A super-peer is a node in a peer-to-peer network that operates both as a server to a set of clients, and as an equal in a network of super-peers. Super-peer networks strike a balance between the efficiency of centralized search, and the autonomy, load balancing and robustness to attacks provided by distributed search. Furthermore, they take advantage of the heterogeneity of capabilities (e.g., bandwidth, processing power) across peers, which recent studies have shown to be enormous. Hence, new and old P2P systems like KaZaA and Gnutella are adopting super-peers in their design. Despite their growing popularity, the behavior of super-peer networks is not well understood. For example, what are the potential drawbacks of super-peer networks? How can super-peers be made more reliable? How many clients should a super-peer take on to maximize efficiency? we examine super-peer networks in detail, gaming an understanding of their fundamental characteristics and performance tradeoffs. We also present practical guidelines and a general procedure for the design of an efficient super-peer network.

Designing an Super-Peer Network

Many network solutions and overlay networks utilize probabilistic techniques to reduce information processing and networking costs. This survey article presents a number of frequently used and useful probabilistic techniques. Bloom filters and their variants are of prime importance, and they are heavily used in various distributed systems. This has been reflected in recent research and many new algorithms have been proposed for distributed systems that are either directly or indirectly based on Bloom filters. In this survey, we give an overview of the basic and advanced techniques, reviewing over 20 variants and discussing their application in distributed systems, in particular for caching, peer-to-peer systems, routing and forwarding, and measurement data summarization.

/pdf/theory-and-practice-of-bloom-filters-for-distributed-systems-5a641nvijc.pdf

Theory and Practice of Bloom Filters for Distributed Systems

Cloud Computing is rising fast, with its data centres growing at an unprecedented rate. However, this has come with concerns over privacy, efficiency at the expense of resilience, and environmental sustainability, because of the dependence on Cloud vendors such as Google, Amazon and Microsoft. Our response is an alternative model for the Cloud conceptualisation, providing a paradigm for Clouds in the community, utilising networked personal computers for liberation from the centralised vendor model. Community Cloud Computing (C3) offers an alternative architecture, created by combing the Cloud with paradigms from Grid Computing, principles from Digital Ecosystems, and sustainability from Green Computing, while remaining true to the original vision of the Internet. It is more technically challenging than Cloud Computing, having to deal with distributed computing issues, including heterogeneous nodes, varying quality of service, and additional security constraints. However, these are not insurmountable challenges, and with the need to retain control over our digital lives and the potential environmental consequences, it is a challenge we must pursue.

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Community Cloud Computing

Recent developments in information technology have brought about important changes in distributed computing. New environments such as massively large-scale, wide-area computer networks and mobile ad hoc networks have emerged. Common characteristics of these environments include extreme dynamicity, unreliability, and large scale. Traditional approaches to designing distributed applications in these environments based on central control, small scale, or strong reliability assumptions are not suitable for exploiting their enormous potential. Based on the observation that living organisms can effectively organize large numbers of unreliable and dynamically-changing components (cells, molecules, individuals, etc.) into robust and adaptive structures, it has long been a research challenge to characterize the key ideas and mechanisms that make biological systems work and to apply them to distributed systems engineering. In this article we propose a conceptual framework that captures several basic biological processes in the form of a family of design patterns. Examples include plain diffusion, replication, chemotaxis, and stigmergy. We show through examples how to implement important functions for distributed computing based on these patterns. Using a common evaluation methodology, we show that our bio-inspired solutions have performance comparable to traditional, state-of-the-art solutions while they inherit desirable properties of biological systems including adaptivity and robustness.

Design Patterns from Biology for Distributed Computing

The success of a P2P file-sharing network highly depends on the scalability and versatility of its search mechanism. Two particularly desirable search features are scope (ability to find infrequent items) and support for partial-match queries (queries that contain typos or include a subset of keywords). While centralized-index architectures (such as Napster) can support both these features, existing decentralized architectures seem to support at most one: prevailing unstructured P2P protocols (such as Gnutella and FastTrack) deploy a "blind" search mechanism where the set of peers probed is unrelated to the query; thus they support partial-match queries but have limited scope. On the other extreme, the recently-proposed distributed hash tables (DHTs) such as CAN and CHORD, couple index location with the item's hash value, and thus have good scope but can not effectively support partial-match queries. Another hurdle to DHTs deployment is their tight control of the overlay structure and the information (part of the index) each peer maintains, which makes them more sensitive to failures and frequent joins and disconnects. We develop a new class of decentralized P2P architectures. Our design is based on unstructured architectures such as gnutella and FastTrack, and retains many of their appealing properties including support for partial match queries, and relative resilience to peer failures. Yet, we obtain orders of magnitude improvement in the efficiency of locating rare items. Our approach exploits associations inherent in human selections to steer the search process to peers that are more likely to have an answer to the query. We demonstrate the potential of associative search using models, analysis, and simulations.

/pdf/associative-search-in-peer-to-peer-networks-harnessing-2nn87629y5.pdf

Associative search in peer to peer networks: harnessing latent semantics

Algorithms by which peers join and leave structured overlay networks can be classified as passive or active. Passive topology maintenance relies on periodic background repair of neighbor pointers. When a node passively leaves the overlay, subsequent lookups may fail silently. Active maintenance has been proven only for fault-free networks. We develop an active topology maintenance algorithm for practical, fault-prone networks. Unlike prior work, it a) maintains ring continuity during normal topology changes and b) guarantees consistency and progress in the presence of faults. The latter property is inherited by novel extension of the Paxos commit algorithm. The topology maintenance algorithm is formally developed using the B method and its event-driven extensions for dynamic systems. Messaging and storage overheads are quantified

Fault Tolerant Active Rings for Structured Peer-to-Peer Overlays

Most research on Distributed Hash Tables (DHTs) assumes ephemeral, lightly loaded deployments. Each node has a lifetime of a few hours and initiates a lookup once every few seconds or minutes. However, in giant internet data centers, each node has a lifetime of weeks or months and initiates hundreds or thousands of lookups every second. In such an environment, one-hop DHTs are superior to multi-hop DHTs. They use lookup bandwidth more efficiently. We qualify conflicting research to show that a single onehop DHT can indeed scale to at least a few hundred thousand nodes in stable, high-capacity enterprise networks. Two new designs are presented: One Hop Sites (1HS), a high-capacity DHT tailored for site redundancy; and the One Hop Federation (1HF), a global, hierarchic DHT that resolves an open latency problem. For both, the analysis a) confirms linear scalability to at least a few hundred thousand nodes and b) identifies the most sensitive design parameters.

Stable High-Capacity One-Hop Distributed Hash Tables

Many distributed hash tables (DHTs) resolve lookups in O(\log n) hops, where n is the number of nodes. One-hop DHTs give lower lookup latencies and lower lookup failure rates. However, it is hard to maintain large, wide-area one-hop topologies. We contribute aecast, a new topology dissemination algorithm for one-hop DHTs. It avoids expensive repair mechanisms and critical points of failure in existing one-hop DHTs. When a node discovers by anti-entropy that it has missed a topology update, it initiates "controlled flooding,rdquo sending the update to nodes in the multicast tree that also missed the update. We compare aecast with a widely cited epidemic multicasting algorithm, pbcast, by analysis and simulation. Aecast gives at least fivefold fewer out-of-date nodes on average within one round of a topology update. We support it with a fault-tolerant topology agreement protocol, so that only legitimate topology changes propagate throughout the overlay. Consequently, we argue that one-hop DHTs deserve greater attention for Internet applications in which reasonably reliable nodes carry high lookup loads.

Topology Dissemination for Reliable One-Hop Distributed Hash Tables

The pace of research on peer-to-peer (P2P) networking in the last five years warrants a critical survey. P2P has the makings of a disruptive technology--it can aggregate enormous storage and processing resources while minimizing entry and scaling costs. Failures are common amongst massive numbers of distributed peers, though the impact of individual failures may be less than in conventional architectures. Thus the key to realizing P2P's potential in applications other than casual file sharing is robustness.P2P search methods are first couched within an overall P2P taxonomy. P2P indexes for simple key lookup are assessed, including those based on Plaxton trees, rings, tori, butterflies, de Bruijn graphs and skip graphs. Similarly, P2P indexes for keyword lookup, information retrieval and data management are explored. Finally, early efforts to optimize range, multiattribute, join and aggregation queries over P2P indexes are reviewed. Insofar as they are available in the primary literature, robustness mechanisms and metrics are highlighted throughout. However, the low-level mechanisms that most affect robustness are not well isolated in the literature. Furthermore, there has been little consensus on robustness metrics. Recommendations are given for future research.

Survey of Research towards Robust Peer-to-Peer Networks: Search Methods.

A location service is the part of a naming architecture that maps identifiers to network addresses. Ideally, the identifiers are globally unique, persistent and semantic-free. It has been acknowledged that Distributed Hash Tables (DHTs) enable, for the first time, the use of semantic-free identifiers in massive, global networks. We argue that hierarchy is essential for dependability in massive, geographically distributed DHTs. Existing hierarchic DHTs embed location information in identifiers. Consequently, if identifiers move between DHTs in the hierarchy, then the changes always propagate to the root DHT. This Location Information Plane (LIP) design is the first hierarchic DHT that contains "moves and changes" within the lower layers of the hierarchy. It protects the root DHT using the rendezvous abstraction. We show how it supports global internet telephony networks based on the Session Initiation Protocol (SIP).

A Dependable Global Location Service using Rendezvous on Hierarchic Distributed Hash Tables

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