基于机会转发的飞行自组网集群路由算法

针对飞行自组织网络(Flying Ad Hoc Network, FANET)中高动态拓扑变化导致数据丢包率较高的问题，提出一种基于节点移动机会转发的集群路由算法CROF(Cluster Routing-Opportunity Forward)。该算法通过考虑节点相对移动趋势度和剩余能量的综合权值来统一对集群头节点以及集群间机会转发节点进行选择。仿真实验结果表明，CROF算法在高动态自组织网络中可以有效提高消息投递率以及网络生命周期。     

一种基于能量效率的自组织网络节点合作方法

针对移动自组织网络中的节点自私性问题,以无线网络环境中的拓扑控制和数据包转发作为网络节点的策略空间,并结合网络节点的能量效率水平,建立了一个基于严格位势博弈的网络节点合作模型。仿真结果表明,该模型不但满足了自组织网络环境下的网络连通性需求,并且通过节点间的合作机制降低了网络能耗,提高了网络节点的能量效率水平,以及数据传输的可靠性和效率。     

机会网络中的数据转发机制分析

机会网络作为一种新兴移动无线自组织网络,在军事及民用领域展现出广泛的应用前景,数据转发机制是其核心问题。论文针对机会网络中的数据转发机制展开讨论,首先对机会网络数据转发机制与传统路由机制进行综合比较,在此基础上介绍数据转发机制面临的问题和性能评估标准,并根据数据转发机制主要特点对其进行了分类,最后对机会网络中的典型数据转发机制进行归纳。     

基于运动状态的延迟容忍网络受控传输路由算法

根据延迟容忍网络(Delay/Disruption Tolerant Networks,DTN)中节点移动特性,提出基于移动节点运动状态的延迟容忍网络受控传输路由协议。通过获取信息传输范围内各邻居节点的运动信息,筛选符合预期要求的节点作为中继节点进行消息转发。     

移动自组织网络环境中负载均衡策略研究

针对移动自组织网络中负载分布不均所导致的网络性能恶化问题,提出了一种基于分组转发行为不确定度量的网络负载计算方法,并以此为基础提出了负载均衡按需路由协议,通过监测分组转发过程中的行为变化特征,采用信息熵的形式对其进行量化和度量,并在路由发现过程中利用节点负载监测信息合理规避网络热点区域,以达到网络负载均衡分布的目的。仿真结果表明,基于负载均衡策略的路由协议能够有效提高分组递交成功率,降低分组传输延迟。     

基于连接质量和节点相关度的机会网络路由

提出利用连接质量估计节点间消息成功转发的概率,并证明了节点间相关度越高,消息转发率越高。在此基础上,提出基于连接质量和节点相关度的机会网络路由机制。路由计算节点转发效用值时,综合了连接质量和节点相关度;消息转发时,不断向相对于目的节点转发效用值高的节点转发消息。仿真结果表明,与传统路由相比,在消息送达率相同的前提下,该路由消息延迟更小、消耗的总能量更少。     

Ad Hoc网络中一种基于自裁减的广播算法

为解决简单泛洪式广播算法所引起的AdHocN络的广播风暴问题,提出了一种基于自裁减的广播算法。算法根据自裁减广播策略,通过设定延时机制和优先转发机制对网络节点是否需要转发广播包进行判定。最后,将算法应用于AODV协议,并与标准AODV协议在不同节点最大移动速度的场景下进行了转发节点数、到达率、端到端平均时延和归一化路由开销等参数的比较,以验证提出算法的有效性。     

ZigBee网络自剪裁路由算法

ZigBee网络中的AODVjr算法通过全网广播路由请求RREQ消息而获得分组发送的最短路径,但节点大量广播RREQ消息增加了网络控制开销,导致网络节点耗能剧增,同时网络堵塞的可能性也大大提升。针对AODVjr算法存在的网络节点耗能剧增问题,在AODVjr算法基础上,结合节点邻居表,提出筛选RREQ消息转发节点,从而限制RREQ消息转发次数的路由算法Zig Bee树节点自剪裁转发算法(ZigBee On-tree Self-pruning Rebroadcast Algorithm,ZOSR)和ZigBee转发节点选择算法(ZigBee On-tree Forwarding Node Selection Algorithm,ZOFNS)。仿真结果表明,算法能有效降低网络节点的转发次数,从而降低网络整体功耗,延长网络工作时间。     

基于IBE和秘密共享的分布式密钥管理和认证

Ad Hoc中的密钥管理和认证分析 移动Ad Hoc网络是一种能在事先没有构建网络基础设施的环境下,由移动节点临时组成的对等式网络,是一种自组织、自管理的网络。网络中每个节点可随时加入或退出,拓扑结构频繁变化,并且由于每个节点的通信覆盖面小,节点间通信常常要经过其它节点的多跳转发。这些特点使     

基于信誉值维护的机会网络自私节点检测机制

机会网络中自私节点的存在严重影响路由转发的性能。为在路由时避开此类节点、消除其对网络性能的影响,提出了一种基于信誉值维护的自私节点检测机制,通过两跳ACK消息来监测节点行为,利用监测信息计算节点的信誉值,并将其作为判断节点是否自私的依据。在多种路由算法上加载该检测机制进行仿真实验,结果表明该检测机制可准确识别机会网络中的自私节点,提高消息投递的成功率,并能有效控制消息副本数和网络开销。     

An altruism‐based trust‐dependent message forwarding protocol for opportunistic networks

In opportunistic networks (OppNets), which are characterized by intermittent end‐to‐end connections, the messages are routed in a store‐carry‐and‐forward fashion using the locally inferred knowledge about the behavior of nodes. As such, most OppNets routing protocols use social metrics that are dependent on the nodes' past information. But the participation of nodes in the message forwarding process is not guaranteed without incentivizing them because most nodes are reluctant in sharing their private resources for public uses. In this paper, some socially derived psychological attributes of a node are introduced to ensure their trustworthy participation in the message forwarding process, leading to the design of an altruism‐dependent trust‐based data forwarding mechanism for OppNets (called ATDTN). In this protocol, each node is associated with a dynamically changing altruism value representing its trust in the network, which is used to determine its status with regard to its participation in message forwarding. Through trace‐driven simulations using the ONE simulator, it is shown that ATDTN outperforms IronMan and SimBet protocols for routing in OppNets (respectively, 18% and 48% improvement), in terms of delivery ratio, end‐to‐end delay, overhead count, and average number of hops, under varying buffer size and time‐to‐live.     

An evolutionary bargaining‐based approach for incentivized cooperation in opportunistic networks

Opportunistic networking enables users to communicate in an environment where connectivity is intermittent or unstable. However, such networking scheme assumes that mobile nodes voluntary cooperate, which cannot be guaranteed. Some nodes can simply exhibit selfish behavior and thus diminish the effectiveness of the approach. In this paper, a game scenario is formulated in which the nodes try to convince each other to participate in packets forwarding. Each node is considered as a player in this game. When a node comes in the communication range of another, a bargaining game starts between them as part of the message forwarding process. Both players try to have a mutual agreement on a price for message forwarding. We present a new incentive mechanism called evolutionary bargaining‐based incentive scheme (EBIS) to motivate selfish nodes to cooperate in data forwarding. In EBIS, a node negotiates with other nodes to obtain an agreeable amount of credit for its forwarding service. Nodes apply a sequential bargaining game and then adapt their strategies using an evolutionary model to maximize the probability of reaching an agreement. Unlike classical bargaining games, nodes in our model are boundedly rational. In addition, we use the evolutionary stable strategy (ESS) concept to determine the adaptive strategies for the nodes. The comparison of EBIS with a benchmarked model demonstrates that EBIS performs better in terms of packet delivery ratio and average latency.     

CPTR: conditional probability tree based routing in opportunistic networks

In opportunistic networks due to the inconsistency of the nodes link, routing is carried out dynamically and we cannot use proactive routes. In these networks, nodes use opportunities gained based on store-carry-forward patterns to forward messages. Every node that receives a message when it encounters another node makes decision regarding the forwarding or not forwarding the node encountered. In some previous methods, the recognition of whether encounter with current node is considered as an appropriate opportunity or not has been carried out based on the comparison of the probability of carrier node and the node encountered. In these methods, if the message is delivered to the encountered node, a better opportunity would be lost. To fight with this challenge we have posed CPTR method by using conditional probability tree method through which in addition to the probability of the delivery of carrier and encountered nodes’ message delivery, the opportunities for after encounter will be involved in messages’ forwarding. Results of simulation showed that the proposed method can improve the ratio of delivery and delay of message delivery compared to other similar methods in networks with limited buffer.     

Message redundancy removal of multi-copy routing in delay tolerant MANET

This article puts forward a new scheme to control message redundancy efficiently in delay tolerant mobile Ad-hoc networks(MANET).The class of networks generally lacks end-to-end connectivity.In order to improve the efficiency that messages are delivered successfully,multiple message copies routing protocols are usually used,but the network load is increased due to a large number of message redundancies.In the study,by using counter method,every node adds an encounter counter based on epidemic routing scheme...     

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

In 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.     

Assessing the influence of selfishness on the system performance of gossip based vehicular networks

In delay tolerant vehicular networks, gossip is an efficient forwarding scheme, which significantly reduces the message transmission overhead while maintaining a relatively high transmission rate in the high mobility vehicular environment. This mechanism requires vehicles as the network nodes to forward messages according to the system-defined gossip probability in a cooperative and selfless way among all the vehicles in the system. However, in the real word vehicular networks, most of the vehicular nodes exhibit selfish and non-collaboration behaviors to reduce the gossip probability in order to save their own energy and other limited resources in the vehicular nodes. In this paper, we study how node selfishness influences the performance of energy-constrained gossip forwarding based vehicular networks. We consider two typical forms of selfishness in the realistic vehicular networks: individual selfishness and social selfishness, and study the networking performance by focusing on the average message transmission delay and mean transmission cost. First, we model the message transmission process with selfish behaviors in the gossip forwarding based delay tolerant vehicular networks using a continuous time Markov chain. Based on this useful model, we derive closed-form formulae for average message transmission delay and mean transmission cost. Then, we give extensive numerical results to analyze the impact of selfishness on system performance of the vehicular networks. The results show that gossip forwarding in delay tolerant vehicular networks is robust to selfish behaviors since even when they increase the message transmission delay, there is a gain on the message transmission cost.     

Performance Modeling for Relay Cooperation in Delay Tolerant Networks

Delay tolerant networks (DTNs) rely on the mobility of nodes and sequences of their contacts to compensate for lack of continuous connectivity and thus enable messages to be delivered from end to end in a “store-carry-forward” way, where multiple relay nodes are usually employed in the message delivery process. In this paper, we focus on such relay cooperation and analytically explore its impact on the delivery performance in DTNs. Specifically, we first develop a continuous time Markov chain-based theoretical framework to model the complicated message delivery process in delay tolerant networks adopting the two-hop relay algorithm. We then derive closed-form expressions for both the expected delivery delay and the corresponding expected delivery cost, where the important relay behaviors of forwarding traffic for itself or for other nodes are carefully incorporated into the analysis.     

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.

     

基于分层的水下传感器网络路由策略

提出一种基于分层的水下传感器网络路由协议（Layered-DBR, layered-depth based routing）。节点进行一次信息广播后,只允许指定深度范围内的节点进行消息接收,以达到控制网络副本的目的,最终建立与网络冗余相关的网络分层模型。在分层网络中,节点首先需要计算消息转发前后的相对深度距离与相对剩余能量,进而计算出消息的转发概率。同时,建立一种消息队列管理机制,该队列同时具有消息转发管理和历史记录管理的功能,并给出消息的入列和出列方法。仿真实验表明,Layered-DBR能够有效地控制网络冗余,与DBR和Flooding算法相比,Layered-DBR能有效地减少网络能耗,延长网络寿命。     

Secure Multi-copy Routing in Compromised Delay Tolerant Networks

Routing in delay tolerant networks (DTNs) is challenging due to their unique characteristics of intermittent node connectivity. Different protocols (single-, multi-copy, erasure-coding-based etc.) utilizing store-carry-and-forward paradigm have been proposed to achieve routing of messages in such environments by opportunistic message exchanges between nodes that are in the communication range of each other. The sparsity and distributed nature of these networks together with the lack of stable connectivity between source destination pairs make these networks vulnerable to malicious nodes which might attempt to learn the content of the messages being routed between the nodes. In this paper, we study DTNs in which malicious nodes are present, to which we refer to as compromised DTNs. We discuss and analyze the effects of presence of malicious nodes on routing of messages in compromised DTNs. We propose a two period routing approach which aims at achieving the desired delivery ratio by a given delivery deadline in presence of malicious nodes. Our simulation results with both random networks and real DTN traces show that, with proper parameter setting, the proposed method can achieve delivery ratios which surpass those reached by other algorithms by a given delivery deadline.