Delay Tolerant Networks Research Articles

Heterogeneous Mobile Networking for Lightweight UAV Assisted Emergency Communication

Due to the frequent natural disasters in recent two years, UAV assisted disaster networks have attracted attention due to the flexible information storage and favorable computation capacity in technical rescue. The previous studies concentrate on dynamically optimizing the service coverage to improve the system performance. However, the continually changing of energy cost, time cost, and the social connections between users are not jointly considered in previous studies. In this paper, we propose a social relationship-based timeliness aware message splitting scheme for the energy-friendly UAV assisted delay tolerant networks. Firstly, we put forward our social network based splitting optimization problem and use social network closeness and message's decaying with time to quantify the messages' value. Next, a social optimization copy splitting algorithm (SOCS) is designed to guarantee the lower expected delay and higher message delivery ratio through UAV assisted interesting areas (IAs). Finally, the extensive simulations show the optimality of the proposed SOCS algorithm using the enhanced social relationship based forwarding scheme.

Prioritized Content Determination and Dissemination Using Reinforcement Learning in DTNs

In a battlefield, several groups of soldiers are deployed with different missions by the command and control center (CC). To continue the missions appropriately and get a better understanding of the situation, the soldiers as well as the CC need to collect information of interest generated in different battle zones using Delay-tolerant Networks (DTN). It is a challenge to determine the topics of interest associated with the events and missions, and efficiently forward the associated content to the CC in this extreme situation. We design a scheme to forward contents generated by the nodes to the CC using Reinforcement Learning (RL) while maximizing the number of interesting data in the respective nodes buffer, and avoiding congestion. In this forwarding process, we focus on identifying the trending topics/keywords among changing missions and their related data at the node level, and the changes of interest of the nodes based on their mobility and connectivity patterns of nodes in DTN. Experiments are conducted using real datasets and ONE simulator to show the effectiveness of Reinforcement Learning (RL) on the prioritized content dissemination in DTN networks.

Fast-MICDTN: a new decentralized control mechanism for content-centric disruption tolerant networks

Information-Centric Networking (ICN) emerges as a promising architecture for the future Internet to keep up with the tremendous growth of Internet users and the explosive increase of mobile data traffic. ICN can be coupled with Disruption Tolerant Networking (DTN) to overcome the limitations of the current Internet architecture in some challenging environments where we cannot establish a network connection, and also lighten the load on the Internet backhaul. Unfortunately, resources constraints, such as energy and buffer space, are among the most serious issues in Mobile Information-Centric Disruption Tolerant Networking (MICDTN). In this paper, we introduce an opportunistic DTN-based forwarding mechanism of Interest and Data for ICN, named Fast-MICDTN. The propagation of the content have been modeled using Markov-Decision Process (MDP). Hence, we characterize the living period in transit of the content to reach the maximum possible number of mobiles. Through extensive simulations based on synthetic mobility model and real-world traces, we prove the efficiency of the new approach in sharing content within a large number of users under a low cost.

Genetic Improvement of Routing Protocols for Delay Tolerant Networks

Routing plays a fundamental role in network applications, but it is especially challenging in Delay Tolerant Networks (DTNs). These are a kind of mobile ad hoc networks made of, e.g., (possibly, unmanned) vehicles and humans where, despite a lack of continuous connectivity, data must be transmitted while the network conditions change due to the nodes’ mobility. In these contexts, routing is NP-hard and is usually solved by heuristic “store and forward” replication-based approaches, where multiple copies of the same message are moved and stored across nodes in the hope that at least one will reach its destination. Still, the existing routing protocols produce relatively low delivery probabilities. Here, we genetically improve two routing protocols widely adopted in DTNs, namely, Epidemic and PRoPHET, in the attempt to optimize their delivery probability. First, we dissect them into their fundamental components, i.e., functionalities such as checking if a node can transfer data, or sending messages to all connections. Then, we apply Genetic Improvement (GI) to manipulate these components as terminal nodes of evolving trees. We apply this methodology, in silico, to six test cases of urban networks made of hundreds of nodes and find that GI produces consistent gains in delivery probability in four cases. We then verify if this improvement entails a worsening of other relevant network metrics, such as latency and buffer time. Finally, we compare the logics of the best evolved protocols with those of the baseline protocols, and we discuss the generalizability of the results across test cases.

DELAY TOLERANT NETWORKING SUPPORT FOR CREATION HIGH-ACCURACY MAGNETIC FIELD MAPS

Context. The main purpose of Correlation Extremal Navigation system is finding coordinates in case of absence of Global Positioning System signal and as a result high-accuracy maps as the main source of information for finding coordinates are very important. Magnetic field map as the main source of information can include errors values, as an example: not good enough equipment or human factor can cause error value of measurements.
 Objective. In order to create high-accuracy maps given work proposes to improve the process of creating magnetic field maps. The given work represents delay tolerant networking as an additional approach for data transmission between magnetic observatory and magnetic station and its improvement.
 Method. Improved Dijkstra’s algorithm together with Ford-Fulkerson’s algorithm for finding path with minimum capacity losses, earliest delivery time and maximum bit rate in case of overlapping contacts should be represented in the given work because nowadays, delay tolerant networking routing protocols do not take into account the overlap factor and resulting capacity losses and it leads to big problems
 Results. For the first time will be presented algorithm that chooses the route that guarantees the minimum of capacity losses, earliest delivery time and maximum bit rate in the delay tolerant networking with overlapping contacts and increases the probability of successful data transmission between magnetic stations and magnetic observatories.
 Conclusions. In order to perform high-accuracy measurement of magnetic field group of people allocate their equipment for magnetic field measurement in remote areas in order to avoid the influence of environment on measurements of magnetometer. Since magnitude of magnetic field can vary dependent on temperature, proximity to the ocean, latitude (diurnal variation of magnetic field) and magnetic storms magnetic station from time to time adjusts its measurements with a help of reference values of magnetic field (magnetic station sends request for reference values to magnetic observatory). The problem of the given approach is that remote areas usually are not covered by network (no Internet) and as a result the adjustment of measurements is impossible. In order to make adjustment of measurements possible and as a result improve accuracy of magnetic maps given work proposed the usage of Delay Tolerant Networking that delivers internet access to different areas around the world and represented its improvement to make its approach even better.The results are published for the first time.

Autonomous Delay Tolerant Network Management Using Reinforcement Learning

Delay tolerant networks (DTNs) offer a set of standardized protocols to enable Internet-like connectivity across the solar system. Unlike other protocols such as the Transmission Control Protocol (TCP) and the Internet Protocol (IP), DTN protocols are robust to end-to-end connection disruptions and long delays. Although the behavior of DTN core protocols is well understood, management of DTNs is still an area of active research. This paper uses reinforcement learning (RL) to automate the management of a DTN node consisting of an orbital relay between the moon and Earth. More specifically, the RL agent is in charge of deciding when to drop packets, when to change the data rate of the neighbor node links, when to reroute bundles to crosslinks, or when not to change any network parameter. The agent’s goal is to maximize the bits received by the Deep Space Network while minimizing the capacity allocated to all controlled links, and control the buffer utilization to avoid memory overflows. To assess the potential of using RL in DTN management, the performance of the trained RL agent is benchmarked against other non-RL-based policies in a realistic lunar scenario. Results show that the RL agent provides the highest reward, outperforming all non-RL policies in this scenario.

Monitor Potential Attack Locations in a Specific Area within DTN Network

In this paper will discuss and examine message transmission from the attacker process within the scope of Delay Tolerance Networks (DTNs). DTNs are a new area of research that can be developed in networking. Delay-tolerant networks are those networks that may not have a complete path between networks end-to-end via direct links and may be under development for a long time. As part of the improvement, we will compare a survey of DTN routing protocols with a real region area, and then taking into account the possibilities of detecting the presence of areas of weakness that lead to penetration, which will occur in the nodes while on the move. In this study, we will use the ONE simulator to track messages within nodes.

Efficient Energy and Delay Tradeoff for Vessel Communications in SDN Based Maritime Wireless Networks

The maritime communication network is assembled by emergent network technologies. However, the adverse maritime environment impedes the efficiency of resources allocation in maritime communication network. Here we show a joint sleeping scheduling and opportunistic transmission scheme in delay-tolerant maritime wireless communication networks based on software defined networking (SDN) to find a better tradeoff between the energy consumption and the delay. Specifically, an energy-limited delay tolerant networking (DTN) node deployed in the ocean receives/transmits data from/to vessels within its communication range. To further save the energy, a long-term energy minimization problem is formulated with sleeping scheduling and opportunistic transmission. After that, a multi-objective minimization problem of energy and delay is first modeled by Lyapunov optimization (LO), which then is solved by convex optimization. Both mathematical analyses and simulation results demonstrate how the maritime communication network allocates satisfactorily with the proposed allocation scheme.

Routing Algorithm Based on Density Clustering for Delay Tolerant Network

Routing Algorithm Based on Density Clustering for Delay Tolerant Network

Mobile Ad Hoc Network in Disaster Area Network Scenario: A Review on Routing Protocols

Disasters could cause communication systems partially or completely down. In such a case, relief operations need a rapidly deployed communication system to save lives. Exchanging information among the rescue team is a vital factor to make important decisions. Communication system required to be robust to failures, rapidly deployable, easily maintainable to provide better services. Wireless ad-hoc networks could be the choice of establishing communication with the aid of existing infrastructure in a post-disaster case. In order to optimize mobile ad-hoc network performance, address the challenges that could lead to unreliable performance is required. One and most crucial key challenge is routing information from a sender to receiver. Due to the characteristics of a disaster environment such as signal attenuation, communication links exist between rescue crew is short-lived, suffer from frequent route breakage, and may result in unreliable end-to-end services. Many routing protocols have been proposed and evaluated in different network environments. This paper presents the basic taxonomy of Mobile Ad Hoc Networks and the state of the art in routing categorizes (Proactive, Reactive, Geographic-aware and Delay tolerant Networks (DTN)). The comparison of existing routing protocols in Mobile Ad-Hoc Networks indicates that overhead in Proactive and Geographic is competitive with delay in Reactive and DTN routing.

DTNB: A Blockchain Transaction Framework With Discrete Token Negotiation for the Delay Tolerant Network

The current blockchain deployment solutions rely on a continuous connectivity network. Unfortunately, the delay tolerant network does not meet this condition. Therefore, we construct a novel blockchain transaction framework with discrete token negotiation called DTNB, which can be deployed on the delay tolerant network to provide transaction services. Specifically, we present the structure of add-chains by modifying the existing block structure. Then, we design a mining qualification determining scheme to achieve fair transactions, including discrete token generation algorithm and mining qualification attribution algorithm, and this scheme avoids the problem that nodes with more stakes in the PoS and DPoS algorithms can obtain mining qualifications with a higher probability. Furthermore, we present two mining schemes and also design a fork processing algorithm, which ensures that blocks on the add-chain generated by the local network can be appended to the main chain with the equal probability. Finally, we design the second consensus algorithm to avoid the problem of false and repeated transactions of the blocks on the add-chains in the local network. Theoretical analysis shows three properties of DTNB, including safety, reliability and activeness, and the experimental simulations demonstrate DTNB has advantages in throughput, block generation time and fork rate.

Prevention of Cardiac Surgery-Associated Acute Kidney Injury by Implementing the KDIGO Guidelines in High-Risk Patients Identified by Biomarkers: The PrevAKI-Multicenter Randomized Controlled Trial.

Prospective, single-center trials have shown that the implementation of the Kidney Disease: Improving Global Outcomes (KDIGO) recommendations in high-risk patients significantly reduced the development of acute kidney injury (AKI) after surgery. We sought to evaluate the feasibility of implementing a bundle of supportive measures based on the KDIGO guideline in high-risk patients undergoing cardiac surgery in a multicenter setting in preparation for a large definitive trial. In this multicenter, multinational, randomized controlled trial, we examined the adherence to the KDIGO bundle consisting of optimization of volume status and hemodynamics, functional hemodynamic monitoring, avoidance of nephrotoxic drugs, and prevention of hyperglycemia in high-risk patients identified by the urinary biomarkers tissue inhibitor of metalloproteinases-2 [TIMP-2] and insulin growth factor-binding protein 7 [IGFBP7] after cardiac surgery. The primary end point was the adherence to the bundle protocol and was evaluated by the percentage of compliant patients with a 95% confidence interval (CI) according to Clopper-Pearson. Secondary end points included the development and severity of AKI. In total, 278 patients were included in the final analysis. In the intervention group, 65.4% of patients received the complete bundle as compared to 4.2% in the control group (absolute risk reduction [ARR] 61.2 [95% CI, 52.6-69.9]; P < .001). AKI rates were statistically not different in both groups (46.3% intervention versus 41.5% control group; ARR -4.8% [95% CI, -16.4 to 6.9]; P = .423). However, the occurrence of moderate and severe AKI was significantly lower in the intervention group as compared to the control group (14.0% vs 23.9%; ARR 10.0% [95% CI, 0.9-19.1]; P = .034). There were no significant effects on other specified secondary outcomes. Implementation of a KDIGO-derived treatment bundle is feasible in a multinational setting. Furthermore, moderate to severe AKI was significantly reduced in the intervention group.

An energy-saving video compression targeting face recognition of disaster victim

In this paper, we propose an energy-saving video compression scheme targeting to work over an IoT network where the perception layer is implemented through smartphone-based delay-tolerant network (DTN). Here, the inter-frame compression is done by a proposed progression-based frame prediction technique and a newly introduced frame-similarity measurement parameter. The inter-frame co-relation is removed by using progression method followed by identifying similarity of the frames selected by the progression method. On the other hand, the intra-frame compression is done by adopting an existing compression technique with suitable modification to make it more energy saving over its existing counterpart. Once the compressed video is transmitted over the IoT network, at the server side it is reconstructed where we use the service of a popular online face recognition API, KAIROS considering an application of disaster victim recognition. The comparative performance of the scheme is evaluated both theoretically and through ONE simulator-based simulation. Precisely, we claim that our scheme saves on average 71.46% energy over its competitors with least memory usage and acceptable reconstruction quality. Finally, the entire scheme is evaluated through testbed implementation and shown that it can recognize faces successfully from the videos transmitted over DTN-based IoT with accuracy more than 0.96 while keeping compression ratio at more than 31.

Spatial Correlation Based Clustering with Node Energy Based Multi-Hop Routing Scheme for Wireless Sensor Networks

Major points of concern in implementing a wireless sensor network (WSN) are the network lifetime and energy utility within any delay tolerant network. Both these parameters define the success of the sensor network. The higher the expectancy of network Lifetime, the higher is the probability of acceptance of the network. Similarly, better the energy utilization in the network, better are the chances of success and implementation of the sensor network. Clustering is one such scheme adopted in WSN towards harnessing the best of above specified parameters for the network implemented. Most popular clustering techniques are the variants of LEACH protocol that facilitate cluster formation based on the proximity of an individual node to other nodes in the sensor network. These protocols are based on a single hop structure from the selected cluster heads in the network. This paper embarks on a multi-hop clustering algorithm that takes into consideration the spatial correlation between the nodes to form clusters and implements a highly energy efficient routing scheme which selects the multi-hop path in the network in a dynamic fashion.

A blockchain-based secure routing protocol for opportunistic networks

Opportunistic Delay Tolerant Networks also referred to as Opportunistic Networks (OppNets) are composed of wireless hosts opportunistically communicating with each other. These networks are designed to operate without the guaranteed existence of a path between the sender and the receiver. Inadequate data security in OppNets has been seriously detrimental to its adoption. This paper explores a secure and decentralized approach that uses the Proof-of-Work (PoW) consensus mechanism and propose a blockchain-based secure routing protocol (called BDRP). In this work, we design an integrated routing protocol that uses Proof-of-Work (PoW) for routing and demonstrates how immutability can be applied to the OppNet paradigm. Blockchain promises transparent, distributed, and tamper-resistant ledger and secure systems that may provide secure routing solutions for OppNets. We aim to study how effectively can Proof-of-Work (PoW) scale-up in OppNets as a consensus mechanism is the most resource and time-intensive component of a blockchain. The work even displays the ways this routing method prevents against attacks such as eavesdropping, masquerading, wormhole, blackhole, and fabrication. The simulation results, along with the theoretical justification, show how the proposed BDRP fares among the existing security policies are used in opportunistic networks.

An Efficient Routing Protocol with Overload Control for Group Mobility in Delay-Tolerant Networking

In delay-tolerant networking (DTN), messages are delivered to destination nodes by using opportunistic contacts between contact nodes, even if stable routing paths from source nodes to destination nodes do not exist. In some DTN network environments, such as military networks, nodes movement follows a group movement model, and an efficient DTN routing protocol is required to use the characteristics of group mobility. In this paper, we consider a network environment, where both intra- and intergroup routing are carried out by using DTN protocols. Then, we propose an efficient routing protocol with overload control for group mobility, where delivery predictability for group mobility is defined and proactive overload control is applied. Performance evaluation results show that the proposed protocol had better delivery ratios and overhead ratios than compared protocols, although the delivery latency was increased.

DTN-Balance: A Forwarding-Capacity and Forwarding-Queue Aware Routing for Self-organizing DTNs

In delay-tolerant networks (DTNs), intermittent network connectivity and lack of global system information pose serious challenges to achieve effective data forwarding. Most state-of-the-art DTN routing algorithms are based on hill-climbing heuristics in order to select the best available next hop to achieve satisfactory network throughput and routing efficiency. An adverse consequence of this approach is that a small subset of good users take on most of the forwarding tasks. This can quickly deplete scarce resources (e.g. storage, battery, etc.) in heavily utilized devices which degrades the network reliability. A system with a significant amount of traffic carried by a small number of users is not robust to denial of service attacks and random failures. To overcome these deficiencies, this paper proposes a new routing algorithm, DTN-Balance, that takes the forwarding capacity and forwarding queue of the relay nodes into account to achieve a better load distribution in the network. For this, we defined a new routing metric called message forwarding utility combining nodal available bandwidth and forwarding workload. Applying small world theory, we impose an upper bound on the end-to-end hop count that results in a sharp increase in routing efficiency. Queued messages in a forwarding node are arranged by DTN-Balance based on message dropping utility metric for a more intelligent decision in the case of a message drop. The performance of our method is compared with that of the existing algorithms by simulations on real DTN traces. The results show that our algorithm provides outstanding forward efficiency at the expense of a small drop in the throughput.

An adaptive multiple spray-and-wait routing algorithm based on social circles in delay tolerant networks

In delay tolerant networks (DTN), the social attributes of nodes show long-term stability, which can be leveraged for more effective routing. In this paper, we first present a novel way of constructing social circles based on the node clustering phenomena in DTN. Then, considering that the forwarding capability of nodes is significantly different, we propose a spray strategy based on social circles (named SC-SS) to improve the spray-and-wait routing algorithm. SC-SS selects the next hop based on the social circle of nodes in the spray phase. Instead of fixing the initial number of copies, we design an adaptive multiple spray-and-wait routing algorithm based on social circles (named SC-AMSW) to further improve the performance of SC-SS. SC-AMSW selectively sprays messages multiple times in the wait phase and determines an appropriate number of redundant message copies based on delivery predictability. We conduct extensive simulations to confirm the effectiveness of our proposed routing algorithms in DTN.

Interrupted time series analysis of the impact of a bundle on surgical site infections after colon surgery

Surgical site infections (SSIs) are monitored in Italy through a national surveillance system. A 4-element bundle was introduced in 2012, consisting of: appropriate preoperative shower and hair removal, perioperative normothermia, and antibiotic prophylaxis. The aim of this study was to evaluate the effect of the intervention on SSI rates after colon surgery. A retrospective cohort study was conducted between 2008 and 2019 in 29 hospitals of northern Italy. An interrupted time series analysis (ITSA) was modeled to assess the bundle's impact on SSI trends. Logistic regression was performed to identify predictors of SSI among procedures performed in the postintervention period, comparing full and partial bundle compliance. Data of 5487 colon surgery procedures were collected (1243 preintervention and 4244 postintervention). The ITSA identified a significant change in the monthly postintervention SSI trend of -0.19% and a change in level of -2.09%. A significant protective effect of full bundle compliance compared to partial bundle compliance (OR 0.74, P.043) was found, whereas the single effect of the bundle elements was nonsignificant. Results of this study suggest this relatively simple bundle protocol is effective in reducing SSI risk.

Efficient forwarding strategy in HDRP protocol based Internet of Things

The Internet of Things (IoT) includes a variety of heterogeneous wireless network technologies such as Delay Tolerant Networks (DTN) and all kinds of smart devices connected over a wireless network. The strong size and cost constraints of DTN nodes lead to corresponding constraints on resources such as energy, memory, communication speed and bandwidth, which in turn limits the contact between DTN nodes. DTN has emerged as a promising new network paradigm that aims to cope with the increasing number of heterogeneous networks and the need for efficient and robust data dissemination to be more stable. But one of the hindering bottlenecks the full applicability of such a DTN-based approach to the IoT, is that forwarding data in an environment could lose when the connection between nodes is intermittent. In this paper, we propose an effective bundle forwarding strategy for the IoT environment in which we control the number of bundle replications to balance energy consumption on the network. Simulation results demonstrate that the proposed solution performs better than other methods in terms of delivery delay and delivery rate (roughly 18% improvement).