嵌入服务通告与发现的ZRP协议

服务通告和发现在MANET(Mobile Ad hoc Networks)网络中,是一个十分重要的组成部分.现有的服务通告和发现协议不是为MANET网络设计的.文章提出了一个适合MANET、基于ZRP(Zone Routing Protocol)的服务通告及发现协议.服务的通告与发现存在于ZRP路由控制分组中,避免了周期性的通告给MANET网络带来的负载,节约了有限的带宽和设备的能耗.     

一种改进的基于移动Agent的网格资源组织与发现方法

网格资源的组织与发现是网格计算的关键问题。为了有效地组织和发现资源,在LDAP目录服务的基础上,利用移动Agent技术和分块索引技术,提出一种改进的基于移动Agent的网格资源组织与发现方法,较好地解决了资源的组织与快速发现问题。     

SOLONet: Sub-optimal location-aided overlay network for MANETs

Overlay networks have made it easy to implement multicast functionality in MANETs. Their flexibility to adapt to different environments has helped in their steady growth. Overlay multicast trees that are built using location information account for node mobility and have a low latency. However, the performance gains of such trees are offset by the overhead involved in distributing and maintaining precise location information. As the degree of (location) accuracy increases, the performance improves but the overhead required to store and broadcast this information also increases. In this paper, we present SOLONet, a design to build a sub-optimal location aided overlay multicast tree, where location updates of each member node are event based. Unlike several other approaches, SOLONet doesn’t require every packet to carry location information or each node maintain location information of every other node or carrying out expensive location broadcast for each node. Our simulation results indicate that SOLONet is scalable and its sub-optimal tree performs very similar to an overlay tree built by using precise location information. SOLONet strikes a good balance between the advantages of using location information (for building efficient overlay multicast trees) versus the cost of maintaining and distributing location information of every member nodes. Abhishek Patil received his BE degree in Electronics and Telecommunications Engineering from University of Mumbai (India) in 1999 and an MS in Electrical and Computer Engineering from Michigan State University in 2002. He finished his PhD in 2005 from the Department of Computer Science and Engineering at Michigan State University. He is a research engineer at Kiyon, Inc. located in San Diego, California. His research interests include wireless mesh networks, UWB, mobile ad hoc networks, application layer multicast, location-aware computing, RFIDs, and pervasive computing. Yunhao Liu received his BS degree in Automation Department from Tsinghua University, China, in 1995, and an MA degree in Beijing Foreign Studies University, China, in 1997, and an MS and a Ph.D. degree in Computer Science and Engineering at Michigan State University in 2003 and 2004, respectively. He is now an assistant professor in the Department of Computer Science at Hong Kong University of Science and Technology. His research interests include wireless sensor networks, peer-to-peer and grid computing, pervasive computing, and network security. He is a senior member of the IEEE Computer Society. Li Xiao received the BS and MS degrees in computer science from Northwestern Polytechnic University, China, and the PhD degree in computer science from the College of William and Mary in 2002. She is an assistant professor of computer science and engineering at Michigan State University. Her research interests are in the areas of distributed and Internet systems, overlay systems and applications, and sensor networks. She is a member of the ACM, the IEEE, the IEEE Computer Society, and IEEE Women in Engineering. Abdol-Hossein Esfahanian received his B.S. degree in Electrical Engineering and the M.S. degree in Computer, Information, and Control Engineering from the University of Michigan in 1975 and 1977 respectively, and the Ph.D. degree in Computer Science from Northwestern University in 1983. He was an Assistant Professor of Computer Science at Michigan State University from September 1983 to May 1990. Since June 1990, he has been an Associate Professor with the same department, and from August 1994 to May 2004, he was the Graduate Program Director. He was awarded ‘The 1998 Withrow Exceptional Service Award’, and ‘The 2005 Withrow Teaching Excellence Award’. Dr. Esfahanian has published articles in journals such as IEEE Transactions, NETWORKS, Discrete Applied Mathematic, Graph Theory, and Parallel and Distributed Computing. He was an Associate Editor of NETWORKS, from 1996 to 1999. He has been conducting research in applied graph theory, computer communications, and fault-tolerant computing. Lionel M. Ni earned his Ph.D. degree in electrical and computer engineering from Purdue University in 1980. He is Chair Professor and Head of Computer Science and Engineering Department of the Hong Kong University of Science and Technology. His research interests include wireless sensor networks, parallel architectures, distributed systems, high-speed networks, and pervasive computing. A fellow of IEEE, Dr. Ni has chaired many professional conferences and has received a number of awards for authoring outstanding papers.     

PON资源自动发现的方案研究与探索

重点阐述解决电信运营商在支持光网规模发展、宽带服务领先过程中所遇到的资源数据与现网数据、资源数据与网管数据存在差异等突出问题。提出结合PON技术、智能ODN技术、移动互联网技术构建资源自动发现引擎架构体系,实现资源数据与现网数据一致性的自动比对校验,提升资源数据管理效率,提高资源数据质量。     

MARE: Resource Discovery and Configuration in Ad Hoc Networks

The emergence of personal portable devices, such as PDA's and Mobile phones, with considerable processing and communication capabilities, has led to a desire to use various combinations of these devices together to achieve new and as yet unrealised operations. Not only are mobile devices expected to offer conventional facilities like email and web browsing but also more demanding multimedia applications. Attaining these operations within a fixed network environment with high-power workstations is non-trivial; however, highly dynamic ad hoc environments further complicate this scenario. In particular, a means of discovering available devices and enabling manipulation of them within a highly active environment is required. In this paper we present a novel architecture called MARE that facilitates the detection and manipulation of resources in ad hoc environments.     

Service Discovery Based on User Latent Intentions

This paper introduces a concept of User latent intentions (ULI) consisting of user preference intentions and user herd intentions for the expression of a user's personalized requirements of services.Theory of TCP-net and herd psychology is employed for the establishment of user preference decision model and user herd decision model,followed with a user-centric service discovery algorithm based on ULI.Simulation and experimental results demonstrate that the proposed ULI-based service discovery approach can increase the effectiveness of service discovery.     

MDFNSSDP:基于最小转发节点覆盖集合的无线自组网服务发现协议

服务发现是在网络中寻找所需服务的技术,它是无线自组网的一项基本技术.本文提出了一个高效的无线自组网服务发现协议:MDFNSSDP.MDFNSSDP在转发服务需求包时能充分利用各项信息最大限度减少需要覆盖的2跳邻居节点数量,并选用最少的转发节点来覆盖这些2跳邻居,从而大大节约了信息包开销,提高了协议效率.MDFNSSDP能在一次服务发现会话中完成多个服务发现任务,并能保证服务发现会话的覆盖范围,这一点已经通过理论分析得到了证明.计算机仿真结果表明了MDFNSSDP的显著优越性.     

基于泛在网络的资源发现与监控模型的研究

泛在网络是一个开放的巨复杂系统,泛在网络环境中的资源具有广域分布、自治、异构、动态等特性,如何对泛在网络资源进行有效的管理以满足用户的需求是一个极具挑战性的问题.文中结合移动Agent技术提出了一种新的泛在网络资源发现与监控模型.详细介绍了它的总体框架.工作机制,并给出了性能评价.     

一种基于位置和DHT的移动ad hoc网络服务发现方案

移动ad hoc网络中要求各节点问在缺乏预备知识的情况下进行相互通讯和协作，因此，对网络中各种服务的自动发现成为了其中的一个关键问题。将各节点的位置信息和DHT技术结合起来．提出了一种高效的面向移动ad hoc网络的服务发现方案。首先直接基于网络的物理拓扑结构来构建一种分布式哈希表．从而有效地消除了现有DHT方案的拓扑结构不匹配问题。然后提出了一种维度映射的方案．以将多维的服务描述信息映射到二维的哈希键值空间上。最后提出一种区域搜索算法，以高效地支持对服务的条件查询。     

一种面向结构化P2P网络的基于闲谈的资源发现方法

 结构化P2P网络下的多属性资源发现一直是一个公开问题.本文针对当前一种新颖的、优于传统方法的多属性资源发现方法－PIRD,深入分析了其在网络动态变化时可能出现的低查询效率问题,并提出一种解决方法:基于闲谈的PIRD(Gossip-based PIRD,G-PIRD).G-PIRD通过闲谈算法估计网络规模,动态调整资源索引的发布以保证高的查询效率.同时针对G-PIRD可能导致的负载不均衡问题,提出一种基于有界LSH(Bounded LSH,B-LSH )的负载均衡策略.试验证明:G-PIRD能动态适应网络变化,保证高效率的多属性资源发现;以及G-PIRD的负载均衡策略在保证高查询效率的同时,大大地降低了节点的索引负载.     

一种基于Echord协议的网格资源发现方法

针对网格集中式的资源发现方法存在单点失效、负载均衡差等问题,提出利用P2P技术进行网格资源发现方法.该方法通过改进Chord协议的后继节点函数和finger表,提出Echord(Enhanced Chord)协议,结合Echord协议特点,将网格中的虚拟组织构建成环状拓扑结构.网格资源被描述成基于XML的RDF形式,并按照一定的资源部署算法被均衡地发布在网格节点上.给出了如何应用Echord协议进行网格资源发现的算法.理论分析和仿真实验结果表明,相比于基于Chord的网格资源发现方法,该方法能改善系统的平均查找长度、消息传播性能、资源随机查找成功率.     

一种基于本体语义的网格服务发现模型

在网格环境中,网格服务的发现机制对于系统的性能和效率有着重要的意义和作用。目前网格服务发现模型多数是集中式的、基于关键字的服务匹配模型,缺乏灵活性和推理能力,发现结果难以令人满意。提出了一种基于本体论语义和Agent代理的网格服务发现模型。采用Agent代理技术进行服务搜索,不同的代理能够提供不同领域的本体知识库,从而达到多领域的服务发现;利用本体论语义进行服务的匹配,从而达到智能化的服务发现。该模型提高了服务发现的准确率,同时也增强了系统的可维护性、灵活性和扩展性以及服务管理的自治性和容错性。     

一种基于信誉的移动自组网区分服务激励机制

为了有效解决移动自组网节点在自觉提供服务方面的自私行为问题,该文提出了一种基于信誉的区分服务激励机制。该机制通过建立一种分簇全局信誉模型,并结合节点能力将服务与信誉进行等级关联,提供差异化服务;信誉级别越高的节点可以使用级别越高的服务,使用服务或者故意不提供服务会减少节点的信誉,节点需要积极提供可靠服务提高信誉才能保障服务的使用。仿真结果表明所提机制能有效抵制节点的自私行为,激励节点积极提供可靠服务。     

基于P2P网络之上移动agent的Web服务发现机制

分析了传统服务发现机制存在的问题，针对移动嵌入式环境，提出了基于P2P之上移动agent的Web服务发现机制，讨论了其体系结构和工作模型设计的关键技术。     

基于马尔可夫决策过程的网格资源发现

传统的网格资源发现方法没有考虑节点和资源本身性能的优劣性。针对这一问题,提出了基于马尔可夫决策过程(MDP)的网格资源发现方法,利用其对固定目标的最优搜索理论建立MDP模型实现报酬最优的资源发现,并对该模型仿真分析,验证其性能。     

一种新的自组网区域路由多径算法

能量消耗是移动自组网（MANET）路由协议研究中的一介热点所在。区域路由协议作为混合式寻路机制,为移动自组网提供了一种灵活的路由选择方式。在其路由发现的过程中,存在着多径问题,合理地利用这些路径进行路由转发,可以降低节点间功耗的偏差,使得整介网络能量消耗比较均匀。仿真表明,区域内路由部分中,该算法可较大地延长网络生存周期,而区域间路由部分所受影响则较小。     

MANET中基于移动代理拓扑发现的策略及其仿真

在MANET环境下,讨论了基于多个移动代理的拓扑发现方案。方案的核心在于通过链路关联度来反映网络的拓扑状况,以移动代理的历史路径和节点信息新鲜度来决定移动代理的漫游策略,仿真实验表明:该算法能够在较短的时间内达到收敛状态,同时给出了节点和代理的最优比例。     

CARD资源发现架构在无线传感网络中的性能研究

(西北工业大学计算机学院,陕西西安,710072)【摘要】CARD架构适用于大规模、高查询率、每次查询的数据传输量较小的Ad-hoc网络,它的核心目标是降低网络资源发现能耗,延长网络生命周期。文章首先介绍了CARD架构的结构;然后,建立了该架构的数学模型,该模型以无线传感器网络为目标场景,并推导出CARD架构的能耗和查询成功率与各个参数之间的函数关系;最后,根据该模型对CARD架构的能耗和查询成功率进行了理论分析,为CARD架构的参数选择提供了可靠的依据,并为对架构的进一步优化打下了坚实基础。     

基于极小独立支配集的MANET虚拟骨干网算法

对规模较大、移动较频繁的MANET(Mobile Ad hoc Networks),用独立支配集构建虚拟骨干网,克服骨干节点之间必须维护连通性的问题,使得拓扑变化较快时骨干网的重构能快速实现;利用极大独立集的求解得到极小独立支配集,并给出基于该支配集的虚拟骨干网数学模型及算法;通过仿真验证算法的有效性、低复杂度和自恢复能力.     

Service Discovery in Agent-Based Pervasive Computing Environments

Directory based service discovery mechanisms are unsuitable for ad-hoc m-commerce environments. Working towards finding an alternate mechanism, we developed Allia: a peer-to-peer caching based and policy-driven agent-service discovery framework that facilitates cross-platform service discovery in ad-hoc environments. Our approach achieves a high degree of flexibility in adapting itself to changes in ad-hoc environments and is devoid of common problems associated with structured compound formation in mobile commerce environments. Device capabilities and limitations, user preferences regarding device usage, application specifics with respect to mobile commerce are factors that our framework adapts to. We have described our initial implementation of Allia over ThinkPads and iPAQs by extending the LEAP Agent Platform and using Bluetooth as the underlying network protocol. In addition, we evaluated Allia's performance by running simulations of our protocol in Glomosim simulator. We also compared our framework against a structured compound-based architecture.