Contributory applications allow users to donate unused resources on their personal computers to a shared pool. Applications such as

A noteworthy advance in distributed computing is due to the recent development of peer-to-peer systems. These systems are essentially dynamic in the sense that no process can get a global knowledge on the system structure. They mainly allow processes to look up for data that can be dynamically added/suppressed in a permanently evolving set of nodes. Although protocols have been developed for such dynamic systems, to our knowledge, up to date no computation model for dynamic systems has been proposed. Nevertheless, there is a strong demand for the definition of such models as soon as one wants to develop provably correct protocols suited to dynamic systems. This paper proposes a model for (a class of) dynamic systems. That dynamic model is defined by (1) a parameter (an integer denoted α) and (2) two basic communication abstractions (query-response and persistent reliable broadcast). The new parameter α is a threshold value introduced to capture the liveness part of the system (it is the counterpart of the minimal number of processes that do not crash in a static system). To show the relevance of the model, the paper adapts an eventual leader protocol designed for the static model, and proves that the resulting protocol is correct within the proposed dynamic model. In that sense, the paper has also a methodological flavor, as it shows that simple modifications to existing protocols can allow them to work in dynamic systems. Key-words: Communication abstraction, Dynamic system, Persistent reliable broadcast, Query-response pattern,

Contributory applications allow users to donate unused resources on their personal computers to a shared pool. Applications such as

This paper offers a survey of the emerging field of private peer-to-peer networks, which can be defined as internet overlays in which the resources and infrastructure are provided by the users, and new users may only join by personal invitation. The last few years have seen rapid developments in this field, many of which have not previously been described in the research literature. We describe deployed systems, classify them architecturally, and identify some technical and social tradeoffs in the design of private peer-to-peer networks.

Peer-to-Peer (P2P) networks have become prevalent recently, thanks in large part to the publicity surrounding file-sharing networks, but P2P is evolving to encompass a wide-ranging set of applications. For many of these, a resource discovery mechanism is an essential basic service, but the properties of P2P networks make provision of this a non-trivial task. Solutions proposed have included central indexes, flooding and message forwarding, but the most promising appears to be the use of Distributed Hash Tables (DHTs). DHTs have been used to provide data lookup within logarithmic message costs whilst only requiring maintenance of limited amounts of routing state. One of the most widely known DHTs is Chord, which provides lookup in typically O(log n) hops across the network, where n is the number of nodes in the structure. Understanding that this message cost is proportional to the network size, our contribution is ROME (Reactive Overlay Monitoring and Expansion), a set of processes which run on top of the Chord DHT to provide control over network size. Every node acts as an

Over the past few years, capturing the characteristics of the Gnutella overlay network has been one of the major research activities in distributed computing. While most of the works are focusing on the node degree distribution, upstream/downstream traffics and file distribution, only a few have been done on modeling the session lifetime distribution. A good model of the session lifetime distribution is basically a key to understand the formation and evolution of the topological structure of Gnutella. In this paper, the main objective is to present a measurement result we did in 2003 on the session lifetime distribution and make comparison with the results obtained by other researchers during 2001 to 2005. In accordance with our measurement, it is found that the lifetime distribution fits to a power law distribution with exponential cut-off. Specifically, for all t ≥ 15 minutes, Pl(t) ∝ (t/780) −1.12 exp(−t/780). By inspecting the slopes of the log-log curve (i.e. ∂ log Pl(t)/ ∂ log t) at 20 minutes (i.e. short lifetime) and 600 minutes (i.e. long lifetime), it is also found that the shape of our model matches to those curves obtained by other researchers based on the measurements in 2001, 2002 and 2004. Therefore it is observed that the session lifetime distribution of Gnutella might be an invariant characteristic independent of the technological advancement or protocol change during the period 2002 to 2005.

This is an addendum to our report “Performance