Increasingly ubiquitous communication networks and connectivity via portable devices have engendered a host of applications in which sources, for example people and environmental sensors, send updates of their status to interested recipients. These applications desire status updates at the recipients to be as timely as possible; however, this is typically constrained by limited network resources. In this paper, we employ a time-average age metric for the performance evaluation of status update systems. We derive general methods for calculating the age metric that can be applied to a broad class of service systems. We apply these methods to queue-theoretic system abstractions consisting of a source, a service facility and monitors, with the model of the service facility (physical constraints) a given. The queue discipline of first-come-first-served (FCFS) is explored. We show the existence of an optimal rate at which a source must generate its information to keep its status as timely as possible at all its monitors. This rate differs from those that maximize utilization (throughput) or minimize status packet delivery delay. While our abstractions are simpler than their real-world counterparts, the insights obtained, we believe, are a useful starting point in understanding and designing systems that support real time status updates.

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Real-time status: How often should one update?

(1) Whereas the objectives of the Community, as laid down in the Treaty, as amended by the Treaty on European Union, include creating an ever closer union among the peoples of Europe, fostering closer relations between the States belonging to the Community, ensuring economic and social progress by common action to eliminate the barriers which divide Europe, encouraging the constant improvement of the living conditions of its peoples, preserving and strengthening peace and liberty and promoting democracy on the basis of the fundamental rights recognized in the constitution and laws of the Member States and in the European Convention for the Protection of Human Rights and Fundamental Freedoms;

Some Preliminary Comments on the DIRECTIVE 95/46/EC OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL of 24 October 1995 on the protection of individuals with regard to the processing of personal data and on the free movement of such data.

Data matching (also known as record or data linkage, entity resolution, object identification, or field matching) is the task of identifying, matching and merging records that correspond to the same entities from several databases or even within one database. Based on research in various domains including applied statistics, health informatics, data mining, machine learning, artificial intelligence, database management, and digital libraries, significant advances have been achieved over the last decade in all aspects of the data matching process, especially on how to improve the accuracy of data matching, and its scalability to large databases. Peter Christens book is divided into three parts: Part I, Overview, introduces the subject by presenting several sample applications and their special challenges, as well as a general overview of a generic data matching process. Part II, Steps of the Data Matching Process, then details its main steps like pre-processing, indexing, field and record comparison, classification, and quality evaluation. Lastly, part III, Further Topics, deals with specific aspects like privacy, real-time matching, or matching unstructured data. Finally, it briefly describes the main features of many research and open source systems available today. By providing the reader with a broad range of data matching concepts and techniques and touching on all aspects of the data matching process, this book helps researchers as well as students specializing in data quality or data matching aspects to familiarize themselves with recent research advances and to identify open research challenges in the area of data matching. To this end, each chapter of the book includes a final section that provides pointers to further background and research material. Practitioners will better understand the current state of the art in data matching as well as the internal workings and limitations of current systems. Especially, they will learn that it is often not feasible to simply implement an existing off-the-shelf data matching system without substantial adaption and customization. Such practical considerations are discussed for each of the major steps in the data matching process.

Data Matching: Concepts and Techniques for Record Linkage, Entity Resolution, and Duplicate Detection

We examine multiple independent sources providing status updates to a monitor through simple queues. We formulate an age of information (AoI) timeliness metric and derive a general result for the AoI that is applicable to a wide variety of multiple source service systems. For first-come first-served and two types of last-come first-served systems with Poisson arrivals and exponential service times, we find the region of feasible average status ages for multiple updating sources. We then use these results to characterize how a service facility can be shared among multiple updating sources. A new simplified technique for evaluating the AoI in finite-state continuous-time queuing systems is also derived. Based on stochastic hybrid systems, this method makes AoI evaluation to be comparable in complexity to finding the stationary distribution of a finite-state Markov chain.

The Age of Information: Real-Time Status Updating by Multiple Sources

Anytime, anywhere network connectivity, together with portable sensing and computing devices have led to applications in which sources, for example people or environmental sensors, send updates of their status, for example location, to interested recipients, say a location service. These applications desire status updates at the recipients to be as timely as possible; however, this is typically constrained by limited network resources. We employ a time-averaged age metric for characterizing performance of such status update systems. We use system abstractions consisting of a source, a service facility and monitors, with the model of the service facility (physical constraints) a given. While prior work examined first-come-first-served (FCFS) queues, this paper looks at the queue discipline of last-come-first-served (LCFS). We explore LCFS systems with and without the ability to preempt the packet currently in service. For each we derive a general expression for system age and solve for the average age a Poisson source can achieve given memoryless service. Specifically, when preemption is allowed, we evaluate how the source would share the service facility with other independent Poisson sources.

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Status updates through queues

Traditionally, the refreshment of data warehouses has been performed in an off-line fashion. Active Data Warehousing refers to a new trend where data warehouses are updated as frequently as possible, to accommodate the high demands of users for fresh data. In this paper, we propose a framework for the implementation of active data warehousing, with the following goals: (a) minimal changes in the software configuration of the source, (b) minimal overhead for the source due to the active nature of data propagation, (c) the possibility of smoothly regulating the overall configuration of the environment in a principled way. In our framework, we have implemented ETL activities over queue networks and employ queue theory for the prediction of the performance and the tuning of the operation of the overall refreshment process. Due to the performance overheads incurred, we explore different architectural choices for this task and discuss the issues that arise for each of them.

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ETL queues for active data warehousing

Phonetic codes such as Soundex and Metaphone havebeen used in the past to address the Record Linkage Problem.However, to the best of our knowledge, no particulareffort was made within this context towards privacy assuranceduring the matching process. Phonetic codes have aninteresting feature which can be cornerstone to providingprivacy. They are mappings of strings which do not exhibitthe one-to-one property.In this paper, we present a novel protocol for achieving privacypreserving record linkage using phonetics, we provideproof of correctness for our approach and finally we illustrateexperimental results concerning performance andmatching accuracy. The proposed protocol can be equallywell applied to codes different than the phonetic ones, which do not exhibit the one-to-one property, such as hash tables with comparable results.

Privacy Preserving Record Linkage Using Phonetic Codes

Performing approximate data matching has always been an intriguing problem for both industry and academia. This task becomes even more challenging when the requirement of data privacy rises. In this paper, we propose a novel technique to address the problem of efficient privacy-preserving approximate record linkage. The secure framework we propose consists of two basic components. First, we utilize a secure blocking component based on phonetic algorithms statistically enhanced to improve security. Second, we use a secure matching component where actual approximate matching is performed using a novel private approach of the Levenshtein Distance algorithm. Our goal is to combine the speed of private blocking with the increased accuracy of approximate secure matching. Category: Ubiquitous computing; Security and privacy

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Secure Blocking + Secure Matching = Secure Record Linkage

In many aspects of everyday life, from education to health care and from economics to homeland security, information exchange involving companies or government agencies has become a common application. Locating the same real world entities within this information however is not trivial at all due to insufficient identifying information, misspellings, etc. The problem becomes even more complicated when privacy considerations arise. This introduction describes an informal approach to the privacy preserving record linkage problem. In this paper we provide a solution to this problem by examining the alternatives offered by phonetic codes, a range of algorithms which despite their age, are still used for record linkage purposes. The main contribution of our work, as our extensive experimental evaluation indicates, is that our methodology manages to offer privacy guarantees for performing Privacy Preserving Record Linkage without the need of computationally expensive cryptographic methods.

Fake injection strategies for private phonetic matching

Privacy-preserving record linkage is a very important task, mostly because of the very sensitive nature of the personal data. The main focus in this task is to find a way to match records from among different organisation data sets or databases without revealing competitive or personal information to non-owners. Towards accomplishing this task, several methods and protocols have been proposed. In this work, we propose a certain methodology for preserving the privacy of various record linkage approaches and we implement, examine and compare four pairs of privacy preserving record linkage methods and protocols. Two of these protocols use n-gram based similarity comparison techniques, the third protocol uses the well known edit distance and the fourth one implements the Jaro-Winkler distance metric. All of the protocols used are enhanced by private key cryptography and hash encoding. This paper presents also a blocking scheme as an extension to the privacy preserving record linkage methodology. Our comparison is backed up by extended experimental evaluation that demonstrates the performance achieved by each of the proposed protocols.

Alexandros Karakasidis

Papers

ETL queues for active data warehousing

Privacy Preserving Record Linkage Using Phonetic Codes

Secure Blocking + Secure Matching = Secure Record Linkage

Fake injection strategies for private phonetic matching

Privacy preserving record linkage approaches