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Energy efficiency and data reliability are important indicators to measure network performance in wireless sensor networks. In existing research schemes of routing protocols, the impact of node coverage on the network is often ignored, and the possibility that multiple sensor nodes may sense the same spatial point is not taken into account, which results in a waste of network resources, especially in large-scale networks. Apart from that, the blindness of geographic routing in data transmission has been troubling researchers, which means that the nodes are unable to determine the validity of data transmission. In order to solve the above problems, this paper innovatively combines the routing protocol with the coverage control technique and proposes the node collaborative scheduling algorithm, which fully considers the correlation characteristics between sensor nodes to reduce the number of active working nodes and the number of packets generated, to further reduce energy consumption and network delay and improve packet delivery rate. In order to solve the problem of unreliability of geographic routing, a highly reliable link detection and repair scheme is proposed to check the communication link status and repair the invalid link, which can greatly improve the packet delivery rate and throughput of the network, and has good robustness. A large number of experiments demonstrate the effectiveness and superiority of our proposed scheme and algorithm. [ABSTRACT FROM AUTHOR]

Summary: Flying ad hoc network (FANET) comprising unmanned aerial vehicles (UAVs) emerges as a promising solution for numerous military and civil applications. Transferring data collected from the environment to the ground station (GS) is a primary concern for meeting the communication demands of most of these applications. However, the highly mobile UAVs with limited communication range, resulting in frequent topology change and intermittent connectivity, make data routing challenging. In such scenarios, geographic routing is a viable solution due to its scalability and robustness. However, the basic forwarding mechanism of geographic routing favors the neighboring UAV nearest to the destination, impacted substantially by link failures and routing holes in a dynamic environment. Additionally, routing decisions ignoring the current load over UAVs contribute to performance degradation due to the high concentration of data traffic near the GS. Thus, to address these issues, a geographic routing protocol named MF‐DLB comprising multimetric forwarding (MF) and a directed acyclic graph‐based load balancing (DLB) scheme is proposed to enhance packet forwarding in FANETs. MF takes account of multiple metrics related to connectivity, geographic progress, link lifetime, and residual energy to select the next hop with a stable communication link while effectively bypassing the routing holes. The second scheme, DLB, focuses on proactively maintaining routing paths near GS for load distribution among underutilized nodes to address the congestion problem. Simulations performed in network simulator ns‐3 confirm the outperformance of MF‐DLB over other related routing schemes in terms of different performance metrics. [ABSTRACT FROM AUTHOR]

Machine learning has, over the decades, ushered in a dramatic transformation across a range of sectors, including network security. Security experts agree that the potential of machine learning algorithms will be indispensable in detecting all kinds of attacks and maximize accuracy when compared to traditional detection methods. In Wireless ad hoc networks that monitor real-time systems, security remains a concern. Selective forwarding and Denial-of-Service (DoS) are the most common Wireless Sensor Network (WSN) security attacks, resulting in systems making incorrect decisions with negative consequences. Further, the dynamic nature of ad hoc networks creates security issues that hamper effective data communication. While numerous methods have been suggested in the literature to address these issues, there remains a gap for more robust solutions. This paper proposes a novel trust entropy model approach that applies machine learning to significantly improve network security. The proposed cluster-based trust entropy method avoids malicious nodes in routing and re-routing packets effectively along alternate paths. In addition, a new dataset is created from the network simulation results of the proposed method. This dataset serves as the base for applying machine learning algorithms, resulting in exceptionally high detection accuracy. This novel approach not only solves the security concerns, but also raises the standard for accuracy and reliability in Wireless Adhoc Networks.

Intelligent vehicular networks can not only connect various smart terminals to manned or unmanned vehicles but also to roads and people's hands. In order to support diverse vehicle-to-everything (V2X) applications in dynamic, intelligent vehicular networks, efficient and flexible routing is fundamental but challenging. Aimed to eliminate routing voids in traditional Euclidean geographic greedy routing strategies, we propose a hyperbolic-embedding-aided geographic routing strategy (HGR) in this paper. By embedding the network topology into a two-dimensional Poincaré hyperbolic disk, greedy forwarding is performed according to nodes' hyperbolic coordinates. Simulation results demonstrated that the proposed HGR strategy can greatly enhance the routing success rate through a smaller stretch of the routing paths, with little sacrifice of routing computation time. [ABSTRACT FROM AUTHOR]

Flying ad hoc networks (FANETs) belong to the family of mobile ad hoc networks (MANETs). They have gained high popularity due to their extensive applications in various industries such as emergency management, military missions, and supervision. However, these networks face important challenges in guaranteeing reliable data transmission because of their dynamic nature and lack of infrastructure. In this paper, a new version of the greedy perimeter stateless routing scheme called GPSR+AODV is proposed in FANET. It combines two routing schemes, namely GPSR and AODV, and is a family member of geographic routing methods. In GPSR+AODV, each UAV consists of a certain hello broadcast period that is adjusted based on the prediction of its spatial coordinates in the future. Additionally, GPSR+AODV modifies the greedy forwarding process and restricts the search space for finding the next-hop node by obtaining a refined candidate set, calculated in the cylindrical coordinate system. Then, each UAV in the refined candidate set is evaluated under a fitness function, and the most suitable next-hop node with the maximum fitness is determined. This function is a combination of four criteria, namely relative velocity, energy level, buffer capacity, and distance to destination. When failing in the greedy forwarding process, GPSR+AODV changes the forwarding technique and uses an AODV-based perimeter forwarding technique to select the best next-hop node. Lastly, GPSR+AODV is implemented by the NS2 simulator, and the simulation results show a successful performance in terms of packet delivery rate, throughput, and delay compared to AGGR, AeroRP, and GPSR. However, the routing overhead in the proposed scheme is higher than that in AGGR.

In recent eras, a large amount of data has been transferred through wireless networks in fifth-generation communication using a two-phase geography greedy forwarding (TPGF) routing algorithm with reconfigurable routing metrics represented by RrTPGF in random duty-cycled wireless multilevel multimedia sensor networks (WMSNs). The proposed method reduces the sleep delay in geographic routing networks. the systematically forwarded node in the geographic routing network to identify the significant neighboring nodes. The proposed algorithm is efficient in identifying the geographical distance of the neighboring node and identifying the sleeping delay of the nodes during the communication process. The proposed algorithm efficiently differentiates the worked node from the unworked node on the basis that it identifies the optimal single routing path with a low sleeping delay time at geographic routing. As per the simulation result, the performance of the proposed method shows better results as compared to the conventional methods when considering the scenario size of 750mm ×450mm and 250 nodes with respect to the average delay of the proposed method, which is reduced to 0.6%, and the average hop counts, which are reduced to 0.56% as compared to the conventional method. [ABSTRACT FROM AUTHOR]

In recent times, huge data is transferred from source to destination through multi path in wireless sensor networks (WSNs). Due to this more congestion occurs in the communication path. Hence, original data will be lost and delay problems arise at receiver end. The above-mentioned drawbacks can be overcome by the proposed efficient reconfigurable geographic routing congestion control (RgRCC) algorithm for wireless sensor networks. the proposed algorithm efficiently finds the node’s congestion status with the help queue length’s threshold level along with its change rate. Apart from this, the proposed algorithm re-routes the communication path to avoid congestion and enhances the strength of scalability of data communication in WSNs. The proposed algorithm frequently updates the distance between the nodes and bypass routing holes, common for geographical routing. when the nodes are at the edge of the hole, it will create congestion between the nodes in WSNs. Apart from this, more nodes sink due to congestion. it can be reduced with the help of the proposed RgRCC algorithm. As per the simulation analysis, the proposed work indicates improved performance in comparison to conventional algorithm. By effectively identifying the data congestion in WSNs with high scalability rate as compared to conventional methods. [ABSTRACT FROM AUTHOR]

Summary The reliable surveillance of a large region typically needs a large number of unmanned aerial vehicles (UAVs), which leads to high operational costs in flying ad hoc networks (FANETs). Therefore, the UAV mobility model plays an important role that affecting the performance of FANET. This research paper comes up with a novel UAV‐shuttle‐enabled mobility management model (US‐MMM) that is a crucial attribute for the large and highly sparse network. The proposed mobility model uses UAV shuttles. A relatively lesser number of UAVs are used than comparative approaches to enhance the connectivity among the UAVs in a sparse network. UAV shuttle is the special self‐governing node, which traverses the network and collects the data to deliver to the base station (BS). The main strength of the proposed mobility model is the self‐governing ability of the UAV shuttle, which leads to high connectivity in the network. The UAV shuttle executes the proposed dynamic path planning algorithm and uses the adaptive ranking algorithm to determine its target. The main contribution of this research work is to develop a subnet scan and Number of Neighbor and Distance‐based Adaptive Ranking of Targets (NN‐DART) algorithm for dynamic route planning of UAV shuttle. The proposed mobility model is used with various routing schemes to check the difference in the performance of various routing schemes. The proposed mobility model is simulated in NS‐2.35, and the results have shown an improvement in the packet delivery ratio, routing overhead, and end‐to‐end delay. [ABSTRACT FROM AUTHOR]

Energy efficiency and data reliability are important indicators to measure network performance in wireless sensor networks. In existing research schemes of routing protocols, the impact of node coverage on the network is often ignored, and the possibility that multiple sensor nodes may sense the same spatial point is not taken into account, which results in a waste of network resources, especially in large-scale networks. Apart from that, the blindness of geographic routing in data transmission has been troubling researchers, which means that the nodes are unable to determine the validity of data transmission. In order to solve the above problems, this paper innovatively combines the routing protocol with the coverage control technique and proposes the node collaborative scheduling algorithm, which fully considers the correlation characteristics between sensor nodes to reduce the number of active working nodes and the number of packets generated, to further reduce energy consumption and network delay and improve packet delivery rate. In order to solve the problem of unreliability of geographic routing, a highly reliable link detection and repair scheme is proposed to check the communication link status and repair the invalid link, which can greatly improve the packet delivery rate and throughput of the network, and has good robustness. A large number of experiments demonstrate the effectiveness and superiority of our proposed scheme and algorithm.

The occurrence of hole regions in Wireless Sensor Networks is a significant challenge when applying a greedy technique in a geographic routing approach. The local minimum phenomenon is commonly attributed to physical obstacles, energy depletion of the nodes, failures in communication between neighbors, or even the incorrect deployment of the nodes in the sensing field. To address the problem of hole regions, most approaches choose to abandon the traditional greedy forwarding mechanism to temporarily adopt the well-known perimeter routing scheme applied to nearby nodes or along the edge of a region of a hole. However, this mechanism does not satisfy the network load balance requirement, because it imposes too much traffic to the nodes in the hole's edge, making them overloaded when compared to other network nodes more distant from holes. In this work, we propose a novel location-free geographic routing technique called PAtCH (Proactive Approach to Circumvent Holes in Wireless Sensor Network) to avoid routing holes in WSNs. Our solution can circumvent hole regions and create routing paths toward the destination. We consider that our sink has a higher communication range, and the Received Signal Strength Indicator (RSSI) is used to assist the construction of the routing paths. Our results show the efficiency achieved by our proposed solution in scenarios with hole regions, also maintaining all the benefits of a classic greedy forwarding technique. [ABSTRACT FROM AUTHOR]

Multi-hop data transmission in Vehicular Ad Hoc Network (VANET) is mostly affected by vehicle's mobility, intermittent connection, insufficient bandwidth, and multichannel switching. Geographic routing technique in cognitive vehicular ad hoc network (CR-VANET) resolves bandwidth scarcity and connectivity issues simultaneously. The proposed QoS aware stochastic relaxation approach (QASRA) is a geographic routing protocol that additionally performs network exploration under inappropriate connectivity and exploits the already existing valid solutions while discovering routes in urban CR-VANET. The candidate forwarders are prioritized depending upon their closeness from destination, relative velocity from sender, and their street efficiency in terms of connectivity and delay. Transmission is done over minimally occupied cognitive or service channels. Different sets of experiments were performed to evaluate the effect of growing vehicular density, primary users (PUs) and CBR connection pairs in an urban scenario. The simulation on NS-2.24 platform demonstrates that at higher velocities, that are in between 20 and 60 km/hr, the average packet delivery ratio (PDR) is 60% when the density of vehicles were altered, 63.6% when PU's count is changed and 69% when number of CBR connection pair is varied. The average end-to-end delay is 1.03 s when the density of vehicles is altered, 0.734 when PU's count is changed and, 0.756 when number of CBR connection pair is varied. The average PU's success ratio is 68.4% when density of vehicles were changed, 61.4% when PU's count is changed and, 64.4% when the number of CBR connection pairs is varied. The analysis done through simulation demonstrates that a successful delivery of both secondary and primary users is achieved in minimum time when compared with other traditional methods. [ABSTRACT FROM AUTHOR]

Vehicle Ad Hoc Networks (VANETs) can help reduce traffic accidents and improve road safety by broadcasting Emergency Messages (EMs) between vehicles in advance so that the vehicle can take action to avoid accidents. However, its advantages are often compromised by factors such as high mobility, uneven nodes distribution, and signal attenuation, resulting in lower reliability and higher delay in the delivery of EMs. Besides, because of its open and mobility, VANETs are vulnerable to cyber security threats and are prone to multiple malicious attacks in the network. Malicious nodes can join the set of candidate forwarding nodes through collusion and identity forgery, which poses a serious challenge to EMs forwarding. In order to resolve the problems above, this paper proposes a geographic routing strategy to deliver EMs based on trusted nodes, focusing on measuring the reliability of link quality and node quality. The link quality between nodes is evaluated by measuring the actual transmission cost and the link signal-to-noise ratio to minimize the possible link interruption; at the same time, the node trust value is introduced to measure the credibility of the node and filter out the possible malicious nodes in the network. The research results show that the protocol is suitable for dense and sparse traffic conditions, can detect and identify malicious nodes, and has significant performance improvements in message delivery rate, end-to-end delay, and network throughput.

In wireless sensor networks, sensor nodes are deployed to collect data, perform calculations, and forward information to either other nodes or sink nodes. Recently, geographic routing has become extremely popular because it only requires the locations of sensor nodes and is very efficient. However, the local minimum phenomenon, which hinders greedy forwarding, is a major problem in geographic routing. This phenomenon is attributed to an area called a hole that lacks active sensors, which either prevents the packet from being forwarded to a destination node or produces a long detour path. In order to solve the hole problem, mechanisms to detect holes and determine landmark nodes have been proposed. Based on the proposed mechanisms, landmark-based routing was developed in which the source node first sends a packet to the landmark node, and the landmark node then sends the packet to the destination. However, this approach often creates a constant node sequence, causing nodes that perform routing tasks to quickly run out of energy, thus producing larger holes. In this paper, a new approach is proposed in which two virtual ellipses are created with the source, landmark, and destination nodes. Then guide the forwarding along the virtual ellipses. Furthermore, a recursive algorithm is designed to ensure a shortcut even if there are multiple holes or a hole has multiple landmarks. Thus, the proposed approach improves both geographic routing and energy efficiency routing. Simulation experiments show that the proposed approach increases the battery life of sensor nodes, lowers the end-to-end delay, and generates a short path.

In Vehicular Ad Hoc Networks (VANETs), high mobility, high-density, and random distribution of vehicles are crucial factors affecting the performance of a routing scheme. High mobility causes frequent changes in network topology, whereas high-density causes communication congestion due to channel contention. Moreover, routing decisions based on a relay vehicle may be less optimal if we do not consider the stability and predict the position of a relay vehicle in such dynamic environments. In addition, periodic beaconing may not be attractive because it creates channel contention and degrades the message's reliability. Owing to these factors, designing an efficient routing scheme for emergency messages is a challenging task, especially in the urban environment. In this paper, we propose a reliable relay selection scheme for Emergency Message Routing in Intermittently Connected Networks (EMR-ICN). EMR-ICN is used for both sparse and dense network environments to establish a stable routing path. We use vehicle-to-infrastructure and vehicle-to-vehicle communication models to support routing in dense and sparse networks. We adopt the position prediction and some mobility metrics for relay selection to ensure a stable routing path. By employing relative positions changes among moving vehicles with respect to a time interval, EMR-ICN predicts the relative positions of neighbor vehicles to exclude unstable neighbors from the list of candidate relay vehicles. Moreover, it selects a reliable relay among the candidate relay vehicles based on distance, movement direction, and speed variation. To minimize channel contention, we adjust the beacons interval according to the estimation of link duration between a vehicle and its neighbors. Simulation results show that EMR-ICN outperforms Greedy Perimeter Stateless Routing (GPSR) and Maxduration-Minangle-GPSR, in terms of message delivery ratio, latency, and the number of hop count. [ABSTRACT FROM AUTHOR]

The occurrence of hole regions in Wireless Sensor Networks is a significant challenge when applying a greedy technique in a geographic routing approach. The local minimum phenomenon is commonly attributed to physical obstacles, energy depletion of the nodes, failures in communication between neighbors, or even the incorrect deployment of the nodes in the sensing field. To address the problem of hole regions, most approaches choose to abandon the traditional greedy forwarding mechanism to temporarily adopt the well-known perimeter routing scheme applied to nearby nodes or along the edge of a region of a hole. However, this mechanism does not satisfy the network load balance requirement, because it imposes too much traffic to the nodes in the hole’s edge, making them overloaded when compared to other network nodes more distant from holes. In this work, we propose a novel location-free geographic routing technique called PAtCH (Proactive Approach to Circumvent Holes in Wireless Sensor Network) to avoid routing holes in WSNs. Our solution can circumvent hole regions and create routing paths toward the destination. We consider that our sink has a higher communication range, and the Received Signal Strength Indicator (RSSI) is used to assist the construction of the routing paths. Our results show the efficiency achieved by our proposed solution in scenarios with hole regions, also maintaining all the benefits of a classic greedy forwarding technique.

With the development of 5G, it is unsurprising that most of the smart devices in the Internet of Things (IoT) will be wirelessly connected with each other in the near future. This kind of lightweight, scalable and green network architecture will be well-received. In a wide variety of IoT application scenarios, sensor nodes deployed in a local space, such as a multistory building, automatically form a distributed 3D wireless IoT and it can be employed to collect and analyze environmental information. Source-location privacy protection is of great importance in these networks and however, most existing schemes focus on only planar distributed networks which are not suitable for the 3D networks. In this paper, we consider a novel trace-back attack for 3D wireless IoT and then design a source-location privacy protection scheme, named DMR-3D, to defend this kind of novel attacks. In DMR-3D, the source node first selects a set of virtual locations to indirectly choose a set of agent nodes based on the cold start sphere structure and the ellipsoid communication pipeline. Then, a sophisticated mechanism is designed based on both the connected graph and Multiple Delaunay Triangulation (MDT) structure of the network to deliver packets from the source node to the destination node via these agent nodes in a relay manner. Analysis and simulation results illustrate that the proposed scheme can effectively protect source-location privacy with a moderate increment of path stretch, time delay and data transmission amount. [ABSTRACT FROM AUTHOR]

Wireless sensor networks (WSNs) are networks with devices that can detect, process, store, and communicate wirelessly. Each network terminal can have multiple sensing devices that can measure physical variations such as temperature, brightness, humidity, and vibration. However, developing and implementing WSNs poses many challenges. This review presents the challenges of WSN using different routing algorithms such as geographic routing, energy-aware routing, delay aware routing, QoS aware routing, secure aware routing, and hierarchical aware routing. Another goal is to find out which WSN component automates interference and behavior. What kind of application is in the WSN depends not only on his work but also on the question of the basis, functionality, and handling of his project. The study was carefully planned, and the systematic review of the literature was set up in a strong framework according to a pre-defined protocol. Finally, we evaluate the performance parameters of previous routing algorithms with diverse routine metrics that are energy consumption, delay, packet delivery ratio, throughput, false ratio, packet loss ratio, and network overhead. [ABSTRACT FROM AUTHOR]

Opportunistic ad hoc networks are characterized by intermittent and infrastructure-less connectivity among mobile nodes. Because of the lack of up-to-date network topology information and frequent link failures, geographic routing utilizes location information and adopts the store–carry–forward data delivery model to relay messages in a delay-tolerant manner. This paper proposes a message-forwarding policy based on movement patterns (MPMF). First, one- and two-hop location information in a geographic neighborhood is exploited to select relay nodes moving closer to a destination node. Message-forwarding decisions are made by referring to selected relay nodes' weight values obtained by calculating the contact frequency of each node with the destination node. Second, when relays in the vicinity of a message-carrying node are not qualified due to the sparse node density and nodal motion status, the destination's movement and the location information of a one-hop relay are jointly utilized to improve the message-forwarding decision. If the one-hop relay is not closer to the destination node or moving away from it, its centrality value in the network is used instead. Based on both synthetic and real mobility scenarios, the simulation results show that the proposed policy performs incomparable efforts to some typical routing policies, such as Epidemic, PRoPHETv2, temporal closeness and centrality-based (TCCB), transient community-based (TC), and geographic-based spray-and-relay (GSaR) routing policies. [ABSTRACT FROM AUTHOR]

In road traffic networks, famous Braess's Paradox demonstrated that the addition of resources can cause the traffic network performance to decrease. The addition of a new route can cause drivers to use this new road and end up reaching a Nash equilibrium which increases the overall travel time. Unlike previous studies that have investigated the paradox in the context of game theory, road traffic network, and latency edge data network, in this paper we show the novel issue of how the addition of resources can lead to a decrease in data network performance while using certain routing algorithm (ie, shortest widest path—used for quality‐of‐service routing, quickest path, geographic routing, quality‐of‐service energy‐aware routing), without even considering congestion. We demonstrate the idea for any network size and describe the fundamental issue. Finally, we describe solutions based on current network's technology. [ABSTRACT FROM AUTHOR]

In mobile ad-hoc networks (MANET), nodes are randomly distributed and move freely, and hence the network may face rapid and unexpected topological changes. In this paper, an improved greedy perimeter stateless routing protocol, called "LDAB-GPSR", is proposed. LDAB-GPSR mainly focuses on maximizing the packet delivery ratio while minimizing the control overhead. In order to accomplish this, two techniques are introduced, the first one is the location prediction technique in which the greedy forwarding strategy is improved by choosing more stable routes for data forwarding. The second one is the adaptive beaconing technique in which the slow start algorithm is employed to adapt the beacon packet interval time based on the mobility of nodes and the data traffic load instead of using the periodic beaconing strategy. These two strategies together improve the overall performance of the GPSR routing protocol. The performance of the new proposed protocol is evaluated by carrying out several NS-2.35 simulation experiments. The simulation results show that LDAB-GPSR protocol outperforms the GPSR+Predict protocol in terms of packet delivery ratio, control traffic overhead, end to end delay, and throughput. The ratios of enhancement approaches 40%. [ABSTRACT FROM AUTHOR]

Underwater Sensor Network (UWSN) is gaining popularity among researchers due to its peculiar features. But there are so many challenges in the design of the UWSN system, and these are quite unsustainable due to the dynamic nature of water waves. Perhaps the most tedious challenge for UWSNs is how to transfer the data at the destination with a minimal energy rate. It can be accomplished by exploiting geographic and opportunistic routing schemes to send the data efficiently to the surface sinks in cooperation with relay nodes. With this aim, we introduce a new protocol for routing, named Geographic and Cooperative Opportunistic Routing Protocol (GCORP). In GCORP, the packets are routed from the source node to the surface sinks in coordination with intermediate relay nodes. In GCORP protocol, initially, multiple sinks-based network architecture is established. Then, a relay forwarding set is being determined by the source node on the basis of depth fitness factor. Finally, the best relay is determined through the weight calculation scheme from the relay forwarding set. We conduct the simulations in NS3 to validate the proposed GCORP routing protocol concerning different network metrics. The simulations conclude that the GCORP protocol shows better performance than existing approaches.

This paper addresses the local minimum phenomenon, routing path enlargement, and load imbalance problems of geographic routing in wireless sensor networks (WSNs) with holes. These issues may degrade the network lifetime of WSNs since they cause a long detour path and a traffic concentration around the hole boundary. Aiming to solve these problems, in this work, we propose a novel geographic routing protocol for WSNs, namely, Q-learning Inspired Hole bypassing (QIH), which is lightweight and efficient. QIH’s conceptual idea is to leverage Q-learning to estimate the distance from a node to the holes. QIH makes routing decisions following the nodes’ residual energy, their estimated distance to the holes, and their distance to the destination. We first confirm the effectiveness of QIH by theoretical analysis. Then, we conduct extensive simulations of QIH in comparison to state-of-the-art protocols. The simulation results show that QIH outperforms the other protocols in terms of network lifetime, packet latency, and energy consumption.

This paper investigates the possibility of using the Wireless Sensor Networks (WSNs) with the Internet of Things (IoT) in which the sensor nodes are attached to the collar of the animals to track the movement pattern of wild animals, and identify the territorial behavior, population and hunting. The random movement of animals creates the network issues such as the energy hole, void problem, poor network lifetime, coverage, and link failure due to animal mobility. To overcome these issues, an efficient data collection mechanism called Location based Clustering and Opportunistic Geographic Routing (LCOGR) is introduced. In this work, a Location Point (LP) is applied to select the Cluster Head (CH) that confirms the uniform distribution of CHs and improves energy efficiency. Also a BYPASS beacon based geographic routing is designed to transmit data to the Base Station (BS) which in turn is connected to the cloud sever. LCOGR ensures stable connectivity and complete coverage of the sensing area. The findings of the simulation show that the suggested strategy considerably increases network efficiency compared to the well-known protocols such as CSDGP, VELCT and MBC. [ABSTRACT FROM AUTHOR]

Summary: Several geographic routing protocols have been proposed for data transmission in wireless multimedia sensor networks (WMSNs), in which forwarding decisions are made locally based on one‐hop neighborhood information of each sensor node. These routing protocols involve one of two routing strategies: distance‐based strategy (greedy) which selects the closest neighbor from the base station as next‐hop or direction‐based strategy (compass) that chooses the neighbor with the smallest angle deviation toward the base station as next‐hop. This article proposes a multipath geographic routing protocol for WMSNs that combines the two routing strategies while taking advantage of their benefits, called greedy‐compass geographic multipath routing (GCGM) protocol. In GCGM, for the selection of a neighbor as next‐hop, a weighting coefficient is associated to each of the two strategies. We performed extensive simulations using OMNeT++ simulator with different scenarios to illustrate the performance of our proposal with our proposed weight values and with various weight values. Simulation results showed that our proposal with the proposed weight values provides better performance compared to GCGM with fixed weight values in terms of several performance criteria. We also compared GCGM with other routing protocols. Simulation results showed that GCGM provides better performance compared to TIGMR, LQEAR, and AGEM. [ABSTRACT FROM AUTHOR]

A Wireless Sensor Network consists of several tiny devices which have the capability to sense and compute the environmental phenomenon. These sensor nodes are deployed in remote areas without any physical protections. A Wireless Sensor Network can have various types of anomalies due to some random deployment of nodes, obstruction and physical destructions. These anomalies can diminish the sensing and communication functionalities of the network. Many kinds of holes can be formed in a sensor network that creates geographically correlated areas. These holes are also responsible for creating communication voids. These voids do not let the packets to reach the destination and minimises the expected network performance. Hence it ought to be resolved. In this paper we presented different kinds of holes that infect the sensor network, their characteristics and the effects on successful communication within the sensor network .Later we presented a detailed review on different routing hole handing techniques available in literature ,their possible strengths and short comes. At last we also presented a qualitative comparison of these routing hole handing techniques.

Vehicular ad hoc network usually operates in various challenging situations like frequent topology changes, high vehicular mobility and the wide range of communication networks. Due to this it is very hard to maintain a higher data rate and also to achieve low latency during data communication. To overcome these problems, given the dynamic natures of all the vehicles in a given network in the proposed routing method, we have defined two fundamental parameters to determine the forwarding vehicle. The first parameter, which we developed, we call it "Channel quality factor (CQF)" or 'Z'. The other parameter known as "Communication expiration time" or 'T' together with CQF is used in the present method to determine the forwarding vehicle. Fuzzy logic is also used to optimize various Quality of Service matrices. This proposed routing method involves two main parts; one is for forwarding Vehicle selection in the road based on the fuzzy logic. The second one is Road selection at the Road Junction to select the right path to reach the signal to the destination vehicle. The simulation results show that our proposed method performs well compare to other well-known protocols (MoZo, BRAVE, OFAODV) in terms of the average end to end delay, packet delivery ratio and control packet overhead, given any number of vehicles in a set of streets. While we are comparing with VEFR protocol, our proposed method shows higher performance in terms of average E2E delay and control packet overhead. However, it is interesting to see that VEFR gives ∼ 5% better result than our proposed method when the number of vehicles in the streets are lower. But in the limit, when the number of vehicles reaches close to ∼ 1900 the difference between the proposed method and method in VEFR goes to zero. At last we compare our proposed method with junction based two V2I protocols. In every cases, it shows better result even though we change the speed of the vehicles, beacon interval, channel data rate and transmission region. [ABSTRACT FROM AUTHOR]

Geographic routing in wireless ad hoc networks is characterized by routing decisions made from locally available position information, which entails network scalability. However, it requires an effective recovery approach to sending a packet bypassing network holes whenever the simple greedy forwarding fails. Among well-known approaches, rotational sweep routing algorithms based on a circular arc are able to achieve packet delivery guarantee as well as low routing path stretch under the impractical assumption that a wireless link exists between two nodes if and only if their distance is less than one unit. Instead, we propose a cooperative rotational sweep algorithm taking into account practically imperfect wireless connections. The algorithm involves a regular rotational sweep procedure and a cooperative one both making use of iterative sweeps with circular arcs of decreasing size subjective to a minimum size constraint. Essentially, the cooperative rotational sweep procedure resolves hidden node issues through exploiting packet header overheads for memory of the latest routing path while iterative sweeps reduce the possibility of missing pivotal relays. Simulation results demonstrate that the proposed scheme presents the benefit of using packet header overheads to support high end-to-end routing success probabilities without sacrificing the inherent feature of localized routing. [ABSTRACT FROM AUTHOR]

Flying ad hoc networks (FANETs) belong to the family of mobile ad hoc networks (MANETs). They have gained high popularity due to their extensive applications in various industries such as emergency management, military missions, and supervision. However, these networks face important challenges in guaranteeing reliable data transmission because of their dynamic nature and lack of infrastructure. In this paper, a new version of the greedy perimeter stateless routing scheme called GPSR+AODV is proposed in FANET. It combines two routing schemes, namely GPSR and AODV, and is a family member of geographic routing methods. In GPSR+AODV, each UAV consists of a certain hello broadcast period that is adjusted based on the prediction of its spatial coordinates in the future. Additionally, GPSR+AODV modifies the greedy forwarding process and restricts the search space for finding the next-hop node by obtaining a refined candidate set, calculated in the cylindrical coordinate system. Then, each UAV in the refined candidate set is evaluated under a fitness function, and the most suitable next-hop node with the maximum fitness is determined. This function is a combination of four criteria, namely relative velocity, energy level, buffer capacity, and distance to destination. When failing in the greedy forwarding process, GPSR+AODV changes the forwarding technique and uses an AODV-based perimeter forwarding technique to select the best next-hop node. Lastly, GPSR+AODV is implemented by the NS2 simulator, and the simulation results show a successful performance in terms of packet delivery rate, throughput, and delay compared to AGGR, AeroRP, and GPSR. However, the routing overhead in the proposed scheme is higher than that in AGGR. [ABSTRACT FROM AUTHOR]

Opportunistic ad hoc networks are characterized by intermittent and infrastructure-less connectivity among mobile nodes. Because of the lack of up-to-date network topology information and frequent link failures, geographic routing utilizes location information and adopts the store–carry–forward data delivery model to relay messages in a delay-tolerant manner. This paper proposes a message-forwarding policy based on movement patterns (MPMF). First, one- and two-hop location information in a geographic neighborhood is exploited to select relay nodes moving closer to a destination node. Message-forwarding decisions are made by referring to selected relay nodes’ weight values obtained by calculating the contact frequency of each node with the destination node. Second, when relays in the vicinity of a message-carrying node are not qualified due to the sparse node density and nodal motion status, the destination’s movement and the location information of a one-hop relay are jointly utilized to improve the message-forwarding decision. If the one-hop relay is not closer to the destination node or moving away from it, its centrality value in the network is used instead. Based on both synthetic and real mobility scenarios, the simulation results show that the proposed policy performs incomparable efforts to some typical routing policies, such as Epidemic, PRoPHETv2, temporal closeness and centrality-based (TCCB), transient community-based (TC), and geographic-based spray-and-relay (GSaR) routing policies.

The Q-learning based geographic routing approaches suffer from problems of low converging speed and inefficient resources utilization in VANET due to the dynamic scale of Q-value table. In addition, the next hop selection based on local information can not always be conducive to the global message forwarding. In this letter, we propose an adaptive unmanned aerial vehicle (UAV) assisted geographic routing with Q-Learning. The routing scheme is divided into two components. In the aerial component, the global routing path is calculated by the fuzzy-logic and depth-first-search (DFS) algorithm using the UAV-collected information like the global road traffic, which is then forwarded to the ground requesting vehicle. In the ground component, the vehicle maintains a fix-sized Q-table converged with a well-designed reward function and forwards the routing request to the optimal node by looking up the Q-table filtered according to the global routing path. The simulation results show the proposed approach performs remarkably well in packet delivering and end-to-end delay. [ABSTRACT FROM AUTHOR]

Device-to-Device (D2D) communication can be better option for some applications like military and natural disaster places where we need temporary communication network. Selection of relay nodes and routing schemes are key issues in large scale Device-to-Device (D2D) cooperative networks which affects the performance of the network. The performance may be degraded because of wrong selection of relay nodes. In this paper, we proposed a hybrid cluster based D2D cooperative routing scheme by combining the geographic routing and clustering routing. The main idea of our algorithm is to establish communication between similar mobility devices to reduce the mobility effect since the link between the devices moving with the same (approximately) mobility is reliable. All the equal mobility devices are grouped to form a cluster; one of the devices in this is selected as a cluster head. We selected Cluster Head (CH) based on geographic routing and threshold based cooperative communication is provided within the cluster to improve the network performance. We evaluated efficacy of our proposed scheme over conventional routing approaches discussed in the literature. From the results it was observed that the proposed routing scheme improves End-to-End transmission delay by 39%, Energy consumption by 35% (approximately) and Bit Error Rate performance. [ABSTRACT FROM AUTHOR]

Summary: Geographic routing in mobile ad hoc network (MANET) has gained much attention even though it fails to find a route when a node meets a void zone (hole). Therefore, an efficient approach is required to avoid the void issues and to effectively transfer the data packets if a path is available between the source and destination nodes. For such, a hybrid evolutionary algorithm is introduced with geographical routing protocol (GRP) for avoiding the void, which selects the shortest route for routing from the source to the destination by combining firefly (FF) algorithm and galactic swarm optimization (HFFGSO). This proposed algorithm exploits the strengths of both the FF algorithm and galactic swarm mechanisms. In this paper, the cross‐layer design approach is implemented, which contains data link and network layer. The proposed hybrid FFGSO‐GRP algorithm improves the routing process within these layers. The implementation process for this proposed technique is carried out in NS2 simulator. From the simulation results, it is observed that our hybrid protocol when compared with the existing approaches proves its significance in terms of packet delivery ratio (PDR), delay, throughput, energy efficiency, power consumption, routing overhead and hop count. [ABSTRACT FROM AUTHOR]

Geographic routing for realistic conditions is often permeated with localization errors resulting in poor performance and high energy consumption. We propose a simple yet novel geographic routing method to accomplish routing in the presence of location and channel errors. In this algorithm, it is proposed that next hop node is selected based on the combined probability of distance, estimated location error and estimated channel access probability associated with neighbor nodes. The metrics observed for performance were the successful packet delivery rate and the energy consumed. Our algorithms performance is better compared to greedy forwarding techniques of algorithms such as Greedy routing scheme (GRS) and geographic random forwarding (GeRaF). Simulations show the throughput for our algorithm is better compared to others along with reducing the energy wasted on lost packets. [ABSTRACT FROM AUTHOR]

Underwater sensor networks (USNs) are getting popular for the purpose of monitoring and exploration of undersea terrain. However, underwater communication channel characteristics limits data gathering capacity and duration of monitoring. Efficient routing protocols can improve performance of USNs having dynamic topology and localization errors. This paper presents LETR; a geo-opportunistic routing protocol that considers localization errors and communication void regions. LETR considers transmission range levels for finding neighbor nodes. Sensor nodes search for neighbors by adapting different transmission range levels. The performance of our proposed protocol is evaluated against different parameters through simulations. The simulation results show that LETR significantly improves network performance in terms of energy consumption, packet loss ratio, fraction of void nodes and the total amount of depth adjustment performed by sensor nodes.

Position-based routing has proven to be well suited for highly dynamic environment such as Vehicular Ad Hoc Networks (VANET) due to its simplicity. Greedy Perimeter Stateless Routing (GPSR) and Greedy Perimeter Coordinator Routing (GPCR) both use greedy algorithms to forward packets by selecting relays with the best progress towards the destination or use a recovery mode in case such solutions fail. These protocols could forward packets efficiently given that the underlying network is fully connected. However, the dynamic nature of vehicular network, such as vehicle density, traffic pattern, and radio obstacles could create unconnected networks partitions. To this end, we propose GeoDTN+Nav, a hybrid geographic routing solution enhancing the standard greedy and recovery modes exploiting the vehicular mobility and on-board vehicular navigation systems to efficiently deliver packets even in partitioned networks. GeoDTN+Nav outperforms standard geographic routing protocols such as GPSR and GPCR because it is able to estimate network partitions and then improves partitions reachability by using a store-carry-forward procedure when necessary. We propose a virtual navigation interface (VNI) to provide generalized route information to optimize such forwarding procedure. We finally evaluate the benefit of our approach first analytically and then with simulations. By using delay tolerant forwarding in sparse networks, GeoDTN+Nav greatly increases the packet delivery ratio of geographic routing protocols and provides comparable routing delay to benchmark DTN algorithms.

In wireless sensor networks (WSNs), providing source node with sink position is an essential principle for geographic routing protocols. Previous works have only focused on the problem of sink localization in a 2-D sensing field while that of 3-D WSNs has received little attention. Providing sink location service with low control overhead and energy consumption is a challenging issue in 3-D WSNs area. In this paper, we propose a unital design based sink location service (UDSL) for WSNs. In this scheme, sink location announcement (SLA) and sink location query (SLQ) packets are forwarded along two paths or blocks. The node located at the intersection of the two paths sends the sink position to the source. In the proposed method, SLA and SLQ messages are constructed using unital design blocks. For this purpose, a mapping from unital design to sink location service has been proposed. However, this basic mapping does not guarantee an intersection of paths,therefore, we propose an enhanced UDSL providing 100% probability of intersection. In order to analyze the proposed scheme's performance, extensive WSNs simulations and experiments have been conducted. The results indicate that UDSL provides reasonable performance in terms of hop counts, path length, and energy consumption for providing sink location service.