Hybrid Routing Research Articles

OpenPubSub: Supporting Large Semantic Content Spaces in Peer-to-Peer Publish/Subscribe Systems for the Internet of Multimedia Things

The decentralized and highly scalable nature of structured peer-to-peer networks, based on distributed hash tables (DHTs), makes them a great fit for facilitating the interaction and exchange of information between dynamic and geographically dispersed autonomous entities. The recent emergence of multimedia-based services and applications in the Internet of Things (IoT) has led to a noticeable shift in the type of data traffic generated by sensing devices from structured textual and numerical content to unstructured and bulky multimedia content. The wide semantic spectrum of human recognizable concepts that can be stemmed from multimedia data, e.g., video and audio, introduces a very large semantic content space. The scale of the content space poses a semantic boundary between data consumers and producers in large-scale peer-to-peer publish/subscribe systems. The exact-match query model of DHTs falls short when participants use different terms to describe the same semantic concepts. In this work, we present OpenPubSub, a peer-to-peer content-based approximate semantic publish/subscribe system. We propose a hybrid event routing model that combines rendezvous routing and gossiping over a structured peer-to-peer network. The network is built on the basis of a high-dimensional semantic vector space as opposed to conventional logical key spaces. We propose methods to partition the space, construct a semantic DHT via bootstrapping, perform approximate semantic lookup operations, and cluster nodes based on their shared interests. Results show that for an approximate event matching upper bound recall of 56.7%, rendezvous-based routing achieves up to 54% recall while decreasing the messaging overhead by 44%, whereas, the hybrid routing approach achieves up to 43.8% recall while decreasing the messaging overhead by 59%.

Telematics Collaborative Resource Allocation Algorithm Based on Cloud Sidecar

This paper provides an in-depth study and analysis of a distributed allocation algorithm for collaborative resources for cloud-edge-vehicle-based Telematics. The approach starts from the emerging application of urban environmental monitoring based on vehicular networking, with an integrated design of data sensing detection and transmission, and collaborative monitoring of vehicle swarm intelligence based on urban air quality collection to avoid redundancy of information and communication overload. A hybrid routing method with minimal delay for reliable data transmission is proposed. The power adjustment algorithm divides the channel into 3 states. When the CBR is less than 0.5, the channel is in an idle state, and when the CBR is greater than 0.5 and less than 0.8, the channel is in an active state. The algorithm designs redundancy strategies based on coding mechanisms to improve the reliability of data transmission, combines coding mechanisms with routing design, incorporates routing switching ideas, and performs probability-based routing decisions to minimize the delay. In straight-line road sections, a fuzzy logic prediction-based vehicle adaptive connectivity clustering routing algorithm is proposed to reduce the communication overhead during vehicle collaboration and ensure high network connectivity; at intersections, a probability-based minimum delay routing decision algorithm is proposed to reduce the information transmission delay. Experiments show that the proposed method effectively improves the efficiency of data-aware collection and transmission, and increases the reliability of transmission. With the explosive growth of video services, the problem of intelligent transmission of DASH-based video streams has become another research hotspot in mobile edge networks. Based on the edge container cloud architecture of vehicular networking, the resource constraints of microservices when deployed in the edge cloud platform were analyzed, and a multi-objective optimization model for microservice resource scheduling was established with the comprehensive performance objectives of shortest microservice invocation distance, highest resource utilization of physical machine clusters, and ensuring load balancing as much as possible.

Optimized hybrid routing protocol for energy-aware cluster head selection in wireless sensor networks

The clustering mechanism in wireless sensor networks (WSNs) is the ideal strategy for constructing an energy efficient protocol for achieving extended network lifetime, energy efficiency, and scalability. The design of energy efficient protocols in WSNs is essential, as the sensor nodes are battery powered, and may be completely drained, resulting in deterioration in network lifetime. Energy efficient protocols aim to maximize network lifetime while minimizing overall energy consumption to avoid interruptions to the wireless sensor nodes deployed for monitoring and recording physical information from the environment. Moreover, hybrid metaheuristic-optimization based clustering and routing protocols are widely used for attaining energy stability and network lifetime. In this study, the golden eagle optimization algorithm (GEOA) and improved grasshopper optimization algorithm (IGHOA) based on the energy efficient cluster-based routing protocol (GEIGOA) are proposed for sustaining energy stability and augmenting network lifetime longevity by overcoming challenges in the cluster head (CH) selection process. In particular, by optimizing the node centrality, node degree, distance to the base station, distance to the neighbors, and residual node energy, GEOA selects an optimal CH from the deployed group of sensor nodes in the network. Furthermore, IGHOA is utilized to determine a reliable and optimal route between the CH and base station (BS) by assessing node degree, residual energy, and distance parameters. Moreover, the proposed GEIGOA was confirmed to be sufficiently capable in improving the probability of preventing the worst nodes from being selected as CHs with different number of sensor nodes, which was predominantly enhanced by 12.64%, 15.82%, 18.96%, and 20.98% compared with the competitive CH selection schemes. In addition, the computational cost incurred by the proposed GEIGOA with different number of sensor nodes was also confirmed to be minimized by 14.98%, 17.21%, 19.76%, and 21.62% compared with the competitive CH selection schemes.

Hybrid routing for safety data with intermittent V2I connectivity

V2I communications complement V2V safety applications by dealing with emergency situations such as crash scenarios that the V2V program cannot handle or that could be addressed more effectively. However, depending on the deployed infrastructure, we can distinguish between three situations regarding allowed communications: infrastructure-based, infrastructure-less and intermittent infrastructure. We will focus in vehicular networks with an intermittent connectivity, where the unavailability of direct communication with RSUs poses huge problems, especially when vehicles have to send safety-related messages to the infrastructure. In fact, a scattered vehicular infrastructure leads to non-homogeneous coverage, especially in highway scenarios extending over long distances; it is very expensive to set up an infrastructure across the whole road. Our objective is to address the challenges related to safety information forwarding towards the RSU in such networks by enabling vehicles to make an optimal forwarding decision based on contextual information relative to the infrastructure and the neighbourhood. In this work, we present HyRSIC (Hybrid Routing for Safety data with Intermittent V2I Connectivity), a routing approach, combining geographical and topological routing, proposed to deal with data forwarding in intermittent infrastructure-based networks. We conducted an in-depth evaluation from three different perspectives: scalability, reliability and efficiency. The results show that HyRSIC is able to scale quickly and adapt promptly to density and speed variations. Compared to GPSR and its variant ILTS+GPSR, HyRSIC offers the best packet delivery ratio for sparse networks, 12-27% higher, and the lowest End-to-End delivery delay, 25-50% less.

A New Hybrid Routing Algorithm based on Genetic Algorithm and Simulated Annealing for Vehicular Ad hoc Networks

A New Hybrid Routing Algorithm based on Genetic Algorithm and Simulated Annealing for Vehicular Ad hoc Networks

An alternative route to extract nickel and cobalt from non-commercial laterite ore

Laterite ores, which represent around two-thirds of nickel reserves, became an important source of nickel and cobalt metals. The objective of the present study was to investigate the efficiency of a hybrid route to extract nickel and cobalt present in a laterite ore sample which was not commercially attractive to be processed through the current routes. The process efficiency was investigated through the application of different test conditions, such as roast temperature, ore sample comminution, and moisture. Chemical analysis by atomic absorption was used to quantify the metals. The solid phase’s identification and characterization were accomplished by X-ray diffraction and Scanning Electron Microscopy. The Rietveld Method was used for the mineral’s phase quantification. In terms of nickel and cobalt extractions, the most favorable condition was: particle size smaller than 38 µm, 50% sulfuric acid (wt.%), and 10% moisture (wt.%), which permitted nickel, cobalt, magnesium, and iron recoveries of 84.5%, 92.0%, and 93.0%, 27.0% respectively. These results indicate the successful application of the route. In addition, it was found that chlorite, chromite, hematite, and goethite were identified as the main nickel and cobalt carriers present in the process residue.

A Hybrid Route Selection Scheme for 5G Network Scenarios: An Experimental Approach.

With the significant rise in demand for network utilization, such as data transmission and device-to-device (D2D) communication, fifth-generation (5G) networks have been proposed to fill the demand. Deploying 5G enhances the utilization of network channels and allows users to exploit licensed channels in the absence of primary users (PUs). In this paper, a hybrid route selection mechanism is proposed, and it allows the central controller (CC) to evaluate the route map proactively in a centralized manner for source nodes. In contrast, source nodes are enabled to make their own decisions reactively and select a route in a distributed manner. D2D communication is preferred, which helps networks to offload traffic from the control plane to the data plane. In addition to the theoretical analysis, a real testbed was set up for the proof of concept; it was composed of eleven nodes with independent processing units. Experiment results showed improvements in traffic offloading, higher utilization of network channels, and a lower interference level between primary and secondary users. Packet delivery ratio and end-to-end delay were affected due to a higher number of intermediate nodes and the dynamicity of PU activities.

Performance Analysis of Wireless Sensor Network by Variation in Cluster Head Selection through mLEACH-CS Algorithm

Abstract: The energy depletion at the nodes due to large volume of data transmission and data reception for large scale Wireless Sensor Networks (WSN) is one of the important areas of concern. Unbalanced energy consumption due to data traffic overhead at the nodes near the base station (BS) results in early node death and reduction in network lifetime. To balance the load at the wireless nodes during clustering, a novel hybrid clustering and routing protocol has been proposed based on mLEACH (modified Low-Energy Adaptive Clustering Hierarchy) and Cuckoo Search (CS) algorithm. Initially, mLEACH protocol is utilized to solve a novel equation designed to select the cluster heads by rotation at every round of data transmission based on the maximum permissible cluster heads in the network. In the second phase, CS algorithm is implemented for uniform distribution of the cluster heads in the network for efficient multi-hop data routing in the network based on several weighted factors. The performance of the proposed algorithm is compared with other algorithms in literature in terms of energy consumption and network lifetime for different positions of the base station and varied number of cluster heads in the model application area. The proposed mLEACH-CS algorithm shows a significant improvement by 60% considering 300 nodes in the WSN architecture while it decreased to 40% for denser network architecture. Optimal choice of the number and position of the cluster heads in certain network architecture has proved beneficial for designing an energy efficient wireless network with improved network lifetime.

Effect of change of Antenna Model with the Variation of Pause Time for Reactive and Hybrid Routing Protocols in Mobile Ad-Hoc Networks

The collection of the many mobile nodes forming a short lived infrastructure with the help of any centralized administration. Since there's a random and dynamic modification in topology due to the quality of host, so the requirement for a study dynamic routing protocol is needed. Mobile ad-hoc network have the attributes like wireless affiliation, continuously dynamic topology, distributed operation and simple deployment. It establishes a short lived affiliation wherever nodes will be part of or leave the network at any time. Communication takes place by routing protocols in effective and economical manner in wireless network. Economical protocols are accustomed forward information packets while not a lot of packet loss. The target of the present paper is to boost the performance of the reactive and hybrid routing protocols with different directional antenna i.e. Omni and Pattern antenna with variation of pause time. The performance metrics in the research paper is PDR, NRL, Throughput and Routing Overhead.

Hybrid Clustering and Routing Algorithm with Threshold-Based Data Collection for Heterogeneous Wireless Sensor Networks.

The concept of the internet of things (IoT) motivates us to connect bulk isolated heterogeneous devices to automate report generation without human interaction. Energy-efficient routing algorithms help to prolong the network lifetime of these energy-restricted smart devices that are connected by means of wireless sensor networks (WSNs). Current vendor-level advancements enable algorithm-level flexibility to design protocols to concurrently collect multiple application data while enforcing the reduction of energy expenditure to gain commercial success in the industrial stage. In this paper, we propose a hybrid clustering and routing algorithm with threshold-based data collection for heterogeneous wireless sensor networks. In our proposed model, homogeneous and heterogeneous nodes are deployed within specific regions. To reduce unnecessary data transmission, threshold-based conditions are presented to prevent unnecessary transmission when minor or no change is observed in the simulated and real-world applications. We further extend our proposed multi-hop model to achieve more network stability in dense and larger network areas. Our proposed model shows enhancement in terms of load balancing and end-to-end delay as compared to the other threshold-based energy-efficient routing protocols, such as the threshold-sensitive stable election protocol (TSEP), threshold distributed energy-efficient clustering (TDEEC), low-energy adaptive clustering hierarchy (LEACH), and energy-efficient sensor network (TEEN).

Hybrid Air Route Network Simulation Based on Improved RW-Bucket Algorithm

The fixed-route network is the basis for airlines to carry out flight direction planning. Some countries and regions have introduced temporary routes as a supplement to the fixed route structure. Temporary routes have the advantages of intercepting curves and straightening, and less detouring areas, which can save airlines fuel consumption and improve operational efficiency. This article takes the mixed airline's route network as the research object. Firstly, the structural properties of mixed air route networks are analyzed by using complex network theory. Secondly, the RW-bucket algorithm to generate a mixed air route network structure is analyzed. According to the conclusion of the analysis, the RW-bucket algorithm is improved. Finally two flight information region route network data are used to verify the proposed hybrid route network construction method by computer simulation.

Design and Optimization of Cluster-Based DSRC and C-V2X Hybrid Routing

With the continuous development of connected and automated vehicles (CAVs) and Internet of Vehicle (IoV) technologies, various application scenarios have put forward higher requirements for vehicular communications. On the one hand, applications related to vehicle driving safety require lower latency and higher throughput. On the other hand, users who use cellular vehicle-to-everything (C-V2X) to transfer data will have to face high communication fees due to the increasing amount of data. Therefore, from the perspective of balancing quality of service (QoS) and user communication costs, this paper integrates dedicated short-range communication (DSRC) and C-V2X, two vehicular communication technologies with their own advantages, into a framework called cluster-based traffic differentiated hybrid routing (CTDHR), to provide services for in-vehicle communication. A vehicle clustering method based on hierarchical clustering is proposed to solve problems (e.g., the communication linking being difficult to maintain and the frequent cell handover due to high-speed movement of vehicles). The CTDHR framework is modeled on the resulting clusters and an objective equation was established. Finally, since the obtained objective equation is a nonlinear integer programming problem, we propose a heuristic algorithm to solve this optimization problem. In the simulation experiments, CTDHR shows better communication performance than the existing DSRC and C-V2X hybrid models. The experimental results show that CTDHR can reduce the communication costs of users while satisfying QoS.

The applications of the routing protocol for low‐power and lossy networks (RPL) on the internet of mobile things

SummaryInternet of Mobile Things (IoMT) have become very popular recently. The routing protocol for low power and lossy networks (RPL) is standardized for static topologies. However, mobility is the nature of IoT. Mobility serves as a promising candidate to harness hand‐off time issues, delay in data transmission, overhead, and low packet delivery rate (PDR) effectively. This study presents a comprehensive account of the mobility‐aware RPL‐based routing protocols to validate and compare the experimental results. Remarkably, classification methods are used in many articles. The aim is to introduce significant research efforts to improve RPL objective functions (OF) performance in hand‐off time, PDR, delay, overhead, and so forth. In this regard, a complete analysis of the existing routing protocols in IoMT has been presented to compare the results. The main focus of this study is on approaches that proposed new OFs for supporting mobility in RPL. Two main categories are considered to study RPL‐based routing protocol mechanisms: The mobile and static sink. The related studies on the mobile sink are divided into three groups: Single metric‐based OF, composite metric OF, and hybrid routing protocols. Also, the related works based on the static sink are categorized into four groups: Fuzzy logic‐based OF, trickle timer‐based OF, composite metrics‐based OF, and modification control messages‐based OF approach. This paper presents a detailed comparison of mechanisms in each category. It also highlights the pros, cons, open issues, and evaluated metrics of each paper. Besides, challenges of mobility in the RPL‐based routing protocol mechanism in IoMT for future studies.

SNR Re-Verification-Based Routing, Band, Modulation, and Spectrum Assignment in Hybrid C-C+L Optical Networks

Band division multiplexing technology is a promising medium-term transitional solution to deal with the traffic flood, by leveraging the existing optical fiber transmission infrastructure. Additionally, the deployment of multi-band optical networks requires updating and upgrading key components, such as multi-band amplifiers and multi-band optical cross-connects. From cost view, it would be a promising way for operators to expand transmission capacity on some of the links with high priority, which are used heavily. Therefore, the application scenario of this paper is positioned in the C-C+L hybrid optical networks. In this scenario, the introduction of the L-band brings additional inter-band stimulated Raman scattering (ISRS) which is a non-negligible nonlinear effect, leading new constraint for service provisioning. This paper proposes an ISRS-aware routing, band, modulation, and spectrum assignment (RBMSA) scheme, considering the impact of ISRS generated by new requests on existing requests. By implementing the SNR re-verification, not only the transmission quality of the current request can be realized, but also the service quality of the existing requests will not be seriously degraded to be unacceptable. A two-dimensional model of request bandwidth and duration is established for band selection. Priority is provided for arranging the requests in the L-band when it is available. For each single request, when the least number of slots required by adopting different modulation formats is the same, lower-order modulation is preferred to improve its SNR tolerance of this request under the ISRS impact. Simulation results indicate that the proposed scheme can effectively decrease the blocking probability, and improve the channel SNR for the successfully established requests.

Hybrid Route Optimisation for Maximum Air to Ground Channel Quality

The urban air mobility market is expected to grow constantly due to the increased interest in new forms of transportation. Managing aerial vehicles fleets, dependent on rising technologies such as artificial intelligence and automated ground control stations, will require a solid and uninterrupted connection to complete their trajectories. A path planner based on evolutionary algorithms to find the most suitable route has been previously proposed by the authors. Herein, we propose using particle swarm and hybrid optimisation algorithms instead of evolutionary algorithms in this work. The goal of speeding the route planning process and reducing computational costs is achieved using particle swarm and direct search algorithms. This improved path planner efficiently explores the search space and proposes a trajectory according to its predetermined goals: maximum air-to-ground quality, availability, and flight time. The proposal is tested in different situations, including diverse terrain conditions for various channel behaviours and no-fly zones.

PAAD (Partially adaptive and deterministic routing): A deadlock free congestion aware hybrid routing for 2D mesh network-on-chips.

Due to the increase in integrated circuit technology processing, there is intense flooding of transistors on Multi-processor System-on-chips, making communication a more complex and costly asset. To regulate communication in such a complex environment, Network-on-chip (NoC) came up as a versatile and inflating communication architecture for large SoCs. It tackled various on-chip communication problems and increased performance. It also provided a great power tradeoff for large-scale System-on-chips (SoCs). Routing plays a very vital role in NoCs performance. Routing should not cause any deadlocks in the network as it can degrade the performance. So deadlock-free routing has been and is instill a concern in NoCs. In this paper, we have introduced a novel deadlock-free congestion-aware routing namely PAAD (Partially adaptive and deterministic routing). It is a conjunction of partially adaptive and deterministic routing which switch with each other based on network congestion. Here we have divided a mesh into different diagonal zones and different algorithms are followed in each zone. When there is no congestion, deterministic routing is followed in each zone, and when there is congestion partially adaptive routing is followed. Hence it takes the advantage of both and enhances the overall efficiency. We have compared our model with different algorithms with regard to latency, throughput, and power performance factor for various traffic patterns. The results reveal that our algorithm performs best than the rest.

Microcrystalline Hybridization Enhanced Coal-Based Carbon Anode for Advanced Sodium-Ion Batteries.

Sodium‐ion batteries (SIBs) are regarded as a kind of promising candidate for large‐scale energy storage technology. The development of advanced carbon anodes with high Na‐storage capacity and initial Coulombic efficiency (ICE) from low cost, resources abundant precursors is critical for SIBs. Here, a carbon microcrystalline hybridization route to synthesize hard carbons with extensive pseudo‐graphitic regions from lignite coal with the assistance of sucrose is proposed. Employing the cross‐linked interaction between sucrose and lignite coal to generate carbon‐based hybrid microcrystalline states, the obtained hard carbons possess pseudo‐graphitic dominant phases with large interlayer spaces that facilitate Na ion's storage and transportation, as well as fewer surface defects that guarantee high ICE. The LCS‐73 with an optimum cross‐link demonstrates the highest Na‐storage capacity of 356 mAh g−1 and an ICE of 82.9%. The corresponding full‐cell delivers a high energy density of 240 Wh kg−1 (based on the mass of anode and cathode materials) and excellent rate capability of 106 mAh g−1 at 10 C in addition to outstanding cycle performance with 80% retention over 500 cycles at 2 C. The proposed work offers an efficient route to develop high‐performance, low‐cost carbon‐based anode materials with potential application for advanced SIBs.

A Hybrid Routing Protocol Based on Naïve Bayes and Improved Particle Swarm Optimization Algorithms

Clustering of sensor nodes is a prominent method applied to wireless sensor networks (WSNs). In a cluster-based WSN scenario, the sensor nodes are assembled to generate clusters. The sensor nodes also have limited battery power. Therefore, energy efficiency in WSNs is crucial. The load on the sensor node and its distance from the base station (BS) are the significant factors of energy consumption. Therefore, load balancing according to the transmission distance is necessary for WSNs. In this paper, we propose a hybrid routing algorithm based on Naïve Bayes and improved particle swarm optimization algorithms (HRA-NP). The cluster heads (CHs) are selected according to the CH conditional probability, which is estimated by the Naïve Bayes classifier. After the selection of the CHs, the multi-hop routing algorithm is applied to the CHs. The best routing path from each CH to the BS is obtained from an improved particle swarm optimization (PSO) algorithm. Simulations were conducted on evaluation factors such as energy consumption, active sensor nodes per round, the sustainability of the network, and the standard deviation of a load on the sensor node. It was observed that HRA-NP outperforms comparable algorithms, namely DUCF, ECRRS, and FC-RBAT, based on the evaluation factors.

A Hybrid Routing Approach Comparison with AODV Protocol Regarding Speed for Disaster Management in MANET

The Mobile Ad-hoc Network (MANET) is a wireless, systematic, autonomous network that can be used in various situations without the need for central control. A disaster is a sudden event that disrupts normal activities. MANET can play an important role in a disaster situation. Situations where normal communication is already interrupted. The MANET route discovery is one of the most important aspects of data transfer in a disaster. Proactive and reactive routing protocols are used as standard in various uses of MANET due to their ease of construction and operation. Their combination makes it a way to get better route discovery and efficiency because long-term route contracts do not provide better performance on heavy traffic and load, especially in a disaster. Because the hybrid method is very useful for rapid convergence of network with low memory and power management. This study introduces a hybrid approach that combines proactive and reactive protocols for route discovery and link breakage. The simulation model was used for the proposed hybrid method. The results after the simulation show that hybrid approach offers better performance during packet delivery ratio, network load, end-to-end delay and throughput as compared to the AODV routing protocols.

Flying Ad hoc Networks (FANET): Performance Evaluation of Topology Based Routing Protocols

Flying Ad hoc Networks (FANETs) has developed as an innovative technology for access places without permanent infrastructure. This emerging form of networking is construct of flying nodes known as unmanned aerial vehicles (UAVs) that fly at a fast rate of speed, causing frequent changes in the network topology and connection failures. As a result, there is no dedicated FANET routing protocol that enables effective communication between these devices. The purpose of this paper is to evaluate the performance of the category of topology-based routing protocols in the FANET. In a surveillance system involving video traffic, four routing protocols with varying routing mechanisms were examined. Additionally, simulation experiments conducted to determine the influence of flying altitude. The results indicate that hybrid routing protocols outperform other types of protocols in terms of average throughput. Proactive protocols, on the other hand, have the least jitter.