International Journal of Sensors Wireless Communications and Control - Volume 10, Issue 5, 2020

With the fast development of cloud computing methods, exponential growth is faced by several users. It is complicated for traditional data centers to perform several jobs in real-time because of inadequate bandwidth resources. Therefore, the method of fog computing is recommended for supporting and providing fast cloud services. It is not a substitute but is a powerful complement to cloud computing. The reduction of energy consumption through the notion of fog computing has certainly been a challenge for current researchers, industries, and communities. Various industries, including finance and healthcare, require a rich resource-based platform for processing large amounts of data with cloud computing across fog architecture. The consumption of energy across fog servers relies on allocating techniques for services (user requests). It facilitates processing at the edge with the probability of interacting with the cloud. This article proposed energy-aware scheduling by using Artificial Neural Network (ANN) and Modified Multiobjective Job Scheduling (MMJS) techniques. The emphasis of the work is on the reduction of energy consumption rate with less Service Level Agreement (SLA) violation in fog computing for data centers. The result shows that there is a 3.9% reduction in SLA violation when a multiobjective function with Artificial Neural Network is applied.

Background: In the last decade, with the advancement of big data technology and the internet of things, Wireless Sensor Networks (WSN) have become fundamental for the success of a different range of applications especially those demanding massive data processing.

Objective: This paper investigates several tracking methods to introduce a novel cluster-based target tracking analysis model.

Methods: Some crucial factors of the cluster-based routing protocols are demonstrated, and a comparison among these different methods is conducted according to our taxonomy, such as cluster formation, predicate/proactive, target speed, single or multi-object tracking, boundary problem, scalability, energy efficiency, and communication cost. This can help the community of researchers by providing clear information for further study.

Results and Conclusion: The proposed paper compares the differences and similarities between the available approaches across different categories in terms of the cluster construction, clustering method, object speed, number of objects, boundary problem, and scalability. Finally, we can recognize some open issues that have so far gained little attention or are unexplored yet.

Background: Radio frequency identification (RFID) technology can be applied in identification, security and tracking system platforms due to its flexible and low-cost implementation. The sensing ability of this technology can also be used to monitor real-life environmental changes and physical phenomena. RFID is designed to work in open wireless communication. Therefore, this system can be attacked by different malware. Enhancing RFID with new security and privacy features isimportant at present.

Objective: The current work is a systematic mapping study on RFID security. The types, contributions, facets and activities of research on RFID security were plotted.

Method: The systematic mapping for a specific search are was done by identifying the number of RQs. These RQs help researchers obtain comprehensive related studies. The RQs must be selected carefully because they determine the research direction and help rapidly obtain the required information and studies.

Results: We gathered 2133 relevant studies and retained 92 primary papers after four filtering processes. We classified them into three facets. Results provide researchers and readers an overview of existing relevant studies and help them identify the properties in the focus area.

Conclusion: The systematic mapping study used to report the design, execution, tool, application and results of a Radio frequency identification (RFID). We systematically chose and deeply analyzed all concepts related (RFID) techniques and implementation methods which provide a complete about the (RFID) state and environment of studies.

Background: Antennas serve a vital aspect in modern wireless communication. Designing antennas with very high directivity is very important to solve the long-distance communication problem. Though regularly excited and evenly spaced linear antenna arrays delivers good directivity but also leads to problem related to higher side lobe. For diminishing the level of side lobe, the array can be constructed either by amending the excitation amplitudes non-uniformly with all physical spaces of the antenna elements keeping consistent or vice versa.

Methods: In this work, a novel mathematical objective function has been formulated. The objective function has been solved using a recently developed evolutionary optimization technique, i.e., Binary cat swarm optimization. So for better efficiency, the cat swarm optimization technique has been modified.

Results: The results have been compared with the popular algorithms like Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Cat Swarm Optimization (CSO) in terms of Side Lobe Level (SLL), achieved fitness and execution time. The proposed algorithm achieves 0.5dB, 1.7 dB and 3dB smaller SLL as compared to CSO, PSO and GA respectively. In addition to SLL, achieved fitness using BCSO is in the range of 0.001 which is smallest among the compared algorithms.

Conclusion: It was found that the modified version namely binary cat swarm optimization algorithm outperform other well-known evolutionary optimization algorithms.

Background: Gathering and scrutinizing the different types of logs are the vital steps in the forensic domain. Logs are commonly gathered by the cloud service providers or by some third party layers which are governed by the cloud service providers. Security of the logs is a crucial issue as the logs can be tampered accidentally or intentionally by an employee in the cloud service provider’s organization or by the forensic investigator.

Objective: The algorithm designed assists in verifying the tampering of the virtual instance logs which can be accidental or intentional. Verification process confirms that the confidentiality and integrity of the logs remains intact. Verification of the potential evidence for past logs is normally carried out by the forensic investigator and the auditor.

Methods: The uniqueness of the research conducted in this paper is a technique which employs the cuckoo filter, which is supportive in proving the integrity of the potential evidences for past logs at a faster pace. The probabilistic data structures cuckoo filter and the bloom filter also support the concealment of logs.

Results: The implemented system and the results observed in it, are very promising in the cloud forensic domain. The performance of the algorithm is better than the earlier system implemented with the log chain and the database.

Conclusion: The secure framework designed in this research paper aids in proving the integrity of the virtual instance logs. The evidence verification process supports concealment of data also.

Aims: The purpose of the study is to use Fast Voltage Stability Index to find out the weakest line of the system so that the weakest transformer of the system can be find out. Methods: In this paper, a technique is proposed to decide the priority selecting the out of service transformer for repair/replacement. Based on voltage stability, priority is assigned for repairing or replacing the particular transformer. Results: By using this method, a number of out of service transformers in the transmission line can be determined and then replaced or repaired. The technique has been implemented in MATLAB software, which is used to rank all the out of service transformer in the system. This MATLAB program has been developed to conduct load-flow studies including Voltage Stability Index. The FVSI proposed by Musirin et al. has been used in this work to rank the transformers which needs repair/ replacement. Transformer located at weakest line should be repaired first technically. Conclusion: The proposed method in this paper aims to improve the reliability and to manage the congestion of the transmission system by repairing or replacing out of service transformer.

Aim: The 5G LTE-Advanced (LTE-A) intended to provide increased peak data rates for the mobile users with the use of Carrier Aggregation (CA) technology. Due to need of uninterrupted bi-directional communication between the eNodeB and User Equipment (UE) in LTEA, Joint Scheduling Algorithm is considered as central research topic. Objective: A modified joint Uplink/ Downlink (UL/DL) Scheduling algorithm to meet on demands service request from the UEs is proposed in this paper. Methods: CA is used for calculate the weight factors for the bandwidth allocation among the mobile users based on the QoS Class Identifier (QCI). However due the huge amount of data flow in the indoor coverage yield introduction of the small cell called femtocells. Femtocells are randomly deployed in macro cell area in order to improve indoor coverage as well capacity enhancement. Results: Mixed types of traffic are considered ranging from real time to non real time flows and quality of service is evaluated in term of throughput, packet loss ratio, fairness index and spectral efficiency. The proposed modified joint user scheduling algorithm results better in delay among the end users due the reduction in the traffic load of the macro cell base station. Conclusion: Simulation results shows that, the proposed methodology suits best for the small scale network architecture with increased spectral efficiency and throughput among the UEs.

Objective: The conventional Ad Hoc On-Demand Distance Vector (AODV) routing algorithm, route discovery methods pose route failure resulting in data loss and routing overhead. In the proposed method, needs significant low energy consumption while routing from one node to another node by considering the status of node forwards the packet. So that while routing it avoids unnecessary control overhead and improves the network performance. Methods: Particle Swarm Optimization (PSO) algorithm is a nature- inspired, population-based algorithm. Particle Swarm Optimization (PSO) is a Computational Intelligence technique which optimizes the objective function. It works by considering that every member of the swarm contributes in finding the ideal solution by keeping a track of their own best known location and the best-known location of the group and keeps updating them whenever there is a change and hence minimizes the objective fitness function. The fitness function which we considered here is the Node lifetime, Link Lifetime and available Bandwidth. If these parameters are with good then status of node will be strong and hence routing of packet over those nodes will reduce delay and improves network performance. Result: To verify the feasibility and effectiveness of our proposal, the routing performance of AODV and PSO-AODV is compared with respect to various network metrics like Network Lifetime, packet delivery ratio and routing overhead and validated the result by comparing both routing algorithm using Network Simulator 2. The results of the PSO-AODV has outperformed the AODV in terms of low energy, less end to end delay and high packet delivery ratio and less control overhead. Conclusion: Here we proposed to use Particle Swarm Optimization in order to obtain the more suitable parameters for the decision making. The existing AODV protocol was modified to make a decision to recover from route failure; at the link failure predecessor node implementing PSO based energy prediction concept and using weights for each argument considered in the decision function. The fitness values for each weight were found through PSO basic form. We observed that the PSO showed satisfactory behaviour improvement than the performance of AODV for all metrics on the investigated scenarios.

Objective: The demand for Cellular based multimedia services is growing day by day, in order to fulfill such demand the present day cellular networks needs to be upgraded to support excessive capacity calls along with high data accessibility. Analysis of traffic and huge network size could become very challenging issue for the network operators for scheduling the available bandwidth between different users. In the proposed work a novel QoS Aware Multi Path scheduling algorithm for smooth CAC in wireless mobile networks. The performance of the proposed algorithm is assessed and compared with existing scheduling algorithms. The simulation results show that the proposed algorithm outperforms existing CAC algorithms in terms of throughput and delay. The CAC algorithm with scheduling increases end-to-end throughput and decreases end-to-end delay. Methods: The key idea to implement the proposed research work is to adopt spatial reuse concept of wireless sensor networks to mobile cellular networks. Spatial reusability enhances channel reuse when the node pairs are far away and distant. When Src and node b are communicating with each other, the other nodes in the discovered path should be idle without utilizing the channel. Instead the other nodes are able to communicate parallelly the end-to-end throughput can be improved with acceptable delay. Incorporating link scheduling algorithms to this key concept further enhances the end-to-end throughput with in the turnaround time. So, in this research work we have applied spatial reuse concept along with link scheduling algorithm to enhance end-to-end throughput with in turnaround time. The proposed algorithm not only ensures that a connection gets the required bandwidth at each mobile node on its way by scheduling required slots to meet the QoS requirements. By considering the bandwidth requirement of the mobile connections, the CAC module at the BS not only considers the bandwidth requirement but also conforming the constrains of system dealy and jitter are met. Results: To verify the feasibility and effectiveness of our proposed work, with respect to scheduling the simulation results clearly shows the throughput improvement with Call Admission Control. The number of dropped calls is significantly less and successful calls are more with CAC. The percentage of dropped calls is reduced by 9 % and successful calls are improved by 91%. The simulation is also conducted on time constraint and ratio of dropped calls are shown. The total time taken to forward the packets and the ration of dropped calls is less when compared to non CAC. On a whole the CAC with scheduling algorithms out performs existing scheduling algorithms. Conclusion: In this research work we have proposed a novel QoS aware scheduling algorithm that provides QoS in Wireless Cellular Networks using Call Admission Control (CAC). The simulation results show that the end-to-end throughput has been increased by 91% when CAC is used. The proposed algorithm is also compared with existing link scheduling algorithms. The results reveal that CAC with scheduling algorithm can be used in Mobile Cellular Networks in order to reduce packet drop ratio. The algorithm is also used to send the packets within acceptable delay.

Background and Objective: The Non-Orthogonal Multiple Access (NOMA) technology is a multi-access scheme that overcomes most of the disadvantages of its predecessor, the OMA technology. Specifically, NOMA technology supports massive connectivity of multiple users by employing the same non-orthogonal spectrum resource. In an uplink NOMA system with grant-free transmission mode, the Base Station (BS) is unaware of which users are active in the networks at a given time. Consequently, there is a need for mechanism to ensure successful recovery of users’ transmitted signals. This paper presents some new Multiuser Detector (MUD) schemes for uplink grant-free NOMA wireless communication networks with system’s model involving Multiple Measurement Vectors (MMV) rather than the Single Measurement Vector (SMV) that many previous works have considered. These MUDs include those that are based on differential Orthogonal Matching Pursuit (OMP), adaptive Simultaneous OMP (SOMP), compressive- multiple signal classification (MUSIC), and sequential compressive-MUSIC algorithms. Methods: The MUDs are employed in the detection of users’ signals in the uplink NOMA systems. Results and Discussion: Comparative performances of these MUDs with another one that is also based on the MMV system model, the SOMP-based MUD are presented for the scenarios when the system is under-loaded, fully loaded and over-loaded. Conclusion: The results suggest that the sequential compressive-MUSIC-based MUD, though shows weak performance at lower range of SNR, outperforms all the other MUDs including the SOMP-based MUD at higher SNR. Its performance is quite outstanding during the over-loaded scenarios, especially at higher SNR. However, its computational complexity is higher that the closely performing compressive-MUSIC-based MUD and SOMP-based MUD.

Background: MANET is a constrained environment having limited energy, restricted bandwidth, and unstable wireless connectivity, etc. It creates a high demand to design an efficient QoS routing protocol having a multi-criteria metric to make efficient routing decisions. Aim: The main aim of QoS based routing protocol EB-OLSR (Energy efficient and Bandwidth aware Optimized Link State Routing) is to achieve enhanced aggregate network throughput. Which is acquired by selecting QoS qualified efficient nodes to transmit data packets. EB-OLSR set out analogous efficient mobile nodes for routing by applying newly defined multi-criteria metric EPNI (Efficiency Parameters for Node Indexing) which estimates the node’s efficiency index on the basis of four QoS parameters that are unconsumed power, slothful period, queue length and residual bandwidth. Methods: We obtained a single node index for each mobile node through EPNI metric based on residual battery, node idle time, packet queue length and residual bandwidth. Results: EB-OLSR produced aggregate network throughput enhancement of 574 bits per second in comparison of MP-OLSR and 390.66 bits per second in comparison to MBQA-OLSR. Average End-to-End Delay for EB-OLSR is 0.41, 0.16 times less and Packet Delivery Ratio enhances 30.74%, 9.5% respectively. Conclusion: Experimental results proved that the EB-OLSR is an energy-efficient and bandwidth aware optimized link-state routing protocol, which successfully meets the main aim of this study i.e. throughput enhancement of mobile ad-hoc network. The EPNI metric is the major strength of the work which is used to get a single-valued weighted sum of multiple criteria.

Background: A novel method to detect the text region from the natural image using the discriminative deep feature of text regions is presented with deep learning concept in this manuscript. Objectives: Curve Text Detection (CTD) from the natural image is generally based on two different tasks: learning of text data and text region detection. In the learning of text data, the goal is to train the system with a sample of letters and natural images, while, in the text region detection, the aim is to confirm whether the detected regions are text region or not. The emphasis of this research is on the development of deep learning algorithm. Methods: A novel approach has been proposed to detect the text region from natural images which simultaneously tackles three combined challenges: 1) pre-processing of the image without losing text region; 2) appropriate segmentation of text region using their strokes, and 3) training of data. In pre-processing, image enhancement and binarization are done then morphological operations are defined with the Maximally Stable Extremal Region (MSER) based segmentation technique which operates on the basis of stroke region of text and then finds out the (Speed Up Robust Feature) SURF key point from those regions. Results: Based on the SURF feature, text region is detected from the images using a trained structure of Artificial Neural Network (ANN) which is based on deep learning mechanism. Conclusion: CTW-1500 dataset is used to simulate the proposed work and the parameters like Precision, Recall, F-Measure (H-mean), Execution time, Accuracy and Error Rate are computed and are compared with the existing work to depict the effectiveness of the work.

Background: In IoT (Internet of Things) environment, a number of sensors and networks exist and they have various and heterogeneous characteristics. Applications, which provides a variety of services based on the sensor networks, also have different service requirements. Therefore, a middleware that is located between sensor networks and application systems is needed for integrating two layers. Objective: This paper proposes a general-purpose middleware for providing intelligent services based on heterogeneous sensors existing in the IoT environment. Methods: The proposed middleware acquires and manages sensing data in real-time. The middleware stores and manages heterogeneous sensors, node, and network metadata. In addition, the middleware infers the situation based on ontologies and rules and provides intelligent services. Results: The paper has proposed integrated metadata to describe heterogeneous sensor, node and network information. The third is the intelligent service management system to provide sensor-based intelligent service to users. The paper has proposed the SS ontology for describing sensors and services and proposed a method for providing intelligent services using the SS ontology and rules. Of course, the three systems operate independently, so they can be used selectively as needed. This paper implemented a prototype system based on the proposed method. Conclusion: We expect that the proposed middleware can be used in various applications for sensorbased intelligent service processing. In the future, we plan to expand the method to provide an intelligent service by automatically gathering semantic data.

Background: Because of some inherent characteristics of MANETs such as infrastructural instability, limitations and shortcomings, multi-hop communication, wireless media and dynamic topology, routing has emerged as the most important challenge in these networks. This prompted a wealth of research which attempted to improve the routing quality through focusing on various qualitative criteria. Objective: However, these researches have not adequately addressed the applied characteristics of MANETs as the most important capability of such networks. In other words, application of these networks in different fields have warranted the development of different services with varying Quality-of-Service requirements. This requires the network to support the quality of various services in proportion with the varying qualitative requirements of transaction services. Methods: In order to efficiently address this issue, this research introduces an enhanced protocol dubbed MMSR-AOMDV based on the development of basic AOMDV protocol and reaping the benefits of Fuzzy Logic. MMSR-AOMDV is a double-step protocol that attempts to enable distinguishing transaction services and supporting the various services associated with the specific demands and requirements of each service based on the performance in each step. For this, MMSRAOMDV has been developed in a way to enable in the first step the assessment of qualitative indicators which are associated with the requirements of the services sent via utilizing multi-route routing and classification techniques, while the second step has been dedicated to offering effective support for multi-service routing quality thanks to the merits of Fuzzy Logic features. Results and Conclusion: The simulation of the proposed protocol using OPNET simulator revealed that in terms of end-to-end delays, packet lost, network throughput and data reception rate, MMSR-AOMDV significantly outperformed other corresponding methods.

Background: Nowadays, Wireless Sensor Network (WSN) plays an important role in various fields. The limited power capability of the sensor nodes in the WSN brings constraints on the performance of the network. Low Energy Adaptive Clustering Hierarchy (LEACH) is a promising protocol for WSN that suffers from higher energy consumption. Objective: The primary objective of this study is to give an alternate harvesting resource power to sensor nodes in the LEACH algorithm which can be equally capable of providing the same or sometimes better results. Methods: This study is based on real-time meteorological data. A real-time wind speed data is taken for the starting of a day to the end of the day on an hourly basis from the weather forecast. Now to convert this rotational energy into electrical energy, we used two types of wind turbines. For the proposed methodology, a micro wind turbine generator and 300watt wind turbine are used. Then this converted electrical energy is given to sensor nodes. For the clustering, the wind power operated nodes are given maximum preference to be elected as the cluster heads based on realtime wind meteorological data. We consider 10 wind-powered sensor nodes. As we increase the number of wind-powered sensor nodes in the network, the performance is increased in terms of a lifetime but then increases the complexity of the network. These wind-powered nodes remain alive in the network. Since the deployment of the sensor nodes is random, each simulation runs for 5 times and the average of first node dead, half node dead and last node dead is considered. Results: The experimental results for the micro wind turbine generator are compared based on with and without the MPPT controller. MPPT controller gives the maximum power by using the tip speed ratio control, power signal feedback control, and hill climb search control method. Therefore, the network lifetime should be higher for the MPPT based wind generator. Network lifetime and Energy consumption are compared for a micro wind turbine generator and 300watt wind turbine. Finally, the performance of the proposed system is compared with the modified solar LEACH implemented using real-time meteorological data. Conclusion: This paper has investigated the wind-based LEACH which uses the real-time meteorological data for the selection of the cluster head. Two types of wind generators are considered for the implementation and it is found that the performance of the commercial 300W wind turbine and the micro wind turbine with and without MPPT is almost similar since the data from both wind turbines are given on hourly basis. The performance of the wLEACH is compared with the sLEACH which shows that the network lifespan of the wLEACH is also nearly the same compared to the sLEACH. However, it was found that wind power generation is cheaper and efficient than solar power generation. Therefore, it is inferred that this proposed wLEACH provides a costefficient solution.

Aims: This paper provides an efficient but simple designed V-Shaped microstrip array antenna on a RT duroid substrate of dimension 50 mm× 40 mm × 1.6 mm. Objective: By considering the ratio of the length of one leg of the V-element and wavelength of the desired frequency, the angle between two legs of V-Patch has been determined. Methods: For a more efficient outcomes, an array design of 4-elements is made and its comparison with single element is done. A simple line feed technique has been used, with feedline width of 3mm. Results: The proposed structure is simulated by using Ansys HFSS software and S-Parameter, antenna gain, directivity, Standing wave ratio and surface current distribution have been determined. Unlike conventional patches, the array contains a separation between two consecutive V-Elements in the shape of a rectangular patch termed as Element Separation Band (ESB) and it plays an important role in modifying the antenna gain and directivity. Conclusion: This antenna produces a return loss of -39.387 dB at 60.58 GHz frequency to cater the present demand of 60 GHz Wi-Gig and WPAN.

Background & Objective: A novel bandstop filter using rising sun shaped structure embedded in substrate is presented. Methods: The proposed filter is inspired from metamaterial. Through parametric analysis, it is found that proposed filter exhibits transmission zeros with great design flexibility through tuning the geometry parameters of rising structure in a small range. The centre frequency of filter is 3.5GHz. After optimization, the filter is fabricated and tested using network analyzer. Its simulated stop band fractional 3 dB bandwidth is 12.5% and measured stopband fractional bandwidth is -13dB. Results and Conclusion: The measured results are little bit shifted that may because of fabrication related errors.

Background: Recently the vast improvement in wireless communications has occurred that satisfies the IEEE standard Wireless LAN (WLAN) ideograms in the range of 2.4~2.5 GHz. WLAN is usually used in the wireless applications and devices such as tab, PCs, and iPhones. Among the various techniques and proposed structure for better execution, Imitation Magnetic Electrode (IME), Electromagnetic Band Cavity (EBC), divided Loop Resonator (VLR), Photonic Group Cavity (PGC), etc. have been used. Objective: This research explores the effect of a proposed Completing Equilateral Trilateral Censored Separated Roar Resonator (CETCSRR) antenna at 2.4 GHz for better coverage in WLAN application. Methods: The dual ETCSRR and single CETCSRR structure has been cut from the top of the patch. The performance has been study in terms of twelve rotational TCSRR pair, number of TCSRR, size of TCSRR and distance between DTCSRRs structures. Finally proof the RL design and its equivalent circuit by using CST and ADS software. Results: Simulated results for dual CETCSRR at resonant frequency 2.441 GHz show RL of - 36.084 dB and gain of 7.75 dB has been obtained. The antenna split gap stores, charges, and works as a capacitor that accelerates gain, radiation pattern with radio frequency Tx and Rx to use as a WLAN scheme. Conclusion: The ETCSRR designed antenna reverberates between 2.43GHz to 2.45 GHz ISM bands along with the alignment and addition of ETCSRR cell. The proposed design is helpful for frequency harmonic explanation as well as predictable upgrade in bandwidth and impression of gain and directivity.

Aims: This paper presents an investigation of image transmission using SC-FDMA system over wireless fading channels. Background: A comparison is performed between the performance of the wireless transmitted image over 3GPP LTE channel (vehicular and pederstain) and mmWaves measured channel at 29.5 GHz. Objectives: One of the important benefits of this work is the real measurement obtained at 29.5 GHz under NLOS scenario using an original sounder based on the ensuring of phase coherence between the transmitter and the receiver. Methods: Cameraman image has been transmitted over the SC-FDMA with different subcarriers mapping schemes. PSNR and MSE are the metrics used to evaluate the performance of the image transmitted under Matlab simulation where their values of the received image are calculated for different SNR values. Results and Conclusion: The simulation results show that the image transmission over mmWaves channel works and the best values of PSNR are attained beyond 12 dB and 14 dB for LSC-FDMA and ISC-FDMA respectively.