Efficient Data Dissemination Research Articles

Optimal path for data dissemination in Vehicular Ad Hoc Networks using meta-heuristic

The optimal path problem can be considered as a type of discrete optimization, which enables reliable and QoS-aware data dissemination in Vehicular Ad Hoc Networks (VANETs). The optimal path is of great importance in vehicular communication due to frequently disconnected network, dynamic topology, and limited bandwidth of wireless interface. In this paper, multi-valued Discrete Particle Swarm Optimization (DPSO), including encoding and decoding phase, is used to optimize the process of identification of an optimal path for efficient data dissemination in VANETs. The proposed algorithm includes link stability calculated by Euclidean distance in the polar coordinate system and the probability of occurrence of obstacles as objective. Extensive simulations are utilized to analyze the effectiveness of the proposed technique on the metrics such as packet delivery ratio, average throughput, and routing overhead. The results obtained demonstrate that the proposed algorithm is better than the other related schemes in the existing literature.

Maximization of Data Dissemination in UAV-Supported Internet of Things

Leveraging unmanned aerial vehicles (UAV) to enable flexible and efficient mobile data dissemination is a promising solution for infrastructure-less Internet of Things (IoT) applications. In this letter, we seek to maximize the amount of UAV-assisted data dissemination among spatially dispersed IoT devices by jointly optimizing the resource assignment strategy and UAV’s mobility in the three dimensional space. Firstly, we formulate the problem of UAV-supported data dissemination as a non-convex optimization, which subjects to minimum data requirement of each IoT device, practical mobility constraints and energy budget of the UAV. Then, we develop an efficient algorithm by tailoring the framework of alternating descent and concave-convex procedure. Simulation results demonstrate the superior performance of the proposed algorithm compared with the benchmark schemes.

Cooperative Data Dissemination in Air-Ground Integrated Networks

By incorporating unmanned aerial vehicles (UAVs) into terrestrial system, the air-ground integrated networks are expected to take the advantage of each communication paradigm. In this letter, we consider data dissemination in air-ground integrated network that a ground base station and a UAV cooperatively serve mobile terminals (MTs). We aim to maximize the minimum received data amount of all MTs by optimizing multiuser scheduling and association, bandwidth allocation and UAV’s mobility, while ensuring UAV’s mobility constraints and energy budget. For the formulated mixed-integer non-convex programming, we develop an efficient cooperative data dissemination algorithm by tactfully handling the non-smooth objective function, binary variables and non-convex constraints. Moreover, simulation results show that the proposed algorithm notably outperforms benchmark schemes at different cases.

Two-Level Cluster Based Routing Scheme for 5G V2X Communication

Efficient data dissemination is a big challenge for both IEEE 802.11p (MAC contentions problem) and cellular vehicle-to-everything communications (limited bandwidth in the high dense network). In this paper, a two-level clustering scheme is proposed for efficient data dissemination in 5G V2X communications. In the proposed protocol, level-1 cluster heads (L1CHs) are selected by a fuzzy logic algorithm using three factors, i.e., relative velocity factor, ${k}$ -connectivity factor, and link reliability factor. The slide link vehicle-to-vehicle (V2V) or the Third Generation Partnership Project V2V overcomes the MAC contention problem in L1CHs selections. Next, the level-2 cluster heads are selected by an improved Q-learning aiming to reduce the number of iterations in the gateway selection to LTE base station. The proposed scheme is evaluated under different network conditions showing that our protocol achieves good results compared to the existing schemes.

Data dissemination on MANET by repeatedly transmission via CDN nodes

The efficient data dissemination in an infrastructure-less environment as MANET is the challenging issues. This paper proposes to adopt the CDN Technique for disseminating information in MANET. The source node disseminates data to surrounding nodes by repeatedly transmitting batches of packets. Our proposed is developed based on the OLSR. The CDN nodes are selected from MPRs to optimally cover all subscribers and to avoid the interference problem. The packets are transmitted to destination by using broadcasting technique. The performance is evaluated as probability of successful transmission by simulation using NS3, and compared with the pure OLSR and clustering-based data transmission algorithm in VANET. Our proposed improves the probability of successful transmission and achieves higher rate at high nodes' density when comparing with pure OLSR and clustering-based algorithm respectively. The closed-form mathematical expression of the probability of successful transmission of our proposed algorithm in multi-hop network environment is derived and verified.

An Efficient Interest-aware Data Dissemination Approach in Opportunistic Networks

Due to the high mobility of humans and resource limitation of smart mobile devices, the design of efficient data dissemination schemes faces great challenges in opportunistic networks (OppNets). The current data dissemination schemes generally concentrate on the similarity among nodes while ignoring the similarity between nodes and data packets, which leads to that data packets move back and forth among the nodes with similar social features instead of reaching to the subscribers directly. In this paper, an efficient interest-aware data dissemination (EIAD) approach is proposed, in which the similarity between nodes and data packets is used to determine whether a node is a potential destination. Moreover, both the social feature and the residual energy are considered to choose an appropriate relay node and then determine the number of packet’s replicas. Furthermore, the broadcast characteristic of wireless data transfer is exploited to reduce unnecessary transmissions and energy consumption. The evaluations towards a real-world dataset reveal that the proposed algorithm outperforms the existing results.

Data dissemination on MANET by repeatedly transmission via CDN nodes

The efficient data dissemination in an infrastructure-less environment as MANET is the challenging issues. This paper proposes to adopt the CDN Technique for disseminating information in MANET. The source node disseminates data to surrounding nodes by repeatedly transmitting batches of packets. Our proposed is developed based on the OLSR. The CDN nodes are selected from MPRs to optimally cover all subscribers and to avoid the interference problem. The packets are transmitted to destination by using broadcasting technique. The performance is evaluated as probability of successful transmission by simulation using NS3, and compared with the pure OLSR and clustering-based data transmission algorithm in VANET. Our proposed improves the probability of successful transmission and achieves higher rate at high nodes' density when comparing with pure OLSR and clustering-based algorithm respectively. The closed-form mathematical expression of the probability of successful transmission of our proposed algorithm in multi-hop network environment is derived and verified.

Efficient data dissemination approach for QoS enhancement in VANETs

Vehicular ad hoc networks (VANETs) have seen tremendous growth in the last decade, providing a vast range of applications in both military and civilian activities. However, such applications require heavy data packets to be shared on the same spectrum without the requirement of excessive radios. Thus, efficient approaches are required which can provide improved data dissemination along with the better quality of services (QoS) to allow heavy traffic to be easily shared between the vehicles. In this paper, an efficient data dissemination approach is proposed which not only improves the vehicle to vehicle connectivity but also improves the QoS between the source and the destination. The effectiveness of the proposed approach is demonstrated in terms of the significant gains attained in the parameters namely, end to end delay, packet delivery ratio, route acquisition time, throughput, and message dissemination rate in comparison with the existing approaches.

An Effective and Efficient Adaptive Probability Data Dissemination Protocol in VANET

Mobile network topology changes dynamically over time because of the high velocity of vehicles. Therefore, the concept of the data dissemination scheme in a VANET environment has become an issue of debate for many research scientists. The main purpose of VANET is to ensure passenger safety application by considering the critical emergency message. The design of the message dissemination protocol should take into consideration effective data dissemination to provide a high packet data ratio and low end-to-end delay by using network resources at a minimal level. In this paper, an effective and efficient adaptive probability data dissemination protocol (EEAPD) is proposed. EEAPD comprises a delay scheme and probabilistic approach. The redundancy ratio (r) metric is used to explain the correlation between road segments and vehicles’ density in rebroadcast probability decisions. The uniqueness of the EEAPD protocol comes from taking into account the number of road segments to decide which nodes are suitable for rebroadcasting the emergency message. The last road segment is considered in the transmission range because of the probability of it having small vehicle density. From simulation results, the proposed protocol provides a better high-packet delivery ratio and low-packet drop ratio by providing better use of the network resource within low end-to-end delay. This protocol is designed for only V2V communication by considering a beaconless strategy. the simulations in this study were conducted using Ns-3.26 and traffic simulator called “SUMO”.

Least fresh first cache replacement policy for NDN-based IoT networks

In-network caching in Named Data Networking (NDN) based Internet of Things (IoT) plays a central role for efficient data dissemination. Data cached throughout the network may quickly become obsolete as they are transient and frequently updated by their producers. As such, NDN-based IoT networks impose stringent requirement in terms of data freshness. While various cache replacement policies were proposed, none has considered the cache freshness requirement. In this paper, we introduce a novel cache replacement policy called Least Fresh First (LFF) integrating the cache freshness requirement. LFF evicts invalid cached contents based on time series forecasting of sensors future events. Extensive simulations are performed to evaluate the performance of LFF and to compare it to the different well-known cache replacement policies in ICN-based IoT networks. The obtained results show that LFF significantly improves data freshness compared to other policies, while enhancing the server hit reduction ratio, the hop reduction ratio and the response latency.

Energy-Aware Incentivized Data Dissemination via Wireless D2D Communications With Weighted Social Communities

Device-to-device (D2D) communications are featured by high energy efficiency and spectrum efficiency, which offers a promising technique for data dissemination over wireless networks. In this paper, we propose a novel solution that exploits D2D communications to enable efficient data dissemination over wireless networks. To distribute some messages to a target group of users, the base station first identifies the most influential users, called initial sources or seeds, and fulfills their requests. Then, these source devices forward their received messages to remaining users via D2D communications. To incentivize the sources in data forwarding, we propose a monetary auction-based mechanism and a moneyless matching-based mechanism, which can be activated depending on the practical application scenario. The monetary mechanism obtains the global optimal solution and achieves truthfulness, but it involves transfer of monetary rewards. In contrast, the moneyless mechanism enables a lightweight implementation, and it guarantees two-sided stability so that both sides of users in data forwarding are willing to accept the pairing result. To expedite data dissemination, we take advantage of social-awareness in a manner different from many existing approaches. We exploit weighted social relationships, which can be direct or indirect links between any two users in a connected community. To evaluate the performance of the proposed approaches, we develop novel schemes to generate and preprocess synthetic and real tracing datasets. Extensive simulation results with both synthetic and real tracing datasets demonstrate that our approaches achieve high utilities.

Efficient and Reliable Data Dissemination Approaches for VANET

Efficient and Reliable Data Dissemination Approaches for VANET

Efficient forwarding strategy in a NDN-based internet of things

The future internet will include a variety of heterogeneous wireless networks and all kinds of smart sensors connected over wireless links. The size and cost constraints on sensor nodes result in corresponding constraints on resources such as energy, memory, computational speed and communications bandwidth which in turn limits the processing and communication capabilities of the sensor nodes. Named data networking (NDN) emerged as a promising new routing mechanism aimed to cope with the increasing number of heterogeneous networks and the need for efficient and robust data dissemination. But, one of the bottlenecks that hinders the full applicability of such a NDN-based approach to the future internet is the energy requirements. In this study, we propose a novel geographic interest forwarding scheme where we add support for push-based traffic and different forwarding techniques designed to balance the energy consumption across the network. Our simulation results show that our proposed approach is more scalable and outperforms the alternative methods in term of data retrieval delay and overall energy consumption.

UAV-Assisted Data Dissemination in Delay-Constrained VANETs

Due to the high mobility of vehicles, the frequent path failures caused by dynamic network topology, and a variety of obstructions, efficient data dissemination with delay constraint in vehicular ad hoc networks (VANETs) is a challenging issue. To address these problems, a novel mobile relaying technique by employing unmanned aerial vehicles (UAVs) is considered to facilitate data dissemination in vehicular environments where the communication infrastructures are not available or the network connectivity is poor. This paper studies and formulates the throughput maximization problem in UAV-assisted VANETs, which aims to achieve high throughput while guarantee the delay constraint of data flows to the vehicles in the area. To maximize the network throughput, the maximization problem tries to find an optimal delivery strategy for data dissemination by optimizing the transmission rate. To solve the problem, the knapsack problem can be reduced to the maximization problem, which is proved NP-hard. A polynomial time approximation scheme is proposed to achieve an approximate solution. Detailed theoretical analysis including time complexity and approximation ratio of the proposed algorithm is presented. Simulation results demonstrate the effectiveness of the proposed algorithm.

An efficient data dissemination model for wireless sensor networks

In a wireless sensor network, one of the most important constraints on sensor nodes is their power source, which is a battery. Sensor nodes carry a limited and generally irreplaceable battery. When providing a routing protocol for WSNs, it is necessary to take the energy constraint of sensor nodes into consideration. In this paper, a new routing algorithm based on a mobile sink is proposed. In the proposed algorithm, data is forwarded from the sensor nodes to the sink, which moves on four determined paths, by using a virtual cellular structure. In this algorithm when the sink moves from one cell to another, the routing in the network can be updated with minimum energy consumption and delay. The simulation results show that the proposed algorithm is more efficient than similar ones.

A robust forwarding node selection mechanism for efficient communication in urban VANETs

In an urban VANET scenario, more number of obstacles like buildings or other roadside constructions are present. For these obstacles, the radio propagation may get affected which leads to poor network performance. To deal with this situation, a new approach is required which is primarily contingent on an obstacle avoidance algorithm, capable of finding the optimized shortest path, along with a potential forwarding vehicle selection strategy to route the packets efficiently. As a solution, this paper proposes a robust forwarding node selection mechanism for efficient communication between vehicles. For this, at first a path is selected avoiding the obstacles with the help of Delaunay Triangulation. Then that path is optimized by removing Torricelli points, priorly placed inside the Delaunay Triangulation. After that a forwarding zone is selected in that optimized shortest path. On that forwarding zone, a robust node is selected using fuzzy logic for efficient data dissemination. Extensive simulation results disclose that the proposed solution outperforms the present methods with respect to throughput, PDR, end-to-end delay and hop-count.

An Efficient and Energy-saving Data Dissemination Mechanism for Low-power and Lossy Networks

A low-power and lossy network (LLN) connects a huge amount of resource-constrained devices. These devices are limited in processing ability, memory, and power supply. With a view to performance, the Trickle timer algorithm was proposed to reduce control overhead of the routing protocol for LLNs, which aims to emphasize a high data transfer rate while consuming low power. In this paper, we propose an efficient and energy-saving data dissemination mechanism for LLNs to overcome the choke-point problem left over by the Trickle timer mechanism. A new parameter is introduced to indicate the neighbor density, and two modes are utilized to distinguish a node’s actions in silence or burst situations. If a node is detected inside a circle of updated nodes, it will enter silence mode to reduce broadcasting frequency. When a node is recognized on the border, it will enter burst mode to increase broadcasting frequency. Simulation results validate that our method outperforms the Trickle timer mechanism in terms of convergence time and energy consumption to disseminate data, especially in a dense LLN.

BiPAD: Binomial Point Process Based Energy-Aware Data Dissemination in Opportunistic D2D Networks

In opportunistic device-to-device (D2D) networks, the epidemic routing protocol can be used to optimize the message delivery ratio. However, it has the disadvantage that it causes excessive coverage overlaps and wastes energy in message transmissions because devices are more likely to receive duplicates from neighbors. We therefore propose an efficient data dissemination algorithm that can reduce undesired transmission overlap with little performance degradation in the message delivery ratio. The proposed algorithm allows devices further away than the k-th furthest distance from the source device to forward a message to their neighbors. These relay devices are determined by analysis based on a binomial point process (BPP). Using a set of intensive simulations, we present the resulting network performances with respect to the total number of received messages, the forwarding efficiency and the actual number of relays. In particular, we find the optimal number of relays to achieve almost the same message delivery ratio as the epidemic routing protocol for a given network deployment. Furthermore, the proposed algorithm can achieve almost the same message delivery ratio as the epidemic routing protocol while improving the forwarding efficiency by over 103% when k≥10.

Dissimilarity Metric Based on Local Neighboring Information and Genetic Programming for Data Dissemination in Vehicular Ad Hoc Networks (VANETs).

This paper presents a novel dissimilarity metric based on local neighboring information and a genetic programming approach for efficient data dissemination in Vehicular Ad Hoc Networks (VANETs). The primary aim of the dissimilarity metric is to replace the Euclidean distance in probabilistic data dissemination schemes, which use the relative Euclidean distance among vehicles to determine the retransmission probability. The novel dissimilarity metric is obtained by applying a metaheuristic genetic programming approach, which provides a formula that maximizes the Pearson Correlation Coefficient between the novel dissimilarity metric and the Euclidean metric in several representative VANET scenarios. Findings show that the obtained dissimilarity metric correlates with the Euclidean distance up to 8.9% better than classical dissimilarity metrics. Moreover, the obtained dissimilarity metric is evaluated when used in well-known data dissemination schemes, such as p-persistence, polynomial and irresponsible algorithm. The obtained dissimilarity metric achieves significant improvements in terms of reachability in comparison with the classical dissimilarity metrics and the Euclidean metric-based schemes in the studied VANET urban scenarios.

An An efficient adaptive neuro-fuzzy system based attack detection technique for VANETs

Vehicular Ad-hoc Networks (VANETs) are generally accepted as an exceptional type of Mobile Ad hoc Network (MANET). VANETs have seen tremendous growth in last decade, providing a vast range of uses in both military as well as civilian activities. The temporary connectivity in the vehicles can also increase the driver's capability on the road. In this paper, an efficient data dissemination approach is proposed which not only improves the vehicle to vehicle connectivity but also improves the QoS between the source and the destination. The effectiveness of the proposed approach is demonstrated when it comes to the significant gets achieved in the parameters namely, end to end delay, packet loss ratio, average download delay and throughput in comparison with the existing approaches.