Towards Distributed Convoy Pattern Mining

Mining movement data to reveal interesting behavioral patterns has gained attention in recent years. One such pattern is the convoy pattern which consists of at least m objects moving together for at least k consecutive time instants where m and k are user-defined parameters. Existing algorithms for detecting convoy patterns, however do not scale to real-life dataset sizes. Therefore a distributed algorithm for convoy mining is inevitable. In this paper, we discuss the problem of convoy mining and analyze different data partitioning strategies to pave the way for a generic distributed convoy pattern mining algorithm.Comment: SIGSPATIAL'15 November 03-06, 2015, Bellevue, WA, US

The Belt and Road Initiative for an intercontinental ecosystem: Strategic implications for multinational enterprises around the world

[Extract] International trade and foreign direct investment (FDI), as well as other forms of cross-border economic activities, are essential to globalization, even in the emerging era of neoglobalization as a unique balance between globalization and deglobalization. Despite the hype, globalization is a relatively new phenomenon

An effective scalable SQL engine for NoSQL databases

NoSQL databases were initially devised to support a few concrete extreme scale applications. Since the specificity and scale of the target systems justified the investment of manually crafting application code their limited query and indexing capabilities were not a major im- pediment. However, with a considerable number of mature alternatives now available there is an increasing willingness to use NoSQL databases in a wider and more diverse spectrum of applications and, to most of them, hand-crafted query code is not an enticing trade-off. In this paper we address this shortcoming of current NoSQL databases with an effective approach for executing SQL queries while preserving their scalability and schema flexibility. We show how a full-fledged SQL engine can be integrated atop of HBase leading to an ANSI SQL compli- ant database. Under a standard TPC-C workload our prototype scales linearly with the number of nodes in the system and outperforms a NoSQL TPC-C implementation optimized for HBase.(undefined

Caju: a content distribution system for edge networks

More and more, users store their data in the cloud. While the content is then retrieved, the retrieval has to respect quality of service (QoS) constraints. In order to reduce transfer latency, data is replicated. The idea is make data close to users and to take advantage of providers home storage. However to minimize the cost of their platform, cloud providers need to limit the amount of storage usage. This is still more crucial for big contents. This problem is hard, the distribution of the popularity among the stored pieces of data is highly non-uniform: several pieces of data will never be accessed while others may be retrieved thousands of times. Thus, the trade-off between storage usage and QoS of data retrieval has to take into account the data popularity. This report presents our architecture gathering several storage domains composed of small-sized datacenters and edge devices; and it shows the importance of adapting the replication degree to data popularity. Our simulations, using realistic workloads, show that a simple cache mechanism provides a eight-fold ecrease in the number of SLA violations, requires up to 10 times less of storage capacity for replicas, and reduces aggregate bandwidth and number of flows by half.Les données des utilisateurs sont de plus en plus externalisées, stockées dans des clouds. Lors de la récupération des données, une certaine qualité de service doit être respectée. Afin de réduire la latence d'accès, les données sont répliquées. L'idée est de rapprocher les données des utilisateurs, mais également, de tirer avantage des systèmes de stockage du fournisseur chez l'utilisateur (les ''boxes''). Cependant, afin de minimiser le coût de leur plate-forme les opérateurs de cloud doivent limiter la quantité de stockage utilisée. Ceci est d'autant plus important que les données sont volumineuses. Ce problème est dur, les données ne sont pas toutes également populaires, la popularité est distribuée de manière très hétérogène: certaines données ne seront jamais accédées alors que d'autres seront demandées des milliers de fois. Le bon compromis entre l'utilisation de l'espace de stockage et la qualité de service doit donc prendre en compte la popularité des données. Ce rapport présente notre architecture qui rassemble plusieurs domaines de stockage composés de data-center de petite taille et de périphériques de bordure; il montre l'importance d'adapter le degré de réplication à la popularité des données. Nos simulations, montrent qu'un simple mécanisme de cache arrive a diviser par 8 le nombre de violations de SLA (Service Level Agreement) tout en nécessitant 10 fois moins de capacité de stockage

Investments in recessions

We argue that the strategy literature has been virtually silent on the issue of recessions, and that this constitutes a regrettable sin of omission. A key route to rectify this omission is to focus on how recessions affect investment behavior, and thereby firms stocks of assets and capabilities which ultimately will affect competitive outcomes. In the present paper we aim to contribute by analyzing how two key aspects of recessions, demand reductions and reductions in credit availability, affect three different types of investments: physical capital, R&D and innovation and human- and organizational capital. We point out that recessions not only affect the level of investment, but also the composition of investments. Some of these effects are quite counterintuitive. For example, investments in R&D are more sensitive to credit constraints than physical capital is. Investments in human capital grow as demand falls, and both R&D and human capital investments show important nonlinearities with respect to changes in demand

On the expressiveness and trade-offs of large scale tuple stores

Proceedings of On the Move to Meaningful Internet Systems (OTM)Massive-scale distributed computing is a challenge at our doorstep. The current exponential growth of data calls for massive-scale capabilities of storage and processing. This is being acknowledged by several major Internet players embracing the cloud computing model and offering first generation distributed tuple stores. Having all started from similar requirements, these systems ended up providing a similar service: A simple tuple store interface, that allows applications to insert, query, and remove individual elements. Further- more, while availability is commonly assumed to be sustained by the massive scale itself, data consistency and freshness is usually severely hindered. By doing so, these services focus on a specific narrow trade-off between consistency, availability, performance, scale, and migration cost, that is much less attractive to common business needs. In this paper we introduce DataDroplets, a novel tuple store that shifts the current trade-off towards the needs of common business users, pro- viding additional consistency guarantees and higher level data process- ing primitives smoothing the migration path for existing applications. We present a detailed comparison between DataDroplets and existing systems regarding their data model, architecture and trade-offs. Prelim- inary results of the system's performance under a realistic workload are also presented

Economic liberalization and the antecedents of top management teams: evidence from Turkish 'big' business

There has been an increased interest in the last two decades in top management teams (TMTs) of business firms. Much of the research, however, has been US-based and concerned primarily with TMT effects on organizational outcomes. The present study aims to expand this literature by examining the antecedents of top team composition in the context of macro-level economic change in a late-industrializing country. The post-1980 trade and market reforms in Turkey provided the empirical setting. Drawing upon the literatures on TMT and chief executive characteristics together with punctuated equilibrium models of change and institutional theory, the article develops the argument that which firm-level factors affect which attributes of TMT formations varies across the early and late stages of economic liberalization. Results of the empirical investigation of 71 of the largest industrial firms in Turkey broadly supported the hypotheses derived from this premise. In the early stages of economic liberalization the average age and average organizational tenure of TMTs were related to the export orientation of firms, whereas in later stages, firm performance became a major predictor of these team attributes. Educational background characteristics of teams appeared to be under stronger institutional pressures, altering in different ways in the face of macro-level change

Differences that matter: hiring modes and demographic (dis)similarity in executive selection

Scholars, practitioners, and policymakers have long acknowledged the importance of understanding the antecedents of top management team (TMT) composition. Yet, research on how and why firms select executives who are demographically dissimilar to incumbent TMT members remains limited. We take a step toward answering these questions by employing a sample of 575 individual-level executive appointments at 170 large European firms between 2005 and 2009. Drawing on the person-group fit perspective, we argue that firms are more likely to appoint socio-demographically dissimilar executives through internal promotion – while external hires are more likely to socio-demographically resemble incumbent top managers. Our results support the hypothesized relationship. They also show that this relationship is influenced by the level of administrative complexity and environmental uncertainty facing the firm. Overall, our theory and results enhance our understanding of ‘why top management teams are composed the way they are’, by highlighting the impact of internal and external hiring modes in the selection of demographically (dis)similar executives

The changing rationale for governance choices: early vs. late adopters of global services sourcing

This article studies how the logic of firm governance choices varies as a function of the time of adoption of particular sourcing practices. Using data on the diffusion of global business services sourcing as a management practice from early experiments in the 1980s through 2011, we show that the extent to which governance choices are affected by process commoditization, availability of external service capabilities, and past governance choices depends on whether firms are early or late adopters. Findings inform research on governance choice dynamics specifically in highly diverse and evolving firm populations