A Tale of Two Data-Intensive Paradigms: Applications, Abstractions, and Architectures

Scientific problems that depend on processing large amounts of data require overcoming challenges in multiple areas: managing large-scale data distribution, co-placement and scheduling of data with compute resources, and storing and transferring large volumes of data. We analyze the ecosystems of the two prominent paradigms for data-intensive applications, hereafter referred to as the high-performance computing and the Apache-Hadoop paradigm. We propose a basis, common terminology and functional factors upon which to analyze the two approaches of both paradigms. We discuss the concept of "Big Data Ogres" and their facets as means of understanding and characterizing the most common application workloads found across the two paradigms. We then discuss the salient features of the two paradigms, and compare and contrast the two approaches. Specifically, we examine common implementation/approaches of these paradigms, shed light upon the reasons for their current "architecture" and discuss some typical workloads that utilize them. In spite of the significant software distinctions, we believe there is architectural similarity. We discuss the potential integration of different implementations, across the different levels and components. Our comparison progresses from a fully qualitative examination of the two paradigms, to a semi-quantitative methodology. We use a simple and broadly used Ogre (K-means clustering), characterize its performance on a range of representative platforms, covering several implementations from both paradigms. Our experiments provide an insight into the relative strengths of the two paradigms. We propose that the set of Ogres will serve as a benchmark to evaluate the two paradigms along different dimensions.Comment: 8 pages, 2 figure

Protocols versus objects: can models for telecommunications and distributed processing coexist?

This paper identifies two paradigms that influence the design of telematics systems nowadays: the protocol-centred and the object-centred paradigms. Both paradigms have been introduced to cope with interoperability, each in their own way. The coexistence of these paradigms can have an enormous impact on the design of telematics systems. This paper identifies some combined uses of both paradigms and some fundamental research problems related to the coexistence of these paradigm

Two Paradigms of Jurisdiction

Globalization causes convergence of legal orders. Or so it is argued. Law and economics scholars predict that legal orders will move towards the same efficient end state. They argue that the requirements of globalization will pressure legal orders to converge on the level of economic efficiency, because regulatory competition between legal orders makes it impossible for individual legal systems to maintain suboptimal solutions. Many comparative lawyers predict a similar convergence. In particular traditional functionalist comparatists have long held that unification of law was both desirable and unavoidable. Their basic argument is based on functional equivalence and can be summarized as follows: legal systems may look different because they have different doctrines and institutions; these differences, however, are only superficial, because the institutions fulfill the same functions and are therefore actually similar. Realizing that legal orders are already similar in substance should make it easy to unify the law formally as well

Paradigms for Parameterized Enumeration

The aim of the paper is to examine the computational complexity and algorithmics of enumeration, the task to output all solutions of a given problem, from the point of view of parameterized complexity. First we define formally different notions of efficient enumeration in the context of parameterized complexity. Second we show how different algorithmic paradigms can be used in order to get parameter-efficient enumeration algorithms in a number of examples. These paradigms use well-known principles from the design of parameterized decision as well as enumeration techniques, like for instance kernelization and self-reducibility. The concept of kernelization, in particular, leads to a characterization of fixed-parameter tractable enumeration problems.Comment: Accepted for MFCS 2013; long version of the pape

Almost Equivalent Paradigms of Contextuality

Various frameworks that generalise the notion of contextuality in theories of physics have been proposed; one is the sheaf-theoretic approach by Abramsky and Brandenburger; an other is the equivalence-based approach by Spekkens. We show that these frameworks are equivalent for scenarios with preparations and measurements, whenever factorizability is justified. This connection gives rise to a categorical isomorphism between suitable categories. We combine the advantages of the two approaches to derive a canonical method for detecting contextuality in such settings.Comment: In Proceedings QPL 2017, arXiv:1802.0973

Paradigms in Management

The paper laments the current confusion in business science with regard to its epistemology. Any scientific discipline needs a firm structural basis, otherwise research is unfocused and flawed. In business science not even the vocabulary is clear: terms like Management and Business Administration mean many things to different people. The paper suggests to replace Burrell and Morgan’s matrix of sociological paradigms with a new typology which is really able to guide research and practice alike. Management scholars have argued too long without any sense of direction and managers have as a result become reserved and somewhat cynical toward Management theory.Epistemology, paradigms in business, theory and practice, management, business science, sociology