Vana Kalogeraki

Bio: Vana Kalogeraki is an academic researcher from Athens University of Economics and Business. The author has contributed to research in topics: Wireless sensor network & Stream processing. The author has an hindex of 33, co-authored 213 publications receiving 5208 citations. Previous affiliations of Vana Kalogeraki include Foundation for Research & Technology – Hellas & University of California, Riverside.

Peer-to-Peer Computing

Abstract: The term “peer-to-peer” (P2P) refers to a class of systems and applications that employ distributed resources to perform a critical function in a decentralized manner. With the pervasive deployment of computers, P2P is increasingly receiving attention in research, product development, and investment circles. This interest ranges from enthusiasm, through hype, to disbelief in its potential. Some of the benefits of a P2P approach include: improving scalability by avoiding dependency on centralized points; eliminating the need for costly infrastructure by enabling direct communication among clients; and enabling resource aggregation. This survey reviews the field of P2P systems and applications by summarizing the key concepts and giving an overview of the most important systems. Design and implementation issues of P2P systems are analyzed in general, and then revisited for each of the case studies described in Section 6. This survey will help people understand the potential benefits of P2P in the research community and industry. For people unfamiliar with the field it provides a general overview, as well as detailed case studies. It is also intended for users, developers, and information technologies maintaining systems, in particular comparison of P2P solutions with alternative architectures and

Online outlier detection in sensor data using non-parametric models

Abstract: Sensor networks have recently found many popular applications in a number of different settings. Sensors at different locations can generate streaming data, which can be analyzed in real-time to identify events of interest. In this paper, we propose a framework that computes in a distributed fashion an approximation of multi-dimensional data distributions in order to enable complex applications in resource-constrained sensor networks.We motivate our technique in the context of the problem of outlier detection. We demonstrate how our framework can be extended in order to identify either distance- or density-based outliers in a single pass over the data, and with limited memory requirements. Experiments with synthetic and real data show that our method is efficient and accurate, and compares favorably to other proposed techniques. We also demonstrate the applicability of our technique to other related problems in sensor networks.

A local search mechanism for peer-to-peer networks

Abstract: One important problem in peer-to-peer (P2P) networks is searching and retrieving the correct information. However, existing searching mechanisms in pure peer-to-peer networks are inefficient due to the decentralized nature of such networks. We propose two mechanisms for information retrieval in pure peer-to-peer networks. The first, the modified Breadth-First Search (BFS) mechanism, is an extension of the current Gnuttela protocol, allows searching with keywords, and is designed to minimize the number of messages that are needed to search the network. The second, the Intelligent Search mechanism, uses the past behavior of the P2P network to further improve the scalability of the search procedure. In this algorithm, each peer autonomously decides which of its peers are most likely to answer a given query. The algorithm is entirely distributed, and therefore scales well with the size of the network. We implemented our mechanisms as middleware platforms. To show the advantages of our mechanisms we present experimental results using the middleware implementation.

Microhash: an efficient index structure for fash-based sensor devices

Abstract: In this paper we propose the MicroHash index, which is an efficient external memory structure for Wireless Sensor Devices (WSDs). The most prevalent storage medium for WSDs is flash memory. Our index structure exploits the asymmetric read/write and wear characteristics of flash memory in order to offer high performance indexing and searching capabilities in the presence of a low energy budget which is typical for the devices under discussion. A key idea behind MicroHash is to eliminate expensive random access deletions. We have implemented MicroHash in nesC, the programming language of the TinyOS [7] operating system. Our trace-driven experimentation with several real datasets reveals that our index structure offers excellent search performance at a small cost of constructing and maintaining the index.

Distributed deviation detection in sensor networks

Abstract: Sensor networks have recently attracted much attention, because of their potential applications in a number of different settings. The sensors can be deployed in large numbers in wide geographical areas, and can be used to monitor physical phenomena, or to detect certain events.An interesting problem which has not been adequately addressed so far is that of distributed online deviation detection in streaming data. The identification of deviating values provides an efficient way to focus on the interesting events in the sensor network.In this work, we propose a technique for online deviation detection in streaming data. We discuss how these techniques can operate efficiently in the distributed environment of a sensor network, and discuss the tradeoffs that arise in this setting. Our techniques process as much of the data as possible in a decentralized fashion, so as to avoid unnecessary communication and computational effort.

Anomaly detection: A survey

Abstract: Anomaly detection is an important problem that has been researched within diverse research areas and application domains. Many anomaly detection techniques have been specifically developed for certain application domains, while others are more generic. This survey tries to provide a structured and comprehensive overview of the research on anomaly detection. We have grouped existing techniques into different categories based on the underlying approach adopted by each technique. For each category we have identified key assumptions, which are used by the techniques to differentiate between normal and anomalous behavior. When applying a given technique to a particular domain, these assumptions can be used as guidelines to assess the effectiveness of the technique in that domain. For each category, we provide a basic anomaly detection technique, and then show how the different existing techniques in that category are variants of the basic technique. This template provides an easier and more succinct understanding of the techniques belonging to each category. Further, for each category, we identify the advantages and disadvantages of the techniques in that category. We also provide a discussion on the computational complexity of the techniques since it is an important issue in real application domains. We hope that this survey will provide a better understanding of the different directions in which research has been done on this topic, and how techniques developed in one area can be applied in domains for which they were not intended to begin with.

A survey of peer-to-peer content distribution technologies

Abstract: Distributed computer architectures labeled "peer-to-peer" are designed for the sharing of computer resources (content, storage, CPU cycles) by direct exchange, rather than requiring the intermediation or support of a centralized server or authority. Peer-to-peer architectures are characterized by their ability to adapt to failures and accommodate transient populations of nodes while maintaining acceptable connectivity and performance.Content distribution is an important peer-to-peer application on the Internet that has received considerable research attention. Content distribution applications typically allow personal computers to function in a coordinated manner as a distributed storage medium by contributing, searching, and obtaining digital content.In this survey, we propose a framework for analyzing peer-to-peer content distribution technologies. Our approach focuses on nonfunctional characteristics such as security, scalability, performance, fairness, and resource management potential, and examines the way in which these characteristics are reflected in---and affected by---the architectural design decisions adopted by current peer-to-peer systems.We study current peer-to-peer systems and infrastructure technologies in terms of their distributed object location and routing mechanisms, their approach to content replication, caching and migration, their support for encryption, access control, authentication and identity, anonymity, deniability, accountability and reputation, and their use of resource trading and management schemes.