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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]

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]

Locally aware routing protocols base their next-hop selection on information about their immediate neighborhood, gathered by means of a beaconing mechanism. In general, beacons may be proactively broadcasted from nodes to their neighbors (‘receiver-initiated’ beaconing) or may be solicited by the node carrying the routed message (‘on-demand’ beaconing). On-demand beaconing is of growing importance, mainly in more dynamic and sparse environments (e.g., delay tolerant networks), and is addressed in this paper. A generic analysis is provided for the case of periodically issued beacons, linking the beacon period to the trade-off between the quality of neighborhood perception (determining the routing effectiveness) and the required amount of signaling (related to energy expenditure at the nodes). The analysis leads to upper and lower bounds for the length of the beacon period, expressed in terms of mobility characteristics. The paper also investigates policies where the inter-beacon intervals vary adapting to the environment, an approach most beneficial when routing is based on metrics bearing some relevance to time. This is the case with the MAD routing protocol, which incorporates the notion of ‘retaining time’, an estimate of the time that the carrying node will retain the message. It is shown that linking the beacon intervals to the each time applicable retaining time leads to an effective and efficient beacon policy. The paper provides simulation-based evaluation results, validating the beacon period bounds and demonstrating that, for the case of MAD, adaptive beaconing is capable of providing even better performance. [ABSTRACT FROM AUTHOR]

Abstract In this paper, we present a broadcast dissemination protocol for messages in opportunistic networks (OppNet) that is efficient in terms of energy consumption and network capacity usage, while not increasing the number of excluded nodes (nodes not receiving messages). The majority of the OppNet broadcast delivery schemes proposed in the literature, do not take into consideration that reducing energy and buffer usage is of paramount importance in these wireless networks normally consisting of small devices. In our protocol, broadcast messages are limited by carefully selecting their prospective forwarders (storers). The keystone of our protocol is the use of Optimal Stopping Theory, which selects the best message storers at every stage of the algorithm, while holding back broad message dissemination until convenient conditions are met. The broadcast efficiency of the proposed protocol out competes other OppNet broadcast proposals in four well-known scenarios. Furthermore, the protocol reduces the number of both dropped messages and nodes not receiving messages, thus maximising network capacity usage, and the span of the message delivery. [ABSTRACT FROM AUTHOR]

Abstract Delay Tolerant Networks (DTNs) have attracted much research interest recently due to its adaptability in areas without infrastructures. In such scenarios, moving data from one place (landmark) to another place (landmark) is essential for data communication between different areas. However, current DTN routing algorithms either fail to fully utilize node mobility or have additional requirements that cannot be satisfied easily in DTNs. Therefore, in this paper, we propose a distributed greedy routing algorithm, namely GreedyFlow, for efficient packet routing between landmarks in DTNs. GreedyFlow builds a local traffic map and a global landmark map on each node. The local traffic map indicates the node's knowledge about the amount of traffic (node transition) between landmarks in the area where it primarily visits. The global landmark map shows the distribution of landmarks in the system and is built offline. In packet routing, the global landmark map shows the general packet forwarding direction, while the local traffic map helps determine the next-hop landmark on the fastest path in the forwarding direction. As a result, packets are greedily forwarded toward their destination landmarks. We also propose advanced components to enhance the consistency of local traffic maps and exploit node-based forwarding, both of which help improve the packet routing efficiency. Extensive real trace driven experiments demonstrate the high efficiency of GreedyFlow. [ABSTRACT FROM AUTHOR]

Abstract This paper presents a performance evaluation through simulations and a comparative study of main routing protocols dedicated to Vehicular Delay-Tolerant Networks. The assessment is conducted under small- and large-scale scenarios with realistic vehicle mobility patterns as defined in the TAPAS Cologne simulation scenario. Through the literature, several evaluations have been conducted on routing for Vehicular Networks, but with an abstraction or a simplification regarding the delay tolerant aspect. Furthermore, considered scenarios were relatively small and too idealistic compared to the real-world environment and its multiples challenges. Moreover, to the best of our knowledge, this is the first extensive study that compares, in the same realistic simulation environment, the main flag-carriers of various categories of VDTN routing protocols, namely Epidemic, Direct Delivery, Prophet and GeoSpray protocols. Simulation results reveal better performance for the geographical approach advocated by GeoSpray compared to the predictive one of Prophet, under all considered scenarios. Moreover, they highlight the possibility for a minimalist and naive protocol such as Direct Delivery to perform well, under specific network conditions, as when considering an anycast communication scheme. Finally, deeper analysis was undertaken on both GeoSpray and Prophet. The studies reveal the potentialities to increase the performances of GeoSpray to some extent and highlight the difficulties of adapting Prophet settings for optimal performance in realistic scenarios. [ABSTRACT FROM AUTHOR]

This paper investigates the use of unmanned aerial vehicles (UAVs)/drones for providing high data rates to mobile relays (MRs) placed on top of high speed train wagons, thus introducing the concept of Travel Hopping Enabled Resource Allocation (THEResA). The objective is to provide high data rate connectivity to train passengers in 5G+/6G networks. With the drone flying at the same train speed, highly directive beams can be formed and steered between the drone and each of the MRs. The simulation results in the paper show that this leads to high data rate connectivity, which will be reflected in the indoor links between the MRs and the train passengers inside the wagons. The drones maintain the connectivity to the cellular infrastructure by using high speed links with the cellular base stations (BSs) deployed along the rail track, e.g., through free space optics (FSO). The drones use the BS sites for recharging and resuming their operation. Therefore, a separate set of drones, or the same drones when they are not flying over trains, can be used to provide connectivity to remote rural areas. In fact, high speed trains might travel through rural areas with low population density. Although it is practical to lay fiber optic cables along the rail track, villages and small rural population agglomerations far from the railroad might not have access to the internet backhaul. UAVs can provide this connectivity in a delay tolerant fashion, by heading from the BSs/train station sites towards remote areas, collecting/transferring data from/to these areas, then returning to the sites along the rail track to recharge their batteries. This paper presents an analysis that shows the feasibility of this approach. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) has successfully revolutionized our society and all aspects of our daily lives. Wake-up radio (WuR) technology on its part has contributed to the success of IoT by significantly reducing latency and power consumption. Moreover, emerging mission critical Industrial IoT (IIoT) applications are time sensitive and generate more stringent delay and reliability constraints. Therefore, WuR-based MAC protocols must be carefully designed to meet these requirements. In this paper, a Dual-Mode MAC protocol (D2MAC) is proposed to fulfill QoS requirements of both delay-tolerant and real-time IoT applications by using service differentiation in the context of WuR-based IoT networks. Our protocol adopts two operation modes: normal mode, used in the case of normal traffic conditions, and priority mode for time–critical data. A Markov chain model is used to evaluate the performance of D2MAC. A simulation model based on MiXiM/ OMNet++ framework is also proposed to validate this analytical model. We illustrate the benefits of using the priority mode (PCA-WuR) to fulfill the requirements of IIoT applications. We also demonstrate that the Performance of PCA-WuR strongly depends on the acceptable delay limit for packet transmission. [ABSTRACT FROM AUTHOR]

Delay-tolerant networks (DTNs) (e.g., Internet, satellite networks, sensor networks, ad hoc networks) have attracted considerable attentions in both academia and industry. As a fundamental problem, the maximum flow is of vital importance for routing and service scheduling in networks. For solving the maximum flow problem of the DTN, an appropriate model should be built first. Compared to the conventional snapshot approach to model the DTN topology, the time aggregated graph (TAG) is capable of accurately characterizing the intermittent connectivity and time-varying capacity for each edge, and thus has been acted as a suitable model for modeling DTNs. However, existing TAG-related works only focus on solving the shortest path problem, and neither the correlation between time intervals nor nodes storage of a DTN are described in TAG, resulting in a non-trivial maximum flow problem in TAG. In this paper, we study the maximum flow problem through our proposed storage time aggregated graph (STAG) for DTNs. First, an intermediate quantity named bidirectional storage transfer series is introduced to each node in STAG, and the corresponding transfer rule is also designed for this series to model the correlation between time intervals. Next, on the basis of the storage transfer series, a STAG-based algorithm is proposed and described in detail to maximize the network flow. In addition, we analyze the effectiveness of the proposed algorithm by giving an illustrative example. [ABSTRACT FROM AUTHOR]

Opportunistic routing (OR) paradigms in vehicular networks via opportunistic candidate set selection have a better performance over the pre-defined next-hop node in terms of packet delivery rate. Nevertheless, uneven vehicle distribution, highly dynamic topology, varying link interference, and bandwidth restrictions impose drastic challenges for satisfying applications requirements in static prioritizing candidate set selection policies. Besides, fulfilling quality of service (QoS) requirements of heterogeneous applications, due to the limited local topology perspective and many involving conflicting routing criteria, will be further compromised. Considering the candidate set selection policy as a Multi-Criteria Decision Making (MCDM) task, an adaptive two-hop cooperative forwarding set selection strategy called APFS is proposed in this paper. By developing a local topology perspective to the two-hop neighbor information, the APFS scheme jointly considers indicators of link stability, delay assessment, and link good-put as routing criteria. Analytical Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methods are employed in two different scenarios in prioritizing candidate forwarding sets. First, classical AHP-TOPSIS technique with a mutable pair-wise comparison matrix is applied, and then Neutrosophic Set (NS) is combined with the classical AHP-TOPSIS method to handle ambiguous vehicular environments. The simulation results show that the APFS strategy using both prioritization policies have significantly improved the performance of packet delivery ratio, average end-to-end delay, throughput, and hop counts as compared to other schemes. [ABSTRACT FROM AUTHOR]

In urban areas, the population density is still growing (the population density starts exceeding 20.000 inhabitants per km 2 ), and so, the density of mobile users becomes very important. People are moving from home to work, from work to active places. One can take benefit of the mobility and the density to justify DTN (Delay Tolerant Network) approach protocol to convey sms (or alternative messaging services) traffic. Indeed, the mobility of users, especially during the day, create an ad hoc mobile network where the nodes are the smartphones hold by mobile clients. In this paper, their performance evaluations are based on a measurement and analysis of sms traces coming from a nationwide cellular telecommunication operator during a two month period, we propose several DTN like basic network protocols for delivering sms . We perform a temporal and spatial analysis of the Mexico City cellular network considering geolocalized sms to characterize the traffic. Such key characterization allows us to answer the question: is it possible to transmit sms using phones as relay in a large city such as Mexico City? We define four network protocols to transmit sms from a source to a destination. We study a mobile dataset including 8 Million users living in Mexico city. This gives us a precise estimation of the average transmission time and the global performance of our approach. Our analysis shows that after 30 min, half of the sms are delivered successfully to destination. On the contrary to the cellular networks, we explain how much the potentiality of the mobile users network can take benefit from complementary properties such as the locality of sms , the density of phones in Mexico City and the mobility of phone users. Moreover, we show that in a realistic scenario, our approach induces reasonable storage cost. [ABSTRACT FROM AUTHOR]

To capture the dynamics of context-aware decision making for network functions in Mobile Ad Hoc Networks (MANETs), the paper introduces the concept of Decision-Related Event Occurrence Times (DREOTs). By considering a generic scenario, the paper develops a broadly applicable analysis methodology, which produces upper and lower bounds for the tail probabilities and moments of a DREOT. The nature and effect of the decision is abstracted away to quantities called 'decision policy impact descriptors'. These are calculated on a case-by-case basis, by considering properties of the specific decision policy and mobility pattern in hand. The power of the approach is demonstrated through a detailed application targeting the analysis of a preexisting routing protocol that bases its next hop forwarding decisions on the location and motion of the neighboring nodes. In the considered application the DREOT represents the time a node retains a message before forwarding it to the next hop and the network nodes move according to the Random Direction mobility model. The proposed methodology is seen to bring more rigorous understanding of the relationship between the retaining time and the relevant context and to yield refined expressions, whose use improves the protocol's performance for all network conditions in a very diverse set. Furthermore, the broad applicability of the methodology is illustrated through a brief discussion of another application, not related to routing. [ABSTRACT FROM AUTHOR]

Controlling congestion is critical to ensure adequate network operation and performance. That is especially the case in networks operating in challenged- or extreme environments where episodic connectivity is part of the network’s normal operation. Consequently, the “pure” end-to-end congestion control model employed by the Internet is not adequate. Our goal is to study congestion control mechanisms that have been proposed for these so-called disruption tolerant networks, or DTNs. In this paper, we conduct a performance study comparing existing DTN congestion control mechanisms for two main application domains, namely: inter-planetary (IPN) and terrestrial networking applications. Our results confirm that congestion control helps increase message delivery ratio, even in highly congested network scenarios. Furthermore, the results show that existing DTN congestion control mechanisms do not perform well in IPN scenarios. Our study also suggests that good design principles for congestion control in DTN scenarios include: combining reactive and proactive control, using local information instead of global knowledge, and employing mechanisms that are routing protocol independent. One important conclusion from our quantitative study is that there is currently no universal congestion control mechanism that fits all DTN scenarios and applications. [ABSTRACT FROM AUTHOR]

This paper proposes a proactive fragmentation mechanism for an optimal DTN message transfer. DTN message transfer is presented to give coverage to a terrestrial sensor network by using a nanosatellite communications link. Satellite communication is modeled with a multi-access mechanism with priority in downlink traffic (ALOHAGP). This new multiple access protocol is based on unslotted ALOHA extended with an adaptive contention mechanism. It uses satellite feedback to implement the congestion control, and to dynamically adapt the channel effective throughput in an optimal way. The effective throughput has been optimized by adapting the protocol parameters as a function of the current number of active sensors received from satellite. Also, regarding the optimal size of a bundle, there is a lack of standard negotiation methods of bundle sizes that can be accepted by a bundle agent in satellite communications. Thus, too large bundles are dropped and too small messages are inefficient. We have characterized this kind of scenario obtaining a probability distribution for frame arrivals to nanosatellite and visibility time distribution providing an optimal proactive fragmentation of DTN bundles. We have found that the proactive effective throughput (goodput) reaches in some cases almost 97% of the reactive fragmentation approach. [ABSTRACT FROM AUTHOR]

How to deliver data to, or collect data from the hundreds of thousands of sensors and actuators integrated in “things” spread across virtually every smart city streets (garbage cans, storm drains, advertising panels, etc.)? The answer to the question is neither straightforward nor unique, given the scale of the issue, the lack of a single administrative entity for such tiny devices (arguably run by a multiplicity of distinct and independent service providers), and the cost and power concerns that their direct connectivity to the cellular network might pose. This paper posits that one possible alternative consists in connecting such devices to their data collection gateways using “oblivious data mules”, namely transport fleets such as taxi cabs which (unlike most data mules considered in past work) have no relation whatsoever with the smart city service providers, nor are required to follow any pre-established or optimized path, nor are willing to share their LTE connectivity. We experimentally evaluate data collection and delivery performance using real world traces gathered over a six month period in the city of Rome. Results suggest that even relatively small fleets, such as an average of about 120 vehicles, operating in parallel in a very large and irregular city such as Rome, can achieve an 80% coverage of the downtown area in less than 24 h. [ABSTRACT FROM AUTHOR]

In conventional networks, routing problem can be modeled as the design of an efficient source-to-destination route based on persistent end-to-end paths. However, in a delay tolerant network (DTN), nodes are intermittently connected and thus, the end-to-end paths will not always exist, in which routing is a challenging issue. Previous DTN routing protocols tend to make routing decision based on the nodes’ contact information. In this paper, we observe that considering both the nodes’ contact information and message property such as the time-to-live (TTL) would help to improve the performance. Embedded this idea, we first propose an expected encounter based routing protocol (EER) which distributes multiple replicas of a message proportionally between two encounters according to their expected encounter values. In case of a single replica of a message, EER makes the routing decision by comparing two encountering nodes’ minimum expected meeting delays to destination. We further propose a community aware routing protocol (CAR) which takes advantages of the high contact frequency property of the nodes within the same community. We also propose the buffer management strategies corresponding for the two protocols. We conduct simulations to evaluate our proposed protocols and some existing ones on three metrics: delivery ratio, latency and goodput. The simulation results illustrate that our proposed EER and CAR protocols outperform other existing ones. [ABSTRACT FROM AUTHOR]

Dynamic networks, in particular Delay Tolerant Networks (DTNs), are characterized by a lack of end-to-end paths at any given instant. Because of that, DTN routing protocols employ a store-carry-and-forward approach, holding messages until a suitable node to forward them is found. But, the selection of the best forwarding node poses a considerable challenge. Additional network information (static or dynamic) can be leveraged to aid routing protocols in this troublesome task. One could use centrality metrics, therefore providing means to differentiate the importance of nodes in the network. Among these metrics, betweenness centrality is one of the most prominent, as it measures the degree to which a vertex is in a position of brokerage by summing up the fraction of shortest paths between other pairs of vertices passing through it. So, in this paper, betweenness centrality is surveyed, that is, its definitions and variants in static and dynamic networks are presented. Also, a survey of standard algorithms used to compute the metric (exact and approximate) is presented. Finally, a survey and a discussion on how DTN routing protocols make use of the betweenness centrality metric and algorithms to aid message forwarding is also presented. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Delay-tolerant networks (DTNs) are network environments that are subject to delays and disruptions. Traditional end-to-end routing protocols fail in such challenging network conditions because of intermittent connections and/or long delays. Research results have shown that per-hop forwarding of multiple copies of the same message to the destination can produce satisfactory routing performance in DTNs. Current methods rely on the fixed setting of a quota value to limit the number of message copies. This paper proposes a dynamic quota-control mechanism, allowing routing to operate effectively with different traffic loads. To remove useless message copies from the network, a low-cost probability-based method is also presented. The proposed routing framework is then extended to interest-based information dissemination, which is used to efficiently disseminate an event message to all interested users. A performance evaluation was conducted using a real social contact trace, and performance comparisons with other DTN routing protocols are provided. [ABSTRACT FROM AUTHOR]

The current Internet design is not capable of supporting communications in environments characterized by very long delays and frequent network partitions. To allow devices to communicate in such environments, delay-tolerant networking solutions have been proposed by exploiting opportunistic message forwarding, with limited expectations of end-to-end connectivity and node resources. Such solutions envision non-traditional communication scenarios, such as disaster areas and development regions. Several forwarding algorithms have been investigated, aiming to offer the best trade-off between cost (number of message replicas) and rate of successful delivered message. Among such proposals, there has been an effort to employ social similarity, inferred from users’ mobility patterns, to improve opportunistic forwarding solutions. However, such proposals present two major drawbacks: first, they focus on distribution of intercontact times over the complete network structure, ignoring the impact that human behavior has on the dynamics of the network; and second, most of the proposed solutions look at challenging networking environments where networks have low density, ignoring the potential use of delay-tolerant networking to support low cost communications in networks with higher density, such as urban scenarios. This paper presents a study of the impact that human behavior has on opportunistic forwarding. Our goal is twofold: (i) to show that performance in low and high density networks can be improved by taking the dynamics of the network into account; and (ii) to show that delay-tolerant networking can be used to reduce communication costs in networks with high density by considering the users’ behavior. [ABSTRACT FROM AUTHOR]

Delay and disruption tolerant networks (DTNs) may experience frequent and long-lived connectivity disruptions. Unlike traditional networks, such as the TCP/IP-based Internet, DTNs are often subject to high latency caused by very long propagation delays (e.g., interplanetary communication) and/or intermittent connectivity. Another feature that sets DTNs apart from conventional networks is that there is no guarantee of end-to-end connectivity between source and destination. Such distinct features pose a number of technical challenges in designing core network functions such as routing and congestion control. In this paper, we survey the state-of-the-art in DTN congestion control. We propose a taxonomy to map the DTN congestion control design space and use it to classify existing DTN congestion control mechanisms. [ABSTRACT FROM AUTHOR]

The increasing pervasiveness of mobile devices with networking capabilities has led to the emergence of Mobile Delay Tolerant Networks (MDTNs). The characteristics of MDTNs, which include frequent and long-term partitions, make message routing a major challenge in these networks. Most of the existing routing protocols either allocate an unlimited number of message copies or use a fixed number of message copies to route a message towards its destination. While the first approach unnecessarily floods the network, the rigidity of the second approach makes it inefficient from the viewpoint of message replication. Hence, the question that we address in this paper is: “how to dynamically allocate message copies in order to strike a balance between the delay and cost of message delivery?”. We present a novel adaptive multi-step routing protocol for MDTNs. In each routing step, our protocol reasons on the remaining time-to-live of the message in order to allocate the minimum number of copies necessary to achieve a given delivery probability. Experiment results demonstrate that our protocol has a higher delivery ratio and a lower delivery cost compared to the state-of-the-art Spray-and-Wait and Bubble protocols. [ABSTRACT FROM AUTHOR]

In wireless networks, topology control can improve energy effectiveness and increase the communication capacity. In predictable delay tolerant networks (PDTNs), intermittent connectivity, network partitioning, and long delays make most of the researchers focus on routing protocol, and the research on topology control is in the very early stage. Most existing topology control approaches for PDTN assume the underlying connections are deterministic, which excludes a large amount of probabilistic connections existing in the challenged environments. In this paper, probabilistic connections are taking into consideration. The predictable delay tolerant networks are modeled as a three dimensional space–time weighted directed graph which includes spatial, temporal and connection probability information. The topology control problem is formulated as finding a sub graph to balance the energy cost and data transferring reliability. This problem is proved to be NP-complete, and two heuristic algorithms are proposed to solve the problem. The first one is to find a sub graph that assures the maximum connection probability between each pair of nodes. The other one is to find the sub graph in which the connection probabilities between each pair of nodes satisfy the given threshold with the minimum energy cost. Extensive simulation experiments demonstrate that the proposed topology control algorithms can achieve our goal. [ABSTRACT FROM AUTHOR]

Social Delay Tolerant Networks (SDTNs) are a special kind of Delay Tolerant Network (DTN) that consists of a number of mobile devices with social characteristics. The current research achievements on routing algorithms tend to separately evaluate the available profit for each prospective relay node and cannot achieve the global optimal performance in an overall perspective. In this paper, we propose a Movement Pattern-Aware optimal Routing (MPAR) for SDTNs, by choosing the optimal relay node(s) set for each message, which eventually based on running a search algorithm on a hyper-cube solution space. Concretely, the movement pattern of a group of node(s) can be extracted from the movement records of nodes. Then the set of commonly visited locations for the relay node(s) set and the destination node is obtained, by which we can further evaluate the co-delivery probability of the relay node(s) set. Both local search scheme and tabu-search scheme are utilized in finding the optimal set, and the tabu-search based routing Tabu-MPAR is proved able to guide the relay node(s) set in evolving to the optimal one. We demonstrate how the MPAR algorithm significantly outperforms the previous ones through extensive simulations, based on the synthetic SDTN mobility model. [ABSTRACT FROM AUTHOR]

Distributed mobile energy storage (DMES) units, which have been recently available in the form of Plug-in Electric Vehicle (PEV) batteries, provide unique opportunities to enhance the efficiency of the smart grid. On the other hand, without communications, uncoordinated supply may risk the stability of the grid, while mobility and variable availability of the batteries make the planning task challenging for the utilities. In this paper, we propose a four-way handshake protocol and a token-based energy forwarding network model for the electricity distribution system that allows energy to be supplied in a store-and-forward fashion similar to packet delivery in delay-tolerant networks. Based on this model, we develop a novel vehicle-to-grid power flow coordination approach, where the power acquired by the delay-tolerant loads is aggregated into tokens which are then matched with the available capacity of the PEV batteries. Energy transactions between delay-tolerant loads and PEVs rely on their communications with the energy management system at the distribution level. Our four-way handshake protocol assures tokens coming from loads and grants coming from storage are matched properly at the distribution level. Our approach provides a convenient supply for loads via PEV batteries while addressing the mobility of vehicles and preserving fairness. We provide a mathematical analysis of the proposed approach and conduct simulations showing that the proposed protocol is able to provide fair access opportunity to PEV owners. Furthermore, by introducing the queuing theory perspective, we enhance the planning capabilities of utilities. [ABSTRACT FROM AUTHOR]

In recent years, Internet of Things (IoT) devices have been deployed even to the most isolated and hard-to-reach areas. Content retrieval from such communication-disruptive remote areas therefore becomes a challenging task, mainly due to the increased infrastructure cost. In this paper, we present a gateway-oriented scheme which facilitates content retrieval from remote IoT deployments, using mobile devices. We call our scheme NDN-over-DTN (NoD), as it combines the information-centric design of the Named Data Networking (NDN) architecture with the store-carry-and-forward approach of Delay/Disruption-Tolerant Networking (DTN). In this work, we evaluate the performance of NoD in a real IoT-content-retrieval scenario, in terms of Average Delay , Cache Hit , Interest Satisfaction and Overhead Ratio. We model the behavior of NoD analytically and introduce an improved NoD version which utilizes cross-layer interaction between NDN and DTN, called NoD-Discovery. We show, both analytically and experimentally, that NoD can exploit jointly the benefits of NDN and DTN and achieve significant performance gains in highly disruptive environments. Notably, our experiments demonstrated that NoD-Default can achieve up to a 48.77% decrease in Average Delay compared to host-centric DTN, while NoD-Discovery can improve performance further by decreasing the Overhead Ratio up to 70.34%, compared to the original NoD-Default implementation. [ABSTRACT FROM AUTHOR]

Abstract: Majority of the existing Delay Tolerant Network (DTN) routing protocols attempt to minimize the message delay, forwarding count, or required storage. However, for many DTN applications such as distributing commercial content, targeting the best performance for only one index and neglecting the others is insufficient. A more practical solution would be to strike a balance between multiple of those performance indices. This paper introduces a Gain-aware Dissemination Protocol (GDP) which attempts to reach the maximum economic gain of content delivery by maintaining a balance between the value achieved via message delivery and the involved forwarding costs given out as user rebates. Economic gain from disseminating content is defined as the generated value upon content delivery minus its forwarding costs. The key concept behind the proposed protocol is to adaptively balance between dissemination latency and forwarding costs in order to maximize the economic gain. Using the DTN simulation software ONE, we characterize the GDP protocol with varying mobility models, content sources, and content generation times. [Copyright &y& Elsevier]

Abstract: Duty cycling is a fundamental mechanism for battery-operated ad hoc networks, such as Wireless Sensor Networks, Delay Tolerant Networks, and solar-powered Wireless Mesh Networks. Because of its utter importance, it has been proposed in a wide variety of flavors, one of the most prominent being that of the asynchronous mechanisms. In particular, schedule-based duty cycling has earned attention due to its low requirements and simplicity of implementation. Despite its potential, a comprehensive and realistic study on the neighbor discovery latency that results from schedule-based asynchronous duty cycling is still missing. This paper fills in this gap, by providing accurate models for major schedule-based mechanisms: Block Designs, Quorum systems and Disco. The provided models consider message loss probability and yield more precise estimations than traditional models. Based on this improved accuracy, the relative latency, a new metric for studying the trade off between latency and power, is proposed as a substitute to the power-latency product. Finally, a practical mapping of which schedule is more adequate for given requirements of latency, energy savings and link reliability is presented. [Copyright &y& Elsevier]

Abstract: This paper considers a field with a number of isolated wireless sensor networks served by some mobile mules and base stations (BSs). Sensing data needs to be carried by mobile mules to BSs via opportunistic contact between them. Also, such contact may not be frequent. Thus there are four types of communications in this environment: (i) inter-node communications within a WSN, (ii) opportunistic WSN-to-mule communications, (iii) opportunistic mule-to-mule communications, and (iv) opportunistic mule-to-BS communications. In such disconnected WSNs, since sensors’ memory spaces are limited and data collection from isolated WSNs to mules and then to BSs relies on opportunistic communications in the sense that contact between these entities is occasional, storing and collecting higher-priority data is necessary. Therefore, there are two critical issues to be addressed: the data storage management in each isolated WSN and opportunistic data collection between these entities. We address the storage management problem by modeling the limited memory spaces of a WSN’s sensor nodes as a distributed storage system. Assuming that there is a sink in the WSN that will be visited by mobile mules occasionally, we address three issues: (i) how to buffer sensory data to reduce data loss due to a shortage of storage spaces, (ii) if dropping of data is inevitable, how to avoid higher-priority data from being dropped, and (iii) how to manage the data nearby the sink to facilitate the downloading jobs of mules when the downloading time is unpredictable. We propose a Distributed Storage Management (DSM) strategy based on a novel shuffling mechanism similar to heap sort. It allows nodes to exchange sensory data with neighbors efficiently in a distributed manner. For the opportunistic data collection problem, based on a utility model, we then develop an Opportunistic Data Exchange (ODE) strategy to guide two mules to exchange data that would lead to a higher reward. To the best of our knowledge, this is the first work addressing distributed storage strategy for isolated WSNs with opportunistic communications using mobile mules. We conduct extensive simulations to investigate the merit of DSM and ODE. The simulation results indicate that the level of data importance collected by our DSM is very close to a global optimization and our ODE could facilitate delivery of important data to BSs through mules. We also implement these strategies in a real sensor platform, which demonstrates that the simple and lightweight protocols can achieve our goals. [Copyright &y& Elsevier]

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%. [ABSTRACT FROM AUTHOR]

With the recent advances and wide availability of heterogeneous wireless access technologies, inter-vehicle communication systems are expected to culminate in the integration of different wireless networks based on such standards as 5G/6G, coupling with multimedia and sensor networks for the next generation of connected and autonomous vehicles. However, the high mobility nature of vehicles poses intrinsic research challenges on the mobility management and the integration of different wireless technologies. Towards this end, in this paper, we propose an ADaptive VehIcle-CEntric LOCation management protocol (ADVICE-LOC) that utilizes the individual mobility projection of each vehicle and estimates the vehicles' residual time within each access point. Its ultimate objective is to eliminate the network communication's overhead, while guaranteeing a high packet delivery ratio and low latency rates. The proposed protocol preemptively adjusts the vehicles' access registration and location updates based on its movement projections. We present our protocol, and we report on its performance evaluation using an extensive set of experiments using SUMO generated vehicles' mobility. Our results indicate that the proposed DEVICE-LOC protocol succeed significantly in reducing the communication overhead while sustaining high packet delivery ratio when compared to previous studies. [ABSTRACT FROM AUTHOR]

Routing in Vehicular Ad Hoc Networks (VANETs) is a challenging problem. While geographic routing protocols are preferred for VANETs due to their scalability, they are focused on finding next-hop nodes closer to the destination without considering their current load or network traffic. In addition, routing decisions based on only one-hop neighbors information might be less optimal since they do not consider the availability of further suitable nodes for forwarding. Thus, such selected next-hop nodes may become overloaded with too much traffic that exceeds their available bandwidth, and may even result in significant packet losses if no other node suitable for forwarding can be found. In this paper, we propose a novel geographic routing protocol named Geo-LU. The proposed protocol improves the routing performance by extending the local view of the network topology at the current forwarder to include two-hop neighbor information. Moreover, it utilizes our proposed link utility (LU) measure. LU considers the utility of a two-hop neighbor link by considering the minimum residual bandwidth on that link and its packet loss rate. By incorporating two-hop neighbor information and our proposed LU measure, the proposed protocol, Geo-LU, can react appropriately to the increased network traffic and to the frequent topology dis-connectivity in VANETs as confirmed by our simulation results. [ABSTRACT FROM AUTHOR]

Disaster Response Networks (DRNs) are specific delay-tolerant networks (DTNs) designed to support temporary communications during disaster recovery with limited energy resources. Existing research on DRNs routing addresses routing metrics like packet delivery delay (PDD), packet delivery ratio (PDR), and total transmission energy (TTE). However, the complex interplay among these metrics remains unclear and makes their control difficult. Moreover, the standard deviation of packet delivery delay (PDS), which is overlooked by the previous works, is an important metric in DRNs. In this paper, we propose the Energy-Aware Risk-averse routing framework (EAR) for DRNs. EAR models the mobility in DRNs using a stochastic multigraph and computes the risks associated with routing paths using the Mean-Risk and Max-Probability models. A " λ -optimal" algorithm is used for finding routing paths with the minimum risks. A parameter L restricting the number of packet replicas and a differentiated service model are utilized to improve packet delivery efficiency (PDE) while maintaining other metrics at an adequate level. We show via extensive simulations that EAR provides flexible control of the routing risks and delivers packets to the destinations in a more energy-efficient way (up to 8x higher PDE with 4% lower PDR) than well-known routing protocols Prophet, MaxProp, RAPID and Spray&Wait. [ABSTRACT FROM AUTHOR]

Cognitive Radio Networks (CRNs) have emerged as a promising next-generation network technology that solves the spectrum scarcity issue and improves spectrum utilization. It is designed to help grant access for unlicensed users and utilize the maximum available licensed bandwidth. Moreover, the Internet of Things (IoT) has brought a significant promise to a multitude of applications and services allowing for anytime and anywhere connectivity. The coexistence of IoT and CRN has enabled a broad range of solutions to be available for users in an efficient and somewhat secure manner. But, with today's resource consuming and time-sensitive IoT applications, the lack of communication security proves to be a challenge. CRNs are prone to more attacks and have much more risks than traditional wireless networks. This paper introduces a security-aware routing protocol that considers jamming attacks which interrupt cognitive radio transmissions. The proposed protocol assigns the most secure channel for each hop within an IoT source-destination pair in accordance to an optimization problem. Moreover, since CRNs are more vulnerable to threats, an Ensemble-based Jamming Behaviour Detection and Identification (E-JBDI) technique is proposed as a second line of defence. It is used to identify the behavior anomaly of jamming attack. Extensive simulations are conducted to showcase the effectiveness of the proposed routing protocol in comparison to other relatively similar state-of-the-art solutions. Results show network performance improvements against increased numbers of proactive jamming attacks. Moreover, results also show the effectiveness of E-JBDI in terms of accuracy, detection and precision-recall rates with values of ≈ 1. [ABSTRACT FROM AUTHOR]

Energy is a scarce resource in mobile wireless networks that consist of devices mainly powered by their batteries. Providing energy ubiquitously to these devices for making them functional for a long time is a challenging task. With the advent of energy sharing techniques, either by wired or wireless mediums, it is possible to extend the lifetime of such networks by utilizing the energy from other energy sources (e.g., chargers, other devices) within the network. In this paper, we explore the utilization of peer-to-peer energy sharing in various applications of mobile networks that consist of agents from low-power devices such as sensors to high-power ones such as electric vehicles. We provide an overview of the current research directions and developments of new protocols and algorithms that exploit the energy sharing techniques to solve the scarce energy problem in mobile networks. For each mobile networking domain, we highlight the specific challenges and describe the approaches followed to address them under various research problems. We also discuss open problems yet to be solved in each specific application. [ABSTRACT FROM AUTHOR]

Wireless Body Area Networks (WBANs) can be considered as an evolution of wireless sensor networks towards wearable and implanted technologies. Radio propagation and mobility are particular in this context, as they are influenced by the characteristics and movement of the human body and by the necessity to keep the transmission power at its minimum to save energy and limit interactions with the wearer. In this paper, we investigate the broadcasting problem in which a node, typically the gateway, tries to send a packet to all other nodes in the network at minimal cost. This problem is not as trivial as it looks and we show through simulation that forwarding strategies coming from the Delay Tolerant Networks world cannot be transposed without adaptation. We enriched the Omnet++ simulator with a WBAN-specific channel model from the literature, and use this model to evaluate 9 classes of broadcasting algorithms, including our own proposals, with respect to their ability to cover the whole network, their completion delay, their cost in terms of transmissions volume and their capability to preserve multiple packets order (i.e. total order broadcast). Our study shows that there is a subtle compromise to find between verbose strategies that achieve good performance at the cost of numerous transmissions, ultimately provoking collisions and more cautious solutions that miss transmission opportunities because of mobility. [ABSTRACT FROM AUTHOR]

The distribution of nodal distance is of vital importance in connectivity analysis of wireless ad hoc networks. Existing research on distance distribution focuses on static network deployment. In this paper we consider the distribution of nodal distance between uniformly deployed static nodes and multiple mobile nodes. The Random-Way-Point (RWP) mobility model is applied for mobile nodes. We derive the analytic expressions of the cumulative distribution function and probability density function of the nodal distance in square and circular areas. The validity of our theoretical results is verified through computer simulations, which show that the analytical results are consistent with the simulated results. [ABSTRACT FROM AUTHOR]

Delay and Disruption Tolerant Networks (DTNs) are networks that experience frequent and long-lived connectivity disruptions. Unlike traditional networks, such as TCP/IP Internet, DTNs are often subject to high latency caused by very long propagation delays (e.g., interplanetary communication) and/or intermittent connectivity. In DTNs there is no guarantee of end-to-end connectivity between source and destination. Such distinct features pose a number of technical challenges in designing core network functions such as routing and congestion control mechanisms. Detecting and dealing with congestion in DTNs is an important problem since congestion can significantly deteriorate DTN performance. Most existing DTN congestion control mechanisms have been designed for a specific DTN application domain and have been shown to exhibit inadequate performance when used in different DTN scenarios and conditions. In this paper, we introduce Smart-DTN-CC, a novel DTN congestion control framework that adjusts its operation automatically based on the dynamics of the underlying network and its nodes. Smart-DTN-CC is an adaptive and distributed congestion aware framework that mitigates congestion using reinforcement learning , a machine learning technique known to be well suited to problems where: (1) the environment, in this case the network, plays a crucial role; and (2) yet, no prior knowledge about the target environment can be assumed, i.e., the only way to acquire information about the environment is to interact with it through continuous online learning. Smart-DTN-CC nodes receive input from the environment (e.g., buffer occupancy, neighborhood membership, etc), and, based on that information, choose an action to take from a set of possible actions. Depending on the selected action's effectiveness in controlling congestion, a reward will be given. Smart-DTN-CC's goal is to maximize the overall reward which translates to minimizing congestion. To our knowledge, Smart-DTN-CC is the first DTN congestion control framework that has the ability to automatically and continuously adapt to the dynamics of the target environment. As demonstrated by our experimental evaluation, Smart-DTN-CC is able to consistently outperform existing DTN congestion control mechanisms under a wide range of network conditions and characteristics. [ABSTRACT FROM AUTHOR]