644 research outputs found
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-
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HARD: Hybrid Adaptive Resource Discovery for Jungle Computing
In recent years, Jungle Computing has emerged as a distributed computing paradigm based on simultaneous combination of various hierarchical and distributed computing environments which are composed by large number of heterogeneous resources. In such a computing environment, the resources and the underlying computation and communication infrastructures are highly-hierarchical and heterogeneous. This creates a lot of difficulty and complexity for finding the proper resources in a precise way in order to run a particular job on the system efficiently. This paper proposes Hybrid Adaptive Resource Discovery (HARD), a novel efficient and highly scalable resource-discovery approach which is built upon a virtual hierarchical overlay based on self-organization and self-adaptation of processing resources in the system, where the computing resources are organized into distributed hierarchies according to a proposed hierarchical multi-layered resource description model. The proposed approach supports distributed query processing within and across hierarchical layers by deploying various distributed resource discovery services and functionalities in the system which are implemented using different adapted algorithms and mechanisms in each level of hierarchy. The proposed approach addresses the requirements for resource discovery in Jungle Computing environments such as high-hierarchy, high-heterogeneity, high-scalability and dynamicity. Simulation results show significant scalability and efficiency of the proposed approach over highly heterogeneous, hierarchical and dynamic computing environments
Systematizing Decentralization and Privacy: Lessons from 15 Years of Research and Deployments
Decentralized systems are a subset of distributed systems where multiple
authorities control different components and no authority is fully trusted by
all. This implies that any component in a decentralized system is potentially
adversarial. We revise fifteen years of research on decentralization and
privacy, and provide an overview of key systems, as well as key insights for
designers of future systems. We show that decentralized designs can enhance
privacy, integrity, and availability but also require careful trade-offs in
terms of system complexity, properties provided, and degree of
decentralization. These trade-offs need to be understood and navigated by
designers. We argue that a combination of insights from cryptography,
distributed systems, and mechanism design, aligned with the development of
adequate incentives, are necessary to build scalable and successful
privacy-preserving decentralized systems
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