Investigating Basic Quality of Service Design Possibilities for Regis University Academic Research Network Edge Routers

The Regis University Academic Research Network (ARNe) had network resources, such as VoIP, that required preservation their ability to receive near real-time forwarding treatment across the network. Quality of Service (QoS) design ideas were examined from four actual implementations described in research cases. Additionally, research involving surveys from Cisco certified professionals was examined, and Cisco technical literature was examined. Case study methodology, involving the study of multiple cases, was the primary tactic utilized in this research. Examination and triangulation of data from the research indicated that ARNe would benefit from moving forward with a basic QoS design and implementation, integrating concepts identified in the data. Additionally, data supported that a basic QoS design and implementation on ARNe would provide Computer Science and Information Science students an opportunity to more fully appreciate QoS through further research and hands-on experience

How acid are lemons? Adverse selection and signalling for skilled labour market entrants

This paper jointly analyses the consequences of adverse selection and signalling on entry wages of skilled employees. It uses German linked employer employee panel data (LIAB) and introduces a measure for relative productivity of skilled job applicants based on apprenticeship wages. It shows that post-apprenticeship employer changers are a negative selection from the training firms’ point of view. Negative selection leads to lower average wages of employer changersin the first skilled job in comparison to stayers. Entry wages of employer changers are specifically reduced by high occupation and training firm retention rates. Additional training firm signals are high apprenticeship wages that signal a positive selection of apprenticeship applicants, works councils and establishment size. Finally, positive individual signals such as schooling background affect the skilled entry wages of employer changers positively

Hollow Heaps

We introduce the hollow heap, a very simple data structure with the same amortized efficiency as the classical Fibonacci heap. All heap operations except delete and delete-min take $O(1)$ time, worst case as well as amortized; delete and delete-min take $O(\log n)$ amortized time on a heap of $n$ items. Hollow heaps are by far the simplest structure to achieve this. Hollow heaps combine two novel ideas: the use of lazy deletion and re-insertion to do decrease-key operations, and the use of a dag (directed acyclic graph) instead of a tree or set of trees to represent a heap. Lazy deletion produces hollow nodes (nodes without items), giving the data structure its name.Comment: 27 pages, 7 figures, preliminary version appeared in ICALP 201

Optimal resizable arrays

A \emph{resizable array} is an array that can \emph{grow} and \emph{shrink} by the addition or removal of items from its end, or both its ends, while still supporting constant-time \emph{access} to each item stored in the array given its \emph{index}. Since the size of an array, i.e., the number of items in it, varies over time, space-efficient maintenance of a resizable array requires dynamic memory management. A standard doubling technique allows the maintenance of an array of size~$N$ using only $O(N)$ space, with $O(1)$ amortized time, or even $O(1)$ worst-case time, per operation. Sitarski and Brodnik et al.\ describe much better solutions that maintain a resizable array of size~$N$ using only $N+O(\sqrt{N})$ space, still with $O(1)$ time per operation. Brodnik et al.\ give a simple proof that this is best possible. We distinguish between the space needed for \emph{storing} a resizable array, and accessing its items, and the \emph{temporary} space that may be needed while growing or shrinking the array. For every integer $r\ge 2$, we show that $N+O(N^{1/r})$ space is sufficient for storing and accessing an array of size~$N$, if $N+O(N^{1-1/r})$ space can be used briefly during grow and shrink operations. Accessing an item by index takes $O(1)$ worst-case time while grow and shrink operations take $O(r)$ amortized time. Using an exact analysis of a \emph{growth game}, we show that for any data structure from a wide class of data structures that uses only $N+O(N^{1/r})$ space to store the array, the amortized cost of grow is $\Omega(r)$, even if only grow and access operations are allowed. The time for grow and shrink operations cannot be made worst-case, unless $r=2$.Comment: To appear in SOSA 202

Optimal energetic paths for electric cars

A weighted directed graph $G=(V,A,c)$, where $A\subseteq V\times V$ and $c:A\to R$, describes a road network in which an electric car can roam. An arc $uv$ models a road segment connecting the two vertices $u$ and $v$. The cost $c(uv)$ of an arc $uv$ is the amount of energy the car needs to traverse the arc. This amount may be positive, zero or negative. To make the problem realistic, we assume there are no negative cycles. The car has a battery that can store up to $B$ units of energy. It can traverse an arc $uv\in A$ only if it is at $u$ and the charge $b$ in its battery satisfies $b\ge c(uv)$. If it traverses the arc, it reaches $v$ with a charge of $\min(b-c(uv),B)$. Arcs with positive costs deplete the battery, arcs with negative costs charge the battery, but not above its capacity of $B$. Given $s,t\in V$, can the car travel from $s$ to $t$, starting at $s$ with an initial charge $b$, where $0\le b\le B$? If so, what is the maximum charge with which the car can reach $t$? Equivalently, what is the smallest $\delta_{B,b}(s,t)$ such that the car can reach $t$ with a charge of $b-\delta_{B,b}(s,t)$, and which path should the car follow to achieve this? We refer to $\delta_{B,b}(s,t)$ as the energetic cost of traveling from $s$ to $t$. We let $\delta_{B,b}(s,t)=\infty$ if the car cannot travel from $s$ to $t$ starting with an initial charge of $b$. The problem of computing energetic costs is a strict generalization of the standard shortest paths problem. We show that the single-source minimum energetic paths problem can be solved using simple, but subtle, adaptations of the Bellman-Ford and Dijkstra algorithms. To make Dijkstra's algorithm work in the presence of negative arcs, but no negative cycles, we use a variant of the $A^*$ search heuristic. These results are explicit or implicit in some previous papers. We provide a simpler and unified description of these algorithms.Comment: 11 page

The pear psylla in Oregon

Since its discovery in Oregon in 1946, the pear psylla, Psylla pyricola Forster, has become the most serious insect pest of pear. Damage to pear trees include the transmission of pear decline disease which has caused losses of trees, injection of a phytotoxic toxin resulting in tree shock and injury, and secretion of honeydew causing fruit marking. Aspects of pear psylla biology are discussed in relation to the pest's control. Natural enemies are known to exert some suppression of pear psylla populations late in the growing season but the application of insecticides, many of which the pest has become resistant to, is the only means presently available for reducing pear psylla populations to subeconomic levels.Published November 1972. Facts and recommendations in this publication may no longer be valid. Please look for up-to-date information in the OSU Extension Catalog: http://extension.oregonstate.edu/catalo