6,753 research outputs found
Optimally Efficient Prefix Search and Multicast in Structured P2P Networks
Searching in P2P networks is fundamental to all overlay networks.
P2P networks based on Distributed Hash Tables (DHT) are optimized for single
key lookups, whereas unstructured networks offer more complex queries at the
cost of increased traffic and uncertain success rates. Our Distributed Tree
Construction (DTC) approach enables structured P2P networks to perform prefix
search, range queries, and multicast in an optimal way. It achieves this by
creating a spanning tree over the peers in the search area, using only
information available locally on each peer. Because DTC creates a spanning
tree, it can query all the peers in the search area with a minimal number of
messages. Furthermore, we show that the tree depth has the same upper bound as
a regular DHT lookup which in turn guarantees fast and responsive runtime
behavior. By placing objects with a region quadtree, we can perform a prefix
search or a range query in a freely selectable area of the DHT. Our DTC
algorithm is DHT-agnostic and works with most existing DHTs. We evaluate the
performance of DTC over several DHTs by comparing the performance to existing
application-level multicast solutions, we show that DTC sends 30-250% fewer
messages than common solutions
Storage and Search in Dynamic Peer-to-Peer Networks
We study robust and efficient distributed algorithms for searching, storing,
and maintaining data in dynamic Peer-to-Peer (P2P) networks. P2P networks are
highly dynamic networks that experience heavy node churn (i.e., nodes join and
leave the network continuously over time). Our goal is to guarantee, despite
high node churn rate, that a large number of nodes in the network can store,
retrieve, and maintain a large number of data items. Our main contributions are
fast randomized distributed algorithms that guarantee the above with high
probability (whp) even under high adversarial churn:
1. A randomized distributed search algorithm that (whp) guarantees that
searches from as many as nodes ( is the stable network size)
succeed in -rounds despite churn, for
any small constant , per round. We assume that the churn is
controlled by an oblivious adversary (that has complete knowledge and control
of what nodes join and leave and at what time, but is oblivious to the random
choices made by the algorithm).
2. A storage and maintenance algorithm that guarantees (whp) data items can
be efficiently stored (with only copies of each data item)
and maintained in a dynamic P2P network with churn rate up to
per round. Our search algorithm together with our
storage and maintenance algorithm guarantees that as many as nodes
can efficiently store, maintain, and search even under churn per round. Our algorithms require only polylogarithmic in bits to
be processed and sent (per round) by each node.
To the best of our knowledge, our algorithms are the first-known,
fully-distributed storage and search algorithms that provably work under highly
dynamic settings (i.e., high churn rates per step).Comment: to appear at SPAA 201
Taxonomy of P2P Applications
Peer-to-peer (p2p) networks have gained immense popularity in recent years and the number of services they provide continuously rises. Where p2p-networks were formerly known as file-sharing networks, p2p is now also used for services like VoIP and IPTV. With so many different p2p applications and services the need for a taxonomy framework rises. This paper describes the available p2p applications grouped by the services they provide. A taxonomy framework is proposed to classify old and recent p2p applications based on their characteristics
Semantic Flooding: Semantic Search across Distributed Lightweight Ontologies
Lightweight ontologies are trees where links between nodes codify the fact that a node lower in the hierarchy describes a topic (and contains documents about this topic) which is more specific than the topic of the node one level above. In turn, multiple lightweight ontologies can be connected by semantic links which represent mappings among them and which can be computed, e.g., by ontology matching. In this paper we describe how these two types of links can be used to define a semantic overlay network which can cover any number of peers and which can be flooded to perform a semantic search on documents, i.e., to perform semantic flooding. We have evaluated our approach by simulating a network of 10,000 peers containing classifications which are fragments of the DMoz web directory. The results are promising and show that, in our approach, only a relatively small number of peers needs to be queried in order to achieve high accuracy
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