On Graph Problems in a Semi-streaming Model
نویسنده
چکیده
Massive graphs arise naturally in a lot of applications, especially in communication networks like the internet. The size of these graphs makes it very hard or even impossible to store set of edges in the main memory. Thus, random access to the edges can't be realized, which makes most o ine algorithms unusable. This essay investigates e cient algorithms that read the edges only in a xed sequential order. Since even basic graph problems often need at least linear space in the number of vetices to be solved, the storage space bounds are relaxed compared to the classic streaming model, such that the bound is O(n · polylog n). The essay describes algorithms for approximations of the unweighted and weighted matching problem and gives a o(log1− n) lower bound for approximations of the diameter. Finally, some results for further graph problems are discussed.
منابع مشابه
Semi-Streaming Algorithms for Annotated Graph Streams
Considerable effort has been devoted to the development of streaming algorithms for analyzing massive graphs. Unfortunately, many results have been negative, establishing that a wide variety of problems require Ω(n2) space to solve. One of the few bright spots has been the development of semi-streaming algorithms for a handful of graph problems — these algorithms use space O(n ·polylog(n)). In ...
متن کاملAlgorithms for streaming graphs
An algorithm solving a graph problem is usually expected to have fast random access to the input graph G and a working memory that is able to store G completely. These powerful assumptions are put in question by massive graphs that exceed common working memories and that can only be stored on disks or even tapes. Here, random access is very time-consuming. To tackle massive graphs stored on ext...
متن کاملGraph Sparsification in the Semi-streaming Model[1]
Semi-stremining model. The title of the paper is “Graph Sparsification in the Semi-streaming Model”. First, we should note that it says semi-streaming and not streaming. In graph problems there is a linear space lower bound for even the simple problems such as determining the connectedness of a graph. In other words, we have to store at least all vertices of the graph. Because of that, this pap...
متن کاملOn Graph Problems in a Semi-streaming Model
We formalize a potentially rich new streaming model, the semi-streaming model, that we believe is necessary for the fruitful study of efficient algorithms for solving problems on massive graphs whose edge sets cannot be stored in memory. In this model, the input graph, G = (V,E), is presented as a stream of edges (in adversarial order), and the storage space of an algorithm is bounded by O(n · ...
متن کاملA Survey of Graph Algorithms in Extensions to the Streaming Model of Computation
There has been a great deal of recent interest in the streaming model of computation where algorithms are restricted to a single pass over the data and have significantly less internal memory available than would be required to store the entire stream of data. Because of the inherent difficulty of solving graph problems in the streaming model, a number of extensions to the streaming model have ...
متن کاملAnalyzing Massive Graphs in the Semi-streaming Model
Massive graphs arise in a many scenarios, for example, traffic data analysis in large networks, large scale scientific experiments, and clustering of large data sets. The semi-streaming model was proposed for processing massive graphs. In the semi-streaming model, we have a random accessible memory which is near-linear in the number of vertices. The input graph (or equivalently, edges in the gr...
متن کامل