基于声誉机制和可变门限秘密共享的Ad hoc网络信任模型

针对当前Ad hoc网络信任模型存在的问题,提出了一种新的移动Ad hoc网络信任模型。该信任模型将声誉机制和可变门限秘密共享理论进行结合,使用到自安全证书管理的信任模型中来,解决了Ad hoc网络中的分布式认证问题。在保证认证可靠性的基础上,尽量减少了网络认证流量,提高了移动Ad hoc网络认证的效率,减轻了网络的负载。     

一种基于Agent的Ad hoc网络路由算法

Ad hoc网络因其具有分布式、无中心、自组织、节点可以移动等特点,在军事通信、灾后紧急救援、传感器网络、局域网、车辆通信等方面有着广阔的应用前景,成为研究领域的一个热点.但同时由于Ad hoc网络拓扑结构的动态变化,使得作为Ad hDc网络关键技术之一的路由算法的实现较为困难.提出了一种基于Agent的Ad hoc网络路由算法,设计并实现了4种Agent.该算法通过在Ad hoc网络中加入一定数量的移动Agent来进行路由探寻,一方面降低了网络负载,另一方面降低了网络发送数据的时延.其实质是在现有的表驱动路由算法和按需驱动路由算法之间寻求一个折中.     

一种移动Ad hoc网的可靠性评估方法*

为了评估移动Ad hoc网的可靠性,综合考虑节点移动性引起的动态连接以及网络组件故障的因素,提出一种移动Ad hoc网的2-终端可靠性计算方法（MANET-RC）,并得到量化表达式。实验结果表明,移动Ad hoc网的可靠性不仅依赖节点、链路可靠性,还依赖于网络拓扑的冗余度和节点在网络中的分布。这为提升自组织网络的安全性能提供了理论依据。     

Ad hoc网络邻居节点表自适应构建与维护算法*

在Ad hoc网络贪婪地理路由协议中,传统的邻居节点表自适应构建与维护采用周期性信标交换算法,在移动环境下会导致通信暂盲现象。在分析节点移动对网络连通性影响的基础上,提出一种基于链路断开概率的自适应信标交换算法来实现邻居节点表自适应构建与维护。仿真结果表明,该算法不但提高了数据分组传送成功率,而且还降低了控制开销,因此该算法适用于移动Ad hoc 网络。     

Ad hoc网络安全技术简介

Ad hoc网络是一种没有有线基础设施支持的移动网络,网络中的节点均由移动主机构成。由于节点的移动性导致网络拓扑结构不断变化,节点通信完全依靠无线链路,相对于有线网络在安全性上面临更大的挑战。本文根据Ad hoc网络面临的安全问题,分析了Ad hoc网络中常见的攻击方式,并集中讨论了Ad hoc网络的安全路由、密钥管理等关键问题。     

基于主动网络的MANET路由研究*

通过对主动网络和移动Ad hoc网络特点的分析,提出了将主动网络与移动Ad hoc网络相结合的思想,分析了这种结合的可行性和有效性.根据用户传输数据的大小和对路由可靠性的要求,提出了两种基于主动网络的移动Ad hoc网络的路由查找方法.仿真结果表明了采用主动网络技术后的移动Ad hoc网络能够方便地满足不同的路由要求.     

战术移动Ad hoc网络仿真系统设计与实现

针对战术移动Ad hoc网络仿真需求,在OPNET仿真环境下设计并实现了战术移动Ad hoc网络仿真系统,该系统能够对战术移动Ad hoc网络各层协议进行仿真,通过仿真结果进行性能分析,这对战术移动Ad hoc网络选择高效适用的技术方案具有实际参考价值.     

一种基于Agent的Ad hoc网络路由算法

Ad hoc网络因其具有分布式、无中心、自组织、节点可以移动等特点,在军事通信、灾后紧急救援、传感器网络、局域网、车辆通信等方面有着广阔的应用前景,成为研究领域的一个热点。但同时由于Adhoc网络拓扑结构的动态变化,使得作为Ad hoc网络关键技术之一的路由算法的实现较为困难。提出了一种基于Agent的Ad hoc网络路由算法,设计并实现了4种Agent。该算法通过在Adhoc网络中加入一定数量的移动Agent来进行路由探寻,一方面降低了网络负载,另一方面降低了网络发送数据的时延。其实质是在现有的表驱动路由算法和按需驱动路由算法之间寻求一个折中。     

一种基于移动Ad Hoc的P2P新型文件共享算法的研究与设计

本文在阐述了P2P模型和移动Ad hoe模型的基础上,提出了一种新型的基于DHT-DHT式的DTPSR文件共享算法,并且通过分析得出算法的时间复杂度为O((logn)2),该算法执行效率高,适合较大型移动Ad hoc网络等特征.     

Ad Hoc网络节点毁坏的拟生灭模型

在Ad hoc网络中由于节点通信是分布式的,网络中的节点毁坏会影响通信链路的中断甚至导致某些节点不可达。为此,基于 M/M/C排队系统,通过合理假设,建立一个Ad hoc网络中节点毁坏及处理过程的拟生灭模型。运用矩阵分析法,在给定参数下,求得稳态概率、毁坏节点的平均队长、毁坏节点到达时无需等待的概率等。该模型能够在保证系统正常工作的情况下,提高Ad hoc网络节点维护效率,为制定维护策略提供参考。     

Topology Dissemination for Reliable One-Hop Distributed Hash Tables

Many distributed hash tables (DHTs) resolve lookups in O(log n) hops, where n is the number of nodes. One-hop DHTs give lower lookup latencies and lower lookup failure rates. However, it is hard to maintain large, wide-area one-hop topologies. We contribute aecast, a new topology dissemination algorithm for one-hop DHTs. It avoids expensive repair mechanisms and critical points of failure in existing one-hop DHTs. When a node discovers by anti-entropy that it has missed a topology update, it initiates "controlled flooding,rdquo sending the update to nodes in the multicast tree that also missed the update. We compare aecast with a widely cited epidemic multicasting algorithm, pbcast, by analysis and simulation. Aecast gives at least fivefold fewer out-of-date nodes on average within one round of a topology update. We support it with a fault-tolerant topology agreement protocol, so that only legitimate topology changes propagate throughout the overlay. Consequently, we argue that one-hop DHTs deserve greater attention for Internet applications in which reasonably reliable nodes carry high lookup loads.     

PCIR: Combining DHTs and peer clusters for efficient full-text P2P indexing

Distributed hash tables (DHTs) are very efficient for querying based on key lookups. However, building huge term indexes, as required for IR-style keyword search, poses a scalability challenge for plain DHTs. Due to the large sizes of document term vocabularies, peers joining the network cause huge amounts of key inserts and, consequently, a large number of index maintenance messages. Thus, the key to exploiting DHTs for distributed information retrieval is to reduce index maintenance costs. Various approaches in this direction have been pursued, including the use of hybrid infrastructures, or changing the granularity of the inverted index to peer level. We show that indexing costs can be significantly reduced further by letting peers form groups in a self-organized fashion. Instead of each individual peer submitting index information separately, all peers of a group cooperate to publish the index updates to the DHT in batches. Our evaluation shows that this approach reduces index maintenance cost by an order of magnitude, while still keeping a complete and correct term index for query processing.     

Locality-Aware and Churn-Resilient Load-Balancing Algorithms in Structured Peer-to-Peer Networks

Structured peer-to-peer overlay networks, like distributed hash tables (DHTs), map data items to the network based on a consistent hashing function. Such mapping for data distribution has an inherent load balance problem. Data redistribution algorithms based on randomized matching of heavily loaded nodes with light ones can deal with the dynamics of DHTs. However, they are unable to consider the proximity of the nodes simultaneously. There are other methods that rely on auxiliary networks to facilitate locality-aware load redistribution. Due to the cost of network construction and maintenance, the locality-aware algorithms can hardly work for DHTs with churn. This paper presents a locality-aware randomized load-balancing algorithm to deal with both the proximity and network churn at the same time. We introduce a factor of randomness in the probing of lightly loaded nodes in a range of proximity. We further improve the efficiency by allowing the probing of multiple candidates (d-way) at a time. Simulation results show the superiority of the locality-aware two-way randomized algorithm in comparison with other random or locality-aware algorithms. In DHTs with churn, it performs no worse than the best chum-resilient algorithm. It takes advantage of node capacity heterogeneity and achieves good load balance effectively even in a skewed distribution of items     

PGSW-OS: a novel approach for resource management in a semantic web operating system based on a P2P grid architecture

A web operating system is an operating system that users can access from any hardware at any location. A peer-to-peer (P2P) grid uses P2P communication for resource management and communication between nodes in a grid and manages resources locally in each cluster, and this provides a proper architecture for a web operating system. Use of semantic technology in web operating systems is an emerging field that improves the management and discovery of resources and services. In this paper, we propose PGSW-OS (P2P grid semantic Web OS), a model based on a P2P grid architecture and semantic technology to improve resource management in a web operating system through resource discovery with the aid of semantic features. Our approach integrates distributed hash tables (DHTs) and semantic overlay networks to enable semantic-based resource management by advertising resources in the DHT based upon their annotations to enable semantic-based resource matchmaking. Our model includes ontologies and virtual organizations. Our technique decreases the computational complexity of searching in a web operating system environment. We perform a simulation study using the Gridsim simulator, and our experiments show that our model provides enhanced utilization of resources, better search expressiveness, scalability, and precision.     

Associative search in peer to peer networks: Harnessing latent semantics

The success of a P2P file-sharing network highly depends on the scalability and versatility of its search mechanism. Two particularly desirable search features are scope (ability to find infrequent items) and support for partial-match queries (queries that contain typos or include a subset of keywords). While centralized-index architectures (such as Napster) can support both these features, existing decentralized architectures seem to support at most one: prevailing unstructured P2P protocols (such as Gnutella and FastTrack) deploy a “blind” search mechanism where the set of peers probed is unrelated to the query; thus they support partial-match queries but have limited scope. On the other extreme, the recently-proposed distributed hash tables (DHTs) such as CAN and CHORD, couple index location with the item’s hash value, and thus have good scope but can not effectively support partial-match queries. Another hurdle to DHTs deployment is their tight control of the overlay structure and the information (part of the index) each peer maintains, which makes them more sensitive to failures and frequent joins and disconnects.We develop a new class of decentralized P2P architectures. Our design is based on unstructured architectures such as Gnutella and FastTrack, and retains many of their appealing properties including support for partial match queries, and relative resilience to peer failures. Yet, we obtain orders of magnitude improvement in the efficiency of locating rare items. Our approach exploits associations inherent in human selections to steer the search process to peers that are more likely to have an answer to the query. We demonstrate the potential of associative search using models, analysis, and simulations.     

Efficient Range Query Processing in Peer-to-Peer Systems

With the increasing popularity of the peer-to-peer (P2P) computing paradigm, many general range query schemes for distributed hash table (DHT)-based P2P systems have been proposed in recent years. Although those schemes can provide range query capability without modifying the underlying DHTs, they have the query delay depending on both the scale of the system and the size of the query space or the specific query, and thus cannot guarantee to return the query results in a bounded delay. In this paper, we propose Armada, an efficient range query processing scheme to support delay-bounded single-attribute and multiple-attribute range queries. It is the first delay-bounded general range query scheme on constant-degree DHTs, and can return the results for any range query within 2logN hops in a P2P system with N peers. Results of analysis and simulations show that the average delay in Armada is less than logN, and the average message cost of single-attribute range queries is about logN+2n 2 (n is the number of peers that intersect with the query). These results are very close to the lower bounds on delay and message cost of range queries over constant-degree DHTs.     

A scalable approach for content based image retrieval in cloud datacenter

The emergence of cloud datacenters enhances the capability of online data storage. Since massive data is stored in datacenters, it is necessary to effectively locate and access interest data in such a distributed system. However, traditional search techniques only allow users to search images over exact-match keywords through a centralized index. These techniques cannot satisfy the requirements of content based image retrieval (CBIR). In this paper, we propose a scalable image retrieval framework which can efficiently support content similarity search and semantic search in the distributed environment. Its key idea is to integrate image feature vectors into distributed hash tables (DHTs) by exploiting the property of locality sensitive hashing (LSH). Thus, images with similar content are most likely gathered into the same node without the knowledge of any global information. For searching semantically close images, the relevance feedback is adopted in our system to overcome the gap between low-level features and high-level features. We show that our approach yields high recall rate with good load balance and only requires a few number of hops.     

An effective single‐hop distributed hash table with high lookup performance and low traffic overhead

Distributed hash tables (DHTs) have been used in several applications, but most DHTs have opted to solve lookups with multiple hops, to minimize bandwidth costs while sacrificing lookup latency. This paper presents D1HT, an original DHT that has a peer‐to‐peer and self‐organizing architecture and maximizes lookup performance with reasonable maintenance traffic, and a Quarantine mechanism to reduce overheads caused by volatile peers. We implemented both D1HT and a prominent single‐hop DHT, and we performed an extensive and highly representative DHT experimental comparison, followed by complementary analytical studies. In comparison with current single‐hop DHTs, our results showed that D1HT consistently had the lowest bandwidth requirements, with typical reductions of up to one order of magnitude, and that D1HT could be used even in popular Internet applications with millions of users. In addition, we ran the first latency experiments comparing DHTs to directory servers, which revealed that D1HT can achieve latencies equivalent to or better than a directory server, and confirmed its greater scalability properties. Overall, our extensive set of results allowed us to conclude that D1HT can provide a very effective solution for a broad range of environments, from large‐scale corporate data centers to widely deployed Internet applications. Copyright © 2014 John Wiley & Sons, Ltd.     

Locality in structured peer-to-peer networks

Distributed hash tables (DHTs), used in a number of structured peer-to-peer (P2P) systems, provide efficient mechanisms for resource placement and location. A key distinguishing feature of current DHT systems, such as Chord, Pastry, CAN and Tapestry, is the way they handle locality in the underlying network. Topology-based node identifier assignment, proximity routing, and proximity neighbor selection are examples of heuristics used to minimize message delays in the underlying network. While these heuristics are sometimes effective, they all rely on a single global overlay that may install the key of a popular object at a node far from most of the nodes accessing it. Furthermore, a response to a lookup message does not contain any locality information about the nodes holding a copy of the object. We address these issues in Plethora, a novel two-level overlay P2P network. A local overlay in Plethora acts as a locality-aware cache for the global overlay, grouping nodes close together in the underlying network. Local overlays are constructed by exploiting the organization of the Internet into autonomous systems (ASs). We present a detailed experimental study that demonstrates performance gains in response time of up to 60% compared to a single global Pastry overlay. We also present efficient distributed algorithms for maintaining local overlays in the presence of node arrivals and departures.