Device-to-device (D2D) communications was initially proposed in cellular networks as a new paradigm for enhancing network performance. The emergence of new applications such as content distribution and location-aware advertisement introduced new user cases for D2D communications in cellular networks. The initial studies showed that D2D communications has advantages such as increased spectral efficiency and reduced communication delay. However, this communication mode introduces complications in terms of interference control overhead and protocols that are still open research problems. The feasibility of D2D communications in Long-Term Evolution Advanced is being studied by academia, industry, and standardization bodies. To date, there are more than 100 papers available on D2D communications in cellular networks, but there is no survey on this field. In this paper, we provide a taxonomy based on the D2D communicating spectrum and review the available literature extensively under the proposed taxonomy. Moreover, we provide new insights into the over-explored and under-explored areas that lead us to identify open research problems of D2D communications in cellular networks.

https://eprints.networks.imdea.org/id/document/2488

A Survey on Device-to-Device Communication in Cellular Networks

Lösung: Man kann die Ebene mit Sechsecken überdecken. Nimmt man die Mittelpunkte der Sechsecke als Punkte für ein Voronoidiagramm, dann haben alle genau 6 Nachbarn, und die Voronoi Polygone sind gerade die Sechsecke. Gäbe es eine Punkteverteilung, bei der jeder Punkt mehr als sechs Nachbarn hätte, dann könnte man die Punkte so hinschieben, dass die Voronoi Polygone regelmässige n-Ecke mit n > 6 wären. Eine solche Überdeckung der Ebene gibt es aber nicht (wie man sich leicht aus einer Betrachtung der Winkel überlegen kann).

Computational geometry

The Ball-Pivoting Algorithm (BPA) computes a triangle mesh interpolating a given point cloud. Typically, the points are surface samples acquired with multiple range scans of an object. The principle of the BPA is very simple: Three points form a triangle if a ball of a user-specified radius p touches them without containing any other point. Starting with a seed triangle, the ball pivots around an edge (i.e., it revolves around the edge while keeping in contact with the edge's endpoints) until it touches another point, forming another triangle. The process continues until all reachable edges have been tried, and then starts from another seed triangle, until all points have been considered. The process can then be repeated with a ball of larger radius to handle uneven sampling densities. We applied the BPA to datasets of millions of points representing actual scans of complex 3D objects. The relatively small amount of memory required by the BPA, its time efficiency, and the quality of the results obtained compare favorably with existing techniques.

/pdf/the-ball-pivoting-algorithm-for-surface-reconstruction-12jv6xu280.pdf

The ball-pivoting algorithm for surface reconstruction

....The most comprehensive guide to designing practical and efficient algorithms!.... The Algorithm Design Manual, Second Edition "...the book is an algorithm-implementation treasure trove, and putting all of these implementations in one place was no small feat. The list of implementations [and] extensive bibliography make the book an invaluable resource for everyone interested in the subject." --ACM Computing Reviews "It has all the right ingredients: rich contents, friendly, personal language, subtle humor, the right references, and a plethora of pointers to resources."-- P. Takis Metaxas, Wellesley College "This is the most approachable book on algorithms I have." -- Megan Squire, Elon University, USA This newly expanded and updated second edition of the best-selling classic continues to take the "mystery" out of designing algorithms, and analyzing their efficacy and efficiency. Expanding onthe first edition, the book now serves as the primary textbook of choice for algorithm design courses while maintaining its status as the premier practical reference guide to algorithms for programmers, researchers, and students. The reader-friendly Algorithm Design Manual provides straightforward access to combinatorial algorithms technology, stressing design over analysis. The first part, Techniques, provides accessible instructionon methods for designing and analyzing computer algorithms. The second part, Resources, is intended for browsing and reference, and comprises the catalog of algorithmic resources, implementations and an extensive bibliography. NEW to the second edition: Doubles the tutorial material and exercises over the first edition Provides full online support for lecturers, and a completely updated and improved website component with lecture slides, audio and video Contains a unique catalog identifying the 75 algorithmic problems that arise most often in practice, leading the reader down the right path to solve them Includes several NEW "war stories" relating experiences from real-world applications Provides up-to-date links leading to the very best algorithm implementations available in C, C++, and Java ADDITIONAL Learning Tools: Exercises include "job interview problems" from major software companies Highlighted take-home lesson boxes emphasize essential concepts Provides comprehensive references to both survey articles and the primary literature Exercises points to relevant programming contest challenge problems Many algorithms presented with actual code (written in C) as well as pseudo-code A full set of lecture slides and additional material available at www.algorist.com Written by a well-known algorithms researcher who received the IEEE Computer Science and Engineering Teaching Award, this new edition of The Algorithm Design Manual is an essential learning tool for students needing a solid grounding in algorithms, as well as a special text/reference for professionals who need an authoritative and insightful guide. Professor Skiena is also author of the popular Springer text, Programming Challenges: The Programming Contest Training Manual.

http://www.r-5.org/files/books/computers/algo-list/common/Steven_Skiena-The_Algorithm_Design_Manual-EN.pdf

The Algorithm Design Manual

https://dash.harvard.edu/bitstream/handle/1/29005173/Formulation%20of%20Functionalized%20PLGA-PEG.pdf?sequence=1

Formulation of functionalized PLGA-PEG nanoparticles for in vivo targeted drug delivery

We consider the problems of conflict detection and resolution in air traffic management (ATM) from the perspective of computational geometry and give algorithms for solving these problems efficiently. For conflict resolution, we propose a simple method that can route multiple aircraft, conflict-free, through a cluttered airspace, using a prioritized routing scheme in space-time. Our algorithms have been implemented into a simulation system that tracks a large set of flights, having multiple conflicts, and proposes modified routes to resolve them. We report on the preliminary results from an extensive set of experiments that are under may to determine the effectiveness of our methods.

/pdf/geometric-algorithms-for-conflict-detection-resolution-in-gpcdmrvl9i.pdf

Geometric algorithms for conflict detection/resolution in air traffic management

We consider the two-point query version of the fundamental geometric shortest path problem: Given a set h of polygonal obstacles iu the plane, having a total of n vertices, build a data structure such that for any two query points s and t we can efficiently determine the length, d(s,t), of an Euclidean shortest obstacle-avoiding path, *(s,t), from s to t. Additionally, our data structure should allow one to report the path x(s, t), in time proportional to its (combinatorial) size. We present various methods for solving this two-point query problem, including algorithms with o(n), O(log n+h), 0( h log n), O(log’ n) or optimal O(log n) query times, using polynomial-space data structures, with various tradeoffs between space and query time. While severa results have been known for approtimate twepoint Euclidean shortest path queries, it has been a well-publicized open problem to obtain sublinear query time for the exact version of the problem. Our methods also yield data structures for twc+point shortest path queries on nonconvex polyhedral

http://ce.sharif.ac.ir/~ghodsi/archive/d-papers/ACM%20SODA/1999/Two-point%20Euclidean%20shortest%20path%20queries%20in%20the%20plane%20.pdf

Two-point Euclidean shortest path queries in the plane

In this paper we give I/O-optimal techniques for the extraction of isosurfaces from volumetric data, by a novel application of the UOoptimal interval tree of Arge aud Vitter. The main idea is to prepmcess the dataset once anal for all to build au efficient search strutture in disk, aud then each time we want to extract au isosurface, we perform au ourput-sensitive query on the search structure to retrieve only those active cells that are intersected by the isosurfaceDuring the query operation, only two blocks of main memory space are needed, and ouly those active cells am brought into the main memory, plus some negligible overhead of disk accesses. This implies hat we can efficiently visualize very large datasets on workstations with just enough maiu memory to hold the isosu&ces tltemselves. The implementation is delicate but not complicated. We give the first implementation of the I/O-optimal interval tree, aud also implement our methods as au VO jilter for Vtk’s isosurface extractiou for the case of uustructured grids. We show that, in practice, our algorithms improve the performauce of isosurface extraction by speeding up the active-cell searching process so that it is no longer a bottleneck Moreover, this search time is independent of the main memory available. The practical efficiency of our techuiques reflects their theoretical optimal&y.

I/O optimal isosurface extraction (extended abstract)

We present a unified infrastructure for parallel out-of-core isosurface extraction and volume rendering of large unstructured grids on distributed-memory parallel machines We parallelize the out-of-core isosurface extraction algorithm of Chiang et al (1998) and the out-of-core ZSweep technique (Farias and Silva, 2001) for direct volume rendering, using the meta-cell technique as a unified underlying building block Our one-time preprocessing first partitions the dataset into meta-cells that are stored in disk From the meta-cells, we build a BBIO tree in disk, which can be used to speed up isosurface extraction, and a bounding-box file in disk, which is used for direct volume rendering At run-time, we use a simple self-scheduling scheme to achieve load balancing among the processors We perform several experiments on a sixteen-node cluster of PCs connected by a gigabit Ethernet, using datasets as large as 66 million cells For the larger datasets, we have found that both our isosurface extraction and direct volume rendering approaches are perfectly scalable up to sixteen nodes

/pdf/a-unified-infrastructure-for-parallel-out-of-core-isosurface-2evhoc08jt.pdf

A unified infrastructure for parallel out-of-core isosurface extraction and volume rendering of unstructured grids

We describe a new technique for dynamically maintaining the trapezoidal decomposition of a connected planar map $\cal M$ with $n$ vertices and apply it to the development of a unified dynamic data structure that supports point-location, ray-shooting, and shortest-path queries in $\cal M$. The space requirement is $O(n\log n)$. Point-location queries take time $O(\log n)$. Ray-shooting and shortest-path queries take time $O(\log^3 n)$ (plus $O(k)$ time if the $k$ edges of the shortest path are reported in addition to its length). Updates consist of insertions and deletions of vertices and edges, and take $O(\log^3 n)$ time (amortized for vertex updates). This is the first polylog-time dynamic data structure for shortest-path and ray-shooting queries. It is also the first dynamic point-location data structure for connected planar maps that achieves optimal query time.

/pdf/a-unified-approach-to-dynamic-point-location-ray-shooting-1mvenkz10p.pdf

A Unified Approach to Dynamic Point Location, Ray Shooting, and Shortest Paths in Planar Maps

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