Multipath routing protocol based on cross-layer approach for MANET

Mobile Ad-hoc Networks (MANETs) involved in many applications, whether smart or traditional and for both civilian and military uses, and that because of their special features, where it does not depend on any infrastructure during its working, as well as the nodes in MANETs have a freedom of movement with the ability to self-configure, in addition, to working as a router or client at the same time. Moreover, MANETs considered as an infrastructure less network, so the cost of this type of networks is less in comparison to other traditional networks. On the other hand, the routing considered one of most important challenges in MANETs due to the perpetual motion and randomness of the nodes that can causing a continuous change of the network topology and thus to all paths between nodes, where finding valid paths between the nodes is the core task of routing protocols. Recently, it has been argued that the traditional layered architecture is ineffective to deal with receiving signal strength related problems. In an effort to improve the performance of MANETs, there has been increased in protocols that rely on cross-layer interaction between different layers. In this paper, a Cross-layer design among Network, MAC and Physical layers based on Threshold Multipath Routing Protocol (CTMRP) is proposed. The CTMRP is designed for decision maker based on threshold value of average paths signal for efficient transmission of the Text, image, audio and video as well as sending the data via multiple paths, which mitigate the negatives effects causes from forcing the nodes to send the data via single. The Route Discovery Delay, Number of RREQ Messages, Number of RREP Messages, End-to-End Delay, Packet Delivery Ratio (PDR), and Throughput were selected as the main performance evaluation metrics. The results show that the proposed algorithm has better performance and lead to increase stability of transmission link

Assessing the Moderating Effect of Innovation on the Relationship between Information Technology and Supply Chain Management: An Empirical Examination

This study examines how innovation (INN) influences the relationship between supply chain management and information technology in Jordan. 211 employees of Jordanian industrial enterprises who work in the Operations Department provided information for the study, which examines this subject. The findings indicate a close connection between information technology and supply chain management. Innovation also dramatically modifies the interaction between supply chain management and information technology. Management help may be the subject of future research

The Role of Business Intelligence adoption as a Mediator of Big Data Analytics in the Management of Outsourced Reverse Supply Chain Operations

The fluctuating and disorganized state of todays global markets is the result of several factors. COVID-19 is an illustration. Supply chain managers should re-evaluate their competitive strategy and leverage big data analytics in light of the rising volatility in demand and supply, rivalry among supply chain partners, and the requirement to deliver tailored goods and services (BDA). Supply chain firms require sophisticated BDA processes and procedures to provide useful insights from big data to better decision-making and supply chain operations, as many leaders in the sector have acknowledged the necessity for improving with data (SCO). This research gives theoretical justification for the influence that BDA has on SCO

Multi-Agent Reinforcement Learning for Network Selection and Resource Allocation in Heterogeneous Multi-RAT Networks

The rapid production of mobile devices along with the wireless applications boom is continuing to evolve daily. This motivates the exploitation of wireless spectrum using multiple Radio Access Technologies (multi-RAT) and developing innovative network selection techniques to cope with such intensive demand while improving Quality of Service (QoS). Thus, we propose a distributed framework for dynamic network selection at the edge level, and resource allocation at the Radio Access Network (RAN) level, while taking into consideration diverse applications' characteristics. In particular, our framework employs a deep Multi-Agent Reinforcement Learning (DMARL) algorithm, that aims to maximize the edge nodes' quality of experience while extending the battery lifetime of the nodes and leveraging adaptive compression schemes. Indeed, our framework enables data transfer from the network's edge nodes, with multi-RAT capabilities, to the cloud in a cost and energy-efficient manner, while maintaining QoS requirements of different supported applications. Our results depict that our solution outperforms state-of-the-art techniques of network selection in terms of energy consumption, latency, and cost

A smart monitoring system for campus using ZigBee wireless sensor networks

The wireless sensor networks are autonomous sensors that are distributed to monitor environmental and physical conditions and pass them across the network to other areas, which is considered one of the key elements that are used in the applications of smart cities. Therefore, this paper aims to provide a design to add more smart applications to the sanctuary and other compounds based on wireless sensor networks using ZigBee technology. The transition from reliance on the style of surveillance and controlled manually by staff to apply the principles of smart applications through wireless sensor network which provides the ability to getting all the necessary information and capabilities of controlling and monitoring are required to automatically and thus saving the time, effort, and money. The system proposed in this paper to design a smart monitoring system at the campus to control the opening and closing of the doors of many halls and the possibility of including lighting systems and appliances. The results obtained from OPNET program show that the network topology, which used within a ZigBee network vary in terms of performance, thus giving options for designers to build their network and choose technologies that suit their project

A Modified Route Discovery Approach For Dynamic Source Routing (DSR) Protocol In Mobile Ad-Hoc Networks

Mobile Ad-hoc networks (MANETs) involved in many applications, whether commercial or military because of their characteristics that do not depend on the infrastructure as well as the freedom movement of their elements, but in return has caused this random mobility of the nodes many of the challenges, where the routing is considered one of these challenges. There are many types of routing protocols that operate within MANET networks, which responsible for finding paths between the source and destination nodes with the modernization of these paths which are constantly changing due to the dynamic topology of the network stemming from the constant random movement of the nodes. The DSR (Dynamic Source Routing) routing protocol algorithm is one of these routing protocols which consist of two main stages; route discovery and maintenance, where the route discovery algorithm operates based on blind flooding of request messages. blind flooding is considered as the most well known broadcasting mechanism , it is inefficient in terms of communication and resource utilization, which causing increasing the probability of collisions, repeating send several copies of the same message, as well as increasing the delay. Hence, a new mechanism in route discovery stage and in caching the routes in DSR algorithm according to the node's location in the network and the direction of the broadcast is proposed for better performance especially in terms of delay as well as redundant packets rate. The implementation of proposed algorithms showed positive results in terms of delay, overhead, and improve the performance of MANETs in general

Multipath Routing Protocol Based On Cross-Layer Approach for MANET

Mobile Ad-hoc Networks (MANETs) involved in many applications, whether smart or traditional and for both civilian and military uses, and that because of their special features, where it does not depend on any infrastructure during its working, as well as the nodes in MANETs have a freedom of movement with the ability to self-configure, in addition, to working as a router or client at the same time. Moreover, MANETs considered as an infrastructure less network, so the cost of this type of networks is less in comparison to other traditional networks. On the other hand, the routing considered one of most important challenges in MANETs due to the  perpetual motion and randomness of the nodes that can causing a continuous change of the network topology and thus to all paths between nodes, where finding valid paths between the nodes is the core task of routing protocols. Recently, it has been argued that the traditional layered architecture is ineffective to deal with receiving signal strength related problems. In an effort to improve the performance of MANETs, there has been increased in protocols that rely on cross-layer interaction between different layers. In this paper, a Cross-layer design among Network, MAC and Physical layers based on Threshold Multipath Routing Protocol (CTMRP) is proposed. The CTMRP is designed for decision maker based on threshold value of average paths signal for efficient transmission of the Text, image, audio and video as well as sending the data via multiple paths, which mitigate the negatives effects causes from forcing the nodes to send the data via single. The Route Discovery Delay, Number of RREQ Messages, Number of RREP Messages, End-to-End Delay, Packet Delivery Ratio (PDR), and Throughput were selected as the main performance evaluation metrics. The results show that the proposed algorithm has better performance and lead to increase stability of transmission link

Sulfur Deficiency Increases Phosphate Accumulation, Uptake, and Transport in Arabidopsis thaliana

Recent studies have shown various metabolic and transcriptomic interactions between sulfur (S) and phosphorus (P) in plants. However, most studies have focused on the effects of phosphate (Pi) availability and P signaling pathways on S homeostasis, whereas the effects of S availability on P homeostasis remain largely unknown. In this study, we investigated the interactions between S and P from the perspective of S availability. We investigated the effects of S availability on Pi uptake, transport, and accumulation in Arabidopsis thaliana grown under sulfur sufficiency (+S) and deficiency (−S). Total P in shoots was significantly increased under −S owing to higher Pi accumulation. This accumulation was facilitated by increased Pi uptake under −S. In addition, −S increased root-to-shoot Pi transport, which was indicated by the increased Pi levels in xylem sap under −S. The −S-increased Pi level in the xylem sap was diminished in the disruption lines of PHT1;9 and PHO1, which are involved in root-to-shoot Pi transport. Our findings indicate a new aspect of the interaction between S and P by listing the increased Pi accumulation as part of −S responses and by highlighting the effects of −S on Pi uptake, transport, and homeostasis

Performance Evaluation of DSR, AODV, and OLSR Routing Protocols in MANET

In recent years, Mobile Ad-hoc Networks (MANETs) is one of the popular research areas due to low cost to employ the network, self-organization, freedom of location, and no base stations. However, broadcast and data aggregation are crucial operations in MANETs. Design of MANET networks with high efficiency is an important task because the nodes in MANET have limited resources for communication such as bandwidth, buffer space, and battery power. Moreover, because of the high mobility of nodes, nodes may change their positions rapidly and these will not only change the network topology, but also make it impossible to keep a durable and regular data routing between two nodes, that can cause link failure. There are many routing protocols that are designed to work in the ad hoc networks, but many challenges continue to push for further improvements in its performance to increase the effectiveness of the networks.In this paper, the performance evaluation of the three routing protocols (DSR, AODV, and OLSR) that are widely used are presented, also compare is the performance of the three networks in different scenarios in terms of the network size and node speed. The results shows a substantial convergence performance of these network protocols in a small-sized networks, but the performance begins to varies with the increasing size of the network

RL-Assisted Energy-Aware User-Edge Association for IoT-based Hierarchical Federated Learning

The extremely heavy global reliance on IoT devices is causing enormous amounts of data to be gathered and shared in IoT networks. Such data need to efficiently be used in training and deploying of powerful artificially intelligent models for better future event detection and decision making. However, IoT devices suffer from many limitations regarding their energy budget, computational power, and storage space. Therefore, efficient solutions have to be studied and proposed for addressing these limitations. In this paper, we propose an energy-efficient Hierarchical Federated Learning (HFL) framework with optimized client-edge association and resource allocation. This was done by formulating and solving a communication energy minimization problem that takes into consideration the data distribution of the clients and the communication latency between the clients and edges. We also implement an alternative less complex solution leveraging Reinforcement Learning (RL) that provides a fast user-edge association and resource allocation response in highly dynamic HFL networks. The proposed two solutions are compared with several state-of-the-art client-edge association techniques, leveraging MNIST dataset. Moreover, we study the trade-off between minimizing the per-round energy consumption and Kullback-Leibler Divergence (KLD) of the data distribution, and its effect on the total energy consumption.This work was made possible by NPRP grant # NPRP13S-0205-200265 from the Qatar National Research Fund (a member of Qatar Foundation)