Routing In Delay Tolerant Networks Research Articles

Space delay-tolerant network routing algorithm based on node clustering and social attributes

Efficient space delay-tolerant network (DTN) routing algorithms have been a hot issue in space network-related research. In this paper, for the problems of high algorithm complexity and high network overhead in space DTN routing algorithms, we introduce a node clustering algorithm and satellite node social attributes in the space DTN routing process and design a spatial delay-tolerant network routing algorithm (CD-SDTN) based on node clustering and social attributes. The algorithm designs the social attributes of the satellite nodes based on the connection frequency of the satellite nodes with the ground station and divides the community using the Circle-k-means algorithm. In the routing process, the center satellite node with the highest activity in the community manages the messages received by the satellite nodes located in the community and plans the forwarding of messages within and between communities. Simulation results show that the CD-SDTN routing algorithm has some advantages in terms of delivery rate, average delay and network overhead compared with Epidemic and Prophet, especially when the number of nodes in the satellite network is large.

Approximating Minimum k-Tree Cover of a Connected Graph Inspired by the Multi-Ferry Routing in Delay Tolerant Networks

In this paper, we consider the problem of covering the vertex set of a given graph by [Formula: see text] trees so as to minimize the maximum weight of the trees, as a subproblem of the multi-ferry scheduling problem proposed by Zhao and Ammar. After pointing out that the approximation ratio of a greedy scheme based on the Kruskal’s algorithm is provably bad, we show that the approximation ratio cannot be better than 3/2 for [Formula: see text] even when the edge selection criterion is modified so as to minimize the increase in the maximum weight in the collection of trees. We then propose two polynomial-time algorithms with a guaranteed approximation ratio. The first algorithm achieves 3-approximation for the class of graphs in which the edge weights satisfy the triangle inequality. The second algorithm achieves 4-approximation for any connected graph with arbitrary edge weights.

Towards a simple and efficient vehicular delay tolerant networks routing protocol for data collection in smart cities

Towards a simple and efficient vehicular delay tolerant networks routing protocol for data collection in smart cities

Evaluation of delay tolerant network routing protocols for data streaming through LEO constellation

In the Era of Mega Low Earth Orbit (LEO) satellite constellation, the efficient networking through Inter-Satellite Links (ISLs) plays a vital role in its mission success. The deployed networking resources must be justified regarding the feasibility, reliability, and Quality of Service (QoS). The main challenge of such networks is the ISLs intermittence due to the dynamic nature of the constellation topology. In addition to the space environment. From this perspective, Delay Tolerant Network (DTN) protocols were proposed for alleviating the events of intermittence. This paper introduces a technique for using the discrete-event network simulator (NS3) for the simulation of LEO constellation networks. This technique considers the dynamic nature of network’s nodes in data streaming through ISLs. The paper presents a performance assessment of LEO constellation networks dedicated for forwarding the payload data through ISLs. The performance measures include both the delay and delivery ratio. The assessment considers different local resources such as transmitted power, Queue size, and transmission rate. The performance measures were applied for some selected DTN protocols such as “Epidemic” and “Spray and Wait”. The results illustrate the effects of different network resources and configurations that may affect the constellation mission.

Bio-inspired Probabilistic Opportunistic Routing for Vehicular Delay-Tolerant Networks Using A Hybrid Swarm Approach

Vehicular Delay Tolerant Network (VDTN) routing has been improved using probabilistic routing to improve the coverage of intermittent vehicular networks. VDTNs are characterized by large transmission ranges of vehicles, rapid vehicular speeds, and restricted mobility movements, particularly in urban areas. As a result, the probabilistic Sore-Carry-and-Forward (SCF) relay vehicle selection can be inaccurate when considering remote vehicles, leading to high overheads. To address this issue, a new bio-inspired VDTN routing protocol is proposed to better estimate the SCF capabilities of remote vehicles so that the duplicated generated bundles’ copies are reduced without altering the bundles’ delivery ratio and average delivery delay. This solution sequentially employs the Ant Colony Optimizer (ACO) and Glowworm Swarm Optimization (GSO) to adaptively control the replication of bundle copies at each bundle forwarding stage based on predefined probabilistic forwarding parameters. Simulation results from a sparse urban mobility scenario show reduced bundle replication rates compared to several probabilistic VDTN routing protocols.

A delay tolerant network routing algorithm based on multi‐step double Q‐learning

AbstractDelay tolerant networks (DTNs) refer to a kind of novel wireless mobile network, where there is no constant end‐to‐end connection between network nodes due to frequent movement, sparse distribution and limited communication range of nodes. Instead of the traditional store‐forward routing strategy, in DTNs, the new store‐carry‐forward routing strategy is adopted for data transmission. Therefore, how to select the best next‐hop node among network nodes is the main challenge of the routing in DTNs. To this end, here, a k‐step double Q‐learning routing (K‐DQLR) algorithm is proposed, which integrates the multi‐step and double Q‐learning algorithms to make an unbiased, accurate and efficient routing decision in DTNs. Besides, a new dynamic reward mechanism is proposed, which combines the number of routing hops and the node centrality to adopt the dynamic network environment of DTNs. The simulation results show that K‐DQLR can significantly increase the delivery ratio while reducing the delivery delay and overhead compared with the related state‐of‐the‐art routing protocols of DTNs.

Vehicular delay tolerant network routing algorithm based on trajectory clustering and dynamic Bayesian network

Vehicular delay tolerant network routing algorithm based on trajectory clustering and dynamic Bayesian network

Enhanced Message Replication Technique for DTN Routing Protocols

Delay-tolerant networks (DTNs) are networks where there is no immediate connection between the source and the destination. Instead, nodes in these networks use a store-carry-forward method to route traffic. However, approaches that rely on flooding the network with unlimited copies of messages may not be effective if network resources are limited. On the other hand, quota-based approaches are more resource-efficient but can have low delivery rates and high delivery delays. This paper introduces the Enhanced Message Replication Technique (EMRT), which dynamically adjusts the number of message replicas based on a node's ability to quickly disseminate the message. This decision is based on factors such as current connections, encounter history, buffer size history, time-to-live values, and energy. The EMRT is applied to three different quota-based protocols: Spray and Wait, Encounter-Based Routing (EBR), and the Destination-Based Routing Protocol (DBRP). The simulation results show that applying the EMRT to these protocols improves the delivery ratio, overhead ratio, and latency average. For example, when combined with Spray and Wait, EBR, and DBRP, the delivery probability is improved by 13%, 8%, and 10%, respectively, while the latency average is reduced by 51%, 14%, and 13%, respectively.

Fuzzy assisted dynamic message replication and routing in delay tolerant networks

Fuzzy assisted dynamic message replication and routing in delay tolerant networks

A DTN oriented adaptive routing algorithm based on node load

In recent years, Delay Tolerant Networks (DTN) have received more and more attention. At the same time, several existing DTN routing algorithms generally have disadvantages such as poor scalability and inability to perceive changes in the network environment. This paper proposes an AdaptiveSpray routing algorithm. The algorithm can dynamically control the initial maximum message copy number according to the cache occupancy rate of the node itself, and the cache occupancy rate is added as an impact factor to the calculation of the probability of each node meeting the destination node. In the forwarding phase, the node will first compare the meeting probability of itself and the meeting node to the destination node, and then choose different forwarding strategies. The simulation shows that the AdaptiveSpray algorithm proposed in this paper has obvious advantages compared with the existing routing algorithms in terms of message delivery rate and average delay.

Analysis of health informatics and bioinformatics connectivity modeling

Health informatics and bioinformatics are closely linked, but the overlapping literature search rate of the analysis methods is low due to the connectivity analysis model. Therefore, a health informatics and bioinformatics connectivity modeling analysis based on a delay-tolerant network routing algorithm is proposed. The analysis is conducted for the topics of both health informatics and bioinformatics disciplines, and a reasonable design of citation measures is designed. The first step in describing the connection between the two disciplines using citation analysis is to extract multidimensional descriptive vectors for the disciplines as a basis for connectivity analysis. The connectivity analysis model is designed with the core of the tolerance network routing algorithm to determine the connectivity of disciplines by detecting the citation overlap between two disciplines. Finally, the connectivity is described by outputting the co-occurrence knowledge structure between disciplines through co-occurrence analysis. The experimental results show that the proposed method improves the completeness rate by 36.6% and 39.2% compared with the conventional connectivity modeling analysis method, which indicates that the proposed method reveals more comprehensive connectivity analysis results.

A context-aware improved POR protocol for Delay Tolerant networks

ABSTRACT The intermittent network connectivity and unawareness of global network knowledge are remarkable challenges when designing efficient Position-based Opportunistic Routing (POR) for Delay Tolerant Networks (DTNs). The best progress set selection of POR effectively handles the intermittent connectivity issue and improves the reliable performance of DTNs. Hence, the optimal progress set selection and catching capacity decide the routing reliability of DTN-POR. This paper proposes a context-aware DTN-POR protocol STAP to ensure reliable DTN routing with minimum overhead STAP design is divided into three folds: application diversity and network failures, context-aware best progress set selection, and enhanced caching management. The application diversity and network failure switch the nodes in harsh environments to DTN mode for transmitting the data packets successfully to the destination. Selecting context-aware relay nodes ensures highly successful data transmissions in the absence of end-to-end connectivity. The probability estimation maximizes the data reachability by considering unique node and application-level context attributes in the best progressive set. Finally, the enhanced catching management strategy limits the number of data copies with effective catch invalidation, resulting in minimum overhead. The proposed STAP accomplishes better results in different scenarios and improves the packet delivery ratio with a minimum duplication rate.

Enhanced UAV-aided vehicular delay tolerant network (VDTN) routing for urban environment using a bio-inspired approach

The evolution of VDTN routing came to solve the problem of routing in sparse Vehicular Ad-hoc Networks (VANETs). Recently, the implication of Unmanned Aerial Vehicles (UAVs) in VANET communication has gathered quicker information dissemination than Roadside Units (RSUs) in urban VANETs, where ground vehicles’ mobility is restricted by the topology of city roads. Gradually, UAVs are emerging for VDTNs: UAV-aided VDTN (UVDTN) routing field has been introduced for sparse areas in order to reduce the network gaps between Vehicle-to-Vehicle (V2V) connections. Meanwhile, the conventional UVDTN routing protocols expose the short contact opportunity time in the case of Vehicle-to-UAV (V2U) and UAV-to-Vehicle (U2V) connections. This constraint entails more congested bundles’ flooding rates and a higher number of lost bundle copies compared to V2V-based forwarding. In this paper, a bio-inspired UVDTN routing protocol is conceived to improve the bundles’ forwarding between ground vehicles and UAVs in terms of flooding optimization and Quality-of-Service (QoS) performances for urban VANET environments. For this purpose, a swarm-inspired approach called the Social Spider Optimization (SSO) is proposed. SSO seeks to find a better selection of next Store-Carry-and-Forward (SCF) relay nodes specifically for V2U and U2V connections. In order to control the bundle replication rate and enhance bundles’ delivery ratio and delay, the proposed bio-inspired UVDTN protocol adjusts the SCF selection decision. The latter is based on predefined historical knowledge-based forwarding parameters and urban geographic topology information. The proposed bio-inspired routing protocol is simulated using the Opportunistic Network Environment (ONE) simulator and compared to a few VDTN and UVDTN routing protocols.

Optimal Cluster Head in DTN Routing Hierarchical Topology (DRHT)

In delay tolerant networking (DTN), nodes are autonomous and behave in an unpredictable way. Consequently, a control mechanism of topology is necessary. This mechanism should ensure the overall connectivity of the network taking into account nodes’ mobility. In this paper, we study the problem of data routing with an optimal delay in the bundle layer, by exploiting: the clustering, the messages ferries and the optimal election of cluster head (CH). We first introduce the DTN routing hierarchical topology (DRHT) which incorporates these three factors into the routing metric. We propose an optimal approach to elect a CH based on four criteria: the residual energy, the intra-cluster distance, the node degree and the head count of probable CHs. We proceed then to model a Markov decision process (MDP) to decide the optimal moment for sending data in order to ensure a higher delivery rate within a reasonable delay. At the end, we present the simulation results demonstrating the effectiveness of the DRHT. Our simulation shows that while using the DRHT which is based on the optimal election of CH, the traffic control during the TTL interval (Time To Live) is balanced, which greatly increases the delivery rate of bundles and decreases the loss rate.

QMIX Aided Routing in Social-Based Delay-Tolerant Networks

Delay-tolerant network (DTN) is a network that’s designed to operate effectively in heterogeneous networks that may lack continuous network connectivity. It is characterized by their lack of instantaneous end-to-end paths, resulting in difficulties in designing effective DTN routing protocols. Traditional routing algorithms largely rely on greedy schemes. Such schemes can not guarantee the packets will be eventually transmitted to their destinations, thereby presenting a poor transmission efficiency. Recently, the social-based method has attracted a large amount of attention in wireless network routing. It can use the community and the centrality information to increase the delivery rate of the whole network. Therefore, in this article, we introduce the social-based mechanism to our DTN routing design. Besides, how the distributed nodes can learn the collaboration strategies is another challenge. Inspired by the recent success of multi-agent learning in online control, we adopt a centralized training and distributed execution learning paradigm and design a hierarchical social-based DTN architecture. Based on this, we propose a collaborative multi-agent reinforcement learning (termed as QMIX) aided routing algorithm.

Socially-Aware Adaptive Delay Tolerant Network (DTN) routing protocol.

Network partitioning and node disconnectivity results in high latency and frequent link disruption in DTNs. Therefore, routing a message toward a destined node is a challenge in such environment. Several DTN routing schemes have been introduced in this regard. Some, recently proposed DTN routing protocols either use a single or combination of multiple social metrics to identify the suitable forwarder node(s). However, these DTN routing protocols produced results at the expense of community formation cost and over utilization of network resources. To address these issues, we propose Socially-Aware Adaptive DTN (SAAD) routing scheme which exploits a social attribute known as Degree Centrality (DC). In this scheme, each node calculates and shares its DC with other nodes at regular intervals. A forwarder node disseminates message to the most influential node possessing highest DC. The proposed routing scheme works great in situations where someone want to improve the energy efficiency and want to involve only relevant nodes. The simulation results show that SAAD has improved to select the best node and has reduced the hop-count, overhead on the expense of delay as compared to Epidemic, PRoPHET and PRoPHETv2.

Performance evaluation of Focused Beam Routing for IoT applications in underwater environment

Underwater applications are becoming more and more interesting to industry and academy. They include data gathering for human safety and environment monitoring, control of underwater robots for various tasks and so on. Because of the accessibility limitations in underwater environment, applications tend to be automated and delay tolerant. In this paper, we consider IoT applications in underwater environment, while using Delay Tolerant Networking (DTN) carry–store–forwarding paradigm. DTN routing protocols are used to forward data from the monitoring mobile sensors to collecting devices at the water surface and vice-versa. One characteristic of routing protocols for DTN is flooding of messages to increase the delivery probability. For instance, Epidemic Routing (ER) protocol creates a copy of each message for each new node that does not already have the message in its memory. This increases the probability of delivery, but on the other hand, creates overhead in each node’s buffer, and uses a lot of valuable energy from the forwarding and receiving nodes. This work aims to analyze by simulations the performance of Focused Beam Routing (FBR) protocol for different FBR angles and different applications. We use Delivery Probability, Average Number of Hops, Overhead Ratio and Buffer Occupancy to simulate our scenarios by The ONE simulator. Simulation results show that for narrow angles of FBR the performance is better. In case of FBR-45, average hop count and overhead ratio are decreased by 10.9% and 16.6% respectively, compared to FBR-180. However, delivery probability decreases by only 3.9%.

Routing in Delay-Tolerant Networks under uncertain contact plans

Delay-Tolerant Networks (DTN) enable store-carry-and-forward data transmission in networks challenged by frequent disruptions and high latency. Existing classification distinguishes between scheduled and probabilistic DTNs, for which specific routing solutions have been developed. In this paper, we uncover a gap in-between where uncertain contact plans can be exploited to enhance data delivery in many practical scenarios described by probabilistic schedules available a priori. Routing under uncertain contact plans (RUCoP) is next formulated as a multiple-copy Markov Decision Process and then exported to local-knowledge (L-RUCoP) and Contact Graph Routing extensions (CGR-UCoP) which can be implemented in the existing DTN protocol stack. RUCoP and its derivations are evaluated in a first extensive simulation benchmark for DTNs under uncertain contact plans comprising both random and realistic scenarios. Results confirm that RUCoP and L-RUCoP closely approach the ideal delivery ratio of an oracle, while CGR-UCoP improves state-of-the-art DTN routing schemes delivery ratio up to 25%.

Routing in Delay-tolerant network Based on Nodes’ Sociality

To solve the problem of low ratio success delivery, long latency caused by the rapid dynamic change of network topology, limited node buffer, large amount of data transmission and large user population density in delay-tolerant network (DTN). This paper propose a routing algorithm in DTN based on nodes’ sociality. In this paper, contact history was used to determine the node link quality; Markov model was used to predict the node position based on the nodes’ movement track; according to nodes’ social similarity to divide community, then calculated node betweenness centrality. Finally, the best forwarding nodes for message transmission were determined. Besides, to increase the ratio of successful delivery, message delivery probability in the relay node’s buffer was calculated. Experimental results show that compared with traditional routing algorithm, the proposed algorithm performs better on the delivery ratio and average end-to-end delay.

A Geographical Routing Approach Based on Probability Delegation Replication (GR-PDR) in VDTN

The routing in vehicular delay tolerant networks (VDTNs) does not presume an end-to-end connectivity from source to destination. One substitute is to use the real-time geographical information of vehicles to relay messages. However, if mobile destination is considered, then real-time information might not be generally available due to the sparse network density in VDTN. In this paper, a geographical routing approach based on the probability delegation replication (GR-PDR) is proposed. The functionality of GR-PDR is categorized into forwarder node selection phase and buffer management phase. The forwarder node selection utilizes the advantages of delegation replication approach to conquer the constraints of routing decisions and local maximum problem. Further, the buffer management is employed to prioritize packets to ensure delivery before the expiration of message lifetime. The proposed GR-PDR ensures that the message will be forwarded to higher quality node, resulting in a high delivery ratio. The approach utilizes the advantages of single-copy and multiple-copy forwarding approaches by avoiding redundant replication and enhancing delivery probability, respectively. The performance results show that the proposed GR-PDR outperforms in terms of packet delivery ratio, average delay and network overhead, when compared with the protocols of the same segment. Statistical analysis validates the effectiveness of the proposed protocol.