Opportunistic Routing Research Articles

An Intelligent and Trust UAV-Assisted Code Dissemination 5G System for Industrial Internet-of-Things

A large number of devices with communication and sensing capabilities are connected to the 5G network and facilitate distributed industrial Internet of Things (IIoT) applications. Those devices can update their program code by using software-defined technologies and upgrade functions without hardware replacement, thus, greatly facilitating the development of IIoT applications. Disseminating code safely to these devices is a pivotal issue. However, the existing methods rarely consider whether the code received by devices is integrated. Therefore, an unmanned aerial vehicle (UAV) assisted trustworthy code dissemination (UTCD) framework in 5G-enabled intelligent IIoT systems is proposed to select credible mobile vehicles (MVs) to disseminate code with opportunistic routing style. In the UTCD framework, a verifiable trust evaluation scheme is proposed to identify the trust of the MVs by sending the UAV to collect the code wait to be verified (CWV) directly from the selected devices (bedrock devices) as evidence. This scheme is a fundamental change from the previous passive, indirect and unverifiable trust evaluation schemes. In UTCD, a bedrock devices selection scheme is presented by selecting as few bedrock devices as possible to collect as much the CWV as possible with the minimum cost. After that, based on the CWV, which is collected from bedrock devices, a complete trust evaluation scheme is proposed to obtain the trust of MVs. Furthermore, a UAV trajectory optimization algorithm is proposed to obtain as much CWV as possible within the limited conditions of UAV. Finally, comprehensive experiments conduct on a real-life dataset demonstrate that the proposed scheme outperforms the existing schemes in terms of the efficiency and security of code dissemination.

Energy-Efficient and Secure Opportunistic Routing Protocol for WSN: Performance Analysis with Nature-Inspired Algorithms and Its Application in Biomedical Applications.

Wireless sensor network (WSN) is made up of tiny sensor nodes. The application of WSN in diverse fields has seen a tremendous escalation in recent years. WSN applications are constrained by the limited set of computing resources possessed by the sensor nodes and the security aspects of data communication in the WSN. Many algorithms based on nature-inspired optimization (NIO) have been proposed in the past to optimize the issue of energy efficiency and security in WSN. In the proposed work, two opportunistic routing algorithms, i.e., intelligent opportunistic routing protocol (IOP) and trust-based secure intelligent opportunistic routing protocol (TBSIOP), are compared against two NIO algorithms developed for achieving energy efficiency and security in WSN for performance analysis. The performance is evaluated by simulating the algorithms on MATLAB and comparing the obtained results with existing ACO-based and PSO-based routing algorithms. It is observed that the TBSIOP outperforms the NIO-based algorithms in terms of energy efficiency, network lifetime, packet delivery ratio, end-to-end delay, and average risk level. All the parameters under consideration are recorded in the presence of a maximum of 50% malicious nodes for 25, 50, and 100 nodes' test cases. The increasing size of the network has a significant effect on the performance of TBSIOP, as the packet delivery ratio is close to 100%. Also, TBSIOP can easily avoid malicious nodes during the routing process as reflected from the results. This will improve the network lifetime of TBSIOP compared to other protocols. As far as the application of the work is concerned, it would be beneficial for smart healthcare services. It can also help in better communication during the sharing of data by providing energy-efficient services and keeping the network alive for a longer period.

An efficient energy consumption and delay aware autonomous data gathering routing protocol scheme using a deep learning mobile edge model and beetle antennae search algorithm for underwater wireless sensor network

AbstractUnderwater wireless sensor network (UWSN) is used to monitor the compactness of ocean surveillance, marine and harsh underwater environment. In this article, an efficient energy consumption and delay aware autonomous data gathering routing protocol (ADGRP) scheme based on deep learning (dl) mobile edge model (mem) and beetle antennae search algorithm (BASA) for UWSN is proposed to overcome above problems. ADGRP is used to gather more data from the underwater environment by the use of the autonomous underwater vehicle (AUV). DL‐MEM is used to increase the network life time. Then the deep learning parameters are optimized by using BAS. The objective function is “to increase the efficiency and lifetime of network by decreasing the energy consumptions and delay.” The simulation process is carried out in MATLAB site. The proposed ADGRP‐DL‐MEM‐BASA provides lower energy consumption 20.83%, 34.66%, 18.03%, 20.92%, 22.34%, lower energy drop 7.85%, 23.94%, 17.93%, 21.93%, 31.94% is compared with the existing energy‐efficient probabilistic depth‐based routing (EEPDBR‐UWSN), ordered contention MAC (OCMAC‐UWSN), Q‐learning based energy‐efficient and void avoidance routing protocol for underwater acoustic sensor networks (QL‐EEBDG‐UWSN), energy‐efficient depth‐base opportunistic routing along Q‐learning for underwater wireless sensor networks (EDORQ‐UWSN), channel‐aware reinforcement learning‐based multipath adaptive routing for underwater wireless sensor networks (CARMA‐ EE‐UWSN) respectively.

Opportunistic Routing for Large Scale IoT Network to Reduce Transmission Overhead

Opportunistic Routing for Large Scale IoT Network to Reduce Transmission Overhead

Towards Energy-Efficient and Delay-Optimized Opportunistic Routing in Underwater Acoustic Sensor Networks for IoUT Platforms: An Overview and New Suggestions.

In underwater acoustic sensor networks (UASNs), the reliable transfer of data from the source nodes located underwater to the destination nodes at the surface through the network of intermediate nodes is a significant challenge due to various unique characteristics of UASN such as continuous mobility of sensor nodes, increased propagation delay, restriction in energy, and heightened interference. Recently, the location-based opportunistic routing protocols seem to show potential by providing commendable quality of service (QoS) in the underwater environment. This study initially reviews all the latest location-based opportunistic routing protocols proposed for UASNs and discusses its possible limitations and challenges. Most of the existing works focus either on improving the QoS or on energy efficiency, and the few hybrid protocols that focus on both parameters are too complex with increased overhead and lack techniques to overcome communication voids. Further, this study proposes and discusses an easy-to-implement energy-efficient location-based opportunistic routing protocol (EELORP) that can work efficiently for various applications of UASN-assisted Internet of Underwater Things (IoUTs) platforms with reduced delay. We simulate the protocol in Aqua-Sim, and the results obtained show better performance than existing protocols in terms of QoS and energy efficiency.

CED-OR Based Opportunistic Routing Mechanism for Underwater Wireless Sensor Networks

CED-OR Based Opportunistic Routing Mechanism for Underwater Wireless Sensor Networks

Shadowing-fading-based intersection geographic opportunistic routing protocol for urban VANETs

Shadowing-fading-based intersection geographic opportunistic routing protocol for urban VANETs

Securing localization-free underwater routing protocols against depth-spoofing attacks

Localization-free depth-based opportunistic routing protocols are an energy efficient choice for underwater wireless sensor networks (UWSNs). However, most depth-based routing protocols are vulnerable to sinkhole attacks caused by depth spoofing. In this paper, we propose an energy-efficient depth-based probabilistic routing protocol (DPR) that is resilient against depth spoofing. By encouraging unqualified (suboptimal) relay nodes to randomly forward data packets, the adversarial effects of depth-spoofing can be mitigated. As the randomized forwarding probability increases, a better packet delivery ratio can be achieved when under depth-spoofing attacks. To keep energy consumption in check, we propose a simulation-based methodology for finding the optimal forwarding probability. By adjusting the unqualified node forwarding probability, the proposed DPR protocol can effectively resist depth-spoofing attacks with a reasonably efficient energy overhead. A delivery ratio exceeding 90% can be achieved under attack with energy overhead as low as 35% under normal conditions. In comparison with relevant existing protocols, the proposed protocol achieves better energy efficiency, resilience efficiency, and scalability.

PERFORMNACE ANALYSIS OF OPPORTUNISTIC ROUTING PROTOCOLS FOR MANETs

The advancements in the wireless networks have increased the utilization of wireless devices in emergency situations such as disaster relief and rescue operations, hurricane affected regions and underground mines and so on. Traditional routing protocols of Mobile Adhoc networks are not appropriate for such scenarios because it requires constant path for its communication. Hence, in order to surmount the restriction of traditional routing protocols, and to increase the network performance in emergency situations, the opportunistic routing paradigm has been suggested in recent research works. The purpose of Opportunistic Routing protocols is to increase the reliability of delivering data packets to their destination by using the broadcast nature of the wireless medium. In this paper, we provide a comprehensive study of the existing literature and performance analysis of opportunistic routing protocols

A Hybrid Opportunistic IoT Secure Routing Strategy Based on Node Intimacy and Trust Value

Routing strategy is one of the most important researches in Opportunistic Internet of Things (IoT), and it highly influences the efficiency of data transmission. In this paper, a hybrid Opportunistic IoT secure routing strategy based on node intimacy and trust value (HIRouter) is proposed to resolve the problem of unbalanced transmission efficiency and security in the message delivery process. According to the records of node encounter and message forwarding, the strategy proposed in this paper can calculate nodes’ intimacy and trust value. The messages are then forwarded based on the intimacy and trust value between nodes. Experimental results verify that HIRouter algorithm we proposed can improve the message delivery rates and reduce the overhead rate in the Opportunistic IoT with dense nodes and frequent interactions between nodes.

Opportunistic Routing for Opto-Acoustic Internet of Underwater Things

Internet of Underwater Things (IoUT) is a technological revolution that could mark a new era for scientific, industrial, and military underwater applications. To mitigate the hostile underwater channel characteristics, this article considers a multimodal underwater network that hybridizes acoustic and optical wireless communications to achieve an ubiquitous control and high-speed low-latency networking performance, respectively. Since underwater optical wireless communications (UOWCs) suffer from limited range, it requires effective multihop routing solutions. In this regard, we propose a sector-based opportunistic routing (SectOR) protocol. Unlike the traditional unicast routing (TUR) techniques, which send packets to a unique relay, opportunistic routing (OR) targets a set of candidate relays by leveraging the broadcast nature of the UOWC channel. OR improves the packet delivery ratio as the likelihood of having at least one successful packet reception is much higher than that in TUR. Contingent upon the performance characterization of a single-hop link, we obtain a variety of local and global metrics to evaluate the fitness of a candidate set (CS) and develop candidate prioritization techniques for various OR metrics. Since rate <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\leftrightarrow $ </tex-math></inline-formula> error and range <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\leftrightarrow $ </tex-math></inline-formula> beamwidth tradeoffs yield different CS diversities, we develop a candidate filtering and searching algorithm to find the optimal sector shaped coverage region by scanning the feasible search space. Moreover, a hybrid acoustic/optic coordination mechanism is considered to avoid duplicate transmission of the relays. Numerical results show that the SectOR protocol can perform even better than optimal unicast routing protocols in well-connected underwater networks.

Network coding data distribution technology between streams of emergency system based-wireless multi-hop network

The usage of network coding technology in the network can effectively improve the network performance in many aspects, such as delay, energy consumption, and throughput. Considering that multiple data streams can be encoded together, the network node forwards the data packet to reduce the transmission times of the encoded data packet in the wireless network. In particular, a measurement standard based on the number of pre-coding transmissions is proposed with the help of network coding and multiplexing technology. First, the opportunistic routing strategy between multiple data streams of network coding is applied to optimize the forwarding and transmission mode of data storage, which can effectively reduce the transmission of data packets. Second, the concept of coding is introduced into the relay nodes in the network, and the data distribution strategy is used to reduce the number of data packet transmissions in the network. Finally, a measurement standard for the number of pre-coding transmissions is designed for the resource allocation path in wireless multi-hop networks. The experimental results show that the strategy proposed in this paper can achieve a lower transmission delay compared with the single-path transmission strategies and the multi-path data distribution strategies without considering network coding.

Realizing Opportunistic Routing in Multi-Channel Environments

Opportunistic Routing (OR), which utilizes the broadcast nature of wireless communication to route packets in a dynamic way, significantly improves the transmission quality. Most of the researches focus on the single channel scenario; however, multi-channel (MC) is widely adopted over wireless communication systems. How to apply OR over MC environments is quite challenging and still an unsolved issue. OR operating over single channel environments collects acknowledgements mainly through overhearing data packets. In contrast, MC environments increase the performance by reducing interference and providing more bandwidth. Since users scatter over multiple channels, the chance of overhearing is reduced. Without overhearing acknowledgements (ACKs), the performance of OR degrades due to duplicate transmissions. To better understand the behavior of OR over MC environments, this paper first surveys current OR methods and constructs a simplified scenario to observe how they behave as the number of interfaces and channels increases. Then, analyze and compare their costs and penalties to find out a potential method. Finally, refine the potential method for MC environments. It is observed that token passing is the most potential method for its high efficiency of utilizing control packets. To apply token passing to OR in MC environments, this paper proposed multi-channel token passing (MCTP) to resolve the hazards of token passing paths and dynamic rate for multiple flows. Simulation results show that MCTP has high performance with low and consistent overheads. In addition, MCTP is scalable with increasing interface and channel numbers, which makes it a prototype for the future OR research in MC environments.

An Opportunistic Routing for Energy-Harvesting Wireless Sensor Networks With Dynamic Transmission Power and Duty Cycle

Opportunistic routing (OR) is widely used in energy-harvesting wireless sensor networks (EH-WSNs). The transmission power of sensor nodes in EH-WSNs is usually adjusted dynamically to make full use of the harvested energy. Many OR algorithms with dynamic transmission power adjustment have been proposed for EH-WSNs. However, fewer studies consider the non-bidirectional communication and the increase in packet retransmission and delay caused by the heterogeneous transmission power/radii. To this end, we propose an opportunistic routing algorithm for EH-WSNs with dynamic transmission power and duty cycle (ORDPD). It adjusts the transmission power of the sensor nodes at the end of each time slot, according to the predicted available energy. It also adjusts the transmission power and duty cycle of the sensor nodes in time slots if the nodes receive packets from other nodes outside their current transmission range. ORDPD also adopts an improved transmission model and information exchange mechanism to dynamically update relay sets and forwarding paths. A series of experiments were conducted to verify the effectiveness of the proposed algorithm. The experimental results demonstrate that the proposed ORDPD reduces non-bidirectional communication and retransmission significantly and performs better than its corresponding competitors.

Proliferation of Opportunistic Routing: A Systematic Review

Opportunistic networks (OppNet) a new paradigm emerges after the great advancement of wireless technology and MANETs (Mobile Ad-hoc Networks). Store-Carry-forward phenomena is used to route the messages in OppNets; therefore, it is called delay tolerant network (DTNs). OppNet is such a heterogeneous flexible network that works in hurricane affected regions and volcanoes environment. The objective of this article is to determine, evaluate, elect and synthesize all terrific quality research work on the basis of Research Questions (RQ) which is significant to use for opportunistic routing. Systematic literature review on state-of-the-art researches on routing protocols are presented with comparative analysis. To eliciting relevant work for review, advanced exploration is conducted on contrasting digital libraries. This work gives the opportunity to the readers to understand what has been done in field of Opportunistic Routing (OR), what parameters effect the performance of protocol, name of the organization; who works in this field. At last, issues, challenges, and upcoming future terms of this network are discussed.

MHADBOR: AI-Enabled Administrative-Distance-Based Opportunistic Load Balancing Scheme for an Agriculture Internet of Things Network

In this article, we present a supervised machine learning multipath and administrative-distance-based load balancing algorithm for an Agriculture Internet of Things (AG-IoT) network. The proposed algorithm is known as an artificial intelligence or simply AI-enabled multihop and administrative-distance-based opportunistic routing (MHADBOR) algorithm, which processes the collected information from source to the destination by means of multihop count and administrative-distance-based communication infrastructure in the network. Beside that, we used cluster heads (CH), microbase stations ($\boldsymbol {\Re BS}$ℜBS), and macrobase stations ($\boldsymbol {\aleph BS}$ℵBS) in the network with a frequent rate to effectively utilize the administrative distance while managing the deployed network traffic in a congestionless communication environment. In addition, the MHADBOR algorithm empowers the participating devices to practice the administrative distance rather than hop count communication when they are in the vicinity of network special components, e.g., CH and $\boldsymbol {\Re BS}$ℜBS outcome statistics of the MHADBOR algorithm in the simulation environment exhibit an extraordinary improvement in contention, congestion, communication, and computing costs, accompanied by throughput and end-to-end (E2E) delay and packet loss ratio in the deployed AG-IoT network.

Adaptively Prioritizing Candidate Forwarding Set in Opportunistic Routing in Vanets

Adaptively Prioritizing Candidate Forwarding Set in Opportunistic Routing in Vanets

A Wireless Mesh Opportunistic Network Routing Algorithm Based on Trust Relationships

To solve the problem of low message delivery rate and high network resource consumption when forwarding messages in opportunistic networks, an opportunistic routing algorithm based on trust relationships for wireless mesh networks is proposed. Firstly, the wireless mesh network is analyzed and the opportunistic routing model is constructed; By analyzing the security mechanism and security threat of communication entities, then measuring the trust degree of links and nodes, establishing the trust relationship between nodes, and defining and quantifying a new security measurement method based on the trust model; Finally, according to the security measurement method defined by the model, select the node with high trust value to participate in the message forwarding process. At the same time, give priority to the node with greater trust with the destination node as the relay node, and allocate the message copy according to the trust degree to make the message pass along the direction of increasing trust, to complete the design of opportunistic routing algorithm in wireless mesh networks. Experimental results show that the routing algorithm can effectively improve the message delivery rate, up to about 95&#x0025;, and reduce the consumption of network resources.

Adaptively Prioritizing Candidate Forwarding Set in Opportunistic Routing in Vanets

Adaptively Prioritizing Candidate Forwarding Set in Opportunistic Routing in Vanets

A Novel Theoretical Probabilistic Model for Opportunistic Routing with Applications in Energy Consumption for WSNs.

This paper proposes a new theoretical stochastic model based on an abstraction of the opportunistic model for opportunistic networks. The model is capable of systematically computing the network parameters, such as the number of possible routes, the probability of successful transmission, the expected number of broadcast transmissions, and the expected number of receptions. The usual theoretical stochastic model explored in the methodologies available in the literature is based on Markov chains, and the main novelty of this paper is the employment of a percolation stochastic model, whose main benefit is to obtain the network parameters directly. Additionally, the proposed approach is capable to deal with values of probability specified by bounded intervals or by a density function. The model is validated via Monte Carlo simulations, and a computational toolbox (R-packet) is provided to make the reproduction of the results presented in the paper easier. The technique is illustrated through a numerical example where the proposed model is applied to compute the energy consumption when transmitting a packet via an opportunistic network.