Exploiting the Synergy Between Gossiping and Structured Overlays

In this position paper we argue for exploiting the synergy between gossip-based algorithms and structured overlay networks (SON). These two strands of research have both aimed at building fault-tolerant, dynamic, self-managing, and large-scale distributed systems. Despite the common goals, the two areas have, however, been relatively isolated. We focus on three problem domains where there is an untapped potential of using gossiping combined with SONs. We argue for applying gossip-based membership for ring-based SONs---such as Chord and Bamboo---to make them handle partition mergers and loopy networks. We argue that small world SONs---such as Accordion and Mercury---are specifically well-suited for gossip-based membership management. The benefits would be better graph-theoretic properties. Finally, we argue that gossip-based algorithms could use the overlay constructed by SONs. For example, many unreliable broadcast algorithms for SONs could be augmented with anti-entropy protocols. Similarly, gossip-based aggregation could be used in SONs for network size estimation and load-balancing purposes

Problem-solving methods for understanding process executions

Problem-solving methods are high-level, domain-independent, reusable knowledge templates that support the development of knowledge-intensive applications. The authors show how to use them to bolster subject-matter experts' understanding of process execution by implementing such methods into the Knowledge-Oriented Provenance Environment

The Death of Semar

Melalui artikel ini penulis menelaah peran memori kultural pada masainterkoneksi global sekarang ini. Penulis mensinyalir bahwa gagasan tradisionaltentang budaya terancam oleh “industri budaya” seperti teknologi informasi danmedia masa. Di Dunia Barat, fungsi budaya sebagai mesin perubahan dan reformasitampak tergerus oleh industri tersebut. Tapi di Asia Tenggara – khususnya Indonesia– kekuatan eksternal serta upaya internal untuk mempertahankan identitas budayalokal tetap terjaga agar berimbang. Isu ini diteropong berdasarkan perpektif Michelde Certeau. Gagasan ini ditampilkan melalui telaah kisah “kematian Semar” dalamWayang. Kesadaran akan keberimbangan antara pengaruh eksternal dan pemeliharaanbudaya internal itu sangatlah penting di dalam menyikapi jaringan kekuatan globalyang memaksakan masuknya berbagai struktur religius, politik, kekuangan danhukum ke dalam budaya Indonesia. This essay will examine the role of cultural memory in an age of globalinterconnection. It will discuss how the traditional idea of culture is threatened by the “culture industry,” information technology and the media. In the West, there seemsto be a loss of culture’s function as an engine of change and reform. But throughoutthe history of South East Asia (and especially in Indonesia) one sees a both a processof appropriation of ideas from the outside, and at the same time, the maintenance ofa deeper cultural identity that is resistant to complete control. It is an unconsciousmemory – or a cultural reflex – present within the languages and stories and rationalities.I will explain this with reading of Michel de Certeau . And I will show how the Wayangstory of the “Death of Semar” is emblematic of this idea. The awareness of these oldprocesses of appropriation and resistance are extremely important in our age of globalnetworks of power that attempt to impose, various religious, political, financial andlegal structures. &nbsp

Socially-Aware Distributed Hash Tables for Decentralized Online Social Networks

Many decentralized online social networks (DOSNs) have been proposed due to an increase in awareness related to privacy and scalability issues in centralized social networks. Such decentralized networks transfer processing and storage functionalities from the service providers towards the end users. DOSNs require individualistic implementation for services, (i.e., search, information dissemination, storage, and publish/subscribe). However, many of these services mostly perform social queries, where OSN users are interested in accessing information of their friends. In our work, we design a socially-aware distributed hash table (DHTs) for efficient implementation of DOSNs. In particular, we propose a gossip-based algorithm to place users in a DHT, while maximizing the social awareness among them. Through a set of experiments, we show that our approach reduces the lookup latency by almost 30% and improves the reliability of the communication by nearly 10% via trusted contacts.Comment: 10 pages, p2p 2015 conferenc

Relation Discovery from Web Data for Competency Management

This paper describes a technique for automatically discovering associations between people and expertise from an analysis of very large data sources (including web pages, blogs and emails), using a family of algorithms that perform accurate named-entity recognition, assign different weights to terms according to an analysis of document structure, and access distances between terms in a document. My contribution is to add a social networking approach called BuddyFinder which relies on associations within a large enterprise-wide "buddy list" to help delimit the search space and also to provide a form of 'social triangulation' whereby the system can discover documents from your colleagues that contain pertinent information about you. This work has been influential in the information retrieval community generally, as it is the basis of a landmark system that achieved overall first place in every category in the Enterprise Search Track of TREC2006

Social Search with Missing Data: Which Ranking Algorithm?

Online social networking tools are extremely popular, but can miss potential discoveries latent in the social 'fabric'. Matchmaking services which can do naive profile matching with old database technology are too brittle in the absence of key data, and even modern ontological markup, though powerful, can be onerous at data-input time. In this paper, we present a system called BuddyFinder which can automatically identify buddies who can best match a user's search requirements specified in a term-based query, even in the absence of stored user-profiles. We deploy and compare five statistical measures, namely, our own CORDER, mutual information (MI), phi-squared, improved MI and Z score, and two TF/IDF based baseline methods to find online users who best match the search requirements based on 'inferred profiles' of these users in the form of scavenged web pages. These measures identify statistically significant relationships between online users and a term-based query. Our user evaluation on two groups of users shows that BuddyFinder can find users highly relevant to search queries, and that CORDER achieved the best average ranking correlations among all seven algorithms and improved the performance of both baseline methods

Similitude:decentralised adaptation in large-scale P2P recommenders

Decentralised recommenders have been proposed to deliver privacy-preserving, personalised and highly scalable on-line recommendations. Current implementations tend, however, to rely on a hard-wired similarity metric that cannot adapt. This constitutes a strong limitation in the face of evolving needs. In this paper, we propose a framework to develop dynamically adaptive decentralised recommendation systems. Our proposal supports a decentralised form of adaptation, in which individual nodes can independently select, and update their own recommendation algorithm, while still collectively contributing to the overall system’s mission. Keyword