Self-Organization in Peer-to-Peer Systems

Peer-to-Peer Systems are about community-based cooperations. The peers share responsibilities and benefits by cooperating in a distributed and decentralized environment. To carry out tasks sensibly, however, a more or less rigid order is required for efficiency and reliability reasons. This order can be partially imposed from the outside, for example within so-called "structed" Peer-to-Peer systems. A common approach here is the use of Distributed Hash Tables. Alternatively, Peer-to-Peer systems can be "unstructured" in the sense that an useful order emerges from own internal processes. Unstructured and structured Peer-to-Peer systems rely both on a more or less decentralized overlay management. Self-organization, therefore, is a key to the success of Peer-to-Peer systems in various forms. This presentation gives an overview of the role of self-organization in Peer-to-Peer systems

An Arbitrary 2D Structured Replica Control Protocol

Traditional replication protocols that logically arrange the replicas into a specific structure have reasonable availability, lower communication cost as well as system load than those that do not require any logical organisation of replicas. We propose in this paper the A2DS protocol: a single protocol that, unlike the existing proposed protocols, can be adapted to any 2D structure. Its read operation is carried out on any replica of every level of the structure whereas write operations are performed on all replicas of a single level of the structure. We present several basic 2D structures and introduce the new idea of obtaining other 2D structures by the composition of several basic ones. Two structures are proposed that have near optimal performance in terms of the communication cost, availability and system load of their read and write operations. Also, we introduce a new protocol that provides better performance for its write operations than those of ROWA protocol while preserving similar read performance

Using System Virtualization to Create Virtualized Networks

The method of system virtualization is very popular for the use in data centers and desktop virtualization today. In this work, system virtualization is applied to core network elements (routers and links) in order to create a virtualized network. The selection of this virtualization method crucially determines the emerging network model. The network model consists of virtual networks, virtual routers, and virtual links that form overlays on top of the physical network. The properties, features, and limitations of this network model are analyzed and described in this paper. Additionally, a proof of concept implementation using currently available technology and infrastructure is presented. Finally the dynamic configurability of virtual resources in such a system virtualization based virtualized network is evaluated

Modeling of Self-Organizing Systems: An Overview

This paper gives a systematic overview on modeling formalisms suitable for modeling self-organizing systems. We distinguish between micro-level modeling and macro-level modeling. On the micro level, the behavior of each entity and the interaction between different object must be described by the model. Macrolevel modeling abstracts from the individual entities and only looks at the behavior of the system variables of interest. The differentiations between discrete and continuous time and between discrete and continuous state space lead to different descriptions of the model

04411 Abtracts Collection -- Service Management and Self-Organization in IP-based Networks

From 03.10.04 to 06.10.04, the Dagstuhl Seminar 04411 ``Service Management and Self-Organization in IP-based Networks\u27\u27 was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available

Modeling Wireless Sensor Networks Using Finite-Source Retrial Queues with Unreliable Orbit

Abstract. Motivated by the need for performance models suitable for modeling and evaluation of wireless sensor networks, we introduce a retrial queueing system with a finite number of homogeneous sources, unreliable servers, orbital search, and unreliable orbit. All random variables involved in model construction are assumed to be independent and exponentially distributed. Providing a generalized stochastic Petri net model of the system, steady-state analysis of the underlying continuous-time Markov chain is performed and steady-state performance measures are computed by the help of the MOSEL-2 tool. The main novelty of this investigation is the introduction of an unreliable orbit and its application to wireless sensor networks. Numerical examples are derived to show the influence of sleep/awake time ratio, message dropping, and message blocking on the senor nodes' performance

Making data centres fit for demand response: introducing GreenSDA and GreenSLA contracts

The power grid has become a critical infrastructure, which modern society cannot do without. It has always been a challenge to keep power supply and demand in balance; the more so with the recent rise of intermittent renewable energy sources. Demand response schemes are one of the counter measures, traditionally employed with large industrial plants. This paper suggests to consider data centres as candidates for demand response as they are large energy consumers and as they are able to adapt their power profile sufficiently well. To unlock this potential, we suggest a system of contracts that regulate collaboration and economic incentives between the data centre and its energy supplier (GreenSDA) as well as between the data centre and its customers (GreenSLA). Several presented use cases serve to validate the suitability of data centers for demand response schemes.Peer ReviewedPostprint (author's final draft