1,171 research outputs found
Searching in Unstructured Overlays Using Local Knowledge and Gossip
This paper analyzes a class of dissemination algorithms for the discovery of
distributed contents in Peer-to-Peer unstructured overlay networks. The
algorithms are a mix of protocols employing local knowledge of peers'
neighborhood and gossip. By tuning the gossip probability and the depth k of
the k-neighborhood of which nodes have information, we obtain different
dissemination protocols employed in literature over unstructured P2P overlays.
The provided analysis and simulation results confirm that, when properly
configured, these schemes represent a viable approach to build effective P2P
resource discovery in large-scale, dynamic distributed systems.Comment: A revised version of the paper appears in Proc. of the 5th
International Workshop on Complex Networks (CompleNet 2014) - Studies in
Computational Intelligence Series, Springer-Verlag, Bologna (Italy), March
201
Self-Healing Protocols for Connectivity Maintenance in Unstructured Overlays
In this paper, we discuss on the use of self-organizing protocols to improve
the reliability of dynamic Peer-to-Peer (P2P) overlay networks. Two similar
approaches are studied, which are based on local knowledge of the nodes' 2nd
neighborhood. The first scheme is a simple protocol requiring interactions
among nodes and their direct neighbors. The second scheme adds a check on the
Edge Clustering Coefficient (ECC), a local measure that allows determining
edges connecting different clusters in the network. The performed simulation
assessment evaluates these protocols over uniform networks, clustered networks
and scale-free networks. Different failure modes are considered. Results
demonstrate the effectiveness of the proposal.Comment: The paper has been accepted to the journal Peer-to-Peer Networking
and Applications. The final publication is available at Springer via
http://dx.doi.org/10.1007/s12083-015-0384-
On the Topology Maintenance of Dynamic P2P Overlays through Self-Healing Local Interactions
This paper deals with the use of self-organizing protocols to improve the
reliability of dynamic Peer-to-Peer (P2P) overlay networks. We present two
approaches, that employ local knowledge of the 2nd neighborhood of nodes. The
first scheme is a simple protocol requiring interactions among nodes and their
direct neighbors. The second scheme extends this approach by resorting to the
Edge Clustering Coefficient (ECC), a local measure that allows to identify
those edges that connect different clusters in an overlay. A simulation
assessment is presented, which evaluates these protocols over uniform networks,
clustered networks and scale-free networks. Different failure modes are
considered. Results demonstrate the viability of the proposal.Comment: A revised version of the paper appears in Proc. of the IFIP
Networking 2014 Conference, IEEE, Trondheim, (Norway), June 201
LHView: Location Aware Hybrid Partial View
The rise of the Cloud creates enormous business opportunities for companies to provide
global services, which requires applications supporting the operation of those services
to scale while minimizing maintenance costs, either due to unnecessary allocation of
resources or due to excessive human supervision and administration. Solutions designed
to support such systems have tackled fundamental challenges from individual component
failure to transient network partitions. A fundamental aspect that all scalable large
systems have to deal with is the membership of the system, i.e, tracking the active components
that compose the system. Most systems rely on membership management protocols
that operate at the application level, many times exposing the interface of a logical overlay
network, that should guarantee high scalability, efficiency, and robustness.
Although these protocols are capable of repairing the overlay in face of large numbers
of individual components faults, when scaling to global settings (i.e, geo-distributed
scenarios), this robustness is a double edged-sword because it is extremely complex for
a node in a system to distinguish between a set of simultaneously node failures and a
(transient) network partition. Thus the occurrence of a network partition creates isolated
sub-sets of nodes incapable of reconnecting even after the recovery from the partition.
This work address this challenges by proposing a novel datacenter-aware membership
protocol to tolerate network partitions by applying existing overlay management techniques
and classification techniques that may allow the system to efficiently cope with
such events without compromising the remaining properties of the overlay network. Furthermore,
we strive to achieve these goals with a solution that requires minimal human
intervention
Overlay networks monitoring
The phenomenal growth of the Internet and its entry into many aspects of daily life has led to a great dependency on its services. Multimedia and content distribution applications (e.g., video streaming, online gaming, VoIP) require Quality of Service (QoS) guarantees in terms of bandwidth, delay, loss, and jitter to maintain a certain level of performance. Moreover, E-commerce applications and retail websites are faced with increasing demand for better throughput and response time performance. The most practical way to realize such applications is through the use of overlay networks, which are logical networks that implement service and resource management functionalities at the application layer.
Overlays offer better deployability, scalability, security, and resiliency properties than network layer based implementation of
services.
Network monitoring and routing are among the most important issues in the design and operation of overlay networks. Accurate monitoring
of QoS parameters is a challenging problem due to: (i) unbounded link stress in the underlying IP network, and (ii) the conflict in measurements caused by spatial and temporal overlap among
measurement tasks. In this context, the focus of this dissertation is on the design and evaluation of efficient QoS monitoring and fault location algorithms using overlay networks.
First, the issue of monitoring accuracy provided by multiple concurrent active measurements is studied on a large-scale overlay test-bed (PlanetLab), the factors affecting the accuracy are
identified, and the measurement conflict problem is introduced. Then, the problem of conducting conflict-free measurements is formulated as a scheduling problem of real-time tasks, its
complexity is proven to be NP-hard, and efficient heuristic algorithms for the problem are proposed. Second, an algorithm for minimizing monitoring overhead while controlling the IP link stress is proposed. Finally, the use of overlay monitoring to locate IP links\u27 faults is investigated. Specifically, the problem of designing an overlay network for verifying the location of IP links\u27
faults, under cost and link stress constraints, is formulated as an integer generalized flow problem, and its complexity is proven to be
NP-hard. An optimal polynomial time algorithm for the relaxed problem (relaxed link stress constraints) is proposed.
A combination of simulation and experimental studies using real-life measurement tools and Internet topologies of major ISP networks is
conducted to evaluate the proposed algorithms. The studies show that the proposed algorithms significantly improve the accuracy and link
stress of overlay monitoring, while incurring low overheads. The evaluation of fault location algorithms show that fast and highly
accurate verification of faults can be achieved using overlay monitoring. In conclusion, the holistic view taken and the solutions
developed for network monitoring provide a comprehensive framework for the design, operation, and evolution of overlay networks
A Practical Study of Self-Stabilization for Prefix-Tree Based Overlay Networks
Service discovery is crucial in the development of fully decentralized computational grids. Among the significant amount of work produced by the convergence of peer-to-peer (P2P) systems and grids, a new kind of overlay networks, based on prefix trees, has emerged. In particular, the Distributed Lexicographic Placement Table (DLPT) approach is a decentralized and dynamic service discovery service. Fault-tolerance within the DLPT approach is achieved through best-effort policies relying on formal self-stabilization results. Self-stabilization means that the tree can become transiently inconsistent, but is guaranteed to autonomously converge to a correct topology after arbitrary crashes, in a finite time. However, during convergence, the tree may not be able to process queries correctly. In this paper, we present some simulation results having several objectives. First, we investigate the interest of self-stabilization for such architectures. Second, we explore, still based on simulation, a simple Time-To-Live policy to avoid useless processing during convergence time
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