A Utility-Based Buffer Management Policy for Improving Data Dissemination in Opportunistic Networks

In opportunistic networks, most existing buffer management policies including scheduling and passive dropping policies are mainly for routing protocols. In this paper, we proposed a Utility-based Buffer Management strategy(UBM) for data dissemination in opportunistic networks. In UBM, we first design a method of computing the utility values of caching messages according to the interest of nodes and the delivery probability of messages, and then propose an overall buffer management policy based on the utility. UBM driven by receivers completely implements not only caching policies, passive and proactive dropping policies, but also scheduling policies of senders. Simulation results show that, compared with some classical dropping strategies, UBM can obtain higher delivery ratio and lower delay latency by using smaller network cost.

Data Distribution Mechanism over Opportunistic Networks with Limited Epidemic

Most of data distribution mechanism in Opportunistic Networks is derived by Epidemic data distribution,and Epidemic data distribution means that when each node meets another node,it may copy its own messages and transfer to another node.On the one hand,the copies improve the forwarding rate,and reduce the transmission delay.However,on the other hand,energy consumption increases and network survival time is reduced because the copies consume transmission resource.Therefore,copy number should be under control.In this paper,we first introduce the existing routing strategy based on Epidemic briefly,and present the Epidemic routing protocol analysis model and copy control mechanism based on the limited Epidemic in Opportunistic Networks.Then based on the limited copies scheme(LCS),we propose an energy balance scheme(EBS),the results show that EBS can improve the network survival time.

A Trust Management Scheme Based on Behavior Feedback for Opportunistic Networks

In the harsh environment where n ode density is sparse, the slow-moving nodes cannot effectively utilize the encountering opportunities to realize the self-organized identity authentications, and do not have the chance to join the network routing. However, considering m ost of the communications in opportunistic networks are caused by forwarding operations, there is no need to establish the complete mutual authentications for each conversation. Accordingly, a novel trust management scheme is presented based on the information of behavior feedback, in order to complement the insufficiency of identity authentications. By utilizing the certificate chains based on social attributes, the mobile nodes build the local certificate graphs gradually to realize the web of "Identity Trust" relationship. Meanwhile, the successors generate Verified Feedback Packets for each positive behavior, and consequently the "Behavior Trust" relationship is formed for slow-moving nodes. Simulation result shows that, by implementing our trust scheme, the d elivery probability and trust reconstruction ratio can be effectively improved when there are large numbers of compromised nodes, and it means that our trust management scheme can efficiently explore and filter the trust nodes for secure forwarding in opportunistic networks.

Reducing energy consumption optimization selection of path transmission routing algorithm in opportunistic networks

Opportunistic networks are random networks and do not communicate with each other among respective communication areas.This situation leads to great difficulty in message transfer.This paper proposes a reducing energy consumption optimal selection of path transmission(OSPT) routing algorithm in opportunistic networks.This algorithm designs a dynamic random network topology,creates a dynamic link,and realizes an optimized selected path.This algorithm solves a problem that nodes are unable to deliver messages for a long time in opportunistic networks.According to the simulation experiment,OSPT improves deliver ratio,and reduces energy consumption,cache time and transmission delay compared with the Epidemic Algorithm and Spray and Wait Algorithm in opportunistic networks.

Trusted Routing Based on Identity-Based Threshold Signature for Opportunistic Networks

In opportunistic Networks,compromised nodes can attack social context-based routing protocols by publishing false social attributes information.To solve this problem,we propose a security scheme based on the identity-based threshold signature which allows mobile nodes to jointly generate and distribute the secrets for social attributes in a totally self-organized way without the need of any centralized authority.New joining nodes can reconstruct their own social attribute signatures by getting enough partial signature services from encounter opportunities with the initial nodes.Mobile nodes need to testify whether the neighbors can provide valid attribute signatures for their routing advertisements in order to resist potential routing attacks.Simulation results show that:by implementing our security scheme,the network delivery probability of the social context-based routing protocol can be effectively improved when there are large numbers of compromised nodes in opportunistic networks.

Impact of Heterogeneity on Forwarding Schemes in Opportunistic Networks

In the paper, we concentrate on the infl uence of heterogeneity on the performance of forwarding algorithms under opportunistic networks. Therefore, we first describe two different heterogeneous network models, and capture the heterogeneity which concern mobile nodes' contact dynamics under the individual models and the spatial models. Then we investigate inter-contact time is not fully follow exponential distribution and compare the performance of the delivery delay between direct forwarding protocol and three-hop forwarding protocol under three network models. We illustrate the performance of message delivery delay under the spray and wait protocol and prophet protocol from simulation results. Our simulation results show that the heterogeneity should be considered for the performance of forwarding protocols.

A Dynamic Resource-Aware Routing Protocol in Resource-Constrained Opportunistic Networks

Recently,Opportunistic Networks(OppNets)are considered to be one of the most attractive developments of Mobile Ad Hoc Networks that have arisen thanks to the development of intelligent devices.OppNets are characterized by a rough and dynamic topology as well as unpredictable contacts and contact times.Data is forwarded and stored in intermediate nodes until the next opportunity occurs.Therefore,achieving a high delivery ratio in OppNets is a challenging issue.It is imperative that any routing protocol use network resources,as far as they are available,in order to achieve higher network performance.In this article,we introduce the Resource-Aware Routing(ReAR)protocol which dynamically controls the buffer usage with the aim of balancing the load in resource-constrained,stateless and non-social OppNets.The ReAR protocol invokes our recently introduced mutual informationbased weighting approach to estimate the impact of the buffer size on the network performance and ultimately to regulate the buffer consumption in real time.The proposed routing protocol is proofed conceptually and simulated using the Opportunistic Network Environment simulator.Experiments show that the ReAR protocol outperforms a set of well-known routing protocols such as EBR,Epidemic MaxProp,energy-aware Spray and Wait and energy-aware PRoPHETin terms of message delivery ratio and overhead ratio.

A Direction-Based Data Forwarding Algorithm for Opportunistic Networks

In this paper, the forwarding objective and mobility law of nodes in opportunistic networks are first investigated to establish a mathematical model for further analysis, then a gradually accelerated data forwarding algorithm is proposed. In this algorithm, according to the distance between data carriers （nodes） and the destination, some intermediate nodes are selected to relay the data. Especially, the forwarded copies can be increased when the delay reaches a threshold, to guarantee the required delivery ratio. The simulation results show that the proposed algorithm can effectively reduce the storage occupancies of nodes and forwarding delay, and guarantee the delivery ratio simultaneously.

ML-Fresh: Novel Routing Protocol in Opportunistic Networks Using Machine Learning

Opportunistic Networks(OppNets)is gaining popularity day-by-day due to their various applications in the real-life world.The two major reasons for its popularity are its suitability to be established without any requirement of additional infrastructure and the ability to tolerate long delays during data communication.Opportunistic Network is also considered as a descendant of Mobile Ad hoc Networks(Manets)and Wireless Sensor Networks(WSNs),therefore,it inherits most of the traits from both mentioned networking techniques.Apart from its popularity,Opportunistic Networks are also starting to face challenges nowadays to comply with the emerging issues of the large size of data to be communicated and blind forwarding of data among participating nodes in the network.These issues lower the overall performance of the network.Keeping this thing in mind,ML-Fresh-a novel framework has been proposed in this paper which focuses to overcome the issue of blind forwarding of data by maintaining an optimum path between any pair of participating nodes available in the OppNet using machine learning techniques viz.pattern prediction,decision tree prediction,adamic-adar method for complex networks.Apart from this,ML-Fresh also uses the history of successful encounters between a pair of communicating nodes for route prediction in the background.Simulation results prove that the ML-Fresh outperforms the existing framework of Opportunistic Networks on the grounds of standard Quality-of-Service(QoS)parameters.

Utilizing blockchains in opportunistic networks for integrity and confidentiality

Opportunistic networks(OppNets)are usually a set of smart,wearable,and portable devices or entities with mobility that connect wirelessly without requiring infrastructure.Such a network is of great importance in data transmission,particularly in incidents and disasters,whether man-made or natural.However,message integrity and confidentiality are of concern when dealing with vital and physiological data transmission under strict privacy regulations.In this work,we propose a structure to classify messages based on their priority in different queues.Furthermore,due to the decentralized architecture of OppNets,we propose a blockchain-based structure for providing security for high-priority messages.It contains three sequences of functional blocks with a light and simplified implementation that make it suitable for battery-powered wearable devices that are limited in energy consumption and computational units.The simulation results show that by increasing the number of nodes in the network,the average of the changes in block sizes is neglectable,which addresses the computation bottleneck.Furthermore,we analyze the performance of the proposed structure in terms of message delivery and network overhead compared with the Epidemic and Prophet routing algorithms.These results indicate advancing the overall performance of the proposed algorithm.

Robust load-balanced backbone-based multicast routing in mobile opportunistic networks

Mobile opportunistic network(MON)is an efficient way of communication when there is no persistent connection between nodes.Multicast in MONs can be used to efficiently deliver messages to multiple destination nodes.However,because multiple destination nodes are involved,multicast routing is more complex than unicast and brings a higher communication cost.Backbone-based routing can effectively reduce the network overhead and the complexity of routing scheme.However,the load of backbone nodes is larger than that of regular nodes.If the backbone node’s buffer is exhausted,it will have a significant impact on the performance of the routing scheme.Load balancing can improve the ability of backbone to deal with the change of network load,and backbone maintenance algorithm can provide backbone robustness.In this paper,we propose a robust load-balanced backbone-based multicast routing scheme in MONs.In the backbone construction algorithm,we transform the problem of backbone construction into a multi-objective optimization problem,and propose a multi-objective evolutionary algorithmbased backbone construction algorithm,namely LBMBCMOEA algorithm.In addition,in order to increase the robustness of the backbone-based routing scheme,we propose a localized multicast backbone maintenance algorithm(MBMA)to deal with the buffer exhaustion of backbone nodes.When a backbone node’s residual buffer is insufficient,MBMA algorithm selects other nodes to replace the backbone node.The results on extensive simulations show that when considering the node buffer size constraints,compared with previous backbone-based multicast routing schemes,our proposed algorithm has better performance,and when the node’s residual buffer is insufficient,MBMA algorithm can significantly improve the performance of the backbone-based multicast routing scheme.

Routing protocol based on social characteristics for opportunistic networks

Opportunistic networks are derived from delay tolerant networks, where mobile nodes have no end-to-end connections. Nodes are represented by people, which means that opportunistic networks can be regarded as social networks. Human mobility plays an important role in affecting the performance of forwarding protocols in social networks, furthermore, the trajectory of people＇s movements are driven by social characteristics. However, current routing protocols rely on simple mobility models, and rarely consider social characteristics. Considering two heterogeneous network models, an social opportunistic networks routing（SONR） was proposed which brings an adapted discrete Markov chain into nodes＇ mobility model and calculates the transition probability between successive status. Comparison was made between Spray, Wait and Epidemic protocol. Simulation show that SONR can improve performance on delivery ratio, delivery latency and network overhead, meanwhile. SONR approaches the performance of Epidemic routing.

QoS-oriented packet scheduling scheme for opportunistic networks

The unique characteristics of opportunistic networks （ONs）, such as intermittent connectivity and limited network resources, makes it difficult to support quality of service （QoS） provisioning, particularly to guarantee delivery ratio and delivery delay. In this paper, we propose a QoS-oriented packet scheduling scheme （QPSS） to make decisions for bundle transmissions to satisfy the needs for the delivery ratio and delivery delay constraints of bundles. Different from prior works, a novel bundle classification method based on the reliability and latency requirements is utilized to decide the traffic class of bundles. A scheduling algorithm of traffic class and bundle redundancy is used to maintain a forwarding and dropping priority queue and allocate network resources in QPSS. Simulation results indicate that our scheme not only achieves a higher overall delivery ratio but also obtains an approximate 14% increase in terms of the amount of eligible bundles.

Disjoint-Path Routing Mechanism in Mobile Opportunistic Networks

The prevalent multi-copy routing algorithms in mobile opportunistic networks(MONs)easily cause network congestion.This paper introduces a disjoint-path(DP)routing algorithm,where each node can only transmit packets once except the source node,to effectively control the number of packet copies in the network.The discrete continuous time Markov chain(CTMC)was utilized to analyze the state transition between nodes,and the copy numbers of packets with the DP routing algorithm were calculated.Simulation results indicate that DP has a great improvement in terms of packet delivery ratio,average delivery delay,average network overhead,energy and average hop count.

Optimization-Based Fragmental Transmission Method for Video Data in Opportunistic Networks

Multimedia data have become popularly transmitted content in opportunistic networks. A large amount of video data easily leads to a low delivery ratio. Breaking up these big data into small pieces or fragments is a reasonable option. The size of the fragments is critical to transmission efficiency and should be adaptable to the communication capability of a network. We propose a novel communication capacity calculation model of opportunistic network based on the classical random direction mobile model, define the restrain facts model of overhead, and present an optimal fragment size algorithm. We also design and evaluate the methods and algorithms with video data fragments disseminated in a simulated environment. Experiment results verified the effectiveness of the network capability and the optimal fragment methods.

Prophet_TD Routing Algorithm Based on Historical Throughput and Encounter Duration

Opportunistic networks are self-organizing networks that do not require a complete path between the source node and the destination node as it uses encounter opportunities brought by nodes movement to achieve network communication.Opportunistic networks routing algorithms are numerous and can be roughly divided into four categories based on different forwarding strategies.The Prophet routing algorithm is an important routing algorithm in opportunistic networks.It forwards messages based on the encounter probability between nodes,and has good innovation significance and optimization potential.However,the Prophet routing algorithm does not consider the impact of the historical throughput of the node on message transmission,nor does it consider the impact of the encounter duration between nodes on message transmission.Therefore,to improve the transmission efficiency of opportunistic networks,this paper based on the Prophet routing algorithm,fuses the impact of the historical throughput of the node and the encounter duration between nodes on message transmission at the same time,and proposes the Prophet_TD routing algorithm based on the historical throughput and the encounter duration.This paper uses the Opportunistic Networks Environment v1.6.0(the ONE v1.6.0)as the simulation platform,controls the change of running time and the number of nodes respectively,conducts simulation experiments on the Prophet_TD routing algorithm.The simulation results show that compared to the traditional Prophet routing algorithm,on the whole,the Prophet_TD routing algorithm has a higher message delivery rate and a lower network overhead rate,and its average latency is also lower when node density is large.

A Mixture Model Parameters Estimation Algorithm for Inter-Contact Times in Internet of Vehicles

Communication opportunities among vehicles are important for data transmission over the Internet of Vehicles(IoV).Mixture models are appropriate to describe complex spatial-temporal data.By calculating the expectation of hidden variables in vehicle communication,Expectation Maximization(EM)algorithm solves the maximum likelihood estimation of parameters,and then obtains the mixture model of vehicle communication opportunities.However,the EM algorithm requires multiple iterations and each iteration needs to process all the data.Thus its computational complexity is high.A parameter estimation algorithm with low computational complexity based on Bin Count(BC)and Differential Evolution(DE)(PEBCDE)is proposed.It overcomes the disadvantages of the EM algorithm in solving mixture models for big data.In order to reduce the computational complexity of the mixture models in the IoV,massive data are divided into relatively few time intervals and then counted.According to these few counted values,the parameters of the mixture model are obtained by using DE algorithm.Through modeling and analysis of simulation data and instance data,the PEBCDE algorithm is verified and discussed from two aspects,i.e.,accuracy and efficiency.The numerical solution of the probability distribution parameters is obtained,which further provides a more detailed statistical model for the distribution of the opportunity interval of the IoV.

Efficient Broadcast Retransmission Based on Network Coding for InterPlaNetary Internet

In traditional wireless broadcast networks,a corrupted packet must be retransmitted even if it has been lost by only one receiver.Obviously,this is not bandwidth-efficient for the receivers that already hold the retransmitted packet.Therefore,it is important to develop a method to realise efficient broadcast transmission.Network coding is a promising technique in this scenario.However,none of the proposed schemes achieves both high transmission efficiency and low computational complexity simultaneously so far.To address this problem,a novel Efficient Opportunistic Network Coding Retransmission(EONCR)scheme is proposed in this paper.This scheme employs a new packet scheduling algorithm which uses a Packet Distribution Matrix(PDM)directly to select the coded packets.The analysis and simulation results indicate that transmission efficiency of EONCR is over 0.1,more than the schemes proposed previously in some simulation conditions,and the computational overhead is reduced substantially.Hence,it has great application prospects in wireless broadcast networks,especially energyand bandwidth-limited systems such as satellite broadcast systems and Planetary Networks(PNs).

Context-Aware Adaptive Routing for Opportunistic Network

Opportunistic networking-forwarding messages in a disconnected mobile ad hoc network via any encountered nodes offers a new mechanism for exploiting the mobile devices that many users already carry. However, forwarding messages in such a network is trapped by many particular challenges, and some protocols have contributed to solve them partly. In this paper, we propose a Context-Aware Adaptive opportunistic Routing algorithm（CAAR）. The algorithm firstly predicts the approximate location and orientation of the destination node by using its movement key positions and historical communication records, and then calculates the best neighbor for the next hop by using location and velocity of neighbors. In the unpredictable cases, forwarding messages will be delivered to the more capable forwarding nodes or wait for another transmission while the capable node does not exist in the neighborhood. The proposed algorithm takes the movement pattern into consideration and can adapt different network topologies and movements. The experiment results show that the proposed routing algorithm outperforms the epidemic forwarding（EF） and the prophet forwarding（PF） in packet delivery ratio while ensuring low bandwidth overhead.