Change search
Refine search result
1 - 36 of 36
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Rows per page
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sort
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
Select
The maximal number of hits you can export is 250. When you want to export more records please use the 'Create feeds' function.
  • 1. Aberer, Karl
    et al.
    Alima, Luc Onana
    Ghodsi, Ali
    KTH, School of Information and Communication Technology (ICT), Electronic, Computer and Software Systems, ECS.
    Girdzijauskas, Sarunas
    Ecole Polytechnique Fédérale de Lausanne.
    Haridi, Seif
    KTH, School of Information and Communication Technology (ICT), Electronic, Computer and Software Systems, ECS.
    Hauswirth, Manfred
    The Essence of P2P: A Reference Architecture for Overlay Networks2005In: Fifth IEEE International Conference on Peer-to-Peer Computing, Proceedings / [ed] Caronni, G; Weiler, N; Waldvogel, M; Shahmehri, N, 2005, p. 11-20Conference paper (Refereed)
    Abstract [en]

    The success of the P2P idea has created a huge diversity of approaches, among which overlay networks, for example, Gnutella, Kazaa, Chord, Pastry, Tapestry, P-Grid, or DKS, have received specific attention from both developers and researchers. A wide variety of algorithms, data structures, and architectures have been proposed. The terminologies and abstractions used, however have become quite inconsistent since the P2P paradigm has attracted people from many different communities, e.g., networking, databases, distributed systems, graph theory, complexity theory, biology, etc. In this paper we propose a reference model for overlay networks which is capable of modeling different approaches in this domain in a generic manner It is intended to allow researchers and users to assess the properties of concrete systems, to establish a common vocabulary for scientific discussion, to facilitate the qualitative comparison of the systems, and to serve as the basis for defining a standardized API to make overlay networks interoperable.

  • 2. Apolonia, N.
    et al.
    Freitag, F.
    Navarro, L.
    Girdzijauskas, Sarunas
    KTH, School of Information and Communication Technology (ICT), Software and Computer systems, SCS.
    Vlassov, Vladimir
    KTH, School of Information and Communication Technology (ICT), Software and Computer systems, SCS.
    Gossip-based service monitoring platform for wireless edge cloud computing2017In: Proceedings of the 2017 IEEE 14th International Conference on Networking, Sensing and Control, ICNSC 2017, Institute of Electrical and Electronics Engineers (IEEE), 2017, p. 789-794, article id 8000191Conference paper (Refereed)
    Abstract [en]

    Edge cloud computing proposes to support shared services, by using the infrastructure at the network's edge. An important problem is the monitoring and management of services across the edge environment. Therefore, dissemination and gathering of data is not straightforward, differing from the classic cloud infrastructure. In this paper, we consider the environment of community networks for edge cloud computing, in which the monitoring of cloud services is required. We propose a monitoring platform to collect near real-time data about the services offered in the community network using a gossip-enabled network. We analyze and apply this gossip-enabled network to perform service discovery and information sharing, enabling data dissemination among the community. We implemented our solution as a prototype and used it for collecting service monitoring data from the real operational community network cloud, as a feasible deployment of our solution. By means of emulation and simulation we analyze in different scenarios, the behavior of the gossip overlay solution, and obtain average results regarding information propagation and consistency needs, i.e. in high latency situations, data convergence occurs within minutes.

  • 3. Bahri, Leila
    et al.
    Soliman, Amira
    KTH, School of Information and Communication Technology (ICT), Software and Computer systems, SCS.
    Squillaci, Jacopo
    Carminati, Barbara
    Ferrari, Elena
    Girdzijauskas, Sarunas
    KTH, School of Information and Communication Technology (ICT), Software and Computer systems, SCS.
    Beat the DIVa: Decentralized Identity Validation for Online Social Networks2016In: 2016 32ND IEEE INTERNATIONAL CONFERENCE ON DATA ENGINEERING (ICDE), 2016, p. 1330-1333Conference paper (Refereed)
    Abstract [en]

    Fake accounts in online social networks (OSNs) have known considerable sophistication and are now attempting to gain network trust by infiltrating within honest communities. Honest users have limited perspective on the truthfulness of new online identities requesting their friendship. This facilitates the task of fake accounts in deceiving honest users to befriend them. To address this, we have proposed a model that learns hidden correlations between profile attributes within OSN communities, and exploits them to assist users in estimating the trustworthiness of new profiles. To demonstrate our method, we suggest, in this demo, a game application through which players try to cheat the system and convince nodes in a simulated OSN to befriend them. The game deploys different strategies to challenge the players and to reach the objectives of the demo. These objectives are to make participants aware of how fake accounts can infiltrate within their OSN communities, to demonstrate how our suggested method could aid in mitigating this threat, and to eventually strengthen our model based on the data collected from the moves of the players.

  • 4.
    Datta, Anwitaman
    et al.
    Swiss Federal Institute of Technology Lausanne.
    Girdzijauskas, Sarunas
    Swiss Federal Institute of Technology Lausanne.
    Aberer, Karl
    Swiss Federal Institute of Technology Lausanne.
    On de Bruijn routing in distributed hash tables: There and back again2004In: The 4th IEEE International Conference on Peer-to-Peer Computing, proceedings, 2004, p. 159-166Conference paper (Refereed)
    Abstract [en]

    We show in this paper that de Bruijn networks, despite providing efficient search while using constant routing table size, as well as simplicity of the understanding and implementation of such networks, are unsuitable where key distribution will be uneven, a realistic scenario for most practical applications. In presence of arbitrarily skewed data distribution, it has only recently been shown that some traditional P2P overlay networks with non-constant (typically logarithmic) instead of constant routing table size can meet conflicting objectives of storage load balancing as well as search efficiency. So this paper while showing that de Bruijn networks fail, to meet these dual objectives, opens up a more general problem for the research community as to whether P2P systems with constant routing table can at all achieve the conflicting objectives of retaining search efficiency as well as storage load balancing, while preserving key ordering (which leads to uneven key distribution).

  • 5.
    Ghoorchian, Kambiz
    et al.
    KTH, School of Information and Communication Technology (ICT), Software and Computer systems, SCS. Swedish Institute of Technology (SICS).
    Girdzijauskas, Sarunas
    KTH, School of Information and Communication Technology (ICT), Software and Computer systems, SCS.
    Rahimian, Fatemeh
    DeGPar: Large Scale Topic Detection usingNode-Cut Partitioning on Dense Weighted Graphs2017In: 2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS), IEEE conference proceedings, 2017, p. 775-785, article id 7980020Conference paper (Refereed)
    Abstract [en]

    Topic Detection (TD) refers to automatic techniques for locating topically related material in web documents. Nowadays, massive amounts of documents are generated by users of Online Social Networks (OSNs), in form of very short text, tweets and snippets of news. While topic detection, in its traditional form, is applied to a few documents containing a lot of information, the problem has now changed to dealing with massive number of documents with very little information. The traditional solutions, thus, fall short either in scalability (due to huge number of input items) or sparsity (due to insufficient information per input item). In this paper we address the scalability problem by introducing an efficient and scalable graph based algorithm for TD on short texts, leveraging dimensionality reduction and clustering techniques. We first, compress the input set of documents into a dense graph, such that frequent co-occurrence patterns in the documents create multiple dense topological areas in the graph. Then, we partition the graph into multiple dense sub-graphs, each representing a topic. We compare the accuracy and scalability of our solution with two state-of-the-art solutions (including the standard LDA, and BiTerm). The results on two widely used benchmark datasets show that our algorithm not only maintains a similar or better accuracy, but also performs by an order of magnitude faster than the state-of-the-art approaches.

  • 6.
    Ghoorchian, Kambiz
    et al.
    KTH, School of Information and Communication Technology (ICT), Software and Computer systems, SCS. SICS Sweden.
    Rahimian, Fatemeh
    KTH, School of Information and Communication Technology (ICT), Software and Computer systems, SCS.
    Girdzijauskas, Sarunas
    KTH, School of Information and Communication Technology (ICT), Software and Computer systems, SCS.
    Semi-Supervised Multiple Disambiguation2015In: IEEE Computer Society Conference Publishing Services / [ed] IEEE, IEEE , 2015Conference paper (Refereed)
    Abstract [en]

    Determining the true entity behind an ambiguousword is an NP-Hard problem known as Disambiguation. Previoussolutions often disambiguate a single ambiguous mention acrossmultiple documents. They assume each document contains onlya single ambiguous word and a rich set of unambiguous contextwords. However, nowadays we require fast disambiguation ofshort texts (like news feeds, reviews or Tweets) with few contextwords and multiple ambiguous words. In this research we focuson Multiple Disambiguation (MD) in contrast to Single Disambiguation(SD). Our solution is inspired by a recent algorithm developed for SD. The algorithm categorizes documents by first,transferring them into a graph and then, clustering the graphbased on its topological structure. We changed the graph-baseddocument-modeling of the algorithm, to account for MD. Also,we added a new parameter that controls the resolution of theclustering. Then, we used a supervised sampling approach formerging the clusters when appropriate. Our algorithm, comparedwith the original model, achieved 10% higher quality in termsof F1-Score using only 4% sampling from the dataset.

  • 7.
    Girdzijauskas, Sarunas
    et al.
    EPFL, Switzerland.
    Chockler, Gregory
    IBM Research, Israel.
    Melamed, Roie
    IBM Research, Israel.
    Tock, Yoav
    IBM Research, Israel.
    Gravity: An Interest-Aware Publish/Subscribe System Based on Structured Overlays2008In: Proceedings of the Second International Conference on Distributed Event-Based Systems, DEBS 2008 / [ed] Roberto Baldoni, 2008Conference paper (Refereed)
  • 8. Girdzijauskas, Sarunas
    et al.
    Chockler, Gregory
    Vifgusson, Ymir
    Tock, Yoav
    Melamed, Roie
    Magnet: Practical Subscription Clustering for Internet-Scale Publish/Subscribe2010In: DEBS '10 Proceedings of the Fourth ACM International Conference on Distributed Event-Based Systems, 2010, p. 172-183Conference paper (Other academic)
    Abstract [en]

    An effective means for building Internet-scale distributed applications, and in particular those involving group-based information sharing, is to deploy peer-to-peer overlay networks. The key pre-requisite for supporting these types of applications on top of the overlays is efficient distribution of messages to multiple subscribers dispersed across numerous multicast groups.

    In this paper, we introduce Magnet: a peer-to-peer publish/subscribe system which achieves efficient message distribution by dynamically organizing peers with similar subscriptions into dissemination structures which preserve locality in the subscription space. Magnet is able to significantly reduce the message propagation costs by taking advantage of subscription correlations present in many large-scale group-based applications.

    We evaluate Magnet by comparing its performance against a strawman pub/sub system which does not cluster similar subscriptions by simulation. We find that Magnet outperforms the strawman by a substantial margin on clustered subscription workloads produced using both generative models and real application traces.

  • 9.
    Girdzijauskas, Sarunas
    et al.
    Ecole Polytechnique Fédérale de Lausanne (EPFL).
    Datta, Anwitaman
    Ecole Polytechnique Fédérale de Lausanne (EPFL).
    Aberer, Karl
    Ecole Polytechnique Fédérale de Lausanne (EPFL).
    On Small World Graphs in Non-uniformly Distributed Key Spaces2005In: Proceedings - International Workshop on Biomedical Data Engineering, BMDE2005, 2005Conference paper (Refereed)
    Abstract [en]

    In this paper we show that the topologies of most logarithmic-style P2P systems like Pastry, Tapestry or P-Grid resemble small-world graphs. Inspired by Kleinberg's small-world model [7] we extend the model of building "routing-efficient" small-world graphs and propose two new models. We show that the graph, constructed according to our model for uniform key distribution and logarithmic outdegree, will have similar properties as the topologies of structured P2P systems with logarithmic out-degree. Moreover, we propose a novel model of building graphs which support uneven node distributions and preserves all desired properties of Kleinberg's small-world model. With such a model we are setting a reference base for nowadays emerging P2P systems that need to support uneven key distributions

  • 10.
    Girdzijauskas, Sarunas
    et al.
    Ecole Polytech Fed Lausanne.
    Datta, Anwitaman
    Ecole Polytech Fed Lausanne.
    Aberer, Karl
    Ecole Polytech Fed Lausanne.
    Oscar: A Data-Oriented Overlay For Heterogeneous Environments2007In: 2007 IEEE 23RD INTERNATIONAL CONFERENCE ON DATA ENGINEERING, VOLS 1-3, 2007, p. 1340-1342Conference paper (Refereed)
    Abstract [en]

    Quite a few data-oriented overlay networks have been designed in recent years. These designs often (implicitly) assume various homogeneity which seriously limit their us ability v in real world. In this paper we present some performance results of the Oscar overlay, which simultaneously deals with heterogeneity as observed in the internet (capacity of computers, bandwidth) as well as non-uniformity observed in data-oriented applications.

  • 11.
    Girdzijauskas, Sarunas
    et al.
    Ecole Polytech Fed Lausann.
    Datta, Anwitaman
    Ecole Polytech Fed Lausann.
    Aberer, Karl
    Ecole Polytech Fed Lausann.
    Oscar: Small-world overlay for realistic key distributions2006In: The Fourth International Workshop on Databases, Information Systems and Peer-to-Peer Computing, September 11, 2006, Seoul, Korea, 2006, p. 247-258Conference paper (Refereed)
    Abstract [en]

    The research on P2P systems which support skewed key distributions has rapidly advanced in the recent years. Yet, the assumptions on the skews we are dealing with remained pretty simple: most of the existing literature assumes simple monotonous key distribution skews. However, this is not always the case. For example, Gnutella filename traces show that complex key-distribut ions rather than monotonous skews occur in practice. We show that one of the seminal P2P systems which support skewed keys - Mercury [7], performs poorly given such complex distributions generated from the trace of Gnutella filenames. We discuss the shortcomings of such state-of-the-art techniques. We present an overlay network Oscar, based on a novel overlay construction mechanism, which does not depend on the key-distribution complexity. We demonstrate through simulations that our technique performs well and significantly surpasses Mercury for such realistic workloads.

  • 12. Girdzijauskas, Sarunas
    et al.
    Datta, Anwitaman
    Aberer, Karl
    Structured Overlay For Heterogeneous Environments: Design and Evaluation of Oscar2010In: ACM Transactions on Autonomous and Adaptive Systems (TAAS), ISSN 1556-4665, Vol. 5, no 1Article in journal (Refereed)
    Abstract [en]

    Recent years have seen advances in building large Internet-scale index structures, generally known as structured overlays. Early structured overlays realized distributed hash tables (DHTs) which are ill suited for anything but exact queries. The need to support range queries necessitates systems that can handle uneven load distributions. However such systems suffer from practical problems including poor latency, disproportionate bandwidth usage at participating peers, or unrealistic assumptions on peers' homogeneity, in terms of available storage or bandwidth resources. In this article we consider a system that is not only able to support uneven load distributions but also to operate in heterogeneous environments, where each peer can autonomously decide how much of its resources to contribute to the system. We provide the theoretical foundations of realizing such a network and present a newly proposed system Oscar based on these principles. Oscar can construct efficient overlays given arbitrary load distributions by employing a novel scalable network sampling technique. The simulations of our system validate the theory and evaluate Oscar's performance under typical challenges, encountered in real-life large-scale networked systems, including participant heterogeneity, faults, and skewed and dynamic load-distributions. Thus the Oscar distributed index fills in an important gap in the family of structured overlays, bringing into life a practical Internet-scale index, which can play a crucial role in enabling data-oriented applications distributed over wide-area networks. 

  • 13. Girdzijauskas, Sarunas
    et al.
    Galuba, Wojciech
    Darlagiannis, Vasilios
    Datta, Anwitaman
    Aberer, Karl
    Fuzzynet: Ringless Routing in a Ring-like Structured Overlay2010In: Peer-to-Peer Networking and Applications, ISSN 1936-6442, E-ISSN 1936-6450, Vol. 4, no 3, p. 259-273Article in journal (Refereed)
    Abstract [en]

    Many structured overlay networks rely on a ring invariant as a core network connectivity element. The responsibility ranges of the participating peers and navigability principles (greedy routing) heavily depend on the ring structure. For correctness guarantees, each node needs to eagerly maintain its immediate neighboring links - the ring invariant. However, the ring maintenance is an expensive task and it may not even be possible to maintain the ring invariant continuously under high churn, particularly as the network size grows. Furthermore, routing anomalies in the network, peers behind firewalls and Network Address Translators (NATs) create non-transitivity effects, which inevitably lead to the violation of the ring invariant. We argue that reliance on the ring structure is a serious impediment for real life deployment and scalability of structured overlays. In this paper we propose an overlay called Fuzzynet, which does not rely on the ring invariant, yet has all the functionalities of structured overlays. Fuzzynet takes the idea of lazy overlay maintenance further by dropping any explicit connectivity and data maintenance requirement, relying merely on the actions performed when new Fuzzynet peers join the network. We show that with sufficient amount of neighbors (O(log N), comparable to traditional structured over-lays), even under high churn, data can be retrieved in Fuzzynet w.h.p. We validate our novel design principles by simulations as well as PlanetLab experiments and compare them with ring based overlays.

  • 14. Guerrieri, A.
    et al.
    Rahimian, Fatemeh
    KTH, School of Information and Communication Technology (ICT), Software and Computer systems, SCS.
    Girdzijauskas, Sarunas
    KTH, School of Information and Communication Technology (ICT), Software and Computer systems, SCS.
    Montresor, A.
    Tovel: Distributed Graph Clustering for Word Sense Disambiguation2017In: IEEE International Conference on Data Mining Workshops, ICDMW, IEEE Computer Society, 2017, p. 623-630, article id 7836725Conference paper (Refereed)
    Abstract [en]

    Word sense disambiguation is a fundamental problem in natural language processing (NLP). In this problem, a large corpus of documents contains mentions to well-known (non-Ambiguous) words, together with mentions to ambiguous ones. The goal is to compute a clustering of the corpus, such that documents that refer to the same meaning appear in the same cluster, subsequentially, each cluster is assigned to a different semantic meaning. In this paper, we propose a mechanism for word sense disambiguation based on distributed graph clustering that is incremental in nature and can scale to big data. A novel, heuristic vertex-centric algorithm based on the metaphor of the water cycle is used to cluster the graph. Our approach is evaluated on real datasets in both centralized and decentralized environments.

  • 15.
    Khelghatdoust, Mansour
    et al.
    KTH, School of Electrical Engineering (EES), Communication Networks.
    Girdzijauskas, Sarunas
    KTH, School of Electrical Engineering (EES), Communication Networks.
    Short: Gossip-based sampling in social overlays2014In: Networked Systems: Second International Conference, NETYS 2014, Marrakech, Morocco, May 15–17, 2014, Revised Selected Papers, 2014, p. 335-340Conference paper (Refereed)
    Abstract [en]

    Performance of many P2P systems depends on the ability to construct a random overlay network among the nodes. Current state-of-the-art techniques for constructing random overlays have an implicit requirement that any two nodes in the system should always be able to communicate and establish a link between them. However, this is not the case in some of the environments where distributed systems are required to be deployed, e.g., Decentralized Online Social Networks, Wireless networks, or networks with limited connectivity because of NATs/firewalls, etc. In this paper we propose a gossip based peer sampling service capable of running on top of such restricted networks and producing an on-the-fly random overlay. The service provides every participating node with a set of uniform random nodes from the network, as well as efficient routing paths for reaching those nodes via the restricted network.

  • 16.
    Klemm, Fabius
    et al.
    Ecole Polytech. Fed. de Lausanne (EPFL), Lausanne .
    Girdzijauskas, Sarunas
    Ecole Polytech. Fed. de Lausanne (EPFL), Lausanne .
    Le Boudec, J.-Y.
    Ecole Polytech. Fed. de Lausanne (EPFL), Lausanne .
    Aberer, Karl
    Ecole Polytech. Fed. de Lausanne (EPFL), Lausanne .
    On Routing in Distributed Hash Tables2007In: Peer-to-Peer Computing, 2007. P2P 2007. Seventh IEEE International Conference on, 2007, p. 113-122Conference paper (Refereed)
    Abstract [en]

    There have been many proposals for constructing routing tables for distributed hash tables (DHT). They can be classified into two groups: A) those that assume that the peers are uniformly randomly distributed in the identifier space, and B) those that allow order-preserving hash functions that lead to a skewed peer distribution in the identifier space. Good solutions for group A have been known for many years. However, DHTs in group A are limited to use randomized hashing and therefore, queries over whole identifier ranges thus do not scale. Group B can handle such queries easily. However, it is more difficult to connect the peers such that the resulting topology provides efficient routing, small routing tables, and balanced routing load. We present an elegant new solution to construct an efficient DHT for group B. Our main idea is to decouple the identifier space from the routing topology. In consequence, our DHT allows arbitrarily skewed peer distributions in the identifier space and does not require the overhead of sampling. Furthermore, the table construction is cheap and does not require active replacement of lost routing entries. To evaluate the performance of routing cost and table construction under high churn, we built an efficient simulator. Using the right data structures, we can easily process the state of over one million peers in RAM.

  • 17.
    Laleh, N.
    et al.
    KTH. University of Insubria, Italy.
    Carminati, B.
    KTH. University of Insubria, Italy.
    Ferrari, Elena
    KTH. University of Insubria, Italy.
    Girdzijauskas, Sarunas
    KTH, School of Information and Communication Technology (ICT), Software and Computer systems, SCS. University of Insubria, Italy.
    Gossip-based behavioral group identification in decentralized OSNs2016In: 12th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2016, Springer, 2016, p. 676-691Conference paper (Refereed)
    Abstract [en]

    DOSNs are distributed systems providing social networking services that become extremely popular in recent years. In DOSNs, the aim is to give the users control over their data and keeping data locally to enhance privacy. Therefore, identifying behavioral groups of users that share the same behavioral patterns in decentralized OSNs is challenging. In the fully distributed social graph, each user has only one feature vector and these vectors can not move to any central storage or other users in a raw form duo to privacy issues. We use a gossip learning approach where all users are involved with their local estimation of the clustering model and improve their estimations and finally converge to a final clustering model available for all users. In order to evaluate our approach, we implement our algorithm and test it in a real Facebook graph.

  • 18.
    Nasir, M. Anis U.
    et al.
    KTH, School of Electrical Engineering (EES), Communication Networks.
    Rahimian, F.
    Girdzijauskas, Sarunas
    KTH, School of Electrical Engineering (EES), Communication Networks.
    Gossip-based partitioning and replication for Online Social Networks2014In: ASONAM 2014 - Proceedings of the 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, 2014, p. 33-42Conference paper (Refereed)
    Abstract [en]

    Online Social Networks (OSNs) have been gaining tremendous growth and popularity in the last decade, as they have been attracting billions of users from all over the world. Such networks generate petabytes of data from the social interactions among their users and create many management and scalability challenges. OSN users share common interests and exhibit strong community structures, which create complex dependability patterns within OSN data, thus, make it difficult to partition and distribute in a data center environment. Existing solutions, such as, distributed databases, key-value stores and auto scaling services use random partitioning to distribute the data across a cluster, which breaks existing dependencies of the OSN data and may generate huge inter-server traffic. Therefore, there is a need for intelligent data allocation strategy that can reduce the network cost for various OSN operations. In this paper, we present a gossip-based partitioning and replication scheme that efficiently splits OSN data and distributes the data across a cluster. We achieve fault tolerance and data locality, for one-hop neighbors, through replication. Our main contribution is a social graph placement strategy that divides the social graph into predefined size partitions and periodically updates the partitions to place socially connected users together. To evaluate our algorithm, we compare it with random partitioning and a state-of-the-art solution SPAR. Results show that our algorithm generates up to four times less replication overhead compared to random partitioning and half the replication overhead compared to SPAR.

  • 19.
    Nasir, Muhammad Anis Uddin
    et al.
    KTH, School of Information and Communication Technology (ICT), Software and Computer systems, SCS.
    Gionis, A.
    De Francisci Morales, G.
    Girdzijauskas, Sarunas
    KTH, School of Information and Communication Technology (ICT), Software and Computer systems, SCS.
    Fully dynamic algorithm for top-k densest subgraphs2017In: CIKM '17 Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, Association for Computing Machinery (ACM), 2017, p. 1817-1826Conference paper (Refereed)
    Abstract [en]

    Given a large graph, the densest-subgraph problem asks to find a subgraph with maximum average degree. When considering the top-k version of this problem, a nattive solution is to iteratively find the densest subgraph and remove it in each iteration. However, such a solution is impractical due to high processing cost. The problem is further complicated when dealing with dynamic graphs, since adding or removing an edge requires re-running the algorithm. In this paper, we study the top-k densest-subgraph problem in the sliding-window model and propose an efficient fully-dynamic algorithm. The input of our algorithm consists of an edge stream, and the goal is to find the node-disjoint subgraphs that maximize the sum of their densities. In contrast to existing state-of-the-art solutions that require iterating over the entire graph upon any update, our algorithm profits from the observation that updates only affect a limited region of the graph. Therefore, the top-k densest subgraphs are maintained by only applying local updates. We provide a theoretical analysis of the proposed algorithm and show empirically that the algorithm offen generates denser subgraphs than state-of-the-art competitors. Experiments show an improvement in efficiency of up to five orders of magnitude compared to state-of-the-art solutions.

  • 20.
    Nasir, Muhammad Anis Uddin
    et al.
    KTH, School of Information and Communication Technology (ICT), Software and Computer systems, SCS.
    Girdzijauskas, Sarunas
    KTH, School of Information and Communication Technology (ICT), Software and Computer systems, SCS.
    Socially-aware distributed hash tables for decentralized online social networks2015In: Peer-to-Peer Computing (P2P), 2015 IEEE International Conference on, IEEE Press, 2015, p. 1-10Conference paper (Refereed)
    Abstract [en]

    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.

  • 21.
    Nasir, Muhammad Anis Uddin
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS).
    Horii, Hiroshi
    Serafini, Marco
    Kourtellis, Nicolas
    Raymond, Rudy
    Girdzijauskas, Sarunas
    KTH, School of Electrical Engineering and Computer Science (EECS).
    Osogami, Takayuki
    Load Balancing for Skewed Streams on Heterogeneous ClustersManuscript (preprint) (Other academic)
    Abstract [en]

    Streaming applications frequently encounter skewed workloads and execute on heterogeneous clusters. Optimal re- source utilization in such adverse conditions becomes a challenge, as it requires inferring the resource capacities and input distribution at run time. In this paper, we tackle the aforementioned challenges by modeling them as a load balancing problem. We propose a novel partitioning strategy called Consistent Grouping (CG), which enables each processing element instance (PEI) to process the workload according to its capacity. The main idea behind CG is the notion of small, equal-sized “virtual workers” at the sources, which are assigned to physical workers based on their capacities. We provide a theoretical analysis of the proposed algorithm and show via extensive empirical evaluation that our proposed scheme outperforms the state-of-the-art approaches, like key grouping. In particular, CG achieves 3.44x better performance in terms of latency compared to key grouping.

  • 22.
    Rahimian, Fatemeh
    et al.
    KTH, School of Information and Communication Technology (ICT), Software and Computer systems, SCS.
    Girdzijauskas, Sarunas
    KTH, School of Electrical Engineering (EES), Communication Networks.
    Haridi, Seif
    KTH, School of Information and Communication Technology (ICT), Software and Computer systems, SCS.
    Parallel Community Detection For Cross-Document Coreference2014Conference paper (Refereed)
    Abstract [en]

    This paper presents a highly parallel solution for cross-document coreference resolution, which can deal with billions of documents that exist in the current web. At the core of our solution lies a novel algorithm for community detection in large scale graphs. We operate on graphs which we construct by representing documents' keywords as nodes and the co-location of those keywords in a document as edges. We then exploit the particular nature of such graphs where coreferent words are topologically clustered and can be efficiently discovered by our community detection algorithm. The accuracy of our technique is considerably higher than that of the state of the art, while the convergence time is by far shorter. In particular, we increase the accuracy for a baseline dataset by more than 15% compared to the best reported result so far. Moreover, we outperform the best reported result for a dataset provided for the Word Sense Induction task in SemEval 2010.

  • 23.
    Rahimian, Fatemeh
    et al.
    KTH, School of Information and Communication Technology (ICT), Software and Computer systems, SCS.
    Girdzijauskas, Sarunas
    KTH, School of Electrical Engineering (EES), Communication Networks.
    Payberah, Amir H.
    KTH, School of Information and Communication Technology (ICT), Software and Computer systems, SCS.
    Haridi, Seif
    KTH, School of Information and Communication Technology (ICT).
    Subscription Awareness Meets Rendezvous Routing2012Conference paper (Refereed)
    Abstract [en]

    Publish/subscribe communication model has become an indispensable part of the Web 2.0 applications, such as social networks and news syndication. Although there exist a few systems that provide a genuinely scalable service for topic-based publish/subscribe model, the content-based solutions are still suffering from restricted subscription schemes, heavy and unbalanced load on the participating nodes, or excessively high matching complexity. We address these problems by constructing a distributed content-based publish/subscribe system by using only those components that are proven to be scalable and can withstand the workloads of massive sizes. Our publish/subscribe solution, Vinifera, requires only a bounded node degree and as we show, through simulations, it scales well to large network sizes and remains efficient under various subscription patterns and loads.

  • 24.
    Rahimian, Fatemeh
    et al.
    KTH, School of Information and Communication Technology (ICT), Communication: Services and Infrastucture (Closed 20120101), Software and Computer Systems, SCS (Closed 20120101). Swedish Institute of Computer Science (SICS), Stockholm.
    Girdzijauskas, Sarunas
    Swedish Institute of Computer Science (SICS), Stockholm.
    Payberah, Amir H.
    KTH, School of Information and Communication Technology (ICT), Communication: Services and Infrastucture (Closed 20120101), Software and Computer Systems, SCS (Closed 20120101). Swedish Institute of Computer Science (SICS), Stockholm.
    Haridi, Seif
    KTH, School of Information and Communication Technology (ICT), Communication: Services and Infrastucture (Closed 20120101), Software and Computer Systems, SCS (Closed 20120101). Swedish Institute of Computer Science (SICS), Stockholm.
    Vitis: A Gossip-based Hybrid Overlay for Internet-scale Publish/Subscribe Enabling Rendezvous Routing in Unstructured Overlay Networks2011In: Proceedings - 25th IEEE International Parallel and Distributed Processing Symposium, IPDPS 2011, 2011, p. 746-757Conference paper (Refereed)
    Abstract [en]

    Peer-to-peer overlay networks are attractive solutions for building Internet-scale publish/subscribe systems. However, scalability comes with a cost: a message published on a certain topic often needs to traverse a large number of uninterested (unsubscribed) nodes before reaching all its subscribers. This might sharply increase resource consumption for such relay nodes (in terms of bandwidth transmission cost, CPU, etc) and could ultimately lead to rapid deterioration of the system's performance once the relay nodes start dropping the messages or choose to permanently abandon the system. In this paper, we introduce {\em Vitis}, a gossip-based publish/subscribe system that significantly decreases the number of relay messages, and scales to an unbounded number of nodes and topics. This is achieved by the novel approach of enabling rendezvous routing on unstructured overlays. We construct a hybrid system by injecting structure into an otherwise unstructured network. The resulting structure resembles a navigable small-world network, which spans along clusters of nodes that have similar subscriptions. The properties of such an overlay make it an ideal platform for efficient data dissemination in large-scale systems. We perform extensive simulations and evaluate Vitis by comparing its performance against two base-line publish/subscribe systems: one that is oblivious to node subscriptions, and another that exploits the subscription similarities. Our measurements show that Vitis significantly outperforms the base-line solutions on various subscription and churn scenarios, from both synthetic models and real-world traces

  • 25.
    Rahimian, Fatemeh
    et al.
    KTH, School of Information and Communication Technology (ICT), Software and Computer systems, SCS.
    Nguyen Huu, Thinh Le
    KTH, School of Information and Communication Technology (ICT), Software and Computer systems, SCS.
    Girdzijauskas, Sarunas
    KTH, School of Electrical Engineering (EES), Communication Networks.
    Locality Awareness in a Peer-to-Peer Publish/Subscribe System2012In: Distributed applications and interoperable systems: 12th IFIP WG 6.1 International Conference, DAIS 2012, Stockholm, Sweden, June 13-16, 2012. Proceedings, Springer, 2012, Vol. 7272, p. 45-58Conference paper (Refereed)
    Abstract [en]

    Peer-to-peer publish/subscribe systems are promising solutions to provide distributed content distribution services at Internet-scale with low cost. One of the potential problems with peer-to-peer overlays, however, is the inefficient traffic and large delays, due to the mismatch between the physical network and the overlay topology. This paper introduces a locality-aware extension to a peer-to-peer publish/subscribe system, named Vitis. The ultimate purpose is to avoid communications over long-distance links, instead, nodes send data over short-distance and low-cost links, when possible, while maintaining an acceptable quality of service. We show, through simulations, that the average data delivery time is up to 40% improved. The cost to pay is at most 10% more relaying in the peer-to-peer overlay.

  • 26.
    Rahimian, Fatemeh
    et al.
    KTH, School of Information and Communication Technology (ICT), Software and Computer systems, SCS.
    Payberah, Amir H.
    KTH, School of Information and Communication Technology (ICT), Software and Computer systems, SCS.
    Girdzijauskas, Sarunas
    KTH, School of Electrical Engineering (EES), Communication Networks.
    Haridi, Seif
    KTH, School of Information and Communication Technology (ICT), Software and Computer systems, SCS.
    Distributed Vertex-Cut Partitioning2014In: In the 14th IFIP international conference on Distributed Applications and Interoperable Systems (DAIS’14)., 2014, p. 186-200Conference paper (Refereed)
    Abstract [en]

    Graph processing has become an integral part of big data analytics. With the ever increasing size of the graphs, one needs to partition them into smaller clusters, which can be managed and processed more easily on multiple machines in a distributed fashion. While there exist numerous solutions for edge-cut partitioning of graphs, very little effort has been made for vertex-cut partitioning. This is in spite of the fact that vertex-cuts are proved significantly more effective than edge-cuts for processing most real world graphs. In this paper we present Ja-be-Ja-vc, a parallel and distributed algorithm for vertex-cut partitioning of large graphs. In a nutshell, Ja-be-Ja-vc is a local search algorithm that iteratively improves upon an initial random assignment of edges to partitions. We propose several heuristics for this optimization and study their impact on the final partitioning. Moreover, we employ simulated annealing technique to escape local optima. We evaluate our solution on various graphs and with variety of settings, and compare it against two state-of-the-art solutions. We show that Ja-be-Ja-vc outperforms the existing solutions in that it not only creates partitions of any requested size, but also requires a vertex-cut that is better than its counterparts and more than 70% better than random partitioning.

  • 27.
    Rahimian, Fatemeh
    et al.
    KTH, School of Information and Communication Technology (ICT), Software and Computer systems, SCS. Computer System Lab. (CSL), SICS Swedish, Sweden.
    Payberah, Amir H.
    Computer System Lab. (CSL), SICS Swedish, Sweden.
    Girdzijauskas, Sarunas
    KTH, School of Electrical Engineering (EES), Communication Networks.
    Jelasity, Mark
    MTA SZTE Research Group on AI, Hungarian Academy of Sciences and University of Szeged, Hungary.
    Haridi, Seif
    KTH, School of Information and Communication Technology (ICT), Software and Computer systems, SCS.
    A Distributed Algorithm for Large-Scale Graph Partitioning2015In: ACM Transactions on Autonomous and Adaptive Systems, ISSN 1556-4665, E-ISSN 1556-4703, Vol. 10, no 2, article id 12Article in journal (Refereed)
    Abstract [en]

    Balanced graph partitioning is an NP-complete problem with a wide range of applications. These applications include many large-scale distributed problems, including the optimal storage of large sets of graph-structured data over several hosts. However, in very large-scale distributed scenarios, state-of-the-art algorithms are not directly applicable because they typically involve frequent global operations over the entire graph. In this article, we propose a fully distributed algorithm called JA-BE-JA that uses local search and simulated annealing techniques for two types of graph partitioning: edge-cut partitioning and vertex-cut partitioning. The algorithm is massively parallel: There is no central coordination, each vertex is processed independently, and only the direct neighbors of a vertex and a small subset of random vertices in the graph need to be known locally. Strict synchronization is not required. These features allow JA-BE-JA to be easily adapted to any distributed graph-processing system from data centers to fully distributed networks. We show that the minimal edge-cut value empirically achieved by JA-BE-JA is comparable to state-of-the-art centralized algorithms such as Metis. In particular, on large social networks, JA-BE-JA outperforms Metis. We also show that JA-BE-JA computes very low vertex-cuts, which are proved significantly more effective than edge-cuts for processing most real-world graphs.

  • 28.
    Rahimian, Fatemeh
    et al.
    KTH, School of Information and Communication Technology (ICT), Software and Computer systems, SCS.
    Payberah, Amir H.
    KTH, School of Information and Communication Technology (ICT), Software and Computer systems, SCS.
    Girdzijauskas, Sarunas
    KTH, School of Electrical Engineering (EES), Communication Networks.
    Jelasity, Mark
    Haridi, Seif
    KTH, School of Information and Communication Technology (ICT), Software and Computer systems, SCS.
    JA-BE-JA: A Distributed Algorithm for Balanced Graph Partitioning2013In: 7th International Conference on Self-Adaptive and Self-Organizing Systems (SASO), 2013 IEEE, IEEE conference proceedings, 2013, p. 51-60Conference paper (Refereed)
    Abstract [en]

    Balanced graph partitioning is a well known NP-complete problem with a wide range of applications. These applications include many large-scale distributed problems including the optimal storage of large sets of graph-structured data over several hosts-A key problem in today's Cloud infrastructure. However, in very large-scale distributed scenarios, state-of-the-Art algorithms are not directly applicable, because they typically involve frequent global operations over the entire graph. In this paper, we propose a fully distributed algorithm, called JA-BE-JA, that uses local search and simulated annealing techniques for graph partitioning. The algorithm is massively parallel: there is no central coordination, each node is processed independently, and only the direct neighbors of the node, and a small subset of random nodes in the graph need to be known locally. Strict synchronization is not required. These features allow JA-BE-JA to be easily adapted to any distributed graph-processing system from data centers to fully distributed networks. We perform a thorough experimental analysis, which shows that the minimal edge-cut value achieved by JA-BE-JA is comparable to state-of-the-Art centralized algorithms such as METIS. In particular, on large social networks JA-BEJA outperforms METIS, which makes JA-BE-JA-A bottom-up, self-organizing algorithm-A highly competitive practical solution for graph partitioning.

  • 29. Sedaghat, M.
    et al.
    Hernandez-Rodriguez, F.
    Elmroth, E.
    Girdzijauskas, Sarunas
    KTH, School of Electrical Engineering (EES), Communication Networks.
    Divide the task, multiply the outcome: Cooperative VM consolidation2015In: Proceedings of the International Conference on Cloud Computing Technology and Science, CloudCom, IEEE conference proceedings, 2015, no February, p. 300-305Conference paper (Refereed)
    Abstract [en]

    Efficient resource utilization is one of the main concerns of cloud providers, as it has a direct impact on energy costs and thus their revenue. Virtual machine (VM) consolidation is one the common techniques, used by infrastructure providers to efficiently utilize their resources. However, when it comes to large-scale infrastructures, consolidation decisions become computationally complex, since VMs are multi-dimensional entities with changing demand and unknown lifetime, and users often overestimate their actual demand. These uncertainties urges the system to take consolidation decisions continuously in a real time manner. In this work, we investigate a decentralized approach for VM consolidation using Peer to Peer (P2P) principles. We investigate the opportunities offered by P2P systems, as scalable and robust management structures, to address VM consolidation concerns. We present a P2P consolidation protocol, considering the dimensionality of resources and dynamicity of the environment. The protocol benefits from concurrency and decentralization of control and it uses a dimension aware decision function for efficient consolidation. We evaluate the protocol through simulation of 100,000 physical machines and 200,000 VM requests. Results demonstrate the potentials and advantages of using a P2P structure to make resource management decisions in large scale data centers. They show that the P2P approach is feasible and scalable and produces resource utilization of 75% when the consolidation aim is 90%.

  • 30.
    Soliman, Amira
    et al.
    KTH, School of Electrical Engineering (EES), Communication Networks.
    Bahri, Leila
    Insubria University, Italy.
    Carminati, Barbara
    Insubria University, Italy.
    Ferrari, Elena
    Insubria University, Italy.
    Girdzijauskas, Sarunas
    KTH, School of Electrical Engineering (EES), Communication Networks.
    DIVa: Decentralized Identity Validation for Social Networks2015Report (Other academic)
    Abstract [en]

    We suggested DIVa, a decentralized, unsupervised, and association rule mining based solution for the learning of fine-grained correlations between profile attributes in Online Social Networks. These correlations can be used for identity validation purposes. In this report, we provide the technical details and the security analysis proofs of the DIVa model.

  • 31.
    Soliman, Amira
    et al.
    KTH, School of Electrical Engineering (EES), Communication Networks.
    Bahri, Leila
    Carminati, Barbara
    Ferrari, Elena
    Girdzijauskas, Sarunas
    KTH, School of Electrical Engineering (EES), Communication Networks.
    DIVa: Decentralized Identity Validation for Social Networks2015In: PROCEEDINGS OF THE 2015 IEEE/ACM INTERNATIONAL CONFERENCE ON ADVANCES IN SOCIAL NETWORKS ANALYSIS AND MINING (ASONAM 2015), Association for Computing Machinery (ACM), 2015, p. 383-391Conference paper (Refereed)
    Abstract [en]

    Online Social Networks exploit a lightweight process to identify their users so as to facilitate their fast adoption. However, such convenience comes at the price of making legitimate users subject to different threats created by fake accounts. Therefore, there is a crucial need to empower users with tools helping them in assigning a level of trust to whomever they interact with. To cope with this issue, in this paper we introduce a novel model, DIVa, that leverages on mining techniques to find correlations among user profile attributes. These correlations are discovered not from user population as a whole, but from individual communities, where the correlations are more pronounced. DIVa exploits a decentralized learning approach and ensures privacy preservation as each node in the OSN independently processes its local data and is required to know only its direct neighbors. Extensive experiments using real-world OSN datasets show that DIVa is able to extract fine-grained community-aware correlations among profile attributes with average improvements up to 50% than the global approach.

  • 32.
    Soliman, Amira
    et al.
    KTH, School of Electrical Engineering (EES), Communication Networks.
    Bahri, Leila
    Girdzijauskas, Šarunas
    KTH, School of Information and Communication Technology (ICT), Software and Computer systems, SCS.
    Carminati, Barbara
    Ferrari, Elena
    CADIVa: Cooperative and Adaptive Decentralized Identity Validation Model for Social Networks2016In: Social Network Analysis and Mining, ISSN 1869-5450, E-ISSN 1869-5469, Vol. 6, no 1, article id UNSP 36Article in journal (Refereed)
    Abstract [en]

    Online social networks (OSNs) have successfully changed the way people interact. Online interactions among people span geographical boundaries and interweave with different human life activities. However, current OSNs identification schemes lack guarantees on quantifying the trustworthiness of online identities of users joining them. Therefore, driven from the need to empower users with an identity validation scheme, we introduce a novel model, cooperative and adaptive decentralized identity validation CADIVa, that allows OSN users to assign trust levels to whomever they interact with. CADIVa exploits association rule mining approach to extract the identity correlations among profile attributes in every individual community in a social network. CADIVa is a fully decentralized and adaptive model that exploits fully decentralized learning and cooperative approaches not only to preserve users privacy, but also to increase the system reliability and to make it resilient to mono-failure. CADIVa follows the ensemble learning paradigm to preserve users privacy and employs gossip protocols to achieve efficient and low-overhead communication. We provide two different implementation scenarios of CADIVa. Results confirm CADIVa's ability to provide fine-grained community-aware identity validation with average improvement up to 36 and 50 % compared to the semi-centralized or global approaches, respectively.

  • 33.
    Soliman, Amira
    et al.
    KTH, School of Information and Communication Technology (ICT), Software and Computer systems, SCS.
    Girdzijauskas, Sarunas
    KTH, School of Information and Communication Technology (ICT), Software and Computer systems, SCS.
    Adagraph: Adaptive graph-based algorithms for spam detection in social networks2017In: 5th International Conference on Networked Systems, NETYS 2017, Springer Verlag , 2017, p. 338-354Conference paper (Refereed)
    Abstract [en]

    In the past years, researchers developed approaches to detect spam in Online Social Networks (OSNs) such as URL blacklisting, spam traps and even crowdsourcing for manual classification. Although previous work has shown the effectiveness of using statistical learning to detect spam, existing work employs supervised schemes that require labeled training data. In addition to the heavy training cost, it is difficult to obtain a comprehensive source of ground truth for measurement. In contrast to existing work, in this paper we present AdaGraph that is a novel graph-based approach for spam detection. AdaGraph is unsupervised, hence it diminishes the need of labeled training data and training cost. Particularly, AdaGraph effectively detects spam in large-scale OSNs by analyzing user behaviors using graph clustering technique. Moreover, AdaGraph continuously updates detected communities to comply with users dynamic interactions and activities. Extensive experiments using Twitter datasets show that AdaGraph detects spam with accuracy 92.3%. Furthermore, the false positive rate of AdaGraph is less than 0.3% that is less than half of the rate achieved by the state-of-the-art approaches.

  • 34.
    Soliman, Amira
    et al.
    KTH, School of Electrical Engineering (EES), Communication Networks.
    Girdzijauskas, Sarunas
    KTH, School of Information and Communication Technology (ICT), Software and Computer systems, SCS.
    Adaptive Graph-based algorithms for Spam Detection in Social Networks2016Report (Other academic)
    Abstract [en]

    As Online Social Networks (OSNs) continue to grow in popularity, a spam marketplace has emerged that includes services selling fraudulent accounts, as well as acts as nucleus of spammers who propagate large-scale spam campaigns. In the past years, researchers developed approaches to detect spam such as URL blacklisting, spam traps and even crowdsourcing for manual classification. Although previous work has shown the effectiveness of using statistical learning to detect spam, existing work employs supervised schemes that require labeled training data. In addition to the heavy training cost, it is difficult to obtain a comprehensive source of ground truth for measurement. In contrast to existing work, in this paper we present a novel graph-based approach for spam detection. Our approach is unsupervised, hence it diminishes the need of labeled training data and training cost. Particularly, our approach can effectively detect the spam in large-scale OSNs by analyzing user behaviors using graph clustering technique. Moreover, our approach continuously updates detected communities to comply with dynamic OSNs where interactions and activities are evolving rapidly. Extensive experiments using Twitter datasets show that our approach is able to detect spam with accuracy 92.3\%. Furthermore, our approach has false positive rate that is less than 0.3\% that is less than half of the rate achieved by the state-of-the-art approaches.

  • 35.
    Soliman, Amira
    et al.
    KTH, School of Information and Communication Technology (ICT), Software and Computer systems, SCS.
    Girdzijauskas, Sarunas
    KTH, School of Information and Communication Technology (ICT), Software and Computer systems, SCS.
    DLSAS: Distributed Large-Scale Anti-Spam Framework for Decentralized Online Social Networks2016In: 2016 IEEE 2ND INTERNATIONAL CONFERENCE ON COLLABORATION AND INTERNET COMPUTING (IEEE CIC), IEEE Press, 2016, p. 363-372Conference paper (Refereed)
    Abstract [en]

    In the last decade, researchers and the open source community have proposed various Decentralized Online Social Networks (DOSNs) that remove dependency on centralized online social network providers to preserve user privacy. However, transitioning from centralized to decentralized environment creates various new set of problems, such as adversarial manipulations. In this paper, we present DLSAS, a novel unsupervised and decentralized anti-spam framework for DOSNs. DLSAS provides decentralized spam detection that is resilient to adversarial attacks. DLSAS typifies massively parallel frameworks and exploits fully decentralized learning and cooperative approaches. Furthermore, DLSAS provides a novel defense mechanism for DOSNs to prevent malicious nodes participating in the system by creating a validation overlay to assess the credibility of the exchanged information among the participating nodes and exclude the misbehaving nodes from the system. Extensive experiments using Twitter datasets confirm not only the DLSAS's capability to detect spam with higher accuracy compared to state-of-the-art approaches, but also the DLSAS's robustness against different adversarial attacks.

  • 36.
    Steinle, Mirko
    et al.
    Ecole Polytechnique Federale de Lausanne.
    Aberer, Karl
    Ecole Polytechnique Federale de Lausanne.
    Girdzijauskas, Sarunas
    Ecole Polytechnique Federale de Lausanne.
    Lovis, Christian
    Geneva University Hospitals (HUG).
    Mapping Moving Landscapes by Mining Mountains of Logs: Novel Techniques for Dependency Model Generation2006In: The 32nd International Conference on Very Large Data Bases, September 12-15, 2006, Seoul, Korea., 2006, p. 1093-1102Conference paper (Refereed)
    Abstract [en]

    Problem diagnosis for distributed systems is usually difficult. Thus, an automated support is needed to identify root causes of encountered problems such as performance lags or inadequate functioning quickly. The many tools and techniques existing today that perform this task rely usually on some dependency model of the system. However, in complex and fast evolving environments it is practically unfeasible to keep such a model up-to-date manually and it has to be created in an automatic manner. For high level objects this is in itself a challenging and less studied task. In this paper, we propose three different approaches to discover dependencies by mining system logs. Our work is inspired by a recently developed data mining algorithm and techniques for collocation extraction from the natural language processing field. We evaluate the techniques in a case study for Geneva University Hospitals (HUG) and perform large-scale experiments on production data. Results show that all techniques are capable of finding useful dependency information with reasonable precision in a real-world environment.

1 - 36 of 36
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf