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In this paper, a game-theoretical autonomous decision-making approach for efficient deployment of unmanned aerial vehicles (UAVs) in a multi-level and multi-dimensional assisted network is analyzed. The UAVs have directional antennas that work as wireless stations, which provide the best coverage for multiple ground mobile/fixed users. In general, UAVs work in a cooperative manner for achieving the suitable deployment with the optimal coverage values for the candidate region. In this paper, a game theory concept is used and the payoff function for each UAV is defined based on the coverage probability value, which depends on the altitude and the characteristic of antennas in the UAVs. We introduce a mathematical formulation for evaluating the payoff values based on a set of actions for each UAV, and the Nash equilibrium for this kind of game. This approach works in an intelligent way based on the interactions between the UAVs and their neighbors in a connected network and it might work even in harsh environments. In order to minimize interference, the UAVs' altitudes are adjusted based on the antennas and other deployment requirements (i.e. search and surveillance purposes) by using the minimum number of UAVs to cover the candidate geographical region. The simulation results show that the proposed approach achieves the maximum coverage value, converges fast with the environmental changes based on the power levels, and robust for failure scenarios. Finally, we compare our approach against one of the traditional approaches called Collaborative Visual Area Coverage Approach (CVACA) based on uniform coverage quality. The simulation results show that the game approach outperforms the traditional approach in term of the coverage value and the computational time. [ABSTRACT FROM AUTHOR]

Routing and parking problems are considered a real challenge in the populated cities. An intelligent routing and parking algorithm is needed to facilitate locating the most appropriate parking spots to vehicles in a way that efficiently utilizes parking resources, reduces the traffic congestion, and minimizes trip driving time. This work proposes a hierarchical optimal algorithm to solve the routing and parking problem (HOPRA) using multi-criteria decision concept and historical traffic data. The problem is divided into three parts: finding the preferred parking lot, identifying the parking entrance (in case there are multiple), and then selecting the preferred route to the destination point. The optimal parking lot is defined based on an objective function that depends on the availability rates of the parking lots. After finding the parking lot and the parking entrance, a multi-objective function is used to specify the preferred route to the selected parking lot. This function depends on the travel distance, the traffic rate of a specific route, and the driver's preferences. We use the Open Street Maps from the AnyLogic software in the implementation stage. We compare HOPRA against the Shortest Route (SR) algorithm that was implemented also in AnyLogic with historical traffic data obtained from HERE technologies for a sample city (Al-Madinah City in Saudi Arabia). The results show that the HORPA algorithm outperforms the SR algorithm in balancing the traffic congestion on the roads and reducing the driving time of the trip. [ABSTRACT FROM AUTHOR]

Unmanned Aerial Vehicles (UAVs) are considered an important element in wireless communication networks due to their agility, mobility, and ability to be deployed as mobile base stations (BSs) in the network to improve the communication quality and coverage area. UAVs can be used to provide communication services for ground users in different scenarios, such as transportation systems, disaster situations, emergency cases, and surveillance. However, covering a specific area under a dynamic environment for a long time using UAV technology is quite challenging due to its limited energy resources, short communication range, and flying regulations and rules. Hence, a distributed solution is needed to overcome these limitations and to handle the interactions among UAVs, which leads to a large state space. In this paper, we introduced a novel distributed control solution to place a group of UAVs in the candidate area in order to improve the coverage score with minimum energy consumption and a high fairness value. The new algorithm is called the state-based game with actor–critic (SBG-AC). To simplify the complex interactions in the problem, we model SBG-AC using a state-based potential game. Then, we merge SBG-AC with an actor–critic algorithm to assure the convergence of the model, to control each UAV in a distributed way, and to have learning capabilities in case of dynamic environments. Simulation results show that the SBG-AC outperforms the distributed DRL and the DRL-EC3 in terms of fairness, coverage score, and energy consumption. [ABSTRACT FROM AUTHOR]

Wireless sensor networks need accurate time synchronization for data consistency and coordination. Although the existing algorithms for time synchronization offer very good accuracy, their energy consumption is high, and distant nodes are poorly synchronized. We propose a Recursive Time Synchronization Protocol (RTSP) which accurately synchronizes all the nodes in a network to a global clock using multi-hop architecture in an energy-efficient way. It achieves better performance due to the MAC-layer time-stamping based on Start of Frame Delimiter byte, infrequent broadcasts by a dynamically elected reference node, compensation of the propagation delay and adjustment of the timestamps at each hop, estimation of the relative skew and offset using least square linear regression on two data points (2LR), adaptive re-synchronization interval, aggregation of the synchronization requests, and energy awareness. A detailed analysis of the sources of errors is also provided. Simulation results show that the RTSP can achieve an average accuracy of 0.3 microseconds in a large multi-hop flat network while using five-times lesser energy than that of FTSP in the long run and performs even better in a clustered network where it can achieve an average accuracy of 0.23 microseconds while using seven-times lesser energy. [ABSTRACT FROM PUBLISHER]

Abstract: Performance of wireless networks under video traffic is subjected to two main issues: power minimization and other QoS requirements such as delay jitter. Mobile Ad Hoc Networks (MANETs) are more sensitive to these issues where each mobile device acts like a router. Thus, routing delay adds significantly to overall end-to-end delay. This paper analyzes the performance of the Warning Energy Aware Clusterhead/Virtual Base Station-On demand (WEAC/VBS-O) protocol in terms of average delay, multi-hop communication and power minimization aspects that are subject to video traffic. H.263 and H.264 standards are utilized to model the simulated network. HCB model is also utilized to minimize the power consumption. The simulation results are demonstrated on a single hop and multi-hop settings. This includes the power consumption and the effect of sudden demise of cluster heads in the Warning Energy Aware Cluster head (WEAC) protocol. [Copyright &y& Elsevier]

A wireless mobile sensor network is a collection of wireless mobile hosts forming nodes that are communicating without the aid of any centralized administration or standard support services. Nodes are classified as sensor nodes and router. Some nodes act both as sensors and routers. While traditional MAC protocols must balance between throughput, delay, and fairness concerns, WSN MAC protocols place an emphasis on energy efficiency as well. Schedule-based MAC protocols have been proposed for WSN. A common theme through all these protocols is putting radios to a low-power "sleep mode" either periodically or whenever possible when a node is neither receiving nor transmitting. In this paper, we propose a novel cluster-based infrastructure creation protocol, namely: the Neighbor-Aware Clusterhead (NAC). We investigate the performance of the NAC protocol under different sleep scheduling protocols and compare it against another cluster-based protocol. In NAC protocol nodes are synchronized with their clusterheads and are allowed to go sleep mode in order to conserve their energy without degrading the performance of the network. The network is divided into clusters managed by a clusterhead. The simulation results show that NAC protocol has a good potential to be a good candidate protocol for SNET. [ABSTRACT FROM AUTHOR]

Recent advances in embedded computing systems have led to the emergence of wireless sensor networks (SNETs), consisting of small, battery-powered ‘motes’ with limited computation and radio communication capabilities. SNETs permit data gathering and computation to be deeply embedded in the physical environment. Large-scale ad hoc sensor networks (ASNET), when deployed among mobile patients, can provide dynamic data query architecture to allow medical specialists to monitor patients at any place via the web or cellular network. In case of an emergency, doctors and/or nurses will be contacted automatically through their handheld personal digital assistants (PDAs) or cellular phones. In specific, the proposed network consists of sensor nodes at the first layer whose responsibility is to measure, collect and communicate, via wired or wireless interface, readings to a microcontroller representing the second layer of the architecture. Deployed microcontrollers process incoming readings and report to a central system via a wireless interface. The implemented network distinguishes between periodic sensor readings and critical or event driven readings where higher priority is given for the latter. In this paper we implement 3 special cases for tracking and monitoring patients and doctors using SNETs. In addition, the performance of a large scale of our implementation has been tested by means of mathematical analysis. [ABSTRACT FROM AUTHOR]

Medium access control (MAC) protocols in ad hoc networks have evolved from single-channel independent transmission mechanisms to multi-channel concurrent mechanisms to efficiently manage the demands placed on modern networks. The primary aim of this study is to compare the performance of popular multi-channel MAC (MMAC) protocols under saturated network traffic conditions and propose improvements to the protocols under these conditions. A novel, dynamically adaptive MMAC protocol was devised to take advantage of the performance capabilities of the evaluated protocols in changing wireless ad hoc network conditions. A simulation of the familiar MAC protocols was developed based on a validated simulation of the IEEE 802.11 standard. Further, the behaviors and performances of these protocols are compared against the proposed MMAC protocols with a varying number of ad hoc stations and concurrent wireless channels in terms of throughput, Jain's fairness index, and channel access delay. The results show that the proposed MMAC protocol, labeled E-SA-MMAC, outperforms the existing protocols in throughput by up to 11.9% under a constrained number of channels and in channel access delays by up to 18.3%. It can be asserted from these observations that the proposed approach provides performance benefits against its peers under saturated traffic conditions and other factors, such as the number of available wireless channels, and is suitable for dynamic ad hoc network deployments. [ABSTRACT FROM AUTHOR]

The migration to wireless network from wired network has been a global trend in the past few decades. The mobility and scalability brought by wireless network made it possible in many applications. Among all the contemporary wireless networks, Mobile Ad hoc NETwork (MANET) is one of the most important and unique applications. On the contrary to traditional network architecture, MANET does not require a fixed network infrastructure; every single node works as both a transmitter and a receiver. Nodes communicate directly with each other when they are both within the same communication range. Otherwise, they rely on their neighbors to relay messages. The self-configuring ability of nodes in MANET made it popular among critical mission applications like military use or emergency recovery. However, the open medium and wide distribution of nodes make MANET vulnerable to malicious attackers. In this case, it is crucial to develop efficient intrusion-detection mechanisms to protect MANET from attacks. With the improvements of the technology and cut in hardware costs, we are witnessing a current trend of expanding MANETs into industrial applications. To adjust to such trend, we strongly believe that it is vital to address its potential security issues. In this paper, we propose and implement a new intrusion-detection system named Enhanced Adaptive ACKnowledgment (EAACK) specially designed for MANETs. Compared to contemporary approaches, EAACK demonstrates higher malicious-behavior-detection rates in certain circumstances while does not greatly affect the network performances. [ABSTRACT FROM PUBLISHER]

Parking in heavily populated areas has been considered one of the main challenges in the transportation systems for the past two decades given the limited parking resources, especially in city centres. Drivers often waste long periods of time hunting for an empty parking spot, which causes congestion and consumes energy during the process. Thus, finding an optimal parking spot depends on several factors such as street traffic congestion, trip distance/time, the availability of a parking spot, the waiting time on the lot gate, and the parking fees. Designing a parking spot allocation algorithm that takes those factors into account is crucial for an efficient and high-availability parking service. We propose a smart routing and parking algorithm to allocate an optimal parking space given the aforementioned limiting factors. This algorithm supports choosing the appropriate travel route and parking lot while considering the real-time street traffic and candidate parking lots. A multi-objective function is introduced, with varying weights of the five factors to produce the optimal parking spot with the least congested route while achieving a balanced utilization for candidate parking lots and a balanced traffic distribution. A queueing model is also developed to investigate the availability rate in candidate parking lots while considering the arrival rate, departure rate, and the lot capacity. To evaluate the performance of the proposed algorithm, simulation scenarios have been performed for different cases of high and low traffic intensity rates. We have tested the algorithm on in-city parking facility in the city of Al Madinah as a case study. The results show that the proposed algorithm is effective in achieving a balanced utilization of the parking lots, reducing traffic congestion rates on all routes to candidate parking lots, and minimizing the driving time to the assigned parking spot. Additionally, the proposed algorithm outperforms the MADM algorithm in terms of the selected three metrics for the five periods. [ABSTRACT FROM AUTHOR]