Delay Tolerant Networks Research Articles

An improved multipath video data communication in a vehicular delay-tolerant network.

A vehicular network offers diverse beneficial services related to video streaming in different types of setups, including rural and urban. Some of the recent issues in vehicular communication include prospect of leveraging machine learning and blockchain for privacy and security enhancement, and resource allocation for video streaming coupled with integration of 6G networks for high data rate. Considering the extreme mobility and dynamic structure of vehicular networks and the high data rates of video streams, a unitary route may not support the required quality of a video stream. To achieve load balancing, connectivity among vehicles, path diversity, and low delay, the multipath transmission with a delay-tolerant network (DTN) concept based on a node disjoint algorithm is considered. In this proposed study, video frames are categorized in accordance with priority and forwarded via two graded paths. The first path carries the video reference frame, which is the most important frame for video decoding. The second path carries neighboring frames during video transmission. For the efficient selection of an optimal relay vehicle, a communication cost function is introduced into the existing DTN. This communication cost function is based on three key enhancement parameters: link stability rate, accessible bandwidth estimation, and transmission delay. The improvement in this study, is the integration of store-carry-forward strategy to the existing multipath data forwarding strategy. On the basis of the simulation outcomes, the proposed multipath video data communication in a vehicular DTN (MVDTN) scheme can enhance video data delivery in terms of packet loss ratio, end-to-end delay, structural similarity index measure, and peak signal-to-noise ratio. Considering the aforementioned metrics, our proposed schemes outperform the baseline schemes, namely, road-based multi-metrics forwarder selection evaluation for multipath video streaming and quality of service-aware multipath video streaming for an urban vehicular ad hoc network by using ant colony optimization.

Enhancing the Communication of IoT Using African Buffalo Delay Tolerant and Risk Packet Jump Approach

The Internet of Things is used in many sectors for different applications in an efficient way. However, sharing huge data to distant destinations is a difficult task such as sending large data from remote area for healthcare application. So that the Delay Tolerant Network is used but, in some cases, the presence of selfish nodes in Delay Tolerant Network may drop all the packets. To overcome this problem the current research affords a novel African Buffalo Delay Tolerant Network with Risk Packet Jump (ABDTN –RPJ) mechanism to improve the communication channel by predicting the selfish and misbehavior node in an earlier stage. Besides, RPJ is introduced to split the huge data to the other neighboring nodes to reduce packet load on the node if the load is greater than the capacity of the node. Finally, the ABDTN –RPJ is implemented and evaluated using the NS2 simulator. The comparison results proved the efficiency of the proposed model by reducing the delay and drop rate.

ReliefChain: A blockchain leveraged post disaster relief allocation system over smartphone-based DTN.

One of the major concerns in any emergency relief operation is appropriate allocation of scarce emergency relief materials to the affected community. Due to several reasons ranging from lack of mechanism to accurately assess demand and utility of relief materials to malicious participation of some of the stakeholders, such allocation may become ad-hoc. Thus, it becomes imperative to have an unchallengeable and globally accessible record of relief requirement vis-à-vis allocation for efficient relief management. Emergency response organizations (e.g. UNICEF) have recommended the adoption of blockchain technology to create such immutable records. However, the usage of blockchain is restricted by the availability of end-to-end internet connection which may not be available in a post-disaster scenario. This paper proposes ReliefChain, a blockchain leveraged post disaster relief allocation system over delay tolerant network that works in such environments. We validate relief requirements to mitigate resource diversion, forecasting the exact demand and enumerating precise utilities of relief items. We design smart contracts for creating new transactions to upload relief requirements and allocations in the blockchain network. The proposed system executes these smart contracts to create an immutable and globally accessible record of relief requirement and allocation. Effectiveness of the proposed system is evaluated through extensive simulation in Ethereum platform. Results substantiate the efficiency of the system over a system using baseline methodologies, in terms of design parameters like shelter specific deficit and average resource deficit while not compromising the blockchain performance in terms of processing time and gas consumption even in presence of malicious forwarders.

Effect of Designed Bundle Protocol about Ventilator Associated Pneumonia on Nurses' Performance, Compliance, and Patient Outcomes

Context: Ventilator-associated pneumonia (VAP) is considered one of the leading causes of morbidity and mortality due to nosocomial infections among ventilated patients.
 Aim: To evaluate the effect of a designed bundle protocol about ventilator-associated pneumonia on nurses' performance, compliance, and patient outcomes.
 Methods: The study employed the quasi-experimental research (pre/post-test) (study/control) design. This study was conducted at the intensive care unit of Benha University Hospital. A convenience sample of 50 critical care nurses and a purposive sample of 66 patients were enrolled in the current study. Three tools were used to collect data. Nurses' knowledge assessment questionnaire; nurses' practice assessment checklist; The VAP bundle compliance checklist; and patient outcomes assessment record.
 Results: Statistically significant improvement in total knowledge and practice mean scores post implementing a designed bundle protocol compared to pre-implementing a designed bundle protocol at p <0.001. Also, there was a statistically significant improvement in nurses’ compliance with a highly statistically significant difference between nurses’ compliance with practices of VAP bundle pre-and post designed bundle protocol implementation. Immediately after a designed bundle protocol implementation, the study group patients exhibited a statistically significant difference between all clinical pulmonary infection score items except for oxygenation status and radiographic findings.
 Conclusion: The study group nurses who received designed bundle protocol training would get improved knowledge, practices, and compliance scores than pre-designed bundle protocol training. Also, the study group of patients who were cared for by trained nurses on the designed bundle protocol would get better outcomes such as a better score of CPIS, shorter length of stay in the intensive care unit, less duration on mechanical ventilation compared to the control group who received routine hospital nursing care. The study recommended replication of the study using a large probability sample from a different geographical area to allow for greater generalization of the results.

Misbehavior of nodes in IoT based vehicular delay tolerant networks VDTNs

Misbehavior of nodes in IoT based vehicular delay tolerant networks VDTNs

A probabilistic routing algorithm based on node communication capability and message strength

SummaryIn delay‐tolerant networks (DTN), node connection time and message transmission time are two important influencing factors that can improve the delivery rate. In this paper, we first define a new concept called communication capability (CC) and then apply this concept to the delivery predictability formulation in Prophet and improve it. Then, in Prophet, the selection of relay nodes relies only on the delivery predictability and ignores the caching and forwarding capability of the node. Therefore, we combine delivery predictability, buffering, and forwarding capability to develop a new adaptive relay node selection strategy. Subsequently, we define two metrics called message priority (MP) and message strength (MS). The node forwards messages sequentially based on message priority and discards messages based on message strength. Finally, we present a probabilistic routing algorithm based on node communication capability and message strength (CAMS). The simulation results show that compared with traditional routing algorithms, the CAMS can effectively improve the message delivery rate, reduce the overhead ratio, and keep average hop counts low.

Average Operation Time of Bundle Protocol in Delay/Disruption-Tolerant Networks

Performance analysis of the Bundle Protocol (BP) in Delay/ disruption-Tolerant Networks (DTN) has gained much interest. The analytic work of the average operation time (AOT) in BP, for different channel conditions and system parameters, though critical to understanding performance and designing system, is still incomplete. Existing results, such as the average file delivery time (AFDT), provide reasonably close estimates in some cases but exhibit large discrepancies in other cases. In this paper, we provide a holistic probabilistic analysis of the BP process, particularly in the number of error bundles and the position of the last error bundle in each and the last rounds of transmission. We provide, for the first time, an exact solution for the AOT of the BP process. The derivation works for both symmetric and asymmetric channels and is in general for any given maximum number of transmissions rounds. When the unlimited number of transmission rounds is considered, AOT becomes AFDT. The results are further utilized to select the optimal bundle size that gives the minimum file delivery time. Validation via simulations and comparison with existing work are also provided.

Performance modeling of Licklider transmission protocol (LTP) via proactive transmission of signaling segments in deep‐space network

SummaryDelay‐tolerant networking (DTN) bundle protocol is considered one of the best transmission protocols to be used in space communications by NASA. There are studies that evaluated the performance, measuring the total transfer time of a complete file from sender to receiver, of the DTN protocol via simulation or emulated experiments beyond the real space‐based experiences. In addition, there is a very few additional research works available for the modeling of the Licklider transmission protocol (LTP). However, these past studies on LTP modeling are implemented as a Logarithmic approach that is based on the calculation of loss segments in file delivery. In this work, the approach is investigated in a different manner. Specifically, the performance model was created based on the probability of the segment's successful delivery on the LTP. Moreover, the original model is enhanced via introducing a burst of transfer and equal interval distribution of signaling segments, specifically check point (CP), along with the retransmission time out (RTO). The results from the developed model for the original DTN protocol and enhanced versions align with the results obtained by PC‐based testbeds.

A context-aware improved POR protocol for Delay Tolerant networks

ABSTRACT The intermittent network connectivity and unawareness of global network knowledge are remarkable challenges when designing efficient Position-based Opportunistic Routing (POR) for Delay Tolerant Networks (DTNs). The best progress set selection of POR effectively handles the intermittent connectivity issue and improves the reliable performance of DTNs. Hence, the optimal progress set selection and catching capacity decide the routing reliability of DTN-POR. This paper proposes a context-aware DTN-POR protocol STAP to ensure reliable DTN routing with minimum overhead STAP design is divided into three folds: application diversity and network failures, context-aware best progress set selection, and enhanced caching management. The application diversity and network failure switch the nodes in harsh environments to DTN mode for transmitting the data packets successfully to the destination. Selecting context-aware relay nodes ensures highly successful data transmissions in the absence of end-to-end connectivity. The probability estimation maximizes the data reachability by considering unique node and application-level context attributes in the best progressive set. Finally, the enhanced catching management strategy limits the number of data copies with effective catch invalidation, resulting in minimum overhead. The proposed STAP accomplishes better results in different scenarios and improves the packet delivery ratio with a minimum duplication rate.

Adaptive secured position based routing protocol for efficient data transmission in Vehicular Adhoc network

Variable number of cars equipped with radio devices allow the driver to exchange messages seamlessly across the network, no matter where they are in relation to each other. Inter-vehicle video transmission is an important feature of the VANET. Foreseeing the development of commercial service, video streaming appears to be a practical answer to a number of expected services. For data transmission in vehicular ad hoc networks, this study examines non-delay-tolerant and delay-tolerant network protocols, respectively.Different performance metric criteria like Packet Loss ratio, Number of Packet delivered, Route Length are evaluated.

A Survey of Implementation of ABCDE Protocols.

Spontaneous awakening trials (SATs), spontaneous breathing trials (SBTs), delirium assessment/management, early mobility have been termed the ABCDE bundle. The ABCDE bundle has been proven to improve patient outcomes. However, there is often a long gap in dissemination and implementation of evidence-based medicine. To determine the prevalent implementation of and determinants for ABCDE protocol adoption in Pennsylvania. We developed a survey of ABCDE bundle protocols. We surveyed factors around implementation including written protocol presence, standardized assessments to guide protocols, timing of creation of protocols, and estimated adherence to protocols. We also collected data on factors that might be determinants for protocol adoption including ICU staffing models, hospital and ICU level factors. We validated the survey tool using the Michigan Health and Hospital Association Keystone ICU collaborative. We then administered the validated survey to a leader of the medical ICU or mixed medical-surgical ICU of all Pennsylvania Hospitals. Multivariable logistic and ordinal regression were used to determine associations between ICU staffing models and hospital and ICU level factors with the presence of ABCDE bundle protocols. In the study cohort of Pennsylvania ICUs (n = 144), we had 100 respondents (69% response). The median number of hospital beds among the respondents was 185 (IQR 111-355) with a median of 14 ICU beds (IQR 10-20). 86% reported spontaneous awakening trial protocols, 60% reported spontaneous breathing trial protocols, 43% reported delirium assessment/management protocols, and 27% reported early mobility protocols. Being a medical ICU compared to a mixed medical-surgical ICU (OR 3.48, 95% CI 1.19-10.21, P = .02) and presence of multidisciplinary rounds (OR 4.97, 95% CI 2.07-11.94, P < .001) were associated with increasing number of ABCDE bundle protocol components. Variable implementation of ABCDE bundle protocols was present across Pennsylvania. Team communication is important to implementation of these protocols.

Selfish Node Detection by Modularized Deep NMF Autoencoder Based Incentivized Reputation Scheme

Delay tolerant network is a boon in emergency fields like flood and war zones. The data gathered by the sensor nodes is transmitted whenever any aggregator node comes in contact with those stationary sensor nodes. However, few nodes can behave differently and don't transmit the information. These nodes which don't take part in communication to preserve it's battery or are compromised are selfish nodes and have to be identified to avoid communication disruption. This article discusses the selfish node's detection schemes and proposes a novel hybrid scheme. Most of the recent schemes work with on node's reputation or incentives if it takes part in communication. This paper has proposed an incentivized reputation scheme that first clusters the nodes using their social features, calculates the weighted social tie as their social connection strength and updates the weighted social tie by applying reward or penalty. The incentive is offered if residual energy and packet delay has a tradeoff or are penalized. A new modularized deep nonnegative matrix deep autoencoder is developed to calculate the reputation of nodes using social features and named IRU-mDANMF (incentivized reputation update by modularized DANMF). The scheme has been experimented with in several scenarios and is performing significantly better than state-of-the-art schemes.

Enhanced UAV-aided vehicular delay tolerant network (VDTN) routing for urban environment using a bio-inspired approach

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.

A Probabilistic Spray-and-Wait Routing Algorithm Based on Node Interest Preference in Delay Tolerant Networks

How to select proper relay nodes to ensure the successful delivery of messages is still a hot topic in delay tolerant networks (DTN). In this paper, we propose a probabilistic Spray-and-Wait routing algorithm based on node interest preference (called NIP-PSW). Firstly, considering the influence of the social attributes of nodes, we define a metric called node interest preference (NIP) to measure the probability of nodes becoming friends. Secondly, in view of the influence of node quality and connection time between nodes on message forwarding, we define the delivery probability (DP). Finally, according to the historical information of nodes, the node interest similarity (NIS) is proposed. In spray phase, NIP and DP are used to select the relay node and allocate the number of message copies adaptively. In wait phase, it is judged whether to forward the message to the encountering nodes again according to the NIS and the DP. In addition, the concept of message storage value (MSV) and the acknowledgment (ACK) mechanism are introduced to manage the buffer of nodes. The simulation results show that the NIP-PSW not only can significantly improve the delivery rate and reduce the average delay but also shows good performance in network overhead and average number of hops.

Compliance with SEP-1 guidelines is associated with improved outcomes for septic shock but not for severe sepsis

BackgroundIn 2018, the Centers for Medicaid and Medicare Services (CMS) issued a protocol for the treatment of sepsis. This bundle protocol, titled SEP-1 is a multicomponent 3 h and 6 h resuscitation treatment for patients with the diagnosis of either severe sepsis or septic shock. The SEP-1 bundle includes antibiotic administration, fluid bolus, blood cultures, lactate measurement, vasopressors for fluid-refractory hypotension, and a reevaluation of volume status. We performed a retrospective analysis of patients diagnosed with either severe sepsis or septic shock comparing mortality outcomes based on compliance with the updated SEP-1 bundle at a rural community hospital. MethodsMortality outcome and readmission data were extracted from an electronic medical records database from January 1, 2019, to June 30, 2020. International Classification of Diseases (ICD)-10 codes were used to identify patients with either severe sepsis or septic shock. Once identified, patients were separated into four populations: patients with severe sepsis who met SEP-1, patients with severe sepsis who failed SEP-1, patients with septic shock who met SEP-1, and patients with septic shock who failed SEP-1. A patient who met bundle criteria (SEP-1 criteria) received each component of the bundle in the time allotted. Using chi-squared test of homogeneity, mortality outcomes for population proportions were investigated. Two sample proportion summary hypothesis test and 95% confidence intervals (CI) determined significance in mortality outcomes. ResultsOut of our 1122 patient population, 437 patients qualified to be measured by CMS criteria. Of the 437 patients, 195 met the treatment bundle and 242 failed the treatment bundle. Upon comparing the two groups, we found the probable difference in mortality rate between the met(14.87%) and failed bundle(27.69%) groups to be significant(95% CI: 5.28–20.34, P=0.0013). However, the driving force of this result lies in the subgroup of patients with severe sepsis with septic shock, which show a higher mortality rate compared to the subgroup with just severe sepsis. The difference was within the range of 3.31% to 29.71%. ConclusionThis study shows that with septic shock obtained a benefit, decreased mortality, when the SEP-1 bundle was met. However, meeting the SEP-1 bundle had no benefit for patients who had the diagnosis of severe sepsis alone. The significant difference in mortality, found between the met and failed bundle groups, is primarily due to the number of patients with septic shock, and whether or not those patients with septic shock met or failed the bundle.

Reliable data exchange in vehicular delay tolerant networks using AI‐based hybrid trust management

SummaryVehicular delay‐tolerant networks (VDTNs) play prominent part in smart transportation and smart city paradigm to diminish the drivers' risk to meet accidents and offer many infotainment and entertainment services. All the operations are carried out by exchanging data among nodes. However, due to open communication nature of VDTN, the data broadcasted by mobile nodes are quiet susceptible to security attacks. Recently, a number of protocols are proposed for open communication. However, securing such communications and establishing trust value among vehicles are major addressable issues. This is because the existing fraudulent peers can lead to catastrophic circumstances on roads. Along with securing the data carriers, the authenticity and reliability of data is also equally important. In order to identify reliable nodes and maintaining the authenticity of data being communicated, a new artificial intelligence (AI)‐based hybrid trust management framework is proposed in this article. The study particularly exploits the proximity‐based k‐nearest neighbour (kNN) classification model for selecting controlling nodes. Further, decision stump is employed to accomplish trust estimation rules, and backpropagation is used to self‐train the mobile nodes, whenever anticipated trust value is not attained. The proposed scheme maintains the integrity of vehicular nodes and efficiently handles the specified. The trust framework uses a multifaceted direct and recommended trust estimation approach to calculate the global trust values. For comparison, the performance of the proposed method was compared with other trust management approaches.

An Analytical Framework for Disruption of Licklider Transmission Protocol in Mars Communications

As one of the main data transport protocols of delay&#x002F;disruption-tolerant networking (DTN), Licklider transmission protocol (LTP) is designed to provide reliable data delivery in an interplanetary Internet environment characterized by frequent and lengthy link disruptions and extremely long signal propagation delays. Some studies have been done on the performance of LTP in cislunar and Mars communications. However, to date the effect of link disruption on LTP for Mars communications has received little attention. In this paper, an analytical framework is presented for the effect of link disruption on reliable data delivery and performance of LTP in Mars communications. The analysis focuses on how various link disruptions affect the number of transmission attempts, the consequent round-trip time (RTT) of data exchange, and the resulting goodput performance of LTP for reliable data block delivery in Mars communications. The analytical framework is validated by means of realistic data block transmission experiments using a PC-based experimental infrastructure, and it can be used to predict the performance of LTP over a deep-space vehicle communication channel in presence of link disruption.

A New Variant of Game Theory Based Decision Making (GTDM) Algorithm Routing Protocols to Improve Energy Efficiency on Vehicular Delay Tolerant Network (VDTN)

These days, the application of Delay Tolerant Networks (DTN) have been expanded into various scenarios of communications field. Vehicular Ad hoc Networks (VANETs) as a communication scenario which treat its subject to disruption and disconnection with frequent partitioning and high latency. Therefore, Vehicular Delay Tolerant Network (VDTN) is introduced as a new research paradigm due to several characteristics match according to specific prerequisites. DTNs is proposed in Vehicular Network because its mechanisms which is using store-carry-forward, can be implemented to deliver the packets, without end-to-end connection, to the destination. One of challenging research of DTN in routing protocol is to meet prerequisites of many applications, especially in vehicular network (VDTN). This paper presents a new variant of Game Theory based on Decision Making (GTDM) that can deliver packet to static node due to improve the energy efficiency of DTNs in city environments. Hence, its destination node (Receiver Node) needs to go to the static node to take their packet under Working Day Movement (WDM), because relay node will be passing by the static node with continuously move to its track to deliver packet. In this paper author will analyze the new variant of GTDM (NVGTDM) which can be more useful than original GTDM for application in city environment with using transportation movement. We conclude that modification of GTDM routing algorithm (NVGTDM) improves energy efficiency as much as 10.38% than the original GTDM. Hence, it can be ensured to compare either to Epidemic or PRoPHET routing algorithm with 55.44% and 68.75% in rates of energy efficiency respectively.

CALAR: Community Aware Location Assisted Routing Framework for Delay Tolerant Networks

Infrastructure less communication strategies havegreatly evolved and found its way to most of our real lifeapplications like sensor networks, terrestrial communications,military communications etc. The communication pattern for allthese scenarios being identical i.e. encounter basedcommunication,characteristics of each communication domainare distinct. Hence the protocols applied for each environmentshould be defined carefully by considering its owncommunication patterns. While designing a routing protocol themain aspects under consideration include delay, connectivity,cost etc. In case of applications having limited connectivity,concept of Delay tolerant network (DTN) is deployed, whichassists delivering messages even in partitioned networks withlimited connectivity by using store and forward architecture.Node properties like contact duration, inter contact duration,location, community, direction of movement, angle of contact etc.were used for designing different classes of routing protocols forDTN. This paper introduces a new protocol that exploits thefeatures of both community based as well as location basedrouting protocols to achieve higher data delivery ratio invehicular scenarios. Results obtained show that proposedalgorithms have much improved delivery ratio comparedtoexisting routing algorithms which use any one of the aboveproperty individually.

Optimal Cluster Head in DTN Routing Hierarchical Topology (DRHT)

In delay tolerant networking (DTN), nodes are autonomous and behave in an unpredictable way. Consequently, a control mechanism of topology is necessary. This mechanism should ensure the overall connectivity of the network taking into account nodes’ mobility. In this paper, we study the problem of data routing with an optimal delay in the bundle layer, by exploiting: the clustering, the messages ferries and the optimal election of cluster head (CH). We first introduce the DTN routing hierarchical topology (DRHT) which incorporates these three factors into the routing metric. We propose an optimal approach to elect a CH based on four criteria: the residual energy, the intra-cluster distance, the node degree and the head count of probable CHs. We proceed then to model a Markov decision process (MDP) to decide the optimal moment for sending data in order to ensure a higher delivery rate within a reasonable delay. At the end, we present the simulation results demonstrating the effectiveness of the DRHT. Our simulation shows that while using the DRHT which is based on the optimal election of CH, the traffic control during the TTL interval (Time To Live) is balanced, which greatly increases the delivery rate of bundles and decreases the loss rate.