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Sor V.,Software Technology and Applications Competence Center | Srirama S.N.,University of Tartu | Salnikov-Tarnovski N.,Software Technology and Applications Competence Center
Software - Practice and Experience | Year: 2015

Platforms with automatic memory management, such as the JVM, are usually considered free of memory leaks. However, memory leaks can happen in such environments, as the garbage collector cannot free objects, which are not used by the application anymore, but are still referenced. Such unused objects can eventually fill up the heap and crash the application. Although this problem has been studied extensively, nevertheless, there are still many rooms for improvement in this area. This paper describes the statistical approach for memory leak detection, as an alternative, along with a commercial tool, Plumbr, which is based on the method. The tool is later analyzed with three case studies of real applications and in the process also analyzes strengths and weaknesses of the statistical approach for memory leak detection. Copyright © 2014 John Wiley & Sons, Ltd.


Mazzucco M.,University of Tartu | Mazzucco M.,Software Technology and Applications Competence Center | Dumas M.,Software Technology and Applications Competence Center
Proceedings - 2011 IEEE 4th International Conference on Cloud Computing, CLOUD 2011 | Year: 2011

We examine the problem of managing a server farm in a way that attempts to maximize the net revenue earned by a cloud provider by renting servers to customers according to a typical Platform-as-a-Service model. The Cloud provider offers its resources to two classes of customers: 'premium' and 'basic'. Premium customers pay upfront fees to reserve servers for a specified period of time (e.g. a year). Premium customers can submit jobs for their reserved servers at any time and pay a fee for the server-hours they use. The provider is liable to pay a penalty every time a 'premium' job can not be executed due to lack of resources. On the other hand, 'basic' customers are served on a best-effort basis, and pay a server-hour fee that may be higher than the one paid by premium customers. The provider incurs energy costs when running servers. Hence, it has an incentive to turn off idle servers. The question of how to choose the number of servers to allocate to each pool (basic and premium) is answered by analyzing a suitable queuing model and maximizing a revenue function. Experimental results show that the proposed scheme adapts to different traffic conditions, penalty levels, energy costs and usage fees. © 2011 IEEE.


Dyachuk D.,University of Saskatchewan | Mazzucco M.,University of Tartu | Mazzucco M.,Software Technology and Applications Competence Center
Proceedings - IEEE/ACM International Workshop on Grid Computing | Year: 2010

With the increasing popularity of Internet-based services and applications, power efficiency is becoming a major concern for data center operators, as high electricity consumption not only increases greenhouse gas emissions, but also increases the cost of running the server farm itself. In this paper we address the problem of maximizing the revenue of a service provider by means of dynamic allocation policies that run the minimum amount of servers necessary to meet user's requirements in terms of performance. The results of several experiments executed using Wikipedia traces are described, showing that the proposed schemes work well, even if the workload is non-stationary. Since any resource allocation policy requires the use of forecasting mechanisms, various schemes allowing compensating errors in the load forecasts are presented and evaluated. © 2010 IEEE.


Mazzucco M.,University of Tartu | Mazzucco M.,Software Technology and Applications Competence Center | Dyachuk D.,University of Saskatchewan | Dyachuk D.,DemonWare
Sustainable Computing: Informatics and Systems | Year: 2012

Cloud providers, like Amazon, offer their data centers' computational and storage capacities for lease to paying customers. High electricity consumption, not only reflects on the data center's carbon footprint but also increases the costs of running the data center itself. We examine the problem of managing a server farm in a way that attempts to maximize the net revenue earned by a Cloud provider renting servers to customers according to a typical Platform-as-a-Service model. As a solution allocation policies which are based on the dynamic powering servers on and off are introduced and evaluated. The policies aim at satisfying the conflicting goals of maximizing the users' experience while minimizing the amount of consumed electricity. Special emphasis is given to cases where user demand is time-varying and cannot be predicted with absolute accuracy. In order to deal with that, allocation policies resilient to errors in the forecasting, as well as a method for finding the parameters leading to the highest revenues are introduced. The results of several experiments are described, showing that the proposed scheme performs well under different traffic conditions. © 2012 Elsevier Inc. All rights reserved.


Sor V.,Software Technology and Applications Competence Center | Sor V.,University of Tartu | Srirama S.N.,University of Tartu
Proceeding of the 2012 ACM Research in Applied Computation Symposium, RACS 2012 | Year: 2012

Memory leaks are major problems in distributed applications, depleting their performance, even if they run on platforms with automatic memory management like Java Virtual Machine. In the context of a Java memory leak detection tool, we faced a need for a graph storage and traversal library that could operate in memory restrained conditions with certain performance requirements. Before implementing a custom library we have evaluated existing open source graph libraries like JGraphT, Jung, jdsl, hgdb, Annas, HyperGraphDB, Dex and Neo4j, that can be used by embedding rather than a separate graph database process. Criteria for the comparison include size of the graph on disk, cpu and memory requirement for performing the shortest path search, license agreement terms. From this evaluation it is observed that graph databases become ideal choice only when hardware can be scaled for large problems, making it necessary for tailored solutions for managing large graphs in embedded environment. Copyright 2012 ACM.


Willemson J.,Cybernetica | Willemson J.,Software Technology and Applications Competence Center
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2011

Pseudonymization is sometimes used as a light-weight alternative to fully cryptographic solutions, when information from different data sources needs to be linked in a privacy-preserving manner. In this paper, we review several previously proposed pseudonymization techniques, point out their cryptographic and design flaws. As a solution, we have developed a simple pseudonymization framework based on X-Road, a unified database access layer serving as the basis for most eGovernment services developed in Estonia. Our solution has been fully implemented and benchmarking results together with the security analysis are presented to conclude the paper. © 2011 Springer-Verlag Berlin Heidelberg.


Laur S.,University of Tartu | Willemson J.,Cybernetica | Willemson J.,Software Technology and Applications Competence Center | Zhang B.,Cybernetica | Zhang B.,University of Tartu
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2011

Most of the multi-party computation frameworks can be viewed as oblivious databases where data is stored and processed in a secret-shared form. However, data manipulation in such databases can be slow and cumbersome without dedicated protocols for certain database operations. In this paper, we provide efficient protocols for oblivious selection, filtering and shuffle - essential tools in privacy-preserving data analysis. As the first contribution, we present a 1-out-of-n oblivious transfer protocol with O(loglogn) rounds, which achieves optimal communication and time complexity and works over any ring ℤN. Secondly, we show how to construct round-efficient shuffle protocols with optimal asymptotic computation complexity and provide several optimizations. © 2011 Springer-Verlag.


Heiberg S.,Cybernetica | Heiberg S.,Software Technology and Applications Competence Center
Lecture Notes in Business Information Processing | Year: 2013

Estonia has implemented a specific form of electronic voting - internet voting - as a method to participate in various types of legally binding elections since 2005. The mitigation of security risks in the method has lead to changes in the voting procedures. Those changes might affect the way we think about traditional voting. © 2013 Springer-Verlag Berlin Heidelberg.


Mazzucco M.,University of Tartu | Mazzucco M.,Software Technology and Applications Competence Center | Dyachuk D.,University of Saskatchewan
Future Generation Computer Systems | Year: 2012

High electricity consumption, associated with running Internet scale server farms, not only reflects on the data center's greenhouse gas emissions, but also increases the cost of running the data center itself. In this paper, we consider the problem of maximizing the revenues of service providers running large scale data centers subject to setup cost by reducing their electricity bill, while considering the fact that clients consuming the offered services have finite non-deterministic patience. As a solution, we present and evaluate the performance of allocation policies which, in the context of both one and two-tiered systems, dynamically switch servers on and off according to changes in user demand. The algorithms we present aim at maximizing the users' experience while minimizing the amount of electricity required to run the IT infrastructure in spite of non-stationary traffic which cannot be predicted with the absolute accuracy. The results of several experiments are presented, showing that the proposed schemes perform well under different traffic conditions. © 2011 Elsevier B.V. All rights reserved.


Kamm L.,University of Tartu | Kamm L.,Software Technology and Applications Competence Center | Kamm L.,Cybernetica | Bogdanov D.,University of Tartu | And 5 more authors.
Bioinformatics | Year: 2013

Motivation: Increased availability of various genotyping techniques has initiated a race for finding genetic markers that can be used in diagnostics and personalized medicine. Although many genetic risk factors are known, key causes of common diseases with complex heritage patterns are still unknown. Identification of such complex traits requires a targeted study over a large collection of data. Ideally, such studies bring together data from many biobanks. However, data aggregation on such a large scale raises many privacy issues. Results: We show how to conduct such studies without violating privacy of individual donors and without leaking the data to third parties. The presented solution has provable security guarantees. © 2013 The Author 2013. Published by Oxford University Press. All rights reserved.

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