CAF: Community aware framework for large scale mobile opportunistic networks

The fundamental challenge in opportunistic networking is when and how to forward a message. Rank-based forwarding, one of the most promising methods for addressing this challenge, ranks nodes based on their social profiles or contact history in order to identify the most suitable forwarders. While these forwarding techniques have demonstrated great performance trends, we observe that they fail to efficiently forward messages in large scale networks. In this paper, we demonstrate using real mobility traces, the weakness of existing rank-based forwarding algorithms in large scale communities. We propose strategies for partitioning large communities into sub-communities based on geographic locality or social interests. We also propose exploiting particular nodes, named MultiHomed nodes, in order to disseminate messages across these sub-communities. We introduce CAF, a Community Aware Forwarding framework, which is designed to be integrated with state-of-the-art rank-based forwarding algorithms, in order to improve their performance in large scale networks. We use real mobility traces to evaluate our proposed techniques. Our results empirically show a delivery success rate increase of up to 40%, along with 5% to 30% improved success delivery rates compared to state-of-the-art rank-based forwarding algorithms; these results are obtained while incurring a marginal increase in cost which is less than 10%. We finally propose an extension of the original framework called Community Destination Aware Framework (CDAF). Assuming that the source node can determine the destination’s community, CDAF further reduces the cost of CAF by a factor of 2 while maintaining similar success rates.     

基于相遇概率时效性和重复扩散感知的机会网络消息转发算法

在机会网络中,为了更合理地选择消息传输中继节点并提高消息投递效率,设计了消息转发效用,并给出了对应的消息副本转发算法。首先,从节点历史相遇信息入手,重点分析了节点的间接相遇概率及其对应的时效性问题,提出了评估相遇信息价值的时效指标;然后,结合节点运动相似性分析了消息重复扩散问题,并提出节点移动偏离指标,用于评价节点重复扩散消息的可能性。仿真实验结果表明:与Epidemic、ProPHET、Maxprop和SAW(Spray And Wait)算法相比,综合考虑投递成功率、开销和延时指标,所提算法表现出了更好性能。     

Efficient fair algorithms for message communication

A computer network serves distributed applications by communicating messages between their remote ends. Many such applications desire minimal delay for their messages. Beside this efficiency objective, allocation of the network capacity is also subject to the fairness constraint of not shutting off communication for any individual message. Processor Sharing (PS) is a de facto standard of fairness but provides significantly higher average delay than Shortest Remaining Processing Time (SRPT), which is an optimally efficient but unfair algorithm. In this paper, we explore efficient fair algorithms for message communication where fairness means that no message is delivered later than under PS. First, we introduce a slack system to characterize fair algorithms completely and develop efficient fair algorithms called Pessimistic Fair Sojourn Protocol (PFSP), Optimistic Fair Sojourn Protocol (OFSP), and Shortest Fair Sojourn (SFS). Then, we prove that a fair online algorithm does not assure minimal average delay attainable with fairness. Our analysis also reveals lower bounds on worst-case inefficiency of fair algorithms. We conduct extensive simulations for various distributions of message sizes and arrival times. During either temporary overload or steady-state operation, SFS and other newly proposed fair algorithms support SRPT-like efficiency and consistently provide much smaller average delay than PS.     

机会社会网络中基于社区的消息传输算法

针对机会网络中的主流转发协议未考虑到节点移动社会性的问题,提出一种基于副本限制和人类社会特性的路由算法。该算法根据节点间的社会关系强度,动态自适应地将节点划分为不同的社区,通过限制消息副本数来减少网络中消息的冗余,并利用活跃性高的节点带动消息的转发和传递。仿真结果表明,该协议能够保证较高的消息传输成功率和相对较低的传输时延,降低网络的资源消耗。     

基于社会自私性的机会网络路由算法

在现有的基于节点自私性的机会网络路由算法中,大部分假设只有个别节点具有自私性。然而在现实世界中,大部分人都具有不同程度自私性。因此,本文提出一种针对社会自私性的机会网络路由算法。在该算法中,节点的自私性体现为追求最大的转发收益,转发收益的大小与消息的优先权和节点间的社会关系强度有关。社会关系越强,消息的优先权越高,节点的转发意愿就越强,相应地消息转发效益就越大。同时,节点优先发送转发收益最大的消息,且选择到与目的节点的社会关系更强,投递率更大且转发意愿较强的节点作为转发节点。最后,通过仿真实验证明该路由算法的可行性和高效性。     

一种基于社区机会网络的消息传输算法

由人携带的具有短距离通信接口的移动设备所组成的网络具有社区性质.当前机会网络中主流的多拷贝路由算法并没有考虑到节点的社区性质,如果将这些算法直接应用到社区机会网络中会造成传输延迟大、消息丢失率高等问题.针对这些问题,提出了一种基于社区机会网络的消息传输算法(CMTS),能够根据节点之间的通信频繁程度,自动将节点划分成不同的社区,自适应地控制消息的拷贝数量并依靠活跃节点将消息传输到目标社区.仿真结果表明,在延迟要求宽松的社区机会网络中,与Spray and Focus算法相比,CMTS算法能够在保证较高消息传输成功率的同时,减少了约20%的消息转发次数,有效地降低了网络资源的消耗.     

A game-theoretic incentive scheme for social-aware routing in selfish mobile social networks

Cooperative data forwarding can improve the performance of data routing in Mobile Social Networks (MSNs). However, previous studies mainly assumed that mobile nodes show selfish behaviors in data relaying merely due to their limited device resources. Nevertheless, the observation of everyday experience infers that they mitigate their selfishness based on their social relationships and content knowledge to achieve their social objective, i.e., they are socially selfish (SS). Therefore, how to promote SS nodes to participate in data forwarding becomes peculiarly challenging in MSNs. In this paper, we propose Game-theoretic Incentive Scheme for Social-aware rOuting, namely GISSO, to stimulate SS nodes in message relaying and guarantee that the routing performance gets maximized when SS nodes follow the scheme. First, we identify the social utility of each message to an intermediate node based on the strength of her social ties and message properties. Then, we apply an alternating-offers bargaining game in which SS nodes trade their messages with the aim of maximizing their social utility. We not only use subgame perfect Nash equilibrium as the agreement of two players to prove the efficiency of our game but also extensively evaluate the performance of GISSO using simulations over two real datasets. The comparison of GISSO with some benchmark social-aware protocols illustrates that GISSO overcomes SS nodes and outperforms the other algorithms regarding message delivery ratio and delay while generates low communication cost.     

一种面向机会网络路由的最优停止决策方法

投递延迟是机会网络的一个重要指标,给定节点缓存和消息副本数目限制,如何选择合适的节点复制消息成为一个关键问题.提出一种基于最优停止理论的路由决策方法（OSDR）.OSDR 将每个时隙上所遇节点和目标节点的平均相遇时间看做一个随机变量,根据该随机变量的统计特性得到一个停止观察、复制消息的规则,该规则呈现简单的阈值结构,即当某个时隙上所遇节点和目标节点的平均相遇时间小于给定阈值时即复制消息. OSDR 可以在较小的相遇间隔和等待成本之间进行折衷,实现数学期望意义上的最小消息投递延迟.介绍了OSDR 的网络模型、最优停止规则的存在性证明过程以及计算方法.模拟实验结果表明,OSDR 相对其他方法,在投递成功率、投递延迟等方面具有明显优势.     

Max-Min Fair Scheduling in Input-Queued Switches

Fairness in traffic management can improve the isolation between traffic streams, offer a more predictable performance, eliminate transient bottlenecks, mitigate the effect of certain kinds of denial-of-service attacks, and serve as a critical component of a quality-of-service strategy to achieve certain guaranteed services such as delay bounds and minimum bandwidths. In this paper, we choose a popular notion of fairness called max-min fairness and provide a rigorous definition in the context of input-queued switches. We show that being fair at the output ports alone or at the input ports alone or even at both input and output ports does not actually achieve an overall max-min fair allocation of bandwidth in a switch. Instead, we propose a new algorithm that can be readily implemented in a distributed fashion at the input and output ports to determine the exact max-min fair rate allocations for the flows through the switch. In addition to proving the correctness of the algorithm, we propose a practical scheduling strategy based on our algorithm. We present simulation results, using both real traffic traces and synthetic traffic, to evaluate the fairness of a variety of popular scheduling algorithms for input-queued switches. The results show that our scheduling strategy achieves better fairness than other known algorithms for input-queued switches and, in addition, achieves throughput performance very close to that of the best schedulers.     

Fair and efficient packet scheduling using Elastic Round Robin

Parallel systems are increasingly being used in multiuser environments with the interconnection network shared by several users at the same time. Fairness is an intuitively desirable property in the allocation of bandwidth available on a link among traffic flows of different users that share the link. Strict fairness in traffic scheduling can improve the isolation between users, offer a more predictable performance and improve performance by eliminating some bottlenecks. This paper presents a simple, fair, efficient, and easily implementable scheduling discipline, called Elastic Round Robin (ERR), designed to satisfy the unique needs of wormhole switching, which is popular in interconnection networks of parallel systems. In spite of the constraints of wormhole switching imposed on the design, ERR is also suitable for use in Internet routers and has better fairness and performance characteristics than previously known scheduling algorithms of comparable efficiency, including Deficit Round Robin and Surplus Round Robin. In this paper, we prove that ERR is efficient, with a per-packet work complexity of O(1). We analytically derive the relative fairness bound of ERR, a popular metric used to measure fairness. We also derive the bound on the start-up latency experienced by a new flow that arrives at an ERR scheduler. Finally, this paper presents simulation results comparing the fairness and performance characteristics of ERR with other scheduling disciplines of comparable efficiency     

非对称占空比传感网中的广播能效优化算法

针对非对称占空比传感网中最小端到端延迟约束下的广播能效优化问题,首先构造了一个能够刻画广播时空特征的时空状态图,将目标问题建模成转发行为子集覆盖问题,然后分别提出了一种面向总能耗优化的最小代价转发行为子集覆盖算法（MC-SCA）和一种面向能量公平性的代价均衡转发行为子集覆盖算法（CB-SCA）。MC-SCA和CB-SCA都是采用迭代的方式选择最优转发行为子集。MC-SCA在每一轮迭代中贪心地选择转发行为代价与新增覆盖节点数量的比值最小的转发行为,而CB-SCA在每一轮迭代中贪心地选择带来更小节点转发能耗负载且更多新增覆盖节点数量的转发行为。仿真结果表明,MC-SCA与典型的随机父节点选择算法（RPNS-A）相比其广播总能耗平均降低了24.23%,而CB-SCA与RPNS-A、MC-SCA以及最小节点负载优先的贪心算法相比其节点最大广播负载值分别平均降低了48.69%、65.21%和10.64%,因此CB-SCA具有更好的广播能量公平性。     

自适应Ad hoc分布式互斥算法

Ad hoc网络的动态拓扑结构和节点自组织给分布式算法的实现带来了诸多困难.针对Ad hoc分布式互斥算法研究滞后的现状,提出了一种自适应的Ad hoc分布式算法ADMUTEX. ADMUTEX算法基于令牌查询方法,它采用Lamport逻辑时戳保证消息的时序性,避免了节点饿死.同时,它在消息复杂度与同步延迟之间作了折衷,而且它不需要节点了解系统的全局信息,能够适应Ad hoc网络的动态拓扑结构和节点频繁出入的情况.分析与仿真结果表明该算法具有较低的消息复杂度、小响应延迟和公平性.     

可信机器学习的公平性综述

人工智能在与人类生活息息相关的场景中自主决策时,正逐渐面临法律或伦理的问题或风险.可信机器学习是建立安全人工智能系统的核心技术,是人工智能领域的热门研究方向,而公平性是可信机器学习的重要考量.公平性旨在研究机器学习算法决策对个人或群体不存在因其固有或后天属性所引起的偏见或偏爱.从公平表征、公平建模和公平决策这3个角度出...     

Enabling opportunistic storage for mobile DTNs

Delay-tolerant Networking (DTN) can enable ad-hoc communication within (sparse) mobile user communities and multi-hop Internet access where IP-based end-to-end communication would fail. DTN message forwarding in ad-hoc networks may lead to message replication and messages remaining stored on several nodes for some time. We leverage these characteristics and provide application support in intermediate nodes: we enable them to understand the resources contained in forwarded and locally stored DTN messages to perform application-specific processing. Based upon this, we create an opportunistic distributed storage for cooperative content caching and retrieval using the nodes’ buffers.     

Refinement of fair action systems

An action system is a framework for describing parallel or distributed systems, for which the refinement calculus offers a formalisation of the stepwise development method. Fairness is an important notion in modelling parallel or distributed systems, and this paper investigates a calculus for refinement of fair action systems. Simulations, which are proof techniques for refinement, are extended to verify fair action systems. Our work differs from others' in that the additional condition concerning fairness is expressed through termination of related iteration statements. For this purpose, existing proof rules for termination are extended. In the tradition of the refinement calculus, our approach to fairness is based on techniques developed mainly for sequential programming. Received: 16 March 1995 / 16 April 1997     

节点转发消息能力动态估计的缓存替换策略

机会网络中的节点以“存储-携带-转发”的方式完成消息转发,消息需要在中继节点缓存较长时间以等待通信机会,高效的缓存替换策略能够提高有限缓存空间的利用率。提出一种基于节点转发消息能力的自适应缓存替换策略。通过动态地感知当前的消息传输状态,并根据其在此节点中的停留时间和消息转发状态,估计节点对该消息的转发能力,进而调整消息的转发以及删除优先级。结果表明所提出的缓存替换策略能够有效提高消息的成功投递率,并大幅度地降低网络负载率。     

基于流的 AD Hoc 网络接入公平性分析与研究

在 Ad Hoc 网络中,系统的不公平性会严重影响服务质量.针对该问题,提出一种以流为单位、用 WFQ 机制进行本地信息调度、采用交换节点信息调节退避时间的协调算法--FBFA.该算法计算节点每条流的服务指数,与邻节点进行交换,结合节点本身的信息和邻居节点的信息确定退避时间,提高系统的公平性.实验结果表明,FBFA 算...     

Twins: A Dual Addressing Space Representation for Self-Organizing Networks

As the size of mobile self-organizing networks increases, the efficiency of location services must increase as well so that addressing/routing scalability does not become an issue. In this paper, we propose a novel architecture, called Twins, tailored for self-organizing networks. Twins architecture involves addressing and locating nodes in large networks, forwarding packets between them, and managing in the presence of mobility/topology changes. Twins defines a logical multidimensional space for addressing and forwarding, while location service and management operations make use of a one-dimensional space. To improve scalability and performance, forwarding is hop-by-hop with greedy next-hop choice and the location service uses a rendezvous paradigm to distribute information among nodes. In this paper, we describe the Twins architecture and present a performance evaluation to assess scalability, fairness in the overhead distribution among nodes, and routing robustness.     

一种基于节点位置余弦相似度的机会网络转发算法

针对机会网络中数据送达率较低的问题,文中根据节点历史接触信息即节点相遇次数、相遇时间长度、节点关系稳定性来计算节点转发效用值。首先选择通信范围内效用值最大的邻居节点作为初始转发节点,再根据余弦相似度选择其他转发节点,使得转发节点能够尽可能均匀地分布。在此基础上,提出一种基于节点位置余弦相似度的机会网络转发算法(Opportunistic Network forwarding algorithm based on Node Cosine Similarity,ONNCS)。该算法使得转发节点能够均匀地分布,因此数据报文能够尽快地被转发到目的节点。实验结果表明,ONNCS具有较高的转发成功率和较低的转发能耗,转发成功率高出其他算法5%～8%。     

Impact of a simple load balancing approach and an incentive-based scheme on MANET performance

Most reactive mobile ad hoc network (MANET) routing protocols such as AODV and DSR do not perform search for new routes until the network topology changes. But, low node mobility does not affect the MANET connectivity and the same routes may be used for a long time. This may cause concentration of traffic on few mobile stations (MSs), which results in congestion and hence longer end-to-end delay. In addition, continuous use of MSs may cause their battery power to get exhausted rapidly. Expiration of MS energy causes disruption of connections traversing through the MSs and could generate many simultaneous new routing requests. Therefore, we propose a load balancing approach called Simple Load Balancing Approach (SLBA), which can be transparently added to any current reactive routing protocol such as AODV and DSR. SLBA minimizes the traffic concentration by allowing each MS to drop RREQ or to give up packet forwarding depending on its own traffic load. Meanwhile, MSs may deliberately give up forwarding packets to save their own energy. For encouraging MSs to volunteer in forwarding packets, we introduce a reward scheme for packet forwarding, named Protocol-Independent Fairness Algorithm (PIFA). We compare the performance of AODV and DSR with and without SLBA and PIFA. Simulation results indicate that SLBA can distribute traffic very well and improve the MANET performance. PIFA is also observed to prevent MANET partitioning and any performance degradation due to selfish nodes.