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Delay tolerant networks (DTNs) is a network evolved from mobile networks. Differing from the traditional network, which has a stable end‐to‐end transmission path, DTNs are sparse and intermittently connected mobile ad hoc network, which are widely used in harsh environments, such as battlefields, seabed, space communication networks, and so on. In DTNs, intermittent connectivity, partitioned network, long delays and node mobility characteristics make the network fail to communicate frequently, therefore, how to successfully forward the message is of extreme importance. Up to now, almost all the traditional models in DTNs use the store‐carry‐forward method. This paper proposes a novel clustered DTN routing model based on sensing node relationship strength. The routing mechanism takes advantage of the number of other nodes encountered by the nodes in the process of movement and the changes in the number of nodes to calculate the strength of the relationship between nodes, and clusters DTN routing according to the strength of the relationship between nodes. Moreover, the relationship between nodes in a cluster and other clusters is used to transmit messages between clusters, and messages are transmitted within clusters according to the strength of the relationship between nodes. Simulation results show that the routing mechanism not only increases the success rate of message transmission, but also reduces the transmission delay of messages and improves network performance. [ABSTRACT FROM AUTHOR]

The intersection of cybersecurity and opportunistic networks has ushered in a new era of innovation in the realm of wireless communications. In an increasingly interconnected world, where seamless data exchange is pivotal for both individual users and organizations, the need for efficient, reliable, and sustainable networking solutions has never been more pressing. Opportunistic networks, characterized by intermittent connectivity and dynamic network conditions, present unique challenges that necessitate innovative approaches for optimal performance and sustainability. This paper introduces a groundbreaking paradigm that integrates the principles of cybersecurity with opportunistic networks. At its core, this study presents a novel routing protocol meticulously designed to significantly outperform existing solutions concerning key metrics such as delivery probability, overhead ratio, and communication delay. Leveraging cybersecurity's inherent strengths, our protocol not only fortifies the network's security posture but also provides a foundation for enhancing efficiency and sustainability in opportunistic networks. The overarching goal of this paper is to address the inherent limitations of conventional opportunistic network protocols. By proposing an innovative routing protocol, we aim to optimize data delivery, minimize overhead, and reduce communication latency. These objectives are crucial for ensuring seamless and timely information exchange, especially in scenarios where traditional networking infrastructures fall short. By large-scale simulations, the new model proves its effectiveness in the different scenarios, especially in terms of message delivery probability, while ensuring reasonable overhead and latency. [ABSTRACT FROM AUTHOR]

Path hopping serves as an active defense mechanism in network security, yet it encounters challenges like a restricted path switching space, the recurrent use of similar paths and vital nodes, a singular triggering mechanism for path switching, and fixed hopping intervals. This paper introduces an active defense method employing multiple constraints and strategies for path hopping. A depth-first search (DFS) traversal is utilized to compute all possible paths between nodes, thereby broadening the path switching space while simplifying path generation complexity. Subsequently, constraints are imposed on residual bandwidth, selection periods, path similitude, and critical nodes to reduce the likelihood of reusing similar paths and crucial nodes. Moreover, two path switching strategies are formulated based on the weights of residual bandwidth and critical nodes, along with the calculation of path switching periods. This facilitates adaptive switching of path hopping paths and intervals, contingent on the network's residual bandwidth threshold, in response to diverse attack scenarios. Simulation outcomes illustrate that this method, while maintaining normal communication performance, expands the path switching space effectively, safeguards against eavesdropping and link-flooding attacks, enhances path switching diversity and unpredictability, and fortifies the network's resilience against malicious attacks. [ABSTRACT FROM AUTHOR]

The Korea Pathfinder Lunar Orbiter (KPLO) was launched on 5 August 2022, equipped on the SpaceX Falcon 9 launch vehicle. At present, the KPLO is effectively carrying out its scientific mission in lunar orbit. The KPLO serves as a cornerstone for the development and validation of Korean space science and deep space technology. Among its payloads is the DTNPL, enabling the first-ever test of delay-tolerant network (DTN) technology for satellites in lunar orbit. DTN technology represents a significant advancement in space communication, offering stable communication capabilities characterized by high delay tolerance, reliability, and asymmetric communication speeds—a necessity for existing satellite and space communication systems to evolve. In this paper, we briefly give an overview of the Korea Lunar Exploration Program (KLEP) and present scientific data gathered through the KPLO mission. Specifically, we focus on the operational tests for DTN-ION conducted for message and file transfer, as well as real-time video streaming, during the initial operations of the KPLO. Lastly, this study offers insights and lessons learned from KPLO DTNPL operations, with the goal of providing valuable guidance for future advancements in space communication. [ABSTRACT FROM AUTHOR]

In socially aware networking, nodes typically behave selfishly due to resource constraints and social correlations, resulting in low network performance. To incentivize selfish nodes to actively participate in message forwarding, this paper proposes a resource-based dynamic pricing and forced forwarding incentive algorithm (DFIA). Firstly, the algorithm introduces virtual currency as a transaction medium and then designs a pricing function based on factors such as the node's resource status, participation contribution, location relevance, and social connectivity. It ensures that the forwarding service is transacted at a reasonable price through bargaining rules. Secondly, a forced forwarding strategy is implemented to compel selfish nodes, which are unwilling to participate in other nodes' message forwarding, to forward a certain number of non-local messages. Meanwhile, in order to prevent nodes from discarding messages and to ensure successful forwarding to the destination, specific rules are used to allocate contribution values to nodes that successfully participate in message forwarding. Lastly, to avoid false quotation behavior, blockchain technology is employed. Transaction information is packaged into blocks and added to the blockchain after consensus validation by other nodes in the network, ensuring the transparency and immutability of transaction data. Simulation results indicate that compared with the existing incentive algorithms, this algorithm not only enhances message delivery probability but also effectively reduces average latency. [ABSTRACT FROM AUTHOR]

Ensuring source location privacy is crucial for the security of underwater acoustic sensor networks amid the growing use of marine environmental monitoring. However, the traditional source location privacy scheme overlooks multi-attacker cooperation strategies and also has the problem of high communication overhead. This paper addresses the aforementioned limitations by proposing an underwater source location privacy protection scheme based on game theory under the scenario of multiple cooperating attackers (SLP-MACGT). First, a transformation method of a virtual coordinate system is proposed to conceal the real position of nodes to a certain extent. Second, through using the relay node selection strategy, the diversity of transmission paths is increased, passive attacks by adversaries are resisted, and the privacy of source nodes is protected. Additionally, a secure data transmission technique utilizing fountain codes is employed to resist active attacks by adversaries, ensuring data integrity and enhancing data transmission stability. Finally, Nash equilibrium could be achieved after the multi-round evolutionary game theory of source node and multiple attackers adopting their respective strategies. Simulation experiments and performance evaluation verify the effectiveness and reliability of SLP-MACGT regarding aspects of the packet forwarding success rate, security time, delay and energy consumption: the packet delivery rate average increases by 30%, security time is extended by at least 85%, and the delay is reduced by at least 90% compared with SSLP, PP-LSPP, and MRGSLP. [ABSTRACT FROM AUTHOR]

The rapid development of mobile communication devices has brought challenges to wireless networks, where data packets are able to organize and maintain local area networks more freely without the constraints of wired devices. Scholars have developed diverse network protocols on how to ensure data transmission while maintaining its self-organizational nature. However, it is difficult for traditional network protocols to meet the needs of increasingly complex networks. In order to solve the problem that the better node set may not be selected when selecting the node set responsible for forwarding in the traditional OLSR protocol, a multi-objective optimized OLSR algorithm is proposed in this paper, which incorporating a new MPR mechanism and an improved NSGA-II algorithm. In the process of route discovery, the intermediate nodes responsible for forwarding packets are determined by the new MPR mechanism, and then the main parameters in the OLSR protocol are provided by the multi-objective optimization algorithm. Matlab was used to build a self-organizing network in this study. In addition, the conventional OLSR protocol, NSGA-II algorithm and multi-objective simulated annealing algorithm are selected to compare with the proposed algorithm. Simulation results show that the proposed algorithm can effectively reduce packet loss and end-to-end delay while obtaining better results in HV and Spacing, two multi-objective optimization result evaluation metrics. [ABSTRACT FROM AUTHOR]

Although several years have passed since its first introduction, the significance of Delay-Tolerant Networking (DTN) remains evident, particularly in challenging environments where traditional networks face operational limitations such as disrupted communication or high latency. This survey paper aims to explore the diverse array of applications where DTN technologies have proven successful, with a focus on emerging and novel application paradigms. In particular, we focus on the contributions of DTN in the Future Internet, including its contribution to space applications, smart cities and the Internet of Things, but also to underwater communications. We also discuss its potential to be used jointly with information-centric networks to change the internet communication paradigm in the future. [ABSTRACT FROM AUTHOR]

Smart cities today can utilize vehicular delay tolerant networks (VDTN) to collect data from connected-objects in the environment for various delay-tolerant applications. They can take advantage of the available intelligent transportation systems (ITS) infrastructures to deliver data to the central server. The system can also exploit multiple and diverse mobility patterns found in cities, such as privately owned cars, taxis, public buses, and trams, along with their vehicle-toeverything (V2X) communications capabilities. In the envisioned convergence between the ITS and V2X, we believe that a simple and efficient routing protocol can be deployed for the delay-tolerant data delivery, contrary to the implementation of optimized solutions that might be resource-demanding and difficult to standardize. In this paper, we analyzed the performances of four baseline VDTN routing protocols, namely: direct delivery, first contact, epidemic, and spray and wait, to understand their strengths and weaknesses. Our simulation results highlighted the trade-off between distinct approaches used by those protocols and pointed out some gaps that can be refined. This study provides new interesting ideas and arguments towards developing a simple, efficient, and high-performing routing protocol for data collection in smart cities. [ABSTRACT FROM AUTHOR]

Opportunistic mobile social networks (OMSNs) have become increasingly popular in recent years due to the rise of social media and smartphones. However, message forwarding and sharing social information through intermediary nodes on OMSNs raises privacy concerns as personal data and activities become more exposed. Therefore, maintaining privacy without limiting efficient social interaction is a challenging task. This paper addresses this specific problem of safeguarding user privacy during message forwarding by integrating a privacy layer on the state-of-the-art OMSN routing decision models that empowers users to control their message dissemination. Mainly, we present three user-centric privacy-aware forwarding modes guiding the selection of the next hop in the forwarding path based on social metrics such as common friends and exchanged messages between OMSN nodes. More specifically, we define different social relationship strengths approximating real-world scenarios (familiar, weak tie, stranger) and trust thresholds to give users choices on trust levels for different social contexts and guide the routing decisions. We evaluate the privacy enhancement and network performance through extensive simulations using ONE simulator for several routing schemes (Epidemic, Prophet, and Spray and Wait) and different movement models (random way, bus, and working day). We demonstrate that our modes can enhance privacy by up to 45% in various network scenarios, as measured by the reduction in the likelihood of unintended message propagation, while keeping the message-delivery process effective and efficient. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) implies a new model and concept in the world of information and communication technology that the non-cooperation of some nodes in providing services to other nodes may result in the disconnection of some things with each other. Consequently, the proximity of such nodes is considerably reduced the network performance. In this paper, a multiphase method based on game theory and direct and indirect reputation has been designed to stimulate selfish and malicious nodes to cooperate in the Internet of Things, which starts with setting up nodes in the IoT network. In the first phase, nodes are grouped in clusters with cluster heads to collect data. Then, they play a dynamic and multi-person game when they promote their own data packet or others' data packet in the second phase (multi-person game phase and data packet sending). The result of the game is applied to affect between nodes in the next phase. Nodes can pick their strategy when data packet forwarding in the third phase (direct and indirect reputation update). Nodes will update the neighboring node and the reputation table if they receive a confirmation message from the destination declaring that the data packet has a direct reputation. The results show that the accuracy of selfish node detection has increased by average of 8% and the false positive rate is 7% in comparison to comparative methods. [ABSTRACT FROM AUTHOR]

This paper addresses the challenge of determining community scale to which network nodes belong and introduces an innovative hypothesis testing approach. It begins with a network sampling method that generates sequences of node dependency values, revealing community structure and scale in a waveform-like manner. Subsequently, the study employs wavelet analysis, a signal processing technique, to extract local signal periodicity information from these sequences. This information is then used to develop a test for assessing node membership in specific community scales. The proposed method is applied to both simulated and real-world social network data, with results from the simulated data demonstrating its effectiveness in evaluating node membership in particular community scales. [ABSTRACT FROM AUTHOR]

Delay tolerant networks supporting heterogeneous communication are a promising network architecture solution that can meet today's communication requirements involving nodes in space, terrestrial and water networks. These networks with dynamic topology and dynamic set of participating nodes make enablement of secure authentication between nodes in this network architecture a critical requirement. In this paper, we propose a novel Quantum-Secure Authentication (QS-Auth) protocol that enables mutual-authentication in Heterogeneous Delay tolerant network environment, while achieving quantum-resistance using the combination of PUF and Post-Quantum signature. The proposed tree-based region structure enables scalability and distributes the responsibility for trust to individual region heads and eliminates high risk root nodes in other tree-based solutions. The proposed scheme can meet the high secure mutual-authentication requirement in critical networks like defence, disaster regions, satellite communications etc. We demonstrate the correctness of our proposed scheme by conducting thorough informal and formal security analysis. The performance analysis is done by the evaluation of efficiency, computation and communication cost. The results of our analysis proves that the proposed protocol meets the security criteria and is well suited for heterogeneous delay tolerant network environments. [ABSTRACT FROM AUTHOR]

Vehicle terminals in the mobile internet of vehicles are faced with difficulty in the requirements for computation-intensive and delay-sensitive tasks, and vehicle mobility also causes dynamic changes in vehicle-to-vehicle (V2V) communication links, which results in a lower task offloading quality. To solve the above problems, a new task offloading strategy based on cloud–fog collaborative computing is proposed. Firstly, the V2V-assisted task forwarding mechanism is introduced under cloud–fog collaborative computing, and a forwarding vehicles predicting algorithm based on environmental information is designed; then, considering the parallel computing relationship of tasks in each computing node, a task offloading cost model is constructed with the goal of minimizing delay and energy consumption; finally, a multi-strategy improved genetic algorithm (MSI-GA) is proposed to solve the above task offloading optimization problem, which adapts the chaotic sequence to initialize the population, comprehensively considers the influence factors to optimize the adaptive operator, and introduces Gaussian perturbation to enhance the local optimization ability of the algorithm. The simulation experiments show that compared with the existing strategies, the proposed task offloading strategy has the lower task offloading cost for a different number of tasks and fog nodes; additionally, the introduced V2V auxiliary task forwarding mechanism can reduce the forwarding load of fog nodes by cooperative vehicles to forward tasks. [ABSTRACT FROM AUTHOR]

In Portugal, more than 98% of domestic cooking oil is disposed of improperly every day. This avoids recycling/reconverting into another energy. Is also may become a potential harmful contaminant of soil and water. Driven by the utility of recycled cooking oil, and leveraging the exponential growth of ubiquitous computing approaches, we propose an IoT smart solution for domestic used cooking oil (UCO) collection bins. We call this approach SWAN, which stands for Smart Waste Accumulation Network. It is deployed and evaluated in Portugal. It consists of a countrywide network of collection bin units, available in public areas. Two metrics are considered to evaluate the system's success: (i) user engagement, and (ii) used cooking oil collection efficiency. The presented system should (i) perform under scenarios of temporary communication network failures, and (ii) be scalable to accommodate an ever-growing number of installed collection units. Thus, we choose a disruptive approach from the traditional cloud computing paradigm. It relies on edge node infrastructure to process, store, and act upon the locally collected data. The communication appears as a delay-tolerant task, i.e., an edge computing solution. We conduct a comparative analysis revealing the benefits of the edge computing enabled collection bin vs. a cloud computing solution. The studied period considers four years of collected data. An exponential increase in the amount of used cooking oil collected is identified, with the developed solution being responsible for surpassing the national collection totals of previous years. During the same period, we also improved the collection process as we were able to more accurately estimate the optimal collection and system's maintenance intervals. [ABSTRACT FROM AUTHOR]

The increasing network traffic from connected vehicles is putting a strain on the limited bandwidth resources of cellular networks. Delay-tolerant networking (DTN) over vehicle-to-vehicle (V2V) communications has been considered as an effective means of offloading the cellular data traffic, while its quantitative performance in urban road traffic remains unclear in many aspects. In this paper, we unveil the benefits of data offloading over vehicular DTNs by city-scale network simulations in Nagoya, Japan. The simulation scenario embraces more than 8 million vehicle trips over five consecutive days. The vehicle routes are carefully calibrated against public statistics on the road traffic volume to enable realistic simulations of V2V communication opportunities between vehicles on the road. The results indicate the strong potential of vehicular DTNs in mixed urban road traffic, comprised of both public transport and privately owned vehicles – a large amount data traffic can be offloaded from cellular networks to V2V communication networks even with the limited ratio of vehicles participating the vehicular DTNs.

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. • CD-SDTN combines satellite node social attributes into routing algorithm. • CD-SDTN uses an improved circle-k-means clustering algorithm. • CD-SDTN proposes a novel definition of social attributes for satellite nodes. • CD-SDTN was significantly more effective compared to Epidemic and Prophet. [ABSTRACT FROM AUTHOR]

Vehicular Ad-hoc Network (VANET) is a pivotal element of the Intelligent Transportation System (ITS) and has gained significant attention in both academia as well as in the industry. The driving experience has been improved with the deployment of VANETs in the transportation system. In this scenario, accurate real-time traffic information is required to be forwarded to the correlated vehicles using Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication. The V2V system is prone to the issue of communication overhead and security, whereas the V2I-based model for data dissemination faces the issue of scalability. In addition to this, wireless communication among vehicles is affected by potential attackers, that not only threaten the vehicle's security but also the commuter's life. An impersonation attack is considered the most common and dangerous attack in VANETs. In this paper, we propose a hybrid system that utilizes both V2V and V2I communications for secure data dissemination in urban scenarios. We use a zone-based stable and secure clustering mechanism to identify Cluster Heads (CH) as a message forwarding node to and from the Road Side Unit (RSU), which reduces the communication overhead and latency of the network. We utilize the concept of Internet Control Message Protocol (ICMP) and the monitoring mode of RSU for the detection and mitigation of impersonation attacks in VANETs. Finally, we validate our results using a network simulator (NS2). [ABSTRACT FROM AUTHOR]

In opportunistic networks, opportunistic routing protocols are used for nodes to forward messages, which are the core technology to realize various opportunistic network applications. However, the existing opportunistic routing protocols generally have three problems: Key nodes forwarded too many messages, resulting in unbalanced energy consumption; Delivered message still occupies the cache space of nodes, resulting in the loss of undelivered message; Nodes constantly sense their surroundings and forward messages, resulting in rapid energy depletion. To better solve these problems, this paper proposes HP-ECD: heuristic Prophet routing protocol based on energy balance, cache optimization, and asynchronous dormancy. Based on Prophet, First, the HP-ECD defines the message forwarding benefits based on multiple node attributes and message importance, to realize the energy balance mechanism of nodes. Then, the HP-ECD designs the message delivery list based on the node history information, to realize the cache optimization mechanism of nodes. Finally, the HP-ECD determines whether a node is in dormancy based on the node running status, to realize the asynchronous dormancy mechanism of nodes. Simulation results show that, compared with Epidemic, Prophet, and EC-CW, HP-ECD greatly improves the message delivery rate and average remaining energy, and reduces the routing overhead rate and average storage time. [ABSTRACT FROM AUTHOR]

The maximum flow problem based on a contact graph in Delay-Tolerant Networking (DTN) is very important for routing and data planning. Common deterministic algorithms employing topological graphs with non-time varying to solve the maximum flow between two nodes include Dinic and Improved Shortest Augmenting Path (ISAP). However, these algorithms cannot be directly applied to topological networks with time series changes. Iosifidis.G gave a solution to this problem based on the time expansion graph, but his method requires high storage space, and an increase in the number of nodes results in increasing complexity. In this paper, we propose a method of dismantling and reconstructing the graph to solve the maximum flow problem in a continuously changing network. Compared with the Storage Policy (SP) algorithm of Iosifidis.G, this method does not require equal time slot splitting of each node, but instead uses discretization to reduce the scale of the graph. Finally, we add this algorithm to Contact Graph Routing (CGR) to optimize DTN data transmission, improve data delivery rate, and reduce unnecessary link occupation. Experimental results show that the optimized CGR can increase average delivery rate by 3% and reduce link usage by 4% compared to CGR. [ABSTRACT FROM AUTHOR]