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Delay/Disruption Tolerant Networks (DTNs) are a special category of IntermittentlyConnectedNetworks (ICNs). It has features such as long-delay, frequent-disruption, asymmetrical-data-rates, and high-bundle-error-rates. DTNs have been mainly developed for planet-to-planet networks, commonly known as Inter-Planetary-Networks (IPNs). However, DTNs have shown undimmed potency in challenged communication networks, such as DakNet, ZebraNet, KioskNet and WiderNet. Due to unique characteristics (Intermittent-connectivity and long-delay) DTNs face tough/several challenges in various research areas i.e bundle-forwarding, key-distribution, privacy, bundle-fragmentation, and malicious/selfish nodes particularly. Malicious/selfish nodes launch various catastrophic attacks, this includes, fake packet attacks, selective packet drops attacks, and denial-of-service/flood attacks. These attacks inevitably consume limited resources (persistent-buffer and bandwidth) in DTNs. Fake-packet and selective-packet-drops attacks are top among the challenging attacks in ICNs. The focus of this article is on critical analyses of fake-packet and selective-packet-drops attacks. The panoramic view on misbehavior nodes mitigation algorithms are analyzed, and evaluated mathematically through several parameters for detection probability/accuracy. This article presents a novel algorithm to detects/mitigates fake-packet and selective-packet-drops attacks. The proposed algorithm uses Merkle-Hash-Tree to detects the aforementioned attacks. The proposed algorithm added root hash along with all packets, when the malicious nodes drop packets or inject fake packets, the algorithm detects malicious nodes. Moreover, trace-driven simulation results show the proposed algorithm of this article accurately (enhanced detection-accuracy, enhanced packet delivery/packet loss ratios, and reduces false-positive/false-negative rates) detects malicious nodes which launch fake-packet and selective-packet-drops attacks, unlike previously proposed algorithms which detect only one attack (fake-packet or packet-drops at a time) or detect only malicious path (do not exactly detect malicious nodes which launch attacks). Furthermore, this article mathematically analyzed various scenarios to track exactly/position of various vehicular nodes.

As an important area for mobile wireless networks, Intermittently Connected Networks (ICNs) have received increasing attention in practice and research in recent years. The main goals of the ICN routing protocol are to maximize the delivery probability and to minimize the delivery delay. These challenges have been investigated in previously proposed protocols with an assumption of fully cooperating nodes. Node cooperation directly impacts ICN performance in terms of delivery probability and delay. However, node cooperation is not guaranteed because a cooperating node consumes its buffer size and energy, thereby highlighting the challenges of memory, computation, and energy efficiencies. This paper addresses the challenge of ensuring node cooperation by proposing a novel routing protocol called Mail Man Ferry (MMF). The new protocol includes a node credit mechanism that ensures the cooperation of the network nodes. Extensive simulations were executed to evaluate the proposed protocol. Varying values of node cooperation in ICNs were employed in the simulation tests. The evaluation shows exciting results in which Mail Man Ferry outperforms previously proposed ICN protocols. [ABSTRACT FROM AUTHOR]

Opportunistic networks (OppNets) leverage opportunistic contacts to flow data across an infrastructure-free network. As of yet, OppNets' performance depends on applying the most suitable forwarding strategy based on the OppNet typology. On the other hand, software-defined networking (SDN) is a paradigm for wired networks that decouples the control and data planes. The control plane oversees the network to configure the data plane optimally. Our proposal uses SDN-like controllers to build a partial overview of the opportunistic network. The forwarding strategy uses this context information to achieve better network performance. As a use case of our proposal, in the context of an OppNet quota-based forwarding algorithm, we present a controller-driven architecture to tackle the congestion problem. Particularly, the controller-driven architecture uses the context information on the congestion of the network to dynamically determine the message replication limit used by the forwarding algorithm. A simulation based on real and synthetic mobility traces shows that using context information provided by the controller to configure the forwarding protocol increments the delivery ratio and keeps a good latency average and a low overhead compared with the baseline forwarding protocols based on message replication. These results strengthen the benefits of using supervised context information in the forwarding strategy in OppNets. [ABSTRACT FROM AUTHOR]

Opportunistic networks (OppNets) leverage opportunistic contacts to flow data across an infrastructure-free network. As of yet, OppNets’ performance depends on applying the most suitable forwarding strategy based on the OppNet typology. On the other hand, software-defined networking (SDN) is a paradigm for wired networks that decouples the control and data planes. The control plane oversees the network to configure the data plane optimally. Our proposal uses SDN-like controllers to build a partial overview of the opportunistic network. The forwarding strategy uses this context information to achieve better network performance. As a use case of our proposal, in the context of an OppNet quota-based forwarding algorithm, we present a controller-driven architecture to tackle the congestion problem. Particularly, the controller-driven architecture uses the context information on the congestion of the network to dynamically determine the message replication limit used by the forwarding algorithm. A simulation based on real and synthetic mobility traces shows that using context information provided by the controller to configure the forwarding protocol increments the delivery ratio and keeps a good latency average and a low overhead compared with the baseline forwarding protocols based on message replication. These results strengthen the benefits of using supervised context information in the forwarding strategy in OppNets.

This paper introduces the concept of intermittently connected sensor networks where sensors are sleep most of time and become active randomly and rarely. In the networks, packet collision probability and power consumption can be reduced. Meanwhile, the delivery delay increases with the use of the low activation values. In this paper, we design the energy‐efficient intermittently connected sensor networks, considering this trade‐off of activation control. We first provide the algorithm that computes the optimal packet forwarding rule achieving the minimum delivery delay, which can be calculated using the activation rates. We then propose the activation rate control methods, which control the activation rates of the sensors based on the density of the sensors and/or the number of wake‐ups of sensors having relay packets. By doing this, we can improve the delay performance, while suppressing the increase in the packet collision probability and the power consumption of sensors. Through simulation experiments, we demonstrate the effectiveness of our activation control methods in the intermittently connected sensor networks. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

There are great challenges in vehicular networks, i.e., continuous connectivity cannot be guaranteed due to interruptions. This paper proposes a novel multihop broadcasting protocol with low signaling overhead in vehicular networks with frequent interruptions named as trinary partitioned black-burst-based broadcast protocol. The protocol operates without any infrastructure. It has low overhead supporting different quality of service levels. Both analysis and comprehensive simulations show that the proposed protocol outperforms the bench mark schemes. [ABSTRACT FROM AUTHOR]

Understanding nodes mobility is of fundamental importance for data delivery in opportunistic and intermittently connected networks referred to as Delay Tolerant Networks (DTNs). The analysis of such mobility patterns and the understanding of how mobile nodes interact play a critical role when designing new routing protocols for DTNs. The Cultural Greedy Ant (CGrAnt) protocol is a hybrid Swarm Intelligence-based approach designed to address the routing problem in such dynamic and complex environment. CGrAnt is based on: (1) Cultural Algorithms (CA) and Ant Colony Optimization (ACO) and (2) operational metrics that characterize the opportunistic social connectivity between wireless users. The most promising message forwarders are selected via a greedy transition rule based mainly on local information captured from the DTN environment. Whenever global information is available, it can also be used to support decisions. We compare the performance of CGrAnt with Epidemic, PROPHET, and dLife protocols in two different mobility scenarios under varying networking parameters. Results obtained by the ONE simulator show that CGrAnt achieves a higher message delivery and lower message redundancy than the three protocols in both scenarios. The only exception is in one of the scenarios, when messages have a time to live lower than 900 min, where CGrAnt delivers a bit less messages than dLife, although with a lower message redundancy. [ABSTRACT FROM AUTHOR]

Geocast routing is one of the most investigated choices for reliable and efficient dissemination of information because of group of vehicles sharing geographic region on the road. Most of geocast routing protocols for intermittently connected Vehicular Adhoc Networks, suffer from low packet delivery, high end-to-end delay and elevated packet loss in intermittently connected networks and low throughput, high hop-to-hop disconnection, larger hop-count in fully connected networks. In this paper, guaranteed geocast routing (GGR) protocol for intermittently connected highway traffic environment has been proposed. GGR utilizes caching and heuristic function for reliable next hop vehicle selection. It also uses FAST (group of neighboring vehicles moving at higher speed than current forwarder) in packet delivery and SLOW (group of neighboring vehicles moving at lower speed than current forwarder) in hop-to-hop failure recovery. One-hop delivery has been guaranteed through acknowledgement. The proposed protocol has been simulated using NS-2 and its performance has been compared with that of adoptive carry-store forward, spray & wait and epidemic routing protocols. Results reveal that the performance of GGR is better in terms of number of routing matrices considered for both intermittently and fully connected networks. [ABSTRACT FROM AUTHOR]

In mobile ad-hoc cognitive radio networks (CRNs), end-to-end paths with available spectrum bands for secondary users may exist temporarily, or may never exist, due to the dynamism of the primary user activities. Traditional CRN routing algorithms, which typically ignore the intermittent connectivity of network topology, and traditional mobility-assisted routing algorithms, which generally overlook the spectrum availability, are obviously unsuitable. To tackle this challenge, we propose a Mobility-Assisted Routing algorithm with Spectrum Awareness (MARSA) to select relays based on not only the probability that a node meets the destination but also the chance at which there exists at least one available channel when they meet. To the best of our knowledge, this paper is the first to bring the idea of mobility-assisted routing to deal with the intermittently connected attribute of mobile ad-hoc CRNs, and the first to enhance the mobility-assisted routing by considering the temporal , spatial, and spectrum domains at the same time. Our simulation results demonstrate the superiority of MARSA over traditional algorithms in intermittently connected mobile CRNs. [ABSTRACT FROM AUTHOR]

Abstract: A Delay and Disruption-Tolerant Network (DTN) is a fault-tolerant network where end-to-end connections are not required for message transmissions between nodes. Usually, a DTN is implemented as a wireless mobile ad hoc network that can be applied, for instance, to rapidly build a basic telecommunication infrastructure in case of catastrophes and disasters, or to support communication in a disruptive military environment. It is important to model DTN behavior to better understand system dynamics and related physical laws, which may impact network performance. An accurate model will be useful to support the design of the network in such challenging scenarios and may allow to test design ideas before actually building the real system. This work proposes a mathematical model for message diffusion in epidemical DTN. Our approach is based on previous models for the spread of human epidemical diseases, namely SIR. Simulation results on message diffusion times in an epidemical DTN show that the model is accurate regarding expected values, however large deviations above and below average are also observed on diffusion times. We further study such deviations and provide insights on how to reduce and deal with them, making the model useful for DTN applications. [Copyright &y& Elsevier]

Recent advances in wireless technology provide interesting and effective solutions for vehicular applications. Due to the high deployment cost, implementing roadside units (RSUs) with low cost while maintaining high data throughput has become an important topic. This letter develops a selfishness detection mechanism for file sharing that addresses fairly use vehicle-to-vehicle communications. In locations where an RSU is not immediately available or cannot be directly used, the selfish behavior of not sharing with neighbors or not downloading from an RSU is difficult to detect. This letter proposes a novel selfishness detection mechanism, SDM, to force vehicles to stabilize at a socially optimal operating point incurring maximum total utility. The SDM along with our proposed hybrid self-history mechanism outperforms previous shared history mechanisms, even though the majority of users are selfish. [ABSTRACT FROM PUBLISHER]

Stateless opportunistic forwarding is a simple fault-tolerant distributed scheme for packet delivery, data gathering, and information querying in intermittently connected networks by which packets are forwarded to the next available neighbors in a “random walk” fashion until they reach their intended destinations or expire. It has been employed in diverse situations, for instance, when: 1) the global network topology is not known or is highly dynamic; 2) the availability of the next-hop neighbors is not easily controllable; or 3) the relaying nodes are computationally constrained. Data delivery in sensor networks, ad hoc networks, and delay-tolerant networks are well-known applications besides searching in peer-to-peer networks. A major challenge for stateless opportunistic forwarding is the difficulty to predict the end-to-end latency. To facilitate latency evaluation, we study a simplified model of stateless opportunistic forwarding, namely a “weighted random walk” in a finite graph. This paper makes several contributions toward the analysis of this model. 1) By spectral graph theory we derive a general formula to efficiently compute the exact hitting and commute times of random walks with heterogeneous transition times at relay nodes. Such transition times can model the heterogeneous delivery times and availability periods of the next-hop neighbors. 2) We study a common class of distance-regular networks with a varying number of geographical neighbors and obtain exact and approximation formulas for the hitting time in such networks. 3) Based on these results, we study other sophisticated settings, such as random geographical locations, topology-aware forwarding, and multicopy random-walk forwarding. Our results provide the basic analytical tools for managing and controlling the performance of stateless opportunistic forwarding in finite networks. [ABSTRACT FROM PUBLISHER]

In delay-tolerant wireless sensor networks, messages for sensor data are delivered using opportunistic contacts between intermittently connected nodes. Since there is no stable end-to-end routing path like the Internet and mobile nodes operate on battery, an energy-efficient routing protocol is needed. In this article, we consider the probabilistic routing protocol using history of encounters and transitivity protocol as the base protocol. Then, we propose an energy-aware routing protocol in intermittently connected delay-tolerant wireless sensor networks, where messages are forwarded based on the node’s remaining battery, delivery predictability, and type of nodes. The performance of the proposed protocol is compared with that of probabilistic routing protocol using history of encounters and transitivity and probabilistic routing protocol using history of encounters and transitivity with periodic sleep in detail, from the aspects of delivery ratio, overhead ratio, delivery latency, and ratio of alive nodes. Simulation results show that the proposed protocol has better delivery probability, overhead ratio, and ratio of alive nodes, in most of the considered parameter settings, in spite of a small increase in delivery latency. [ABSTRACT FROM AUTHOR]

In this letter, an analytical framework to model nodes in Intermittently Connected Networks (ICNs) is proposed. A relationship is derived in the z-domain between the discrete probability densities of their buffer state occupancies and the sizes of the arriving bulks. Under a fixed epidemic-routing-based forwarding strategy, expressions are obtained for the average buffer occupancy and its standard deviation with immediate protocol advantages. [ABSTRACT FROM PUBLISHER]

With the proliferation of mobile devices, an increasing number of sensing applications are using mobile sensor networks. These mobile networks are severely energy-constrained, and energy usage is one of the most common causes of failure in their deployments. In these networks, nodes that exhaust their energy before the targeted system lifetime degrade system performance; nodes that run past the system lifetime cannot fully utilize their stored energy. Although much work has focused on policies to reduce and regulate energy usage in fixed and dense networks, intermittently connected networks have been largely overlooked. Due to variations in hardware, software, node mobility, and environment, it is especially difficult for intermittently connected mobile networks to improve operations collectively in a dynamic environment. Here, we present and evaluate Collaborative Adaptive Targeted System Lifetime (CA-TSL), an adaptive policy that enforces a system-wide targeted lifetime in an intermittently connected system by adapting node energy usage to an estimated desired energy profile. For evaluation, we present both real-system and large-scale simulated results. Our approach improves sink data reception by an average of 50 percent, and an additional 30 percent when a density estimation technique is also employed. In addition, it reduces system lifetime variations by up to 5.5\times. [ABSTRACT FROM PUBLISHER]