Barter trade improves message delivery in opportunistic networks

To address the problems of large overhead and inaccurate judgment for selfish node of the existing selfish node detecting algorithm in opportunistic networks, a high-efficiency and low-overhead algorithm to detect the selfish node HLSND algorithm is proposed. The algorithm combines the SV list interactive information and attributes of the message forwarded by encounter node to judge its selfishness. According to the message attributes forwarded by the node, it can be judged whether it has the selfish behavior of forged the message in SV list. The RSSI technique is used to measure the distance of the nodes to improve the judgment accuracy of self – interest behavior. At the same time, information of selfish node is carried when forward other message to reduce the system overhead. The simulation results show that the HLSND detection algorithm can effectively improve the throughput and message delivery rate in the network and reduce the energy consumption and time delay of the system.

This paper investigates the optimization of Automatic Identification System (AIS) message transmission for Virtual Aids to Navigation (VATONs) in maritime communication networks under challenging environmental conditions. The study addresses critical network bottlenecks by analysing the impact of path loss (α = 2 to 4.0) on communication reliability and evaluating opportunistic networking solutions, specifically Epidemic routing protocols, for enhanced message delivery. Using OMNeT++ simulations with 40 vessels across a 100km × 100km maritime area, we demonstrate that traditional shore-to-ship communication suffers significant degradation when path loss exponents exceed 2.8, with packet reception rates dropping below 20% at α > 3.2. Our research reveals that Epidemic routing can effectively address these connectivity gaps through ship-to-ship relay mechanisms, maintaining critical VATON position updates even when direct shore-based communication fails. The findings indicate that opportunistic networking achieves substantial improvements in message delivery rates under adverse conditions. This work presents a proof-of-concept demonstration of opportunistic networking principles in maritime environments, establishing a foundation for future field validation studies.

In opportunistic networks, selfish nodes will refuse to forward messages for others to save their precious resources such as bandwidth, buffer and energy, and the system performance will degrade significantly. Therefore, it is necessary to motivate the selfish nodes to cooperatively forward messages. However, current cooperation mechanisms for opportunistic networks mainly focus on encouraging nodes to participate in message forwarding, but fail to consider the node congestion problem. When many messages are forwarded to the nodes with high connection degree, these nodes will become congested and discard most messages, which will seriously degrade the routing performance. To stimulate the selfish nodes with limited buffer to cooperatively forward messages, this paper proposes a congestion-aware node cooperation mechanism based on double auction, called CANCMDA. In CANCMDA, nodes first determine the self congestion degree according to current free buffer and message receiving speed. Then, combining message delivery probability and congestion degree, nodes trade messages based on double auction model. The double auction trade process is a bayesian game, and nodes get the optimal bid by solving the bayesian equilibrium to trade messages. The experimental results show that CANCMDA can effectively stimulate selfish nodes to cooperatively forward messages when congested, and achieves higher message delivery ratio with lower overhead ratio, compared with other mechanisms.

During the data forwarding in opportunistic network, the selfishness of rational nodes leads to a serious decline in network performance. To solve this problem, this paper proposes a mechanism referred as TFT-NP (transmission failure tolerance and node punishment). TFT-NP takes transmission failure into account, and judges whether the node is selfish or not. It introduces repeated-game theory and sets the penalty cycle of selfish node reasonably. It forces rational nodes to cooperate for a greater profit. Experimental results show that, in opportunistic network with selfish nodes, TFT-NP can improve message delivery rate and reduce message delay significantly.

Analyzing the effect of nodes' selfishness in the opportunistic network is a hot research. In previous studies, people only perform simulation scenarios under simple movement models. In practice, selfish nodes with different movement models will have different effects in the network. So it's necessary to study the effect of selfishness in the opportunistic network under different movement models. In real-life scenarios, the characteristics of the mobile node's movement is random and clustered. So, in this paper, we discuss how the selfishness of nodes affects performance of the opportunistic network with two movement models, the random walk model (RW) and the clustered movement model. With the experiments, we get the conclusion that effects of selfishness in the opportunistic network is related to the movement model.

In Vehicular Ad Hoc Networks (VANETs), vehicles act as independent nodes that can freely establish connections and exchange messages. However, during data forwarding, vehicle nodes may exhibit selfish behavior due to limited resources such as buffer space and bandwidth, or because of social bias, which leads to a decrease in message delivery rate and an increase in communication overhead. To address this issue, this paper proposes a Dual-Trust Selfish Node Detection Algorithm (DTSDA) based on behavioral and social characteristics. The algorithm first employs a node forwarding behavior evaluation mechanism to detect selfish behaviors caused by resource constraints. Then, it introduces behavioral and social features to construct a dual-trust computation model, which further identifies nodes that are difficult to classify. Finally, a message acknowledgment feedback mechanism is incorporated to detect potential false negatives. Experiments are conducted on the ONE simulation platform, and the proposed DTSDA is compared with STCDA, CCSDA, and DSNDA algorithms. The results demonstrate that DTSDA significantly improves the message delivery rate while reducing the end-to-end delay. This study shows that the proposed algorithm can accurately detect selfish nodes in highly dynamic VANET environments, providing a new approach to enhancing communication reliability in vehicular networks.

In the next generation Internet, it is expected that human, smart devices, and “things” will be able to communicate and interact with each other opportunistically in order to share their data. An analysis of this type of relationship is made possible due to the advent of the Opportunistic Internet of Things (OppIoT), a new paradigm that enable information sharing and dissemination among opportunistic communities formed based on human mobility and opportunistic contacts. Designing data dissemination and routing protocols for opportunistic IoT is a challenge since contacts between nodes and users’ social behaviors are to be tighten together as design constraints. Nonetheless, as opportunistic networking rely on spontaneous connectivity between the users and wireless devices, it can be argued that OppIoT is a form of opportunistic social networks (OppNets) extension, with focus on the relationship between human and opportunistic connection of smart things. As such, some routing protocols that have been designed to work for infrastructureless OppNets can also be applied in OppIoT systems. In this context, the History Based Routing Protocol for Opportunistic Networks (HiBOp) is an appealing choice. In this paper, an acknowledgement (ACK) forwarding mechanism to boost the performance of HiBOp is proposed based on the concept of centrality. Simulation results are provided, showing that HiBOp with centrality outperforms HiBOp in terms of predefined performance metrics.

SummaryOpportunistic network applications are usually assumed to work only with unordered immutable messages, like photos, videos, or music files, while applications that depend on ordered or mutable messages, like chat or shared contents editing applications, are ignored. In this paper, we examine how total ordering can be achieved in an opportunistic network. By leveraging on existing dissemination and causal order algorithms, we propose a commutative replicated data type algorithm on the basis of Logoot for achieving total order without using tombstones in opportunistic networks where message delivery is not guaranteed by the routing layer. Our algorithm is designed to use the nature of the opportunistic network to reduce the metadata size compared to the original Logoot, and even to achieve in some cases higher hit rates compared to the dissemination algorithms when no order is enforced. Finally, we present the results of the experiments for the new algorithm by using an opportunistic network emulator, mobility traces, and Wikipedia pages.

The lack of pre-existing infrastructure or dynamic topology makes it impossible to establish end-to-end connections in opportunistic networks (OppNets). Instead, a store-and-forward strategy can be employed. However, such loosely knit routing paths depend heavily on the cooperation among participating nodes. Selfish or malicious behaviors of nodes impact greatly on the network performance. In this paper, we design and validate a dynamic trust management model for secure routing optimization. We propose the concept of incorporating social trust into the routing decision process and design a trust routing based on social similarity (TRSS) scheme. TRSS is based on the observation that nodes move around and contact each other according to their common interests or social similarities. A node sharing more social features in social history record with the destination is more likely to travel close to the latter in the near future and should be chosen as the next-hop forwarder. Furthermore, social trust can be established based on an observed node's trustworthiness and its encounter history. Based on direct and recommended trust, those untrustworthy nodes will be detected and purged from the trusted list. Since only trusted nodes' packets will be forwarded, the selfish nodes have the incentives to behave well again. Simulation evaluation demonstrates that TRSS is very effective in detecting selfish or even malicious nodes and achieving better performance.

Delay-tolerant networks consist of mobile nodes that communicate in unscheduled opportunity without network infrastructure support. When mobile nodes move in highly dynamic networks, they suffer from many challenging issues such as broken network topology and transient connectivity among nodes. In this paper, we propose a geo-routing scheme with an angle-based decision policy (GRAD) for message delivery in delay-tolerant networks. This scheme can select relay nodes in geographic proximity to perform message delivery towards a destination. After a definite number of relays, the message can be destined to a destination. Simulation results show that GRAD can attain a higher rate of successful message delivery and lower communication cost as compared with a classical Spray and Wait scheme under area-confined random waypoint and SLAW mobility patterns in delay-tolerant networks.

Opportunistic networking is an evolution of Ad hoc mobile communication paradigm. Sharing information in opportunistic networks is challenging due to intermittent connectivity, short connection durations and a highly dynamic topology. Numbers of researches have proposed data dissemination approach to increase the chances of delivering information to the destination node with the minimum duration of time. This paper presents the mechanism of identifying the best location based on social interaction to increasing the data dissemination successful rate in opportunistic network. From the simulation results, we found that in the high density population, placing data based on identified location increases the data exchange between nodes about 38% compared to random data placement. Therefore placing data in the right place contribute the effective of data dissemination among mobile nodes.

Opportunistic networks are a kind of Ad Hoc networks that make use of meeting opportunities from mobile nodes to realize the network communication which doesn't need a full path between the source nodes and destination nodes. It’s tolerant in latency and network division. It’s a great challenge to design routing protocols in opportunistic networks in that the movements of nodes are uncertain leading to intermittent connection which make it hard to transmit message to its destination. However, the problems have also attracted more and more attention from researchers. Firstly, in this paper, we introduced the basic concept of opportunistic networks. Secondly we classified and interpreted routing protocols according to the infrastructure, scenario, forwarding mechanism etc. Thirdly, we carried out the computer simulation and analysis for opportunistic network routing protocols in aspect of message delivery ratio, network latency, routing overhead and the number of lost packets. Then we summarized the advantages and disadvantages of routing protocol and discussed its applicability. Finally we looked ahead the hotspot of recent routing protocols under opportunistic networks.

In Mobile Ad hoc Network, co-operation between mobile nodes is inevitable for enabling reliable network connectivity due to the absence of pre-deployed infrastructure. In such a network, mobile nodes spend significant amount of energy for detecting routes and forwarding packets in order to enforce co-operation. The energy drain of mobile nodes due to the above fact induces them to refuse forwarding of packets for their neighbouring nodes in order to participate in the network. The mobile nodes that forward their own packets but drop the packets received from neighbours are known as selfish nodes. Detecting selfish nodes is one of the most challenging issues that need to be addressed for enforcing co-operation. The core objective of this research work is to essentially identify and highlights various reputation-based selfish node mitigation approaches available in the literature with their merits and limitations. This paper presents context-aware reputation-based selfish node mitigation approaches that are classified into three categories viz., History-based reputation mechanism, Condition probability-based reputation mechanism and Futuristic probability-based reputation mechanism. This paper further presents a review on a number of selfish node mitigation frameworks and also aims in emphasizing the role of statistical reliability co-efficient that could aid in effective and efficient mitigation of selfish nodes.

Opportunistic networks are a new evolution of mobile ad hoc networks composed of intermittently connected nodes, in which the routing for the dynamic topology is a challenging issue. In opportunistic networks, the mobile nodes with common interest or close relationship may form into groups and move together, which brings us a good feature to employ when designing the routing protocol for opportunistic networks under resource constraints. Our main idea in this paper is to maximize the message delivery probability in a group-aware opportunistic network under the constraints of bandwidth and buffer space. Embedded this idea, we propose a cooperative routing protocol using the group feature, which includes the cooperative message transfer scheme and the buffer management strategy. In the cooperative message transfer scheme, the limited bandwidth is considered and the message transfer priorities are designed to maximize the delivery probability. In the buffer management strategy, by considering the constraint of buffer space, we propose the cooperative message caching scheme and the dropping order of the messages is designed to minimize the reduced delivery probability. Finally, we conduct the simulations to demonstrate the effectiveness of our proposed routing protocol.

How to shorten time delay and enhance delivery ratio is still an open problem in the study of opportunistic networks. Most proposals are trying to deal with this issue by introducing infrastructures. Although related research has been proven to be useful in improving the routing performance of the network, there is still room for further improvement. In this article, inspired by the powerful message synchronization capability of wireless sensor networks (WSNs), we propose a new opportunistic network framework called WON that introduces WSNs into opportunistic network. With the support of WSNs, fast message delivery and high success ratio can be achieved. We specifically present the layered architecture of WON and compare WON to existing architectures in opportunistic networking. The simulation results concerning delivery delay and success ratio are highly encouraging. Finally, open issues are outlined.