Impacts of user-selfishness on cooperative content caching in social wireless networks

Cooperative caching can be an effective mechanism for reducing electronic content provisioning cost in Social Wireless Networks (SWNETs). These networks are formed by a collection of mobile data enabled devices physically gathering in settings such as university campus, malls, airport and other public places. In this paper, we first propose an optimal collaborative object caching policy in order to minimize the object provisioning cost in SWNETs with homogenous user requests and a peer-rebate model for promoting collaboration. Then using an analytical model we study the impacts of user selfishness on the provisioning cost and the earned rebate when certain nodes in an SWNET selfishly deviate from the optimal policy. User selfishness is motivated in order to either increase individually earned rebate or to reduce content provisioning cost. The analytical model is validated by experimental results from simulated SWNETs using the network simulator ns2.     

Addressing space‐constraint driven selfishness in smart opportunistic environment

A smart opportunistic environment is a physical space, which allows the smart physical objects to communicate in the presence of disruption in connectivity. Because, the objects in such an environment are buffer constrained, some of the objects will not participate in data forwarding, when there is scarcity of storage (buffer) space. In this paper, we focus on such selfish behavior of objects triggered by space constraints in a smart opportunistic environment. We propose a novel data forwarding algorithm, selfishness and buffer‐aware routing (SBR), in which a node is chosen as a relay, based on its capability, which is a function of its available buffer space and past encounter history (delivery predictability) with the destination. SBR can efficiently utilize the limited buffer space in a node with a buffer management scheme, WSD. It can also detect space constraint driven selfish behavior of nodes and resolve it using a reputation‐based technique, MSD. We have conducted simulation using both synthetic and real‐world traces for evaluating our proposed SBR algorithm. For analyzing the performance of the algorithm in real‐time, a smart vehicular test‐bed is developed. Simulation results and test‐bed implementation show that our algorithm performs better in terms of higher delivery ratio, lower overhead ratio, and lower delivery delay, compared with existing opportunistic data forwarding algorithms.     

基于债务的机会网络"物-物交换"激励机制

针对机会网络简单"物-物交换"(SBT)激励机制降低网络性能的问题,设计了一种基于债务的"物-物交换"(DBT)激励机制.DBT通过引入债务关系改变了SBT中严格的等价交换原则,增加了单次交易的转发数据量,从而提高了网络性能.为使债务关系可靠运行,设计了基于信任的惩罚机制和基于债务的缓存策略.仿真实验证明,和SBT相比,DBT在有效激励节点协作的同时提高了网络性能.     

Social‐based reputation‐aware data forwarding for improved multicast delivery in the presence of selfish nodes in DTNs

Delay/disruption tolerant networks (DTNs) are potentially applicable in the challenged scenarios like post‐disaster environments. In such networks, data forwarding generally relies on the mutual cooperation of the nodes. However, in reality, despite the availability of necessary resources for data forwarding, a node could misbehave by dropping messages received from other nodes with whom it has no strong social ties. Such a node is called a socially selfish node, which would cause a poor delivery ratio in the network. In this paper, we aim to address the problem of multicast data forwarding in the presence of such selfish nodes, by means of efficient relay selection in DTNs. First, we define a realistic reputation model, in contrast to existing models, to define the socially selfish/misbehaving nodes in the network. Further, a game‐theoretic analysis is carried out that implies data forwarding cost is also an influential parameter in handling selfishness/misbehavior. Subsequently, the problem is formulated as a constrained optimization problem, which is NP hard. Therefore, a heuristic is proposed by combining the reputation of a node and the cost of message forwarding to appropriately identify relay nodes, thus improve the performance of the multicast message delivery in the network. We utilize a social metric, centrality to minimize the message forwarding cost in terms of the number of relay nodes. Finally, the comparative performance evaluation in ONE simulator with practical scenarios shows the superiority of the proposed scheme over the other prominent schemes.     

Ad hoc网络寻路阶段的合作激励机制研究

如何激励属于不同利益最大化实体的自私节点合作是当前Adhoc网络研究中的一个热点问题.现有的自私节点检测和激励机制主要针对数据传输阶段,不能适应寻路阶段的特点.文中基于邻居节点中继和生成的路由请求包之间的统计关系,提出了一种适用于按需路由协议寻路阶段的自私行为检测和惩罚机制,并利用博弈论工具将其建模为噪声环境下的重复囚徒困境博弈,对算法激励合作的有效性进行分析.理论分析和仿真结果显示,该算法能够有效地惩罚寻路中的自私行为,促进节点合作.     

Impact of node distance on selfish replica allocation in a mobile ad-hoc network

Many data replication techniques have been proposed to minimize performance degradation caused by network partitioning in a mobile ad-hoc network. Most of them assume that all mobile nodes collaborate fully in terms of sharing their memory space. However, in reality, some nodes may selfishly decide to only cooperate partially, or not at all, with other nodes. Recently, a new approach to selfish replica allocation has been proposed to handle node selfishness. However, there is still much room for improvement. We empirically observe that the previous selfish replica allocation strategy suffers from long query delay and poor data accessibility, because it utilizes only non-selfish nodes that may be faraway nodes. In this paper, we propose a novel replica allocation strategy in the presence of selfish nodes, that takes into account both selfish behavior and node distance. Moreover, through a novel node leveling technique, we utilize the memory space of all connected nodes, including selfish nodes. The conducted simulations demonstrate that the proposed strategy outperforms existing replica allocation techniques in terms of data accessibility, query delay, and communication cost.     

基于重复博弈的无线自组网络协作增强模型

在缺乏集中控制的无线自组网络中,节点在转发过程中所表现出的自私行为将严重影响其网络服务的可靠性.在节点理性假设的基础上,针对自组网络节点的预期收益及其协作交互过程建立了一个重复博弈模型,提出了一个激励一致性条件,在此条件下,节点将迫于惩戒机制威慑而自愿采取合作策略;并分析了节点对将来利益重视程度、机制参数和作弊检测效率对协作效果的影响.仿真结果表明,通过合理选择惩戒机制参数,能够有效抵御网络规模的增长及节点合作意愿、作弊检测效率的降低所导致的协作性削弱,进而提高存在自私节点时的整体网络性能.     

Exploring the impact of social properties on routing in cognitive radio networks

In this paper, we study the social properties, including community, friendship, and individual selfishness of cognitive radio networks and analyze the effect of these social properties on the performance of routing protocols. We first introduce the concept of cooperation willingness considering social relations and individual selfishness. Then, we model the impact of cooperation willingness on the routing performance in cognitive radio networks. After that, we perform extensive simulations to evaluate the accuracy of our model. The simulation results show that our model matched the simulation results well. Finally, our results suggest that community members, friends, and nodes with lower individual selfishness should be selected in the forwarding routes.     

MANETs环境下的模糊信任模型*

详细剖析了MANETs 路由协议中存在的节点自私问题, 提出了一种综合、有效的解决方案。     

基于博弈的DTMSN路由选择和信任决策

针对延时容忍移动传感器网络中节点自私性检测存在未考虑节点由于自身问题不能转发数据而引起信誉值计算不精确和重传数据造成能量浪费的问题,通过引入剩余能量和能否进行数据转发的两个概念,结合相应的惩罚机制,进一步提高了延时容忍移动传感器网络中节点自私性检查的准确度,同时可以延长网络的生存时间。对于现有延时容忍移动传感器网络中缺乏相应的激励机制,引入博弈的思想,通过理论证明,在条件允许的情况下节点会选择合作的行为,从而增加节点主动转发数据的积极性,提高网络的投递成功率,减少网络开销。