Data Mining - Concepts and Techniques.

The Grid 2: Blueprint for a New Computing Infrastructure

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

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Rfid Handbook Fundamentals And Applications In Contactless Smart Cards And Identification

A survey on bio-inspired networking

Existing density-based data stream clustering algorithms use a two-phase scheme approach consisting of an online phase, in which raw data is processed to gather summary statistics, and an offline phase that generates the clusters by using the summary data. In this article we propose a data stream clustering method based on a multi-agent system that uses a decentralized bottom-up self-organizing strategy to group similar data points. Data points are associated with agents and deployed onto a 2D space, to work simultaneously by applying a heuristic strategy based on a bio-inspired model, known as flocking model. Agents move onto the space for a fixed time and, when they encounter other agents into a predefined visibility range, they can decide to form a flock if they are similar. Flocks can join to form swarms of similar groups. This strategy allows to merge the two phases of density-based approaches and thus to avoid the computing demanding offline cluster computation, since a swarm represents a cluster. Experimental results show that the bio-inspired approach can obtain very good results on real and synthetic data sets.

/pdf/a-single-pass-algorithm-for-clustering-evolving-data-streams-4uz4atig8e.pdf

A single pass algorithm for clustering evolving data streams based on swarm intelligence

This paper presents "Self-Chord," a peer-to-peer (P2P) system that inherits the ability of Chord-like structured systems for the construction and maintenance of an overlay of peers, but features enhanced functionalities deriving from ant-inspired algorithms, such as autonomous behavior, self-organization, and capacity to adapt to a changing environment. As opposed to the structured P2P systems deployed so far, resource indexing and placement is uncorrelated with network structure and topology, and resource keys are organized and managed by self-organizing mobile agents through simple local operations driven by probabilistic choices. Self-Chord has three main features that are particularly advantageous in Grid and Cloud Computing: 1) it is possible to give a semantic meaning to keys, which enables the execution of range queries; 2) the keys are fairly distributed over the peers, thus improving the balancing of storage responsibilities; 3) maintenance load is also limited because it is not necessary to reassign keys when new peers or resources are added to the system--the mobile agents will spontaneously reorganize the keys. The efficiency and effectiveness of Self-Chord were assessed both with a simulation framework and with an analytical model inspired by fluid dynamics.

/pdf/self-chord-a-bio-inspired-p2p-framework-for-self-organizing-478ectbehg.pdf

Self-chord: a bio-inspired P2P framework for self-organizing distributed systems

This paper presents "Self-Chord," a peer-to-peer (P2P) system that inherits the ability of Chord-like structured sys- tems for the construction and maintenance of an overlay of peers, but features enhanced functionalities deriving from ant-inspired algorithms, such as autonomous behavior, self-organization, and capacity to adapt to a changing environment. As opposed to the structured P2P systems deployed so far, resource indexing and placement is uncorrelated with network structure and topology, and resource keys are organized and managed by self-organizing mobile agents through simple local operations driven by prob- abilistic choices. Self-Chord has three main features that are particularly advantageous in Grid and Cloud Computing: 1) it is possible to give a semantic meaning to keys, which enables the execution of range queries; 2) the keys are fairly distributed over the peers, thus improving the balancing of storage responsibilities; 3) maintenance load is also limited because it is not necessary to reassign keys when new peers or resources are added to the system—the mobile agents will spontaneously reorganize the keys. The efficiency and effectiveness of Self-Chord were assessed both with a simulation framework and with an analytical model inspired by fluid dynamics.

Self-Chord: A Bio-Inspired P2P Framework for

Social media, in recent years, have become an invaluable source of information for both public and private organizations to enhance the comprehension of people interests and the onset of new events. Twitter, especially, allows a fast spread of news and events happening real time that can contribute to situation awareness during emergency situations, but also to understand trending topics of a period. The article proposes an online algorithm that incrementally groups tweet streams into clusters. The approach summarizes the examined tweets into the cluster centroid by maintaining a number of textual and temporal features that allow the method to effectively discover groups of interest on particular themes. Experiments on messages posted by users addressing different issues, and a comparison with state-of-the-art approaches show that the method is capable to detect discussions regarding topics of interest, but also to distinguish bursty events revealed by a sudden spreading of attention on messages published by users.

Bursty Event Detection in Twitter Streams

The Internet of Things (IoT) aims to bridge the gap between the physical and the cyber world to allow a deeper understanding of user preferences and behaviors. The interactions and relations between users and things need of an effective and efficient recommendation approaches to better meet users interests. Suggesting useful things in IoT environment is a very important task for many applications such as urban computing, smart cities, health care, etc., and it needs to be widely investigated. The goal of recommendation systems is to produce a set of significant suggestions for a user with given characteristics. In this paper, a multi-agent algorithm that, by exploiting of a decentralized and self organizing strategy, builds a distributed recommendation system in IoT environment, is proposed. Things are represented through bit vectors, the thing descriptors, obtained through a locality preserving hash function that maps similar things into similar bit vectors. Cyber agents manage the thing descriptors and exchange them on the basis of ad-hoc probability functions. The outcome is the emergence of an organized overlay-network of cyber agents that allows to obtain an efficient things recommender system. Preliminaries results confirm the validity of the approach.

Agostino Forestiero

Papers

A single pass algorithm for clustering evolving data streams based on swarm intelligence

Self-chord: a bio-inspired P2P framework for self-organizing distributed systems

Self-Chord: A Bio-Inspired P2P Framework for

Bursty Event Detection in Twitter Streams

Multi-agent recommendation system in Internet of Things