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... shows medium WLAN delay as compared to TORA and OLSR. The maximum values of WLAN delay are highlighted in Table 2. ...Context 2
... shows medium WLAN delay as compared to TORA and OLSR. The maximum values of WLAN delay are highlighted in Table 2. ...Similar publications
Energy preservation of the sensor become a prime objective of the routing protocols for prolong the period of sensor network and for efficient running of wireless sensor network applications. Taking this aspect into consideration, improved CBCCP approach has been developed that take energy, distance and node Density as parameter to choose cluster h...
In Internet of Vehicle (IoV), each vehicle uses a routing protocol to find a path for sending its messages to the last destination. Nowadays, the studies of IoV routing protocols and their impact on the performances of network with different network scenarios has significantly developed a precise understanding of the requirements and goals for desi...
Complex task processing and frequent data communication in Wireless Multimedia Sensor Networks (WMSN) demand for energy-efficient and Quality of Service (QoS) guarantee to support new applications especially in the sensing layer of Internet-of-Vehicles. However, the WMSN is heterogeneous and the energy distribution is not uniform, the current routi...
One of the most advanced evolutions of Wireless communication is Wireless Sensor Network (WSN), which plays a vital role in many applications. The growth and attention towards the designing of many new QoS aware routing protocol for WSN has been increased for the past few decades. Energy awareness has a greater significance while developing a routi...
![Fig 4: The SPIN Protocol [30].](profile/Abdul-Wahab-Yakubu/publication/339987122/figure/fig1/AS:870124949090305@1584465362796/The-SPIN-Protocol-30_Q320.jpg)
![Fig 5: Example depiction of Directed Diffusion [35].](profile/Abdul-Wahab-Yakubu/publication/339987122/figure/fig2/AS:870124949098499@1584465362853/Example-depiction-of-Directed-Diffusion-35_Q320.jpg)
![Comparison of LEACH and non-LEACH type protocols. Adapted from [51].](profile/Abdul-Wahab-Yakubu/publication/339987122/figure/tbl1/AS:870124949098500@1584465362879/Comparison-of-LEACH-and-non-LEACH-type-protocols-Adapted-from-51_Q320.jpg)
Citations
... However, in the event that a node does possess a downward link, it will transmit a reply payload that updates the receiving node's height. However, in order for the height to be updated, it must be greater than the replied packet or other packets [20]. ...
Nowadays, Unmanned Aerial Vehicles (UAVs), have indeed revolutionized various industries and opened up new possibilities. Additionally, a Flying Ad hoc Network (FANET), a group of UAVs can perform specific functions like delivering goods, assisting people after a disaster, monitoring the weather and environment, among others. FANET is another kind of ad-hoc mobile network. It is capable of connecting with its environment and other nodes to obtain critical information. It is particularly difficult to route across FANETs because of how mobility they are and how fast they may change layouts. Therefore, routing algorithms are crucial for improving the performance of ad-hoc networks. This article will analyse the performance of the AODV, DSDV, and TORA routing protocols in the FANET environment. The NS-2 simulator has been used for testing parameters such as jitter, throughput, End-to-End delay, and packet delivery ratio (PDR). The simulation results indicate that TORA outperforms AODV and DSDV routing protocols across all performance metrics except End-to-End Delay.
... The application layer is the highest-level layer of the IoT structure [31] responsible for intelligent services at a high level delivered by this layer to meet the requirements of the customers [32]. This layer functions as the visible interface and coordinator of capabilities in IoT architecture [33,34]. It converts raw data into practical insights and provides valueadded services to end-users. ...
One of the major needs and challenges of this century is the use of cutting-edge technology considering the industry 4.0 revolution. The Internet of Things (IoT) falls in the category of a cutting-edge example of such innovation in the computing and information industry. In IoT compared to classical networking methods practically; every device we employ is accessible at any time from any location. Nevertheless, IoT continues to encounter several security challenges, and the magnitude of cyber physical security risks is escalating alongside the widespread use of IoT technologies considering Moore’s laws expected to be 30 billion devices by 2025. IoT will continue to face vulnerabilities and risks unless there is a comprehensive understanding and proactive approach towards tackling its security concerns. To
ensure both the cyber and physical security of IoT devices during data gathering and sharing, it is imperative to evaluate security considerations, identify instances of cyber-attacks, and implement effective security protocols at multiple layers for making highly secured IoT. Conventional security measures like data classification, strict access controls, monitoring privileged account access, encrypting sensitive data, security awareness training, network segregation, segmentation cloud security, application security, patch management, and physical security employed in the realm of IoT are inadequate in light of the current security difficulties posed by the proliferation of sophisticated attacks and threats. Utilization of artificial intelligence (AI) techniques, especially machine and deep learning models is becoming a compelling and effective approach to enhance security of the IoT devices. This research article presents a comprehensive review of the key aspects of IoT security, including the challenges, potential opportunities, and AI-driven solutions. The primary goal of this article is to provide technical resources for cybersecurity experts and researchers working on IoT initiatives.
Pada saat bencana alam yang mengakibatkan infrastruktur jaringan dan komunikasi di suatu wilayah menjadi lumpuh, dibutuhkan suatu sistem komunikasi yang berjalan tanpa infrastruktur jaringan. Komunikasi yang dilakukan dalam penanganan bencana dapat dilakukan menggunakan perangkat komunikasi yang berbasis Mobile ad-hoc Network (MANET) yang tidak membutuhkan infrastruktur jaringan, atau dapat juga menggunakan perangkat komunikasi yang berbasis wireless mesh network (WMN) yang menggunakan beberapa node router yang ditempatkan secara terbatas. Pada penelitian ini, dilakukan simulasi sistem komunikasi berbasis jaringan MANET dan WMN menggunakan Network Simulator 2 versi 2.35 dengan protokol routing ZRP dan TORA. Simulasi diuji dengan empat skenario yang berbeda. Parameter yang digunakan untuk menguji kinerja jaringan adalah packet delivery ratio , end to end delay , throughput dan routing overhead . Dari hasil pengujian, protokol routing TORA pada skenario node sudah tersebar dan protokol routing ZRP untuk seluruh skenario di jaringan WMN memiliki nilai rata-rata packet delivery ratio yang tinggi. Sedangkan protokol routing TORA pada skenario node yang menyebar memiliki nilai rata-rata end-to-end delay yang rendah serta throughput yang tinggi. Pada jaringan MANET memiliki nilai rata-rata end-to-end delay yang rendah serta throughput yang tinggi dan protokol routing TORA dengan skenario node yang menyebar memiliki nilai rata-rata packet delivery ratio yang tinggi serta routing overhead yang tinggi.
