Opportunistic Routing Algorithm Research Articles

Survey on Various DTN Routing Algorithms for Vehicular ADHOC Network (VANET)

Vehicle Adhoc Network (VANET) permits self-organized infrastructure. Link or Connectivity breakage or long delay (intermittent connection) is an important issue in the VANET which arises due to the dynamic topological changes. Mainly two algorithms Vehicle assisted Data Delivery (VADD) and Opportunistic routing algorithm supports for handling delay/disruption tolerant network (DTN). Intention of DTN is to create dynamic link between the sender and receiver vehicle in the case of link disruption or absence of path between two nodes and forwards the data using store carry and forward. VADD carry and forward the data as much as possible in disconnected network using intersection mode, straightway mode or destination mode. Opportunistic routing can deal the unreliable data and intermittent connectivity in VANET by considering the multiple nodes as a next hop forwarder instead of considering pre-selected single node to be the best forwarder. This paper gives the study about various opportunistic routing algorithms for handling delay/disruption tolerant network.

An Intelligent Opportunistic Routing Algorithm for Wireless Sensor Networks and Its Application Towards e-Healthcare.

The lifetime of a node in wireless sensor networks (WSN) is directly responsible for the longevity of the wireless network. The routing of packets is the most energy-consuming activity for a sensor node. Thus, finding an energy-efficient routing strategy for transmission of packets becomes of utmost importance. The opportunistic routing (OR) protocol is one of the new routing protocol that promises reliability and energy efficiency during transmission of packets in wireless sensor networks (WSN). In this paper, we propose an intelligent opportunistic routing protocol (IOP) using a machine learning technique, to select a relay node from the list of potential forwarder nodes to achieve energy efficiency and reliability in the network. The proposed approach might have applications including e-healthcare services. As the proposed method might achieve reliability in the network because it can connect several healthcare network devices in a better way and good healthcare services might be offered. In addition to this, the proposed method saves energy, therefore, it helps the remote patient to connect with healthcare services for a longer duration with the integration of IoT services.

A Dynamic Routing Path Reduction Protocol in Underwater Wireless Sensor Network

Recently, underwater wireless sensor networks (UWSNs) have emerged as a promising networking technique for various underwater applications. An energy efficient routing protocol plays a vital role in data transmission and practical applications. However, due to the specific characteristics of UWSNs, such as dynamic structure, narrow bandwidth, rapid energy consumption, and high latency, it is difficult to build routing protocols for UWSNs. In this paper, We propose a location aware opportunistic routing algorithm for under water communication. We analyse three main problems in under water communication; forwarding set selection forwarding set ranking to handle FSR problem, void handling method to handle the communication void (CV) and overhear and suppression procedure to deal with duplicate forwarding suppression (DFS) problems. The importance of the work is that it will provide an energy efficient pressure based opportunistic routing algorithm for wireless sensor network (UWSN). The routing protocol has been implemented in the ns2-AqaSim simulator and testbed for measurement of the performance metrics of the UASN. The simulation results showed that the novel routing method throughput has increased by 16%, 33%, and 55% when compared with SUN, VBF and DF method. It can effectively improve the throughput of nodes, balance positioning performance as well as energy use efficiency, and optimize the positioning result of UWASN.

Energy-Efficient Depth-Based Opportunistic Routing with Q-Learning for Underwater Wireless Sensor Networks.

Underwater Wireless Sensor Networks (UWSNs) have aroused increasing interest of many researchers in industry, military, commerce and academe recently. Due to the harsh underwater environment, energy efficiency is a significant theme should be considered for routing in UWSNs. Underwater positioning is also a particularly tricky task since the high attenuation of radio-frequency signals in UWSNs. In this paper, we propose an energy-efficient depth-based opportunistic routing algorithm with Q-learning (EDORQ) for UWSNs to guarantee the energy-saving and reliable data transmission. It combines the respective advantages of Q-learning technique and opportunistic routing (OR) algorithm without the full-dimensional location information to improve the network performance in terms of energy consumption, average network overhead and packet delivery ratio. In EDORQ, the void detection factor, residual energy and depth information of candidate nodes are jointly considered when defining the Q-value function, which contributes to proactively detecting void nodes in advance, meanwhile, reducing energy consumption. In addition, a simple and scalable void node recovery mode is proposed for the selection of candidate set so as to rescue packets that are stuck in void nodes unfortunately. Furthermore, we design a novel method to set the holding time for the schedule of packet forwarding base on Q-value so as to alleviate the packet collision and redundant transmission. We conduct extensive simulations to evaluate the performance of our proposed algorithm and compare it with other three routing algorithms on Aqua-sim platform (NS2). The results show that the proposed algorithm significantly improve the performance in terms of energy efficiency, packet delivery ratio and average network overhead without sacrificing too much average packet delay.

Release and collection method of residual energy for one-dimensional linear-zone internet of things

Energy consumption is one of the most important considerations when designing routing and transmission protocols of sensing networks in internet of things. In order to achieve low and balanced power consumption, an effective method is to refer to the residual energy of nodes. Some existing energy-efficiency routing algorithms are designed according to the residual energy of nodes, but they do not give the way of residual energy collection. In this paper, we design a strategy for releasing and collecting residual energy for one-dimensional linear topology networks. By listening to the broadcast messages and evaluating residual energy of forward nodes, nodes can dynamically update the residual energy information of all potential forwarders. The collection error is also analysed theoretically. This method can be applied to opportunistic routing and relay node selection algorithms. The simulation results show that our proposed method has very low collection error, and the error will not accumulate with the operation of the network.

Normalized Advancement Based Totally Opportunistic Routing Algorithm With Void Detection and Avoiding Mechanism for Underwater Wireless Sensor Network

Underwater wireless sensor network (UWSN) is the enabling technology for a new era of underwater monitoring and actuation applications. In this network, data aggregation and forwarding are intensely constrained due to channel impairment, and therefore require due consideration. One way to address the data collection of UWSN is by enhancing the routing protocol using the Opportunistic Routing (OR) technique. This article proposes a normalized advancement based opportunistic routing protocol called NA-TORA. NA-TORA is a geographically opportunistic routing protocol in which the next-hop forwarder is selected based on Normalized Advancement (NA). NA is calculated from Expected Transmission Count (ETX) and node' s energy consumption to find an optimal forwarding node. However, the forwarded data may not be received on the designated sink node due to the existence of a void node in the data forwarding route. To overcome the issue of void nodes, we have incorporated a void node detection and avoiding mechanism on NA-TORA, called NA-TORA with VA. The proposed scheme recursively detect void nodes and avoid these nodes to participate in data routing by utilizing the angle of transmission adjustment and transmission range extension method. The novelty of this work lies within its data transmission phase, where normalized advancement is used to select a potential candidate forwarder. Apart from that, the proposed routing protocol operates in two different modes, i.e., standard operating mode (NA-TORA), and void avoidance mode (NA-TORA with VA). Comprehensive simulations were performed to compare the performance of NA-TORA and NA-TORA with VA with some well-known existing routing protocols.

Energy Efficient SOCGO Protocol for Hole Repair Node Scheduling in Reliable Sensor System

A sensor node in the wireless sensor network (WSN) has an inadequate energy, and it cannot be interchanged due to the arbitrary placement, so the objective is to extend the network lifetime. An inadequate energy becomes a crucial problem to solve energy efficiency in WSN. In this work, we propose a new Self-Organizing Cluster based Greedy best-first search Opportunistic routing (SOCGO) protocol for balanced energy routing. In our proposed work, the operation of work is divided into four stages for energy balanced routing. They are Sleep state, active state, guard state and death state. The residual energy consumed through the examining adjacent nodes is presented as an aspect to estimate the detection rate, and it can achieve through the novel approach named as hybrid K-means and Greedy best-first search algorithm. Furthermore, the presence of coverage holes pairs within WSN can be recovered through an Opportunistic routing algorithm. This method repairs the coverage hole pairs and improves the network lifetime. Then this proposed SOCGO protocol can be implemented in both the homogeneous and heterogeneous environment. Simulation outcomes deliberates that our proposed SOCGO algorithm attains enhanced performance regarding the network lifetime, throughput, energy consumption, average end to end delay and packet delivery ratio.

Energy Optimization for WSN in Ubiquitous Power Internet of Things

This paper attempts to solve the problems of uneven energy consumption and premature death of nodes in the traditional routing algorithm of rechargeable wireless sensor network in the ubiquitous power Internet of things. Under the application environment of the UPIoT, a multipath routing algorithm and an opportunistic routing algorithm were put forward to optimize the network energy and ensure the success of information transmission. Inspired by the electromagnetic propagation theory, the author constructed a charging model for a single node in the wireless sensor network (WSN). On this basis, the network energy optimization problem was transformed into the network lifecycle problem, considering the energy consumption of wireless sensor nodes. Meanwhile, the traffic of each link was computed through linear programming to guide the distribution of data traffic in the network. Finally, an energy optimization algorithm was proposed based on opportunistic routing, in a more realistic low power mode. The experimental results show that the two proposed algorithms achieved better energy efficiency, network lifecycle and network reliability than the shortest path routing (SPR) and the expected duty-cycled wakeups minimal routing (EDC). The research findings provide a reference for the data transmission of UPIoT nodes.

An energy efficient void avoidance opportunistic routing protocol for underwater sensor

Underwater sensor network is an emerging technology due to its numerous applications in aqueous environments. However, limitations of these networks include limited bandwidth, high propagation delays and power constraints. Hence, new routing protocols must be designed specifically for USN. Opportunistic routing offers a promising method to overcome these limitations. The proposed protocol is a novel energy-efficient void avoidance opportunistic routing algorithm. The protocol deals with the issue of void holes during transmission while reducing energy consumption and keeping the packet delivery ratio at a satisfactory level. To evaluate the performance, two common metrics have been used for routing protocols in USNs; energy consumption and packet delivery ratio. Simulations were carried out in ns2 with Aqua-Sim. The performance of the proposed routing protocol is compared to VAPR. The performance evaluation of EEVA-OR indicate its benefit as compared to VAPR in terms of void detection, energy consumption and packet delivery ratio.

A Novel Routing Scheme for Creating Opportunistic Context-Virtual Networks in IoT Scenarios.

The massive amount of traffic required by the emerging Internet of Things (IoT) paradigm can be supported by the imminent arrival of 5G next-generation networks. However, the limited capacity of resources in IoT nodes, e.g., battery lifetime or buffer space, opens a challenge to be taken into account when proposing new routing solutions on IoT scenarios with intermittent connectivity. In this paper, we propose the concept of Opportunistic Context-Virtual Networks (OCVNs). The novelty of this approach is to create virtual groups of nodes that share interests in common for routing purposes. Therefore, only the nodes that are interested in the content of the messages that are flowing throughout the network are used as relaying nodes, providing their own resources for the sake of the communication. By leveraging the use of store-carry-and-forward mechanisms, a novel routing algorithm is proposed and evaluated over two realistic scenarios. Experimental results reveal that our solution outperforms other well-known opportunistic routing algorithms in terms of delivery probability and overhead ratio, while resource usage of relaying nodes is significantly reduced.

Energy Efficient Opportunistic Routing Protocol (EE-OR) for Underwater Wireless Sensor Network

The surface of the earth consists of 71 percent water. In recent years, research has focused on using underwater sensor networks (USN) to monitor and manage these aqueous environments. Research on the communication protocols in Terrestrial sensor networks (TSN) has been well investigated and various protocols proposed. In contrast with terrestrial wireless sensor networks, the characteristics of acoustic communication lead to challenges in deploying fully functional and operational USNs. In our proposed architecture, we present a new energy efficient opportunistic routing protocol (EE-OR). The proposed protocol is a novel energy-efficient opportunistic routing algorithm for USNs. The protocol deals with the issue of ranking of nodes during candidate set selection while reducing energy consumption and keeping the packet delivery ratio at a satisfactory level. In order to evaluate the performance, we used two common metrics that have been used for routing protocols in USNs; energy consumption and packet delivery ratio. Simulations were carried out in NS-2 with Aqua-Sim. The performance of the proposed protocol is compared with the standard DBR protocols. The comprehensive performance evaluation attests the benefit of EE-OR as compared to the mentioned protocol in terms of energy consumption, end-to-end delay and packet delivery ratio.

An Opportunistic Network Routing Algorithm Based on Cosine Similarity of Data Packets between Nodes

The mobility of nodes leads to dynamic changes in topology structure, which makes the traditional routing algorithms of a wireless network difficult to apply to the opportunistic network. In view of the problems existing in the process of information forwarding, this paper proposed a routing algorithm based on the cosine similarity of data packets between nodes (cosSim). The cosine distance, an algorithm for calculating the similarity between text data, is used to calculate the cosine similarity of data packets between nodes. The data packet set of nodes are expressed in the form of vectors, thereby facilitating the calculation of the similarity between the nodes. Through the definition of the upper and lower thresholds, the similarity between the nodes is filtered according to certain rules, and finally obtains a plurality of relatively reliable transmission paths. Simulation experiments show that compared with the traditional opportunistic network routing algorithm, such as the Spray and Wait (S&W) algorithm and Epidemic algorithm, the cosSim algorithm has a better transmission effect, which can not only improve the delivery ratio, but also reduce the network transmission delay and decline the routing overhead.

Probability Prediction-Based Reliable and Efficient Opportunistic Routing Algorithm for VANETs

In the vehicular ad hoc networks (VANETs), due to the high mobility of vehicles, the network parameters change frequently and the information that the sender maintains may outdate when it wants to transmit data packet to the receiver, so for improving the routing efficiency and reliability, we propose the probability prediction-based reliable and efficient opportunistic routing (PRO) algorithm for VANETs. The PRO routing algorithm can predict the variation of signal-to-interference-plus-noise ratio (SINR) and packet queue length (PQL) of the receiver. The prediction results are used to determine the utility of each relaying vehicle in the candidate set. The calculation of the vehicle’s utility is the weight-based algorithm, and the weights are the variances of SINR and PQL. The relaying priority of each relaying vehicle is determined by the value of its utility. By these innovations, the PRO can achieve better routing performance (such as the packet delivery ratio, the end-to-end delay, and the network throughput) than the SRPE, ExOR (street-centric), and greedy perimeter stateless routing algorithms.

Totally opportunistic routing algorithm (TORA) for underwater wireless sensor network.

Underwater Wireless Sensor Network (UWSN) has emerged as promising networking techniques to monitor and explore oceans. Research on acoustic communication has been conducted for decades, but had focused mostly on issues related to physical layer such as high latency, low bandwidth, and high bit error. However, data gathering process is still severely limited in UWSN due to channel impairment. One way to improve data collection in UWSN is the design of routing protocol. Opportunistic Routing (OR) is an emerging technique that has the ability to improve the performance of wireless network, notably acoustic network. In this paper, we propose an anycast, geographical and totally opportunistic routing algorithm for UWSN, called TORA. Our proposed scheme is designed to avoid horizontal transmission, reduce end to end delay, overcome the problem of void nodes and maximize throughput and energy efficiency. We use TOA (Time of Arrival) and range based equation to localize nodes recursively within a network. Once nodes are localized, their location coordinates and residual energy are used as a matrix to select the best available forwarder. All data packets may or may not be acknowledged based on the status of sender and receiver. Thus, the number of acknowledgments for a particular data packet may vary from zero to 2-hop. Extensive simulations were performed to evaluate the performance of the proposed scheme for high network traffic load under very sparse and very dense network scenarios. Simulation results show that TORA significantly improves the network performance when compared to some relevant existing routing protocols, such as VBF, HHVBF, VAPR, and H2DAB, for energy consumption, packet delivery ratio, average end-to-end delay, average hop-count and propagation deviation factor. TORA reduces energy consumption by an average of 35% of VBF, 40% of HH-VBF, 15% of VAPR, and 29% of H2DAB, whereas the packet delivery ratio has been improved by an average of 43% of VBF, 26% of HH-VBF, 15% of VAPR, and 25% of H2DAB. Moreover, the average end-to-end delay has been reduced by 70% of VBF, 69% of HH-VBF, 46% of VAPR, and 73% of H2DAB. Furthermore, average hope-count has been improved by 57%, 53%, 16% and 31% as compared to VBF, HHVBF, VAPR, and H2DAB, respectively. Also, propagation delay has been reduced by 34%, 30%, 15% and 23% as compared to VBF, HHVBF, VAPR, and H2DAB, respectively.

MobiT: Distributed and Congestion-Resilient Trajectory-Based Routing for Vehicular Delay Tolerant Networks

Packet routing is important for vehicular delay tolerant networks (VDTNs). Opportunistic routing algorithms based on historical records are insufficiently accurate in forwarder selection due to movement randomness of vehicles. Trajectory-based routing algorithms tackle vehicle movement randomness but cannot be directly used in VDTNs due to the dependence on APs. In this paper, we develop a distributed trajectory-based routing algorithm (called MobiT) for VDTNs. This non-trivial task faces three challenges. First, vehicle trajectories must be sufficiently collected. Second, the trajectories cannot be updated frequently due to limited resources of the repository nodes. Third, achieving high routing performance even with partially collected trajectories. Our real trace study lays the foundation of the design of MobiT. Taking advantage of different roles of vehicles, MobiT uses service vehicles that move in wide areas to collect vehicle trajectories, and rely on the service vehicles and roadside units (called schedulers) for routing scheduling. By using regular temporal congestion state of road segments, MobiT schedules the packet to arrive at a roadside unit prior to the destination vehicle to improve routing performance. Furthermore, MobiT leverages vehicles’ long-term mobility patterns to assist routing. Our trace-driven simulation and real experiments show the effectiveness and efficiency of MobiT.

Cross-Layer and Reliable Opportunistic Routing Algorithm for Mobile Ad Hoc Networks

For improving the efficiency and the reliability of the opportunistic routing algorithm, in this paper, we propose the cross-layer and reliable opportunistic routing algorithm (CBRT) for Mobile Ad Hoc Networks, which introduces the improved efficiency fuzzy logic and humoral regulation inspired topology control into the opportunistic routing algorithm. In CBRT, the inputs of the fuzzy logic system are the relative variance (rv) of the metrics rather than the values of the metrics, which reduces the number of fuzzy rules dramatically. Moreover, the number of fuzzy rules does not increase when the number of inputs increases. For reducing the control cost, in CBRT, the node degree in the candidate relays set is a range rather than a constant number. The nodes are divided into different categories based on their node degree in the candidate relays set. The nodes adjust their transmission range based on which categories that they belong to. Additionally, for investigating the effection of the node mobility on routing performance, we propose a link lifetime prediction algorithm which takes both the moving speed and moving direction into account. In CBRT, the source node determines the relaying priorities of the relaying nodes based on their utilities. The relaying node which the utility is large will have high priority to relay the data packet. By these innovations, the network performance in CBRT is much better than that in ExOR, however, the computation complexity is not increased in CBRT.

Social identity–aware opportunistic routing in mobile social networks

AbstractMobile social networks, as a type of delay‐tolerant networks, are composed of nodes with different social properties in which information can be shared among them through opportunistic links. In such networks, it is important to analyze social properties of mobile nodes for transmitting information because they lack a stable source‐to‐destination delivery path and connect intermittently. Many social‐aware routing algorithms have been proposed to address these problems. However, these algorithms fail to achieve an optimal performance since they ignored an important social property, social identity. In this paper, we propose a social identity–aware opportunistic routing algorithm by considering social identities and social influences of mobile nodes in mobile social networks. It is shown that the social identity–aware opportunistic routing algorithm substantially improves the routing performance compared with the existing algorithms according to the simulation results in 2 real‐world human contact traces.

SROR: designing a social-based routing protocol for context-aware ubiquitous learning

Social-aware routing in delay-tolerant networks (DTNs) are a recent emerging technology that addresses intermittent connection issues, and has the potential to better support context-aware ubiquitous learning and create a social learning community without the infrastructure. This study proposes a novel social-based routing protocol called the Social Relation Opportunistic Routing (SROR) algorithm for mobile opportunistic networks, based on the three properties of social relations, social profiles, and social mobility patterns. The time complexity of finding an optimal routing solution is NP-Complete. Thus, our objective is to compute the optimal relay node for routing the data so that the delivery ratio is maximised heuristically. We demonstrate that the SROR algorithm outperforms the existing benchmark routing protocols and achieves the highest data delivery ratio with maximised routing efficiency under the dynamic social environments. With this advanced technology, an authentic and seamless context-aware ubiquitous learning environment can be realised and supported in the future.

SROR: designing a social-based routing protocol for context-aware ubiquitous learning

Social-aware routing in delay-tolerant networks (DTNs) are a recent emerging technology that addresses intermittent connection issues, and has the potential to better support context-aware ubiquitous learning and create a social learning community without the infrastructure. This study proposes a novel social-based routing protocol called the Social Relation Opportunistic Routing (SROR) algorithm for mobile opportunistic networks, based on the three properties of social relations, social profiles, and social mobility patterns. The time complexity of finding an optimal routing solution is NP-Complete. Thus, our objective is to compute the optimal relay node for routing the data so that the delivery ratio is maximised heuristically. We demonstrate that the SROR algorithm outperforms the existing benchmark routing protocols and achieves the highest data delivery ratio with maximised routing efficiency under the dynamic social environments. With this advanced technology, an authentic and seamless context-aware ubiquitous learning environment can be realised and supported in the future.

The Maximum Uniform Message Distribution Problem

This paper introduces the maximum uniform message distribution (MUMD) problem, which can be present in delay-tolerant communication networks, where the destination of the messages is not present in the network. This type of behavior arises in scenarios of natural disasters or social conflicts where a global communication network is not available. In these scenarios, the people inside the affected area might use their mobile devices to communicate in an opportunistic manner. During this communication, the devices can duplicate, exchange, and gather messages with the intention of afterward delivering them to the global communication network. A device successfully delivers all messages in its memory when it reaches the global communication network. We model the MUMD as a computational problem and analyze the effectiveness of the existing opportunistic routing algorithms to solve this problem. Furthermore, we design an algorithm for the MUMD and perform experimental simulations to analyze its performance. Our results show that the greater the number of copies of messages and the more uniformly distributed through the network they are, the higher the probability that deliveries will be successful.