Efficient Circuit Simulation in MapReduce

The MapReduce framework has firmly established itself as one of the most widely used parallel computing platforms for processing big data on tera- and peta-byte scale. Approaching it from a theoretical standpoint has proved to be notoriously difficult, however. In continuation of Goodrich et al.\u27s early efforts, explicitly espousing the goal of putting the MapReduce framework on footing equal to that of long-established models such as the PRAM, we investigate the obvious complexity question of how the computational power of MapReduce algorithms compares to that of combinational Boolean circuits commonly used for parallel computations. Relying on the standard MapReduce model introduced by Karloff et al. a decade ago, we develop an intricate simulation technique to show that any problem in NC (i.e., a problem solved by a logspace-uniform family of Boolean circuits of polynomial size and a depth polylogarithmic in the input size) can be solved by a MapReduce computation in O(T(n)/log n) rounds, where n is the input size and T(n) is the depth of the witnessing circuit family. Thus, we are able to closely relate the standard, uniform NC hierarchy modeling parallel computations to the deterministic MapReduce hierarchy DMRC by proving that NC^{i+1} subseteq DMRC^i for all i in N. Besides the theoretical significance, this result has important applied aspects as well. In particular, we show for all problems in NC^1 - many practically relevant ones, such as integer multiplication and division and the parity function, being among these - how to solve them in a constant number of deterministic MapReduce rounds

Complexity of Stability

Graph parameters such as the clique number, the chromatic number, and the independence number are central in many areas, ranging from computer networks to linguistics to computational neuroscience to social networks. In particular, the chromatic number of a graph (i.e., the smallest number of colors needed to color all vertices such that no two adjacent vertices are of the same color) can be applied in solving practical tasks as diverse as pattern matching, scheduling jobs to machines, allocating registers in compiler optimization, and even solving Sudoku puzzles. Typically, however, the underlying graphs are subject to (often minor) changes. To make these applications of graph parameters robust, it is important to know which graphs are stable for them in the sense that adding or deleting single edges or vertices does not change them. We initiate the study of stability of graphs for such parameters in terms of their computational complexity. We show that, for various central graph parameters, the problem of determining whether or not a given graph is stable is complete for ???, a well-known complexity class in the second level of the polynomial hierarchy, which is also known as "parallel access to NP.

Complexity of Stability

Graph parameters such as the clique number, the chromatic number, and the independence number are central in many areas, ranging from computer networks to linguistics to computational neuroscience to social networks. In particular, the chromatic number of a graph (i.e., the smallest number of colors needed to color all vertices such that no two adjacent vertices are of the same color) can be applied in solving practical tasks as diverse as pattern matching, scheduling jobs to machines, allocating registers in compiler optimization, and even solving Sudoku puzzles. Typically, however, the underlying graphs are subject to (often minor) changes. To make these applications of graph parameters robust, it is important to know which graphs are stable for them in the sense that adding or deleting single edges or vertices does not change them. We initiate the study of stability of graphs for such parameters in terms of their computational complexity. We show that, for various central graph parameters, the problem of determining whether or not a given graph is stable is complete for \Theta_2^p, a well-known complexity class in the second level of the polynomial hierarchy, which is also known as "parallel access to NP.

An Open Pouring Problem

We analyze a little riddle that has challenged mathematicians for half a century. Imagine three clubs catering to people with some niche interest. Everyone willing to join a club has done so and nobody new will pick up this eccentric hobby for the foreseeable future, thus the mutually exclusive clubs compete for a common constituency. Members are highly invested in their chosen club; only a targeted campaign plus prolonged personal persuasion can convince them to consider switching. Even then, they will never be enticed into a bigger group as they naturally pride themselves in avoiding the mainstream. Therefore each club occasionally starts a campaign against a larger competitor and sends its own members out on a recommendation program. Each will win one person over; the small club can thus effectively double its own numbers at the larger one’s expense. Is there always a risk for one club to wind up with zero members, forcing it out of business? If so, how many campaign cycles will this take?ISSN:1868-896

Finding Optimal Solutions With Neighborly Help

Can we efficiently compute optimal solutions to instances of a hard problem from optimal solutions to neighboring (i.e., locally modified) instances? For example, can we efficiently compute an optimal coloring for a graph from optimal colorings for all one-edge-deleted subgraphs? Studying such questions not only gives detailed insight into the structure of the problem itself, but also into the complexity of related problems; most notably graph theory\u27s core notion of critical graphs (e.g., graphs whose chromatic number decreases under deletion of an arbitrary edge) and the complexity-theoretic notion of minimality problems (also called criticality problems, e.g., recognizing graphs that become 3-colorable when an arbitrary edge is deleted). We focus on two prototypical graph problems, Colorability and Vertex Cover. For example, we show that it is NP-hard to compute an optimal coloring for a graph from optimal colorings for all its one-vertex-deleted subgraphs, and that this remains true even when optimal solutions for all one-edge-deleted subgraphs are given. In contrast, computing an optimal coloring from all (or even just two) one-edge-added supergraphs is in P. We observe that Vertex Cover exhibits a remarkably different behavior, demonstrating the power of our model to delineate problems from each other more precisely on a structural level. Moreover, we provide a number of new complexity results for minimality and criticality problems. For example, we prove that Minimal-3-UnColorability is complete for DP (differences of NP sets), which was previously known only for the more amenable case of deleting vertices rather than edges. For Vertex Cover, we show that recognizing beta-vertex-critical graphs is complete for Theta_2^p (parallel access to NP), obtaining the first completeness result for a criticality problem for this class

Delaying Decisions and Reservation Costs

We study the Feedback Vertex Set and the Vertex Cover problem in a natural variant of the classical online model that allows for delayed decisions and reservations. Both problems can be characterized by an obstruction set of subgraphs that the online graph needs to avoid. In the case of the Vertex Cover problem, the obstruction set consists of an edge (i.e., the graph of two adjacent vertices), while for the Feedback Vertex Set problem, the obstruction set contains all cycles. In the delayed-decision model, an algorithm needs to maintain a valid partial solution after every request, thus allowing it to postpone decisions until the current partial solution is no longer valid for the current request. The reservation model grants an online algorithm the new and additional option to pay a so-called reservation cost for any given element in order to delay the decision of adding or rejecting it until the end of the instance. For the Feedback Vertex Set problem, we first analyze the variant with only delayed decisions, proving a lower bound of $4$ and an upper bound of $5$ on the competitive ratio. Then we look at the variant with both delayed decisions and reservation. We show that given bounds on the competitive ratio of a problem with delayed decisions impliy lower and upper bounds for the same problem when adding the option of reservations. This observation allows us to give a lower bound of $\min{\{1+3\alpha,4\}}$ and an upper bound of $\min{\{1+5\alpha,5\}}$ for the Feedback Vertex Set problem. Finally, we show that the online Vertex Cover problem, when both delayed decisions and reservations are allowed, is $\min{\{1+2\alpha, 2\}}$-competitive, where $\alpha \in \mathbb{R}_{\geq 0}$ is the reservation cost per reserved vertex.Comment: 14 Pages, submitte

Quantifizierung lokaler Grundwassereintritte in die Spree und deren Bedeutung für die Verockerungsproblematik in der Laustiz

Local groundwater inflow is an unknown but central component for the precipitation and accumulation of iron in the Spree River, Lusatia. In this study, the natural tracer radon was used to map and quantify local groundwater inflows into the Spree and Kleine Spree rivers in the Lusatian lignite mining district. During two measurement campaigns, the total groundwater inflow for a 20 km long reach of the Kleine Spree and a 34 km long reach of the Spree ranged between ~3,000 and ~7,000 m³ d⁻¹ (Kleine Spree) and between ~20,000 and ~38,000 m³ d⁻¹ (Spree). Particularly high groundwater inflow was identified (up to 70% of total inflow) along the Spreewitzer Rinne, a local aquifer consisting of excavated mining materials. Along these river reaches, large amounts of dissolved iron are entering the rivers with inflowing groundwater. Using the measured iron and sulphate loadings, we calculated that up to 120 tons/day of iron (oxy)-hydroxide was retained in the combined Spree and Klein Spree catchments

Rust for secure IoT applications : why C is getting rusty

Memory corruption is still the most used type of exploit in today’s malware landscape. Human error inevitably introduces memory vulnerabilities into software by using memory-unsafe languages like C and C++, affecting not only security but also safety, dependability, and even basic functionality of devices. The Rust language guarantees memory safety without a garbage collector, promises comparable performance to C/C++, and allows for gradual extension of existing codebases by using its foreign function interface. This report presents the risks of having memory vulnerabilities in embedded applications, what a switch to Rust looks like, how the development experiences differ between Rust and C/C++, and if there are significant differences in performance