Landfills and open dumping sites around the world are adding to the global warming issue. This is because of the existence of the main greenhouse gases in landfill gas (LFG); namely, methane (CH4) ...and carbon dioxide (CO2). The current study was focused on the determination of air emissions from the Muhammad wala dump site. This site was constructed in 1992 and expected to have lifespan of 28 years. Utilizing LandGEM software, the landfill emissions were estimated with taking into consideration the 60% content of methane, the methane generation rate constant of 0.02125 year−1, and methane generation potential capacity constant of 23.25 m3/Mg. The outcomes of this study indicated that the maximum volume of emitted gas is at the next year after the site closure (2021). It was estimated that total volume of LFG, methane, carbon dioxide, and non-methane organic compounds were 2.257 × 10+08, 1.354 × 10+08, 9.026 × 10+07, and 5.416 × 10+05 m3/year, respectively.
Light intensity, temperature, and humidity are key factors affecting photosynthesis, respiration, and transpiration. Among these factors, temperature is a crucial parameter to establish an optimal ...greenhouse climate. Temperature can be controlled by using an appropriate climate screen, which has a considerable impact on crop quantity and quality. The precise measurements of longwave radiative properties of screens are vital to the selection of the most suitable screen for greenhouses so that the desired temperature and a favorable environment can be provided to plants during nighttime. The energy-saving capability of screens can also be calculated by using these properties as inputs in a physical model. Two approaches have been reported so far in the literature for the measurement of these properties, i.e., spectrophotometry and wideband radiometry. In this study, we proposed some modified radiation balance methods for determining the total hemispherical longwave radiative properties of different screens by using wide-band radiometers. The proposed method is applicable to materials having zero porosity, partial opacity, and asymmetric screens with 100% solidity. These materials were not studied previously under natural conditions. The existing and proposed methods were applied and compared, and it was found that the radiometric values obtained from the developed methodology were similar to those previously reported in the literature, whereas the existing method gave unstable results with zero reflectance.
Network establishment and management in the data center need a considerable investment of time and money. To increase the cost productivity of networks, maximizing the utilization of network ...resources is mandatory. Many network inconsistencies may occur due to the utilization of maximum link capacity. Nowadays, Fat-Tree topology is a popular network architecture in data center networks therefore many researchers are designing routing algorithms for fat-tree topology by adopting load balancing methods. The inefficient way of obtaining network traffic statistics from network devices is a major problem to achieve load balancing traditionally. Software-Defined Network (SDN) platform provides researchers, an environment to develop a user-defined routing algorithm that can be flexible as well as cost-efficient. In this paper, an SDN based system has been proposed for Fat-Tree topology that provides a solution that enables networks to make effective resource utilization and minimize the maximum link capacity utilization of network using intent-based networking (IBN). The proposed system provides a permanent unique path from source to destination that allows traffic to flow uniformly and enables all the links to be offloaded by providing them with equal traffic share proactively. By taking a proactive approach which is inherence of an IBN, the proposed system provides the secure channel to provision the host in network with load balancing capability in the running network by restricting illegal in-premise access to the network.
The fifth-generation mobile network presents a wide range of services which have different requirements in terms of performance, bandwidth, reliability, and latency. The legacy networks are not ...capable to handle these diverse services with the same physical infrastructure. In this way, network virtualization presents a reliable solution named network slicing that supports service heterogeneity and provides differentiated resources to each service. Network slicing enables network operators to create multiple logical networks over a common physical infrastructure. In this research article, we have designed and implemented an intent-based network slicing system that can slice and manage the core network and radio access network (RAN) resources efficiently. It is an automated system, where users just need to provide higher-level network configurations in the form of intents/contracts for a network slice, and in return, our system deploys and configures the requested resources accordingly. Further, our system grants the automation of the network configurations process and reduces the manual effort. It has an intent-based networking (IBN) tool which can control, manage, and monitor the network slice resources properly. Moreover, a deep learning model, the generative adversarial neural network (GAN), has been used for the management of network resources. Several tests have been carried out with our system by creating three slices, which shows better performance in terms of bandwidth and latency.
Summary
Nowadays, the continuously increasing demand for high data traffic and providing different quality of services (QoS) to the customer are very challenging tasks for all network operators. In ...the last few years, mobile data traffic is increased to a significant extent and half of the traffic is provided through WiFi technology which is known as WiFi offloading. To overcome the increasing traffic demand, WiFi offloading is the best option to reduce the burden of cellular networks. So, by aggregating existing indoor WiFi technology to the cellular network increases the network capacity and provides better QoS to customers. In this article, we propose and implement the LTE‐WiFi aggregation system where eNodeB is responsible for the aggregation of the WiFi access point without modifying the core network. Furthermore, the proposed system is integrated with the mobile‐CORD (M‐CORD) platform which leverages software defined networking (SDN), network function virtualization (NFV), and cloud technologies for providing a 5G environment. M‐CORD platform has three main modules: service orchestrator (XOS), SDN controller ONOS, and OpenStack. One of the important features of M‐CORD is to provide virtualized core network functions that enable the users to automatically customize, monitor, and control the resources of the network. Due to ONOS controller support, we can easily scale up the network instances by giving the configurations to service orchestrator XOS of the M‐CORD. The implementation of the proposed system is based on the OpenAirInterface (OAI) platform which provides open sources implementation of core and access networks. The aggregation of both LTE and WiFi technologies is done at the PDCP layer in a very tight coupling way. Moreover, we test our proposed system with three kinds of policies for UDP and TCP traffic: LTE only, WiFi only, and LTE‐WiFi aggregated. The experimental results show that our proposed LTE‐WiFi aggregated system gives better performance and provides high bandwidth as compared to the LTE network.
The Figure presents the proposed system architecture, which is deployed in two phases: the first phase consists of the deployment of the LWA system in a very tight coupling fashion in which WiFi AP is directly connected to eNodeB and eNodeB is responsible for handling WiFi traffic. For that aggregation OAI (OpenAirInterface), 5G RAN is deployed with software‐defined radio (SDR) USRP B210. After that RAN part is aggregated with WLAN AP, both technologies are aggregated at the common PDCP layer. The UE can communicate with both technologies, that is, LTE and WiFi simultaneously. The second part of this system is to integrate the LWA system with the M‐CORD platform for better monitoring and control. The M‐CORD platform is the best option because it supports OAI LTE network functions (NFs) and provides an open‐source 5G environment for testing. So, the M‐CORD system controls the LWA system with XOS which automatically deploys the services to the mobile network. XOS treats everything like a service and each service has synchronizer which acts as a communicator between different services. Afterward, the vEPC of the M‐CORD which is controlled by the XOS is connected to LTE‐WiFi aggregated system. So, the LWA system is totally outside the M‐CORD and XOS should be able to monitor and control it with the help of synchronizers.
On-demand service is the main feature of the 5G network, and Network Function Virtualization (NFV) provides it by virtualizing the existing 5G network infrastructure. NFV crafts various virtual ...networks on a shared physical network, but one of the core challenges in future 5G networks is to automate the modeling of Virtualized Network Functions (VNFs) and end-to-end Network Service (NS) orchestration with less human interaction. Traditionally, the descriptor of VNF and NS is created manually, which requires expert-level skills. This manual approach has a big threat of human error, which can be avoided by using the Intent-Based Networking (IBN) approach. The IBN approach eliminates the requirement of expertise for designing VNFs and NS by taking users’ intentions as an input. In this paper, the proposed system presents the Intent Management System for VNF modeling and end-to-end NS orchestration for multi-platforms. This system takes the high-level information related to a specific service, configures it accordingly, and converts it into the selected platform. The proposed system is tested using Mobile Central Office Re-architected as Data Center (M-CORD) and Open-Source Management and Orchestration (OSM) orchestrators. The results section shows that the proposed system reduces the effort of the end-user in creating network slices and provides seamless end-to-end service orchestration.
Emerging technologies such as network function virtualization and software-defined networking (SDN) have made a phenomenal breakthrough in network management by introducing softwarization. The ...provision of assets to each virtualized network functions autonomously as well as efficiently and searching for an optimal pattern for traffic routing challenges are still under consideration. Unfortunately, the traditional methods for estimating the desired performance indicators are insufficient for a self-driven SDN. In the last decade, a combination of machine learning and cognitive techniques construct a knowledge plane (KP) for the Internet which introduces numerous benefits to networking, like automation and recommendation. Furthermore, the inclusion of KP to the conventional three planes SDN architectures recently has added another knowledge defined networking (KDN) architecture to drive an SDN autonomously. In this article, a self-driving system has been proposed based on KDN to achieve the selection of an optimal path for the deployment of service function chaining (SFC) and reactive traffic routing among the edge clouds. Considering the limited resource of edge clouds, the proposed system also maintains a balance among edge cloud resources while orchestrating SFC resources. The graph neural network has been also applied in the proposed system to recognize the composite relationship concerning topology, traffic features, and routing patterns for accurate estimation of key performance indicators. The proposed system improves resource utilization efficiency for SFC deployment by 20%, maximum network throughput by 5%, and CPU load by 13%.
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