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Dynamic navigation devices like Global Positioning Systems (GPSs) are deployed for various purposes in different areas and these devices are usually the central point of interest of various groups like hackers to exploit the data sent and received by GPS systems. The GPS data is usually manipulated using spoofing attacks. This paper proposes a robust solution to the spoofing attacks carried out to manipulate, control and modify the location sharing of smart containers. The primary focus of this paper is securing the GPS information shared by the smart containers. The location shared by the smart containers is secured by encrypting it with Pretty Good Privacy (PGP) algorithm to avoid spoofing attacks in particular. The encrypted GPS location is sent across any communication channel. The receiver side will decrypt the encrypted GPS location at the receiving end. Hence, using this method of PGP encryption will ensure the safe and secure sharing of GPS location by the smart containers. As a result, GPS security has been improved by 80%.

The ability to check the location of both static and dynamic devices is improving increasingly with each passing day. To track locations of both static and dynamic machines, Global Positioning System (GPS) is used to exchange the location between the sender and the receiver. However, there are still challenges in the sage and secure transmission and reception of GPS location. The most common challenge is spoofing attacks data. This paper proposes the implementation of a Pretty Good Privacy (PGP) encryption algorithm to ensure the safety of GPS packets shared across the communication channels. The GPS location is first encrypted and subsequently sent across a communication channel, which is strong encryption and cannot be decrypted by an unauthorized user.

This work focuses on a compact circularly polarized wideband rectangular dielectric resonator antenna (RDRA) for X-band wireless applications. The wideband response of the RDRA is initially generated by a coaxial probe, a compact RDR, an air gap in the DR and a slot of rectangular shape in the ground. The circular polarization is achieved via incorporation of a unique feeding mechanism. The edge feeding of the RDRA with a coaxial probe generates the orthogonal modes in RDRA that make the design polarized circularly. The axial ratio performance is improved by adding a copper strip on the top of the DR. To validate the simulated results, the prototype design is fabricated and measured results are noted. For −10 dB reference value, the prototype has 59.74% impedance bandwidth (8.45–14.09 GHz). For 3 dB reference value of the axial ratio, the prototype has 9.24% Circular Polarization (CP) performance (10.084–11.084 GHz). The design has 6.5 dBic peak gain and 95.5% peak efficiency. Results show that simulated results are in close agreement with the measured results.

The development of the 5G mobile communication standard attempts to meet the future needs of data users. The impact of Cyber Physical Systems (CPS) is crucial in Internet of Things (IoT) and other emerging technologies. The design of medium access mechanisms for CPS such as radio resource scheduling schemes has a significant effect on network performance. Recent literature shows that limited work is available on uplink scheduling schemes, particularly in the 5G domain. Planning a network that can address the modern needs of users entails efficient CPS scheduling mechanisms such that resources are amicably distributed between users of contrasting priorities. The prime focus of this work is to design and develop an uplink radio resource scheduling framework for CPS-based future networks such as 5G. In the designed framework, scarce radio resources are sought to be distributed efficiently according to the service-based needs of users. The proposed scheduling scheme is a service aware (SA) scheduler designed for CPS in accordance with the 5G network peculiarities, intended to achieve higher throughput and reduced latency. The proposed SA scheduler supports multi-bearer traffic and is capable of providing resources in adverse channel conditions in an efficient manner. The SA scheduling mechanism&rsquo, s performance is evaluated and compared with renowned scheduling algorithms such as blind equal throughput (BET), maximum throughput (MT), and proportional fair (PF) scheduling schemes. The simulation results obtained in a cellular environment demonstrate that the SA scheduler achieves acceptable cell throughput and end-to-end delay results in all scenarios and out-performs other contemporary scheduling schemes.

Internet of Things (IoT) as refers to a network of devices that have the ability to connect, collect and exchange data with other devices over the Internet. IoT is a revolutionary technology that have tremendous applications in numerous fields of engineering and sciences such as logistics, healthcare, traffic, oil and gas industries and agriculture. In agriculture field, the farmer still used conventional agriculture methods resulting in low crop and fruit yields. The integration of IoT in conventional agriculture methods has led to significant developments in agriculture field. Different sensors and IoT devices are providing services to automate agriculture precision and to monitor crop conditions. These IoT devices are deployed in agriculture environment to increase yields production by making smart farming decisions and to collect data regarding crops temperature, humidity and irrigation systems. However, the integration of IoT and smart communication technologies in agriculture environment introduces cyber security attacks and vulnerabilities. Such cyber attacks have the capability to adversely affect the countries’ economies that are heavily reliant on agriculture. On the other hand, these IoT devices are resource constrained having limited memory and power capabilities and cannot be secured using conventional cyber security protocols. Therefore, designing robust and efficient secure framework for smart agriculture are required. In this paper, a Cyber Secured Framework for Smart Agriculture (CSFSA) is proposed. The proposed CSFSA presents a robust and tamper resistant authentication scheme for IoT devices using Constrained Application Protocol (CoAP) to ensure the data integrity and authenticity. The proposed CSFSA is demonstrated in Contiki NG simulation tool and greatly reduces packet size, communication overhead and power consumption. The performance of proposed CSFSA is computationally efficient and is resilient against various cyber security attacks i.e., replay attacks, Denial of Service (DoS) attacks, resource exhaustion.

Cultivation of olive trees for the past few years has been widely spread across Mediterranean countries, including Spain, Greece, Italy, France, and Turkey. Among these countries, Spain is listed as the largest olive producing country with almost 45% of olive oil production per year. Dedicating land of over 2.4 million hectares for the olive cultivation, Spain is among the leading distributors of olives throughout the world. Due to its high significance in the country's economy, the crop yield must be recorded. Manual collection of data over such expanded fields is humanly infeasible. Remote collection of such information can be made possible through the utilization of satellite imagery. This paper presents an automated olive tree counting method based on image processing of satellite imagery. The images are pre-processed using the unsharp masking followed by improved multi-level thresholding-based segmentation. Resulting circular blobs are detected through the circular Hough transform for identification. Validation has been performed by evaluating the proposed scheme for the dataset formed by acquiring images through the “El Sistema de Información Geográfica de Parcelas Agrícolas”viewer over the region of Spain. The proposed algorithm achieves an accuracy of 96% in detection. Computation time was recorded as 24 ms for an image size of 300 × 300 pixels. The less spectral information is used in our proposed methodology resulting in a competitive accuracy with low computational cost in comparison to the state-of-the-art technique.

Video recorders record the output of each security camera. After an incident, the video footage can be used for evidence by locating a suspect or criminal for a crime. A manual scan of the video footage requires a considerable amount of manpower and time, a luxury which cannot be afforded when tracking down a person of interest (POI). An automated system is proposed in this paper which aims at finding the desired POI through the available volume of video data quickly and accurately. It is visualized to go through all the available videos and detect the POI using facial recognition. Thereafter, it would create a video montage of all the desired frames and incorporate time and location information to produce a path map followed by the POI. The proposed system reduces the human burden, human error and reduces the time taken when searching the POI manually. Validation has been performed on various video data collected by ourselves as well. The results depict that the proposed system is able to correctly identify POI with an accuracy of 86% for video data captured in a constrained environment. Videos captured by a cell phone in an unconstrained environment result in an accuracy of around 80%. Real video tested in our university campus revealed the proposed system is capable of generating tracking information for POI effectively.

Wireless Body Area Networks (WBANs) and Wireless Local Area Networks (WLANs) have been widely regarded as solution providers for future Cyber-Physical Systems (CPS)-based ehealthcare amenities. The IEEE 802.11 standard specifies media access protocols in wireless networks, along with channel access methods. WBANs are expected to improve the existing healthcare services significantly, but several research challenges also have to be tackled for apt utilization of the technology. Guarantee of Quality-of-Service (QoS) differentiation between various health parameters, such as temperature and blood pressure, during mobility is a major challenge for the provision of ehealthcare services. The scheme proposed in this paper for the Mobile Wi-Fi based connectivity of WBANs is designed to provide QoS-based priorities for ehealthcare subscribers by altering the Contention Window (CW) for different applications of patient health monitoring. The relationship between CW and QoS is utilized to achieve efficient resource assignment. Three different health parameters, i.e., ECG (Electrocardiogram), BP (blood pressure) and temperature. are monitored using medical CPS in this work. The performance evaluation results, such as end-to-end packet delay and throughput for various data traffic classes reveal that the proposed scheme improves QoS provision.

The information technology’s new revolution is Internet of Things (IoT), where physical world is connected to the internet. IoT applications are diversified such as smart health, smart industry, smart homes and most importantly smart logistics for perishable items conservation. Although IoT devices have revolutionized world but due to their constrained nature they are at the cost of a greater risk of personal data loss, security breaches and misuse. In this research, a review is presented for proposing two state of the art modules i.e. communication model of smart logistics and security of IoT devices in Smart Logistics. As the smart logistics have perishable items i.e. fruits, vegetables, meat, medicine, chemicals, and cosmetics etc. which are sensitive to temperature, humidity and pressure etc. If the sensors monitoring these items have been handled abnormally due to security attacks, it will give huge loss. Therefore, security of smart logistics is of paramount importance in this research. In order to expedite research in this emergent area of IoT, in this research paper a brief review on progress of IoT in smart logistics, and its security has been presented.

IoT data traffic in future mobile networks is expected to grow significantly and, thus, pose challenges for service providers. IoT traffic is anticipated to be in the form of huge number of small data packets. These packets would consume radio resources inadequately and result in reduced spectral efficiency. This paper proposes a unique application of packet aggregation in mobile networks for enhanced spectral efficiency. Additionally, the timer mechanism for avoiding long delays is also incorporated to further improve the system performance. Results indicate that improvement in spectral efficiency would help in increased system capacity.

The ever growing space between the high-speed processor and slower main memory has always remained a performance bottleneck. Attempts have been made to address this challenge through the advent of smarter memories, an improved memory hierarchy, and deployment of high speed bus controllers. Another important dimension is to add cache units to the processor in order to benefit from the temporal and spatial, and even instruction locality and therefore, reduce the processormemory gap that ultimately results in a performance boost. In this paper, we demonstrate that increasing the cache size in order to reduce the capacity based misses results in further optimizing the performance. This results in increasing the associativity and block size and thus, reduce the conflict and compulsory based misses. We discuss the cache parameters set to achieve the minimum miss rate for the simpleScaler suite including Rijndael, Sha, Compress, Go, and Dijkstra benchmarks. Explicitly, we reduce the miss rate by using different cache configurations such as increasing the cache size, altering the block size, and varying the associativity. Notably, we achieve a minimal possible miss rate for the Rijndael benchmark, which is 104. The results show the validity of an n size cache and x associativity, which is equal to an n/2 cache size and 2x associativity – 2: 1 cache rule of thumb.

In this work, a multiband frequency reconfigurable Dielectric Resonator Antenna for different wireless protocols has been discussed. The overall design consists of Dielectric Resonator (DR) placed on Fr4 substrate. The resonator is excited by CPW (coplanar waveguide). The feedline, ground and radiator are positioned on the same surface. The overall design is low profile because of the reduced height of the DR. The DR has relative permittivity $\left(\varepsilon_{\mathrm{r}}\right)$ of 15. The dual band design is reconfigured to other four bands with the help of two switching configurations. The resonant frequencies are reconfigured between 1.2 GHz to 6.5 GHz. The substrate FR4 has a thickness of 1.6mm and 0.002 tangent loss. The ground plane has the dimensions of 50×45 mm2. The DR has an height of 2mm. Two ideal switches SI and S2 are placed on the two sides of the feedline. The combination of these two ideal RF PIN diodes is used to obtain three switching arrangements. A fourth possible arrangement is excluded as it disconnects the DRA from the feedline. The switching arrangements are ON-ON, ON-OFF and OFF-ON. In ON-ON state, the two achieved resonance frequencies are 4.27 GHz (WBAN) and 5.64 GHz (WLAN). In ON-OFF state the obtained resonance frequencies are 2.1 GHz (LTE) and 5.47 GHz (WLAN). For ON-OFF state, the two resonance frequencies are 2.16 GHz (LTE) and 5.73 GHz (WLAN). The simulated values for all the switching configuration confirm the potential of the prototype for use in the targeted wireless protocols.

All over the world, road congestion is among the most prevalent transport challenges usually in urban environments which not only increases fuel consumption and emission of harmful gases, but also causes stress for the drivers. Intelligent Transportation System (ITS) enables a better use of the infrastructure by connecting vehicles to other vehicles as well as infrastructure and thus delivers a faster communication opportunity to ensure safe and secure driving. Machine-to-machine (M2M) communication is one of the latest information and communication technologies which offers ubiquitous connectivity among several smart devices. The use of mobile (cellular) M2M communications has emerged due to the wide range, high reliability, increased data rates, decreased costs as well as easy and short-term deployment opportunities. Since the radio spectrum is a scarce resource, M2M traffic can potentially degrade the performance of mobile networks due to the large number of devices sending small-sized data. This paper presents an efficient data multiplexing scheme by using Long-Term Evolution Advanced (LTE-Advanced) Relay Nodes, which aggregates M2M traffic to maximize radio resource utilization. Extensive system-level simulations are performed using an LTE-Advanced-based model developed in the RIVERBED modeler to evaluate the performance of the proposed data multiplexing scheme. Simulation results show that approximately 40 % more smart M2M devices used in ITS and logistics are served per LTE-Advanced cell under the present system settings.

Artificial Intelligence (AI) and Machine Learning (ML) are envisaged to play key roles in 5G networks. Efficient radio resource management is of paramount importance for network operators. With the advent of newer technologies, infrastructure, and plans, spending significant radio resources on estimating channel conditions in mobile networks poses a challenge. Automating the process of predicting channel conditions can efficiently utilize resources. To this point, we propose an ML-based technique, i.e., an Artificial Neural Network (ANN) for predicting SINR (Signal-to-Interference-and-Noise-Ratio) in order to mitigate the radio resource usage in mobile networks. Radio resource scheduling is generally achieved on the basis of estimated channel conditions, i.e., SINR with the help of Sounding Reference Signals (SRS). The proposed Non-Linear Auto Regressive External/Exogenous (NARX)-based ANN aims to minimize the rate of sending SRS and achieves an accuracy of R = 0.87. This can lead to vacating up to 4% of the spectrum, improving bandwidth efficiency and decreasing uplink power consumption.

In a network topology, where 5G (mm Waves) have better coverage footprint compared to 4G (LTE or LTE-A) technology, mobile devices would generally be handed over from 4G to 5G. In this work, a supervised intelligent prediction technique for improved handover success rate (HSR) from 4G to 5G technology is proposed. The technique is applicable for base stations enabled with sub-6-GHz and mm-wave bands. This technique is novel since it can predict HSR even before switching to 5G radio circuitry or initiating its measurement gap for acquisition of mm-wave reference signal received power (RSRP) unlike conventional algorithms. Thus, preempting all handovers which are likely to fail will provide improvements in latency, delay, and handover success rate, as well as decrease call drops. Therefore, this research work answers previous research shortcomings and can unleash applications of supervised intelligent algorithms for predicting the HSR from 4G to 5G. The proposed algorithm is validated by showing improvements obtained through simulation results performed using Python-based framework. The proposed algorithm is tested for reliability with increasing parameters such as the intensity number of UEs and simulation time. Improvements in standard handover algorithm are also proposed.

The ever-growing Internet of Things (IoT) data traffic is one of the primary research focuses of future mobile networks. 3rd Generation Partnership Project (3GPP) standards like Long Term Evolution-Advanced (LTE-A) have been designed for broadband services. However, IoT devices are mainly based on narrowband applications. Standards like LTE-A might not provide efficient spectrum utilization when serving IoT applications. The aggregation of IoT data at an intermediate node before transmission can answer the issues of spectral efficiency. The objective of this work is to utilize the low cost 3GPP fixed, inband, layer-3 Relay Node (RN) for integrating IoT traffic into 5G network by multiplexing data packets at the RN before transmission to the Base Station (BS) in the form of large multiplexed packets. Frequency resource blocks can be shared among several devices with this method. An analytical model for this scheme, developed as an r-stage Coxian process, determines the radio resource utilization and system gain achieved. The model is validated by comparing the obtained results with simulation results.

Consensus based control of multi-agent systems has a widespread applications in many fields. For example, autonomous computing, wireless sensor networks and robotics etc. It has several interesting results for clustering in data mining and Economics dispatch problem in distributed electric generation. A lot of theoretical analysis have been applied for such problems using consensus approach but still a practical approach to consensus based control of multi-agent systems is needed. This paper presents theoretical as well as practical systems for smart grid using consensus algorithm. Economic dispatch problem which is the major issue in smart grid is resolved through distributed consensus approach. For experimental purpose, a framework of Arduino IDE is selected for analysis, communication and simulation. Each Arduino board is an intelligent and autonomous agent that is in communication with all its neighbour’s nodes for adapting changes in demand and generation of power in Smart grid. Moreover, a dynamically changing behaviour of the systems is also in focus of this paper.

Long-Term Evolution employs a hard handover procedure. To reduce the interruption of data flow, downlink data is forwarded from the serving eNodeB (eNB) to the target eNB during handover. In cellular networks, unbalanced loads may lead to congestion in both the radio network and the backhaul network, resulting in bad end-to-end performance as well as causing unfairness among the users sharing the bottleneck link. This work focuses on congestion in the transport network. Handovers toward less loaded cells can help redistribute the load of the bottleneck link; such a mechanism is known as load balancing. The results show that the introduction of such a handover mechanism into the simulation environment positively influences the system performance. This is because terminals spend more time in the cell; hence, a better reception is offered. The utilization of load balancing can be used to further improve the performance of cellular systems that are experiencing congestion on a bottleneck link due to an uneven load.