OF MULTI-CLASS TRAFFIC IN A NETWORK

2021 ◽  
Vol 9 (1) ◽  
pp. 691-697
Author(s):  
N. Sugirtham, R. Sherine Jenny
Keyword(s):  
Quality Of Service ◽  
User Satisfaction ◽  
File Transfer ◽  
Network Resources ◽  
Network Applications ◽  
End To End Delay ◽  
Opinion Score ◽  
Quality Of Service Parameters ◽  
First In First Out

Network applications demand quality of service for enhanced call quality and increased user satisfaction. Hence, implementing queuing discipline at switches and routers in a network will govern the way packets are buffered while waiting for transmission. Queuing disciplines like first-in first-out (FIFO) queuing, priority queuing (PQ), weighted-fair queuing (WFQ), custom queuing and modified weighted round robin are more prominently deployed in network applications. These queuing disciplines help to control and manage network resources by fixing priorities for specific types of data on the network. The paper aims to analyze the quality of service parameters for various real time applications like File transfer protocol(FTP), email, database, Voice over IP(VOIP), video and web browsing,etc., and helps to optimise the use of available network resources. Moreover the quality of the network is compared using different QoS parameters such as end-to-end delay, throughput, jitter and Mean Opinion Score (MOS). This paper focuses on various queuing disciplines with low and high network traffic.

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