Recent Advances in Electrical & Electronic Engineering - Volume 13, Issue 2, 2020

Background: This paper is a review of optical fiber communications and also presents the different types of disasters and different protection schemes to combat these disasters. In the optical communication network, the failure of a network caused by disasters (e.g. predictable disaster, unpredictable disaster, Intentional attacks) leads to the failure of several optical communication channels and huge data loss. Most of the previous works on optical network survivability assume that the failures are going to occur in future, and the network is made survivable to ensure connectivity in events of failures. With the advancements in technology, the predictions of tornados, cyclone and landslides are becoming more accurate by using some early warning systems. Objective: Significant improvement in optical communication network survivability can be achieved using our proposed protection scheme in the event of a major earthquake, cloud burst and landslides. Conclusion: The review concludes that a large amount of data could be lost even if there is a very short disruption in the optical backbone network.

Background: The increased cost of treatments in the health care industry and advancements in technologies have led to a promising area of development in Wireless Sensor Networks and semiconductor technologies. Wireless Body Area Networks is a subset of WSN in which sensor nodes are placed on the human body or implanted inside the body to determine various physical parameters of the human body. This information is forwarded to the medical centers or central servers through gateways. The direct advantage of this technology is the existence of portable health monitoring applications as well as location independent monitoring applications. But, still, the existence of smart hospitals needs a lot of focused research related to practical problems faced by patients as well as practitioners. Introduction: The aim of this paper is to present an essential depiction of WBAN development in both medical and non- medical applications. The important features of various wireless technologies supported by WBAN have also been presented. It is apparent that to determine the overall performance of a network in terms of different parameters like temperature, power consumption, throughput and delay, etc., a significant role is played by the routing protocols. Since WBAN directly deals with the human body and hence implementation of a new protocol is a challenging task before researchers, this paper reviews each category of routing protocols and their corresponding limitations. A comparison among routing protocols will guide researchers in implementing a specific protocol for targeted application. The paper also focuses on the future of WBAN which will provide the research areas for further exploration. Conclusion: It is found that QoS aware protocols are employed specifically for critical applications. If we consider radiation imparted from the sensors and tissue protection of the human body, the thermal aware routing protocol is the solution. Another important conclusion of this paper is that the various protocols do not provide an optimal solution for selecting the forward node during routing and this solution primarily depends on the residual energy of the nodes and distance of the node from the sink. A study of protocols developed from 2004 onwards till date shows that implementation of WBAN using integration of IoT, EoT, and fog computing has been the emerging topic of research in recent years.

Objectives: Since the adequacy of Learning Objects (LO) is a dynamic concept and changes in its use, needs and evolution, it is important to consider the importance of LO in terms of time to assess its relevance as the main objective of the proposed research. Another goal is to increase the classification accuracy and precision. Methods: With existing IR and ranking algorithms, MAP optimization either does not lead to a comprehensively optimal solution or is expensive and time - consuming. Nevertheless, Support Vector Machine learning competently leads to a globally optimal solution. SVM is a powerful classifier method with its high classification accuracy and the Tilted time window based model is computationally efficient. Results: This paper proposes and implements the LO ranking and retrieval algorithm based on the Tilted Time window and the Support Vector Machine, which uses the merit of both methods. The proposed model is implemented for the NCBI dataset and MAT Lab. Conclusion: The experiments have been carried out on the NCBI dataset, and LO weights are assigned to be relevant and non - relevant for a given user query according to the Tilted Time series and the Cosine similarity score. Results showed that the model proposed has much better accuracy.

Background: Multistage interconnection networks are being used in computer and communications. Multiprocessor architectures for parallel computing exercise these interconnection networks for connecting various processing elements and transfer data between sub-systems of a digital system. The vast diversity of the field poses an obstacle to realize different kinds of interconnection networks and their relationship. Methods: This paper consists of an extensive survey of multistage interconnection networks. Results: A broad classification of multistage interconnection networks based on network functionality, reliability and fault tolerance is presented in order to emphasize the important principles which differentiate the network architectures. For each class of network, significant results are given and the basic design principles are explained. Conclusion: The various multistage interconnection networks design provide high performance, availability, throughput, lower latency, less power consumption along with improved fault-tolerance and reliability. However, there is a rising demand for new fault-tolerant and reliable multistage interconnection networks.

Background: The study of bugs that are reported and close may indicate the growth and working of a software project. It may also indicate the quality of the project. Methods: As software projects grow, the number of bugs reported generally increases each year. To maintain quality, the developers have to resolve and close these increasing numbers of bugs. Results: The present paper discusses the relations between bugs being reported and bugs being closed. It also discusses some parameters related to the study of bugs. In this paper, new parameters have been introduced that help in the improvement of quality and this is the novelty of paper. Conclusion: The research mainly covers the problem of finding the relation of collaborative growth with the quality of software. The paper also covers improvements in parameters like the rate of bug fixing. It also discusses the significance of these parameters. We have suggested a new parameter called the bug closing rate. And this can be calculated in two ways.

Background: In Wireless Sensor Networks, Localization is the most dynamic field for research. The data extracted from the sensor nodes that carries physical location information is very much helpful in WSNs as it is useful in major applications such as for the purpose of monitoring of any environment, tracking and for the detection purpose. Localization is known as the estimation of unknown node locations and its positions by communicating through localized nodes as well as unlocalized nodes. Objective: The aim of this study is to present classification of various localization algorithms and to compare them. Methods: The prime consideration is to know that how localization affects the network lifetime and how these algorithms work for increasing the lifetime of a network in a severe. Results: This paper also aims for finding the position of the node with respect to range based, anchor based and distributed localization techniques for harsh environments. Additionally, this paper also features the concern that occurs with these localization techniques. Conclusion: The technique that gives highly accurate location coordinates and having less hardware cost is distributed RSSI based localization algorithm.

Objective: Optical networks exploit the Wavelength Division Multiplexing (WDM) to meet the ever-growing bandwidth demands of upcoming communication applications. This is achieved by dividing the enormous transmission bandwidth of fiber into smaller communication channels. The major problem with WDM network design is to find an optimal path between two end users and allocate an available wavelength to the chosen path for the successful data transmission. Methods: This communication over a WDM network is carried out through lightpaths. The merging of all these lightpaths in an optical network generates a virtual topology which is suitable for the optimal network design to meet the increasing traffic demands. But, this virtual topology design is an NP-hard problem. This paper aims to explore Mixed Integer Linear Programming (MILP) framework to solve this design issue. Results: The comparative results of the proposed and existing mathematical models show that the proposed algorithm outperforms with the various performance parameters. Conclusion: Finally, it is concluded that network congestion is reduced marginally in the overall performance of the network.

Background: In this paper, the design of a dual-band microstrip patch antenna with operating frequencies of 2.16 GHz and 2.79 GHz is proposed. Methods: The proposed antenna design is based upon the defected ground structure and rectangular patch with corner cuts. The presented antenna structure is simulated and optimized using CST microwave studio software. Results: The antenna resonates at 2.16 GHz and 2.79 GHz. The bandwidth of the proposed antenna is 2.08 GHz-2.25 GHz at center frequency 2.16 GHz and is 2.7 GHz-2.87 GHz at center frequency 2.79 GHz. The optimized antenna model is fabricated and measured. The measured and simulated results are presented and discussed. The proposed antenna provides a maximum gain of 4.463 dB and the maximum directivity of 5.846 dBi. The maximum radiation efficiency and total efficiency of the antenna are 79.85% and 69.01%, respectively. Conclusion: The proposed antenna is suitable for dual-band wireless applications.

Background: Energy consumption is an important parameter in wireless sensor networks since it affects the lifetime of sensor nodes. Methods: Battery powered wireless sensor networks cannot sustain for long hence impractical for real-time applications. With energy harvesting and relevant protocols, this issue of extending the lifetime of nodes has been solved largely. The performance can be enhanced further if proper traffic analysis and modeling are done as a proactive approach. Results: A proper understanding of the traffic dynamics provides a base for further network optimization and detection of anomalies within the network. Much of the reported work in energy harvesting based WSN till now, is to design the efficient protocols only, traffic analysis and modeling is the ignored parameter. In this paper traffic models appropriate for the energy harvesting based system have been analyzed and their performance is evaluated for a MAC protocol. Conclusion: Results show that Weibull distribution is the most useful model for traffic modeling in energy harvesting based wireless sensor networks.

Background: Currently, Wireless sensor networks are the most prominent area in research. Energy consumption is one of the important challenges in wireless sensor networks. Objective: The objective of this paper is to increase the network lifetime and throughput of the wireless sensor network. Methods: The fuzzy logic approach is used to improve the network lifetime and throughput. The proposed approach gave better results in comparison to existing approaches of Low Energy Fuzzy Based Unequal Clustering Multi-hop Architecture (LEFUCMA) and Low Energy Adaptive Unequal Clustering Using Fuzzy C-Means (LAUCF). Results: The proposed approach is 11.39 % better in terms of network lifetime in comparison to LEFUCMA and 34.27 % in terms of network lifetime in comparison to LAUCF. Conclusion: The proposed approach is 34.29 % better in terms of network throughput as a comparison of LEFUCMA and 112.85 % in terms of network throughput in comparison to LAUCF.

Background: Several techniques are available to evaluate the two-terminal reliability (2TR) of static networks; however, the advent of dynamic networks in recent past, e.g., Delay Tolerant Networks (DTNs), has made this task extremely challenging due to their peculiar characteristics with an associated disruptive operational environment. Recently, a Cartesian product-based method has been proposed to enumerate time-stamped-minimal path sets (TS-MPS)-a precursor to compute the 2TR of such networks. However, it cannot be used to generate time-stamped-minimal cut sets (TS-MCS). TS-MCS cannot only be used as an alternative to generate 2TR but also to compute other unexplored reliability metrics in DTNs, e.g., the weakest link. Objective: To propose a novel approach to enumerate both TS-MPS and TS-MCS of a dynamic network, thereby computing the 2TR of such networks. Methods: The proposed technique converts the time aggregated graph model of a dynamic network into a Line Graph (LG) while maintaining the time-varying graph’s node reachability information. This LG is used thereafter to generate TS-MCS as well as TS-MPS to compute 2TR of the network. Results: The DTN examples are presented to show the efficacy and salient features of our algorithm to obtain 2TR of such networks. Conclusion: The terminologies and techniques used for studying/analyzing network reliability of static networks can be extended to dynamic networks as well, e.g., the notion of minimal path sets to TS-MPS or minimal cut sets to TS-MCS, to assess their network reliability-a potential area of furthering network reliability research.

Background: Security in WSNs is the most significant because sensor nodes deployed are in an unattended environment, and the information is communicated over insecure wireless channels. Therefore, there is a need to put enhanced security measures for securing sensor nodes as well as ensure secured transmission of information. Objective: These resource-constrained networks suffer from various attacks namely, node clone attack, Sybil attack, and DoS attack. In this paper, we proposed a hybrid cryptography algorithm, which secured WSNs from node clone attack. Methods: The proposed algorithm uses a combination of symmetric (AES) and asymmetric (ECC) cryptography techniques along with the hash function. Further, the proposed algorithm checks the integrity of messages during communication in the sensor network. Results: The performance of the proposed hybrid algorithm was examined through the various metrics like communication, computation, and storage overheads. The comparison of the results validates the efficiency of the proposed hybrid algorithm. Conclusion: The proposed hybrid algorithm provides a secure and efficient solution to the energy sensor networks.

Background: With the immense significance of cloud computing over the decade, different IT companies offer varieties of cloud services. Objective: The selection of cloud services from the expanding range of Cloud Service Providers (CSPs) makes it difficult for the Cloud Consumers (CCs) to choose a CSP based on their preferences. Methods: In this context, this paper proposes an efficient trust management architecture for cloud service selection and put forward Combined Preference Ranking Algorithm (CPRA) for initial ranking of CSPs and their services before doing any transaction in the past based on CCs requirements. Results: The proposed trust management architecture prompts the CSPs to improve the Quality of Service (QoS) by adhering to Service Level Agreement (SLA). Conclusion: The experimental results show that compared with other ranking approaches CPRA generates the accurate ranking list of CSPs with minimal execution time.

Background: Speed and rotor position estimation is mandatory for vector control scheme of Permanent Magnet Synchronous Motor (PMSM). Methods: The estimation accuracy of Non-adaptive (Open loop) methods degrades as mechanical speed reduces. The system becomes more robust against parameter mismatch and signal noises by employing adaptive observers for estimation of speed and position. Sensorless scheme adopted for estimating the PMSM rotor position based on its performance which eliminates the need for speed sensors which are usually required in such control applications. Results: To achieve this goal, a Space Vector Pulse Width Modulation (SVPWM) control scheme is applied to work in conjunction with a vector control PMSM drive using Simulink. The PI controller uses from estimated speed feedback for the speed sensorless control of PMSM. Conclusion: In this paper, a comprehensive analysis of sensor-based and sensorless based on Sliding Mode Observer (SMO) techniques for vector control of PMSM is presented with regards to the steadystate and dynamic performance robustness against parameter sensitivity, stability and computational complexity. The control scheme is simulated in the MATLAB/Simulink software environment.

Background: The vibration signals acquired from multistage gearbox’s slow-speed gear with localized fault may be directly mixed with source noise and measured noise. In addition, Constrained Independent Component Analysis (CICA) method has strong immunity to the measured noise but not to the source noise. These questions cause the difficulty for applying CICA method to directly extract lowfrequency and weak fault characteristic from the gear vibration signals with source noise. Methods: In order to extract the low-frequency and weak fault feature from the multistage gearbox, the source noise and measured noise are introduced into the independent component analysis (ICA) algorithm model, and then an enhanced Constrained Independent Component Analysis (CICA) method is proposed. The proposed method is implemented by combining the traditional Wavelet Transform (WT) with Constrained Independent Component Analysis (CICA). Results: In this method, the role of a supplementary step of WT before CICA analysis is explored to effectively reduce the influence of strong noise. Conclusion: Through the simulations and experiments, the results show that the proposed method can effectively decrease noise and enhance feature extraction effect of CICA method, and extract the desired gear fault feature, especially the low-frequency and weak fault feature.

Background: Wireless positioning is one of the most important technologies for realtime applications in wireless sensor systems. This paper mainly studies the indoor wireless positioning algorithm of robots. Methods: The application of the K-nearest neighbor algorithm in Wi-Fi positioning is studied by analyzing the Wi-Fi fingerprint location algorithm based on Received Signal Strength Indication (RSSI) and K-Nearest Neighbor (KNN) algorithm in Wi-Fi positioning. The KNN algorithm is computationally intensive and time-consuming. Results: In order to improve the positioning efficiency, improve the positioning accuracy and reduce the computation time, a fast weighted K-neighbor correlation algorithm based on RSSI is proposed based on the K-Means algorithm. Thereby achieving the purpose of reducing the calculation time, quickly estimating the position distance, and improving the positioning accuracy. Conclusion: Simulation analysis shows that the algorithm can effectively shorten the positioning time and improve the positioning efficiency in robot Wi-Fi positioning.