There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

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Table Of Integrals Series And Products

The distributed nature and dynamic topology of Wireless Sensor Networks (WSNs) introduces very special requirements in routing protocols that should be met. The most important feature of a routing protocol, in order to be efficient for WSNs, is the energy consumption and the extension of the network's lifetime. During the recent years, many energy efficient routing protocols have been proposed for WSNs. In this paper, energy efficient routing protocols are classified into four main schemes: Network Structure, Communication Model, Topology Based and Reliable Routing. The routing protocols belonging to the first category can be further classified as flat or hierarchical. The routing protocols belonging to the second category can be further classified as Query-based or Coherent and non-coherent-based or Negotiation-based. The routing protocols belonging to the third category can be further classified as Location-based or Mobile Agent-based. The routing protocols belonging to the fourth category can be further classified as QoS-based or Multipath-based. Then, an analytical survey on energy efficient routing protocols for WSNs is provided. In this paper, the classification initially proposed by Al-Karaki, is expanded, in order to enhance all the proposed papers since 2004 and to better describe which issues/operations in each protocol illustrate/enhance the energy-efficiency issues.

Energy-Efficient Routing Protocols in Wireless Sensor Networks: A Survey

Providing ubiquitous connectivity to diverse device types is the key challenge for 5G and beyond 5G (B5G). Unmanned aerial vehicles (UAVs) are expected to be an important component of the upcoming wireless networks that can potentially facilitate wireless broadcast and support high rate transmissions. Compared to the communications with fixed infrastructure, UAV has salient attributes, such as flexible deployment, strong line-of-sight connection links, and additional design degrees of freedom with the controlled mobility. In this paper, a comprehensive survey on UAV communication toward 5G/B5G wireless networks is presented. We first briefly introduce essential background and the space–air–ground integrated networks, as well as discuss related research challenges faced by the emerging integrated network architecture. We then provide an exhaustive review of various 5G techniques based on UAV platforms, which we categorize by different domains, including physical layer, network layer, and joint communication, computing, and caching. In addition, a great number of open research problems are outlined and identified as possible future research directions.

UAV Communications for 5G and Beyond: Recent Advances and Future Trends

Providing ubiquitous connectivity to diverse device types is the key challenge for 5G and beyond 5G (B5G). Unmanned aerial vehicles (UAVs) are expected to be an important component of the upcoming wireless networks that can potentially facilitate wireless broadcast and support high rate transmissions. Compared to the communications with fixed infrastructure, UAV has salient attributes, such as flexible deployment, strong line-of-sight (LoS) connection links, and additional design degrees of freedom with the controlled mobility. In this paper, a comprehensive survey on UAV communication towards 5G/B5G wireless networks is presented. We first briefly introduce essential background and the space-air-ground integrated networks, as well as discuss related research challenges faced by the emerging integrated network architecture. We then provide an exhaustive review of various 5G techniques based on UAV platforms, which we categorize by different domains including physical layer, network layer, and joint communication, computing and caching. In addition, a great number of open research problems are outlined and identified as possible future research directions.

Device-to-Device (D2D) communication has emerged as a promising technology for optimizing spectral efficiency in future cellular networks. D2D takes advantage of the proximity of communicating devices for efficient utilization of available resources, improving data rates, reducing latency, and increasing system capacity. The research community is actively investigating the D2D paradigm to realize its full potential and enable its smooth integration into the future cellular system architecture. Existing surveys on this paradigm largely focus on interference and resource management. We review recently proposed solutions in over explored and under explored areas in D2D. These solutions include protocols, algorithms, and architectures in D2D. Furthermore, we provide new insights on open issues in these areas. Finally, we discuss potential future research directions.

A Survey of Device-to-Device Communications: Research Issues and Challenges

The Internet-of-Things (IoT) is the future of the Internet, where everything will be connected. Studies have revealed that fog/edge computing-based services will play a major role in extending the cloud by carrying out intermediary services at the edge of the network. Fog/edge computing-based IoT’s (FECIoT) distributed architecture enhances service provisioning along the Cloud-to-Things continuum, thereby making it suitable for mission-critical applications. Furthermore, the proximity of fog/edge devices to where the data is produced makes it stand-out in terms of resource allocation, service delivery, and privacy. From the business perspective, FECIoT will lead to a boom and spring up of small-to-medium-sized enterprises, thereby encouraging inclusion for all. To this end, we present a comprehensive survey on state-of-the-art IoT literature over the period 2008–2018 and propose the FECIoT framework which covers the enabling technologies, services, and open research issues. A tutorial approach is employed, progressing from basic to more advanced concepts within the IoT domain. Lastly, we show how FECIoT can be deployed in real-life cyber-physical systems, such as the intelligent transportation system, smart grid, smart health-care, smart homes, and smart environment.

Fog/Edge Computing-Based IoT (FECIoT): Architecture, Applications, and Research Issues

Intelligent transportation systems (ITS) are fast moving from connected vehicles on the road to autonomous driving. Vehicular communication is a key enabler for the deployment of advanced ITS applications such as platooning and remote vehicle control. DSRC and C-V2X are two key wireless technologies that will play a vital role in the implementation and deployment of an autonomous transport system. We review the current standardization efforts for both of these technologies with a focus on MAC and PHY layers. The automotive industry and research community have been working on new standards -- IEEE 802.11bd (for DSRC) and 5G NR V2X (for C-V2X) -- to meet the high reliability and low latency requirements of autonomous driving. We also highlight the major changes that have been made to previous standards such as IEEE 802.11p and C-V2X. Finally, we present open challenges that need to be addressed to further improve these standards for vehicular communications.

Vehicular Communications for ITS: Standardization and Challenges

Fog computing is a promising technology that can provide storage and computational services to future 6G networks. To support the massive Internet of Things (IoT) applications in 6G, fog computing will play a vital role. IoT devices and fog nodes have energy limitations and hence, energy-efficient techniques are needed for storage and computation services. We present an overview of massive IoT and 6G enabling technologies. We discuss different energy-related challenges that arise while using fog computing in 6G enabled massive IoT. We categorize different energy-efficient fog computing solutions for IoT and describe the recent work done in these categories. Finally, we discuss future opportunities and open challenges in designing energy-efficient techniques for fog computing in the future 6G massive IoT network.

Energy efficient fog computing for 6G enabled massive IoT: Recent trends and future opportunities

A research study was conducted to find the effect of Zingiber officinale, Carum apticum, withania somnifera, Trigonella Foenum Graecum, Silybum marianum, Allium sativum and Berberis lyceum, on the growth performance of broiler chicks A total of 240 day old chicks were purchased and were reared for 35 days in summer month Feed and water were provided ad libitum Total numbers of chicks were divided into four groups (A, B, C and D) each having 60 chicks Each group was further subdivided into three groups (replicates) each having 20 chicks Aqueous extract of these plants was mixed at the rate of 5, 10 and 15 ml/lit with water offered to group B, C and D, respectively while group A served as a control Mean weight gain, dressing percentage, breast weight and leg weight were significantly high (P<005) in group C with lower FCR (Feed Conversion Ratio) while mean feed intake was significantly high in control group It was concluded from this study that these locally available plants if offered as supplement to broiler may result in improvement of broiler efficiency

Muhammad Awais Javed

Papers

A Survey of Device-to-Device Communications: Research Issues and Challenges

Fog/Edge Computing-Based IoT (FECIoT): Architecture, Applications, and Research Issues

Vehicular Communications for ITS: Standardization and Challenges

Energy efficient fog computing for 6G enabled massive IoT: Recent trends and future opportunities

Effect of aqueous extract of plant mixture on carcass quality of broiler chicks.