Abstract: In this paper, a new service oriented networking
paradigm is presented, where network nodes (peers) are self-
organized into individual service entities. The key idea relies on
the overlay approach, where there exists a virtual service plane,
fragmented into self-organized and self-managed entities called
islands of service transparency. The islands are formed in an
upstream, ad-hoc mode from the non-networking resources (i.e
VoD, grid server, etc) towards all ingress routers of the network,
using link state advertisements and multi-cost path selection
algorithms (i.e residual bandwidth, server capacity, storage, etc).
Organization and re-organization of nodes around non-network
resources is transparent to end-users, and thus any request
within a specific service island is transparently routed to the
islands resource for execution. A service proxy is commissioned
to resolve service addresses and service attributes to QoS metrics.
In this paper, we present the main notations and metrics of the
proposed architecture as well as node behavior and potential
GMPLS extensions for implementation issues
Abstract: We argue the case for a new paradigm for architecting structured P2P overlay networks, coined AESOP. AESOP consists of 3 layers: (i) an architecture, PLANES, that ensures significant performance speedups, assuming knowledge of altruistic peers; (ii) an accounting/auditing layer, AltSeAl, that identifies and validates altruistic peers; and (iii) SeAledPLANES, a layer that facilitates the coordination/collaboration of the previous two components. We briefly present these components along with experimental and analytical data of the promised significant performance gains and the related overhead. In light of these very encouraging results, we put this three-layer architecture paradigm forth as the way to structure the P2P overlay networks of the future.
Abstract: We present a new overlay, called the Deterministic Decentral-
ized tree (D2-tree). The D2-tree compares favourably to other overlays for
the following reasons: (a) it provides matching and better complexities,
which are deterministic for the supported operations; (b) the manage-
ment of nodes (peers) and elements are completely decoupled from each
other; and (c) an eącient deterministic load-balancing mechanism is pre-
sented for the uniform distribution of elements into nodes, while at the
same time probabilistic optimal bounds are provided for the congestion
of operations at the nodes.
Abstract: Service Oriented Computing and its most famous implementation technology Web Services (WS) are becoming an important enabler of networked business models. Discovery mechanisms are a critical factor to the overall utility of Web Services. So far, discovery mechanisms based on the UDDI standard rely on many centralized and area-specific directories, which poses information stress problems such as performance bottlenecks and fault tolerance. In this context, decentralized approaches based on Peer to Peer overlay networks have been proposed by many researchers as a solution. In this paper, we propose a new structured P2P overlay network infrastructure designed for Web Services Discovery. We present theoretical analysis backed up by experimental results, showing that the proposed solution outperforms popular decentralized infrastructures for web discovery, Chord (and some of its successors), BATON (and itĒs successor) and Skip-Graphs.
Abstract: We present a new overlay, called the
Deterministic Decentralized tree
-tree compares favorably to other overlays for the following reasons: (a)
it provides matching and better complexities,which are deterministic for the supported
operations; (b) the management of nodes (peers) and elements are completely decoupled from each other; and (c) an efficient deterministic load-balancing mechanism
is presented for the uniform distribution of elements into nodes, while at the same
time probabilistic optimal bounds are provided for the congestion of operations at the
nodes. The load-balancing scheme of elements into nodes is deterministic and general
enough to be applied to other hierarchical tree-based overlays. This load-balancing
mechanism is based on an innovative lazy weight-balancing mechanism, which is
interesting in its own right.
Abstract: We present a new overlay, called the Deterministic Decentralized tree ( TeX-tree). The TeX-tree compares favorably to other overlays for the following reasons: (a) it provides matching and better complexities, which are deterministic for the supported operations; (b) the management of nodes (peers) and elements are completely decoupled from each other; and (c) an efficient deterministic load-balancing mechanism is presented for the uniform distribution of elements into nodes, while at the same time probabilistic optimal bounds are provided for the congestion of operations at the nodes. The load-balancing scheme of elements into nodes is deterministic and general enough to be applied to other hierarchical tree-based overlays. This load-balancing mechanism is based on an innovative lazy weight-balancing mechanism, which is interesting in its own right.
Abstract: The proliferation of peertopeer
(P2P) systems has come with various
compelling applications including file sharing based on distributed
hash tables (DHTs) or other kinds of overlay networks.
Searching the content of files (especially Web Search) requires
querying with scoring and ranking. Existing approaches
have no way of taking into account the correlation between
the keywords in the query. This paper presents our solution
that incorporates the queries and behavior of the users in the P2P
network such that interesting correlations can be inferred.
Abstract: MINERVA1 is a novel approach towards P2P Web search
that connects an a-priori unlimited number of peers, each of which maintains
a personal local database and a local search facility. Each peer posts
a small amount of metadata to a physically distributed directory layered
on top of a DHT-based overlay network that is used to efficiently select
promising peers from across the peer population that can best locally execute
a query. This paper proposes a live demonstration of MINERVA,
showcasing the full information lifecycle: crawling web pages, disseminating
metadata to a distributed directory, and executing queries online. We
additionally invite all visitors to instantly join the network by executing
a small piece of software.
Abstract: In this work we tackle the open problem of self-join size (SJS) estimation in a large-scale distributed data system, where tuples of a relation are distributed over data nodes which comprise an overlay network. Our contributions include adaptations of five well-known SJS estimation centralized techniques (coined sequential, cross-sampling, adaptive, bifocal, and sample-count) to the network environment and a novel technique which is based on the use of the Gini coefficient. We develop analyses showing how Gini estimations can lead to estimations of the underlying Zipfian or power-law value distributions. We further contribute distributed sampling algorithms that can estimate accurately and efficiently the Gini coefficient. Finally, we provide detailed experimental evidence testifying for the claimed increased accuracy, precision, and efficiency of the proposed SJS estimation method, compared to the other methods. The proposed approach is the only one to ensure high efficiency, precision, and accuracy regardless of the skew of the underlying data.
Abstract: Our position is that a key to research efforts on ensuring high
performance in very large scale sharing networks is the idea of
volunteering; recognizing that such networks are comprised of
largely heterogeneous nodes in terms of their capacity and
behaviour, and that, in many real-world manifestations, a few
nodes carry the bulk of the request service load. In this paper we
outline how we employ volunteering as the basic idea using
which we develop altruism-endowed self-organizing sharing
networks to help solve two open problems in large-scale peer-topeer
networks: (i) to develop an overlay topology structure that
enjoys better performance than DHT-structured networks and,
specifically, to offer O(log log N) routing performance in a
network of N nodes, instead of O(log N), and (ii) to efficiently
process complex queries and range queries, in particular.
Abstract: Efficient query processing in traditional database
management systems relies on statistics on base data. For centralized systems, there is a rich body of research results on such statistics, from simple aggregates to more elaborate synopses such as sketches and histograms. For Internet-scale distributed systems, on the other hand, statisticsmanagement still poses major challenges. With the work in this paper we aim to endow peer-to-peer data management over structured
overlays with the power associated with such statistical information, with emphasis on meeting the scalability challenge.
To this end, we first contribute efficient, accurate, and decentralized algorithms that can compute key aggregates such as Count, CountDistinct, Sum, and Average. We show how to construct several types of histograms, such as simple Equi-Width, Average Shifted Equi-Width, and Equi-Depth histograms. We present a full-fledged open-source implementation
of these tools for distributed statistical synopses,
and report on a comprehensive experimental performance evaluation, evaluating our contributions in terms of efficiency, accuracy, and scalability.
Abstract: The peer-to-peer computing paradigm is an intriguing alternative to Google-style search
engines for querying and ranking Web content. In a network with many thousands or
millions of peers the storage and access load requirements per peer are much lighter
than for a centralized Google-like server farm; thus more powerful techniques from information
retrieval, statistical learning, computational linguistics, and ontological reasoning
can be employed on each peerĒs local search engine for boosting the quality
of search results. In addition, peers can dynamically collaborate on advanced and particularly
difficult queries. Moroever, a peer-to-peer setting is ideally suited to capture
local user behavior, like query logs and click streams, and disseminate and aggregate
this information in the network, at the discretion of the corresponding user, in order to
incorporate richer cognitive models.
This paper gives an overview of ongoing work in the EU Integrated Project DELIS
that aims to develop foundations for a peer-to-peer search engine with Google-or-better
scale, functionality, and quality, which will operate in a completely decentralized and
self-organizing manner. The paper presents the architecture of such a system and the
Minerva prototype testbed, and it discusses various core pieces of the approach: efficient
execution of top-k ranking queries, strategies for query routing when a search request
needs to be forwarded to other peers, maintaining a self-organizing semantic overlay
network, and exploiting and coping with user and community behavior.