An important goal in P2P networks is that all peers provide resources. However, free riding and tragedy of common are real issues in P2P networks. To resolve these problems, most of the existing work is concerning probabilistic estimation to evaluate the trustworthiness or mechanism design to provide incentive. Instead of design a protocol to solve free riding, we build a micro-payment architecture for these existing protocols using virtual currency which can be more precisely measured and easily be replaced by reputation or other tokens. Our system can avoid from long-term trust learning interactions and high cost of collecting and analyzing reputation information. It can also provide peers incentive to truly report their connection type and security to malicious attacks.
Building a semantic search system on top of peer-to-peer (P2P) networks is becoming an attractive and promising
alternative scheme for the reason of scalability, Data freshness and search cost. In this paper, we present a Suffix Arrays
based algorithm for Semantic Search (SASS) in P2P systems, which generates a distributed Semantic Overlay Network
(SONs) construction for full-text search in P2P networks. For each node through the P2P network, SASS distributes
document indices based on a set of suffix arrays, by which clusters are created depending on words or phrases shared
between documents, therefore, the search cost for a given query is decreased by only scanning semantically related
documents. In contrast to recently announced SONs scheme designed by using metadata or predefined-class, SASS is an
unsupervised approach for decentralized generation of SONs. SASS is also an incremental, linear time algorithm, which
efficiently handle the problem of nodes update in P2P networks. Our simulation results demonstrate that SASS yields
high search efficiency in dynamic environments.
Clustering or grouping of similar objects is one of the most widely used procedures in data mining, which has received
enormous attentions and many methods have been proposed in these recent decades. However these traditional clustering
algorithms require all the data objects to be located at one single site where it is analyzed. And such limitation cannot
face the challenge as nowadays monstrous sizes of data sets are often stored on different independently working
computers connected to each other via local or wide area networks instead of one single site. Therefore in this paper, we
propose a fully distributed clustering algorithm, called a fully distributed clustering based on fractal dimension
(FDCFD), which enables each site to collaborate in forming a global clustering model with low communication cost. The
main idea behind FDCFD is via calculating fractal dimension to group points in a cluster in such a way that none of the
points in the cluster changes the cluster's fractal dimension radically. In our theoretical analysis, we will demonstrate
that our approach can work very well for clustering data that is inherently distributed, collect information spread over
several local sites to form a global clustering meanwhile without communication costs and delays for transmitting.
Efficient organization of the nodes in decentralized peer-to-peer (P2P) networks is a challenging problem, especially in
the absence of a global schema. Node clustering is an available way to optimize infrastructure and decrease traffic cost in
P2P networks. This paper proposes a Density-based Distributed Node Clustering (DDNC) approach to discovering
clusters in P2P networks. This approach is completely distributed, in which each node only depends on the knowledge of
its neighbors for node clustering. Unlike other graph based algorithms, the DDNC approach utilizes density of node's
neighbor for discovering clusters. For a given node, the DDNC determines its neighbor density by computing the link
time with its neighbors, which not only considers the node connectivity but also connection quality. The DDNC scheme
can also dynamically adapt its clusters according to the participation and departure of nodes. Experimental results have
shown ours scheme's feasibility and efficiency.
Clustering plays an important role in data mining. It helps to reveal intrinsic structure in data sets with little or no prior
knowledge. The approaches of clustering have received great attention in recent years. However many published
algorithms fail to do well in determining the number of cluster, finding arbitrary shapes of clusters or identifying the
presence of noise. In this paper we present an efficient clustering algorithm which employs the theory of grid, density
and fractal that can partition points in the same cluster with minimum change of fractal dimension meanwhile
maximizing the self-similarity in the clusters. We show via experiments that FDC can quickly deal with multidimensional
large data sets, identify the number of clusters, be capable of recognizing clusters of arbitrary shape and
furthermore explore some qualitative information from data sets.
The scheme of dynamic coordination rules in peer-to-peer database uses rule caching and forwarding to successfully solve the dependence tree break problem in the situation that peers can join and leave freely. But there are still problems that weaken the performance of query processing in this scheme. Coordination rules in cache are merged in run time when bypassing break points. If dependence trees can be optimized into a form robust against peer absence beforehand, the query process will be more efficient. This paper proposes such mechanism by doing coordination rule combinations when new peer joins the dependence tree and new forwarded coordination rule arrives in cache. When some peers leave, queries take one existing bypass rule for reformulation, instead of concatenating cached ones from scratch. In effect, this mechanism optimizes dependence tree into a more robust topology whenever new peer joins. Even when there is no peer absence, bypass rules can make query processing more efficient without following through many mediating peers, especially when data are updated frequently and frequent queries are needed. At the same time, the original dependence tree are maintained for data cache query when the target peer is absent. Since dynamic coordination rules are expressed in XSLT, we try to find a way to form one XSLT whose function is equal to a chain of XSLTs, similar to the XML reasoning. The protocol also needs to be improved to inform to launch topology optimization when new peer join or rule changes.
Today, the main traffic in peer-to-peer (P2P) network is still multimedia files including large numbers of music files. The study of Music Information Retrieval (MIR) brings out many encouraging achievements in music search area. Nevertheless, the research of music search based on MIR in P2P network is still insufficient. Query by Humming (QBH) is one MIR technology studied for years. In this paper, we present a server based P2P music sharing system which is based on QBH and integrated with a Hierarchical Index Structure (HIS) to enhance the relation between surface data and potential information. HIS automatically evolving depends on the music related items carried by each peer such as midi files, lyrics and so forth. Instead of adding large amount of redundancy, the system generates a bit of index for multiple search input which improves the traditional keyword-based text search mode largely. When network bandwidth, speed, etc. are no longer a bottleneck of internet serve, the accessibility and accuracy of information provided by internet are being more concerned by end users.
Peer-to-Peer (P2P) systems are currently receiving considerable interest. However, as experience with P2P networks shows, the selfish behaviors of peers may lead to serious problems of P2P network, such as free-riding and white-washing. In order to solve these problems, there are increasing considerations on reputation system
design in the study of P2P networks. Most of the existing works is concerning probabilistic estimation or social
networks to evaluate the trustworthiness for a peer to others. However, these models can not be efficient all the
time. In this paper, our aim is to provide a general mechanism that can maximize P2P networks social welfare in
a way of Vickrey-Clarke-Groves family, while assuming every peer in P2P networks is rational and selfish, which
means they only concern about their own outcome. This mechanism has some desirable properties using an O(n)
algorithm: (1) incentive compatibility, every peer truly report its connection type; (2) individually rationality;
and (3) fully decentralized, we design a multiple-principal multiple-agent model, concerning about the service
provider and service requester individually.
Chord which used in structured P2P network is a successful routing algorithm based on DHT (Distributed Hash Table).
In Chord nodes locate along the Chord ring by being assigned the node identifiers and data store in corresponding nodes
with key identifier. Finger table is built in each node and is maintained when nodes join and depart. The problems in
Chord are unidirectional clockwise routing along ring and information redundancy in routing table. An improved method
is presented which is bidirectional routing table. Routing can perform along clockwise and anticlockwise according to
the locations of the current node and destination node. The next hop direction is optimization that the next node is the
nearest one apart from the destination node. This strategy limits the search area in half-ring, reduces the average hops
and enhances the search efficiency. The redundancy routing information is deleted in order to decrease the added storage
space in bidirectional routing table, thus the items share the routing information.
DHT (Distributed Hash Table) is the key technology in structured P2P. DHT sets up logic topology with certain structure
among the nodes and builds relations between nodes and data resources according to some rules. Routing table structure
based on B+ tree for DHT is presented which builds up the balanced multilevel ordered tree-indexes to the routing tables
so as to form levels indexes and ordered link between nodes. In term of this method, key search performs along the
ordered indexes in B+ tree and the problem of resources location which is the core problem in DHT network is resolved
efficiently. This Routing table structure is of advantaged to manage numerous routing information in network and makes
the ruleless information well-regulated. It not only enhances the lookup efficiency and achieves the range search but also
can control the lookup length in the height of B+ tree. When nodes join and depart, index structure can make the
maintained routing information few in each node by updating linked message only. At the same time, for linked
information of successor node being mainly stored in every node, the storage cost is decreased. It is effective and
scalable routing table structure.
In a large-scale warship electronic equipment ATE, the main testing system is designed as an intermediate-level test
system, which will perform automatic test and fault localization up to SRUs level. UUTs of the system are faulty LRUs.
Different from small-scale aircraft avionics, Built-In Test (BIT) in current warships electronic equipments might arise
too much ambiguous fault isolation and could not detect the failure of cables, which results in high false removal rates
and causes a lot of manpower and resources waste. The situation will be worse when the deployment of main testing
system is usually confined to the site. In this paper, we aim at developing a kind of Portable Maintenance Aid Equipment
(PMAE) based on VXI bus technology in order to overcome above restrictions where 0-slot controller as well as some
dedicated test modules are designed using ARM based embedded system. The PMAE could cooperate with the main
testing system in realizing remote measurement and control through virtual instrument (VI) technology, thus the
localization veracity of faulty LRUs and cables could be greatly improved. Test results indicated good performance of
this scheme, thereby greatly augmenting diagnostic capacity and efficiency of the large-scale warships ATE.