Feb 21
The IUP Journal of Telecommunications
Focus
The modern network research mainly focuses on the internetworking/interfacing of various devices operated under different standards and protocols under wireless environment. This issue contains four papers related to Wireless Wensor Network (WSN) protocols, IoT-enabled network access, hybrid data transmission to characterize physical channel behavior and image processing algorithms to realize an effective data compression for better channel utilization.
WSN contains a large number of small and tiny sensor nodes operated with limited power and memory but need a secured and efficient routing path to forward the incoming packet to enhance the sensor network reliability and lifetime. The first paper, "Performance Analysis of LEACH and LEACH-CC Protocol with Cryptographic Algorithms in Wireless Sensor Networks", by Deepika Verma, R S Gamad and Neelu Nihlani, deals with the implementation of Low-Energy Adaptive Clustering Hierarchy (LEACH) and LEACH-CC protocol along with cryptographic algorithms in MATLAB. The paper implements LEACH and LEACH-CC protocol with RSA and ECC algorithm and compares the performance based on energy, security and lifetime of the network to confirm a higher data per unit energy for LEACH-CC than LEACH.
The second paper, "Human Health Monitoring System Using IoT Applications", by Keshav Sharma and Pawan Kumar Dahiya, describes the various techniques of human health monitoring system using IoT devices interfaced with Raspberry Pi and FPGA platform. The paper analyzes Raspberry Pi and FPGA-based wellbeing framework utilizing IoT devices and establishes a straightforward link with an individual over Global System for Mobile (GSM) or internet connected servers. The proposed framework describes a better and effective wellbeing administration to the patient and thus aids in quick treatment.
Nowadays, for efficient transmission through wireless channel, some hybrid techniques are being proposed by combining the Time Division Multiple Access (TDMA) and Direct Sequence Spread Spectrum (DSSS) to achieve better interference reduction and higher channel capacity. The third paper, "Hybrid Data Transmission Approach for Unmanned Aerial Vehicles", by Katikala Saitheja and R V S Satyanarayana, proposes a novel hybrid technique for data transmission with the combination of TDMA with DSSS technique and thereby assuring more number of users. In DSSS, the user data is multiplied with Barker code for spreading, while the TDMA allocates time slots to each user to allow the same frequency channel by dividing the signal into time slots.
The last paper, "Feature Priors for Image Segmentation Using HMRF Algorithm", by Gyanender Kumar and Lincoln Hadda, reports the Hidden Markov Random Field (HMRF) model and finds its Expectation Maximization (EM) algorithms. The main idea behind developing HMRF is to adjoin the data faithfulness and model smoothness. The paper also uses HMRF-EM along with the Gaussian mixture models, and then implements color image segmentation process. These algorithms are implemented in MATLAB and confirm that the results obtained from HMRF segmentation are much smoother than the direct k-means clustering.
Consulting Editor
|
|
|||
| Article | Price (₹) | ||
| Performance Analysis of LEACH and LEACH-CC Protocol with Cryptographic Algorithms in Wireless Sensor Networks |
100
|
||
| Human Health Monitoring System Using IoT Applications |
100
|
||
| Hybrid Data Transmission Approach for Unmanned Aerial Vehicles |
100
|
||
| Feature Priors for Image Segmentation Using HMRF Algorithm |
100
|
||
Performance Analysis of LEACH and LEACH-CC Protocol with Cryptographic Algorithms in Wireless Sensor Networks
In Wireless Sensor Network (WSN), the life span depends on the energy consumption of the sensor node by reducing the energy consumption of each node, which in turn increases the lifetime of the network. Clustering with data aggregation is an effective technique to reduce the energy consumption. Besides prolonging the network lifetime, fulfilling security requirements is vital as wireless sensor nodes are generally applied in crucial application where security plays an important role. Sensor nodes are prone to node compromise and different attacks, so security issues are extremely important while communicating over the internet. The paper deals with the implementation of Low-Energy Adaptive Clustering Hierarchy (LEACH) and LEACH-CC protocol individually and with cryptographic algorithms Rivest Shamir Adleman (RSA), ElGamal and Elliptic Curve Cryptography (ECC) in MATLAB. We also developed a program for encrypting and decrypting text files.
Human Health Monitoring System Using IoT Applications
Nowadays, Internet of Things (IoT) makes everything interconnected and perceived as the succeeding specialized rebellion. There are numerous applications of IoT such as smart automation at home, smart city, smart vehicle parking, in various agriculture fields, industrial automation process and health monitoring system. In human health monitoring system, IoT makes health equipment more effective by permitting real-time intensive care of patient health, in which various sensors take statistics of the patient and diminish humanoid error. IoT is emerging as a most important platform for numerous amenities and applications. In IoT, health monitoring system monitors patient's health remotely outside the hospital settings. This system continuously uploads patient's report on cloud system which helps the doctor to study in detail the variations in the patient's health conditions. Remote health monitoring structure is totally built on Global System for Mobile (GSM) network. By means of this system, the time period of both doctor and patients is saved; in addition, the surgeon can also assist in an emergency situation. The paper describes various techniques of human health monitoring system using IoT devices. Raspberry Pi and FPGA platform are mostly used to set up a platform for human health monitoring.
Hybrid Data Transmission Approach for Unmanned Aerial Vehicles
In the last few years, wireless communication technologies have undergone several advancements. In this context, Unmanned Aerial Vehicles (UAVs) play a vital role. It is a big challenge to get accurate data with minimum collision in UAVs. The features of Direct Sequence Spread Spectrum (DSSS) like multiple access and antijamming are useful to get accurate data with minimum collision. DSSS can transmit and control data. DSSS is a common technique for data transmission. As the number of users increases, DSSS may not be sufficient to transmit and control data. To overcome this problem, we propose a novel hybrid technique for data transmission. The paper introduces a hybrid approach with the combination of Time Division Multiple Access (TDMA) with DSSS. TDMA can divide the frame into equal time slots, so it is easy to access more number of users with minimum data collision. In DSSS, the user data is multiplied with Barker code for spreading and TDMA allocates time slots to each user to allow the same frequency channel by dividing the signal into time slots. The paper uses 13-bit Barker code with the spread spectrum, i.e.,13 users can allow at a time and Bit Error Rate (BER) is evaluated. The work can be carried out in MATLAB.
Feature Priors for Image Segmentation Using HMRF Algorithm
Image segmentation is a process of dividing the image into some distinct regions. These regions are specially coherent in nature and have similar attributes. This technique is widely used for image analysis and to interpret the desired feature. The paper studies the Hidden Markov Random Fields (HMRF) and finds its Expectation Maximization (EM) algorithms. The main idea behind developing HMRF is to adjoin the "data faithfulness" and "model smoothness" which has very similar nature with the active contours, Gradient Vector Flow (GVF), graph cuts and random walks. The paper also uses HMRF-EM along with the Gaussian mixture models, and then color image segmentation process. These algorithms are implemented in MATLAB. In color image segmentation experiments, it is observed that the results obtained from HMRF segmentation are much smoother than the direct k-means clustering. The segmented object is much closer to the original shape than clustering. The segmentation time for Bacteria 1, Bacteria 2, SAR and brain images is 0.35, 0.43, 0.12 and 0.12, respectively. The accuracy for Bacteria 1, Bacteria 2, SAR and brain images is 97.70%, 98.06%, 98.89% and 97.35%, respectively.