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Kostas Tsichlas

Possible papers associated with this exact author name in Arrow. This page groups case-insensitive exact name matches and is not a full identity disambiguation profile.

7 papers
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Possible papers

7

TCS Journal 2023 Journal Article

Threshold-based network structural dynamics

  • Evangelos Kipouridis
  • Paul G. Spirakis
  • Kostas Tsichlas

The interest in dynamic processes on networks is steadily rising in recent years. In this paper, we consider the ( α, β ) -Threshold Network Dynamics ( ( α, β ) -Dynamics), where α ≤ β, in which only structural dynamics (edge dynamics of the network) are allowed, guided by local threshold rules executed by each node. In particular, in each discrete round t, each active pair of nodes u and v, computes a value E ( u, v ) (the potential of the pair) as a function of the local structure of the network at round t around the two nodes. If E ( u, v ) < α then the link (if it exists) between u and v is removed; if α ≤ E ( u, v ) < β then an existing link among u and v is maintained; if β ≤ E ( u, v ) then a link between u and v is established if not already present. New nodes cannot be inserted as a result of the protocol, and existing nodes cannot be removed. The microscopic structure of ( α, β ) -Dynamics appears to be simple, so that we are able to rigorously argue about it, but still flexible, so that we are able to design meaningful microscopic local rules that give rise to interesting macroscopic behaviors. Our goals are the following: a) to investigate the properties of the ( α, β ) -Threshold Network Dynamics and b) to show that ( α, β ) -Dynamics is expressive enough to solve complex problems on networks. Our contribution in these directions is twofold. We rigorously exhibit the claim about the expressiveness of ( α, β ) -Dynamics, both by designing a simple protocol that provably computes the k-core of the network as well as by showing that ( α, β ) -Dynamics are in fact Turing-Complete. Second and most important, we construct general tools for proving stabilization that work for a subclass of ( α, β ) -Dynamics and prove speed of convergence in a restricted setting.

TIME Conference 2021 Conference Paper

Investigation of Database Models for Evolving Graphs

  • Alexandros Spitalas
  • Anastasios Gounaris
  • Kostas Tsichlas
  • Andreas Kosmatopoulos

We deal with the efficient implementation of storage models for time-varying graphs. To this end, we present an improved approach for the HiNode vertex-centric model based on MongoDB. This approach, apart from its inherent space optimality, exhibits significant improvements in global query execution times, which is the most challenging query type for entity-centric approaches. Not only significant speedups are achieved but more expensive queries can be executed as well, when compared to an implementation based on Cassandra due to the capability to exploit indices to a larger extent and benefit from in-database query processing.

I&C Journal 2020 Journal Article

Dynamic Interpolation Search revisited

  • Alexis Kaporis
  • Christos Makris
  • Spyros Sioutas
  • Athanasios Tsakalidis
  • Kostas Tsichlas
  • Christos Zaroliagis

A new dynamic Interpolation Search (IS) data structure is presented that achieves O ( log ⁡ log ⁡ n ) search time with high probability on unknown continuous or even discrete input distributions with measurable probability of element collisions, including power law and Binomial distributions. No such previous result holds for IS when the probability of element collisions is measurable. Moreover, our data structure exhibits O ( 1 ) search time with high probability (w. h. p.) for a wide class of input distributions that contains all those for which o ( log ⁡ log ⁡ n ) expected search time was previously known.

TCS Journal 2020 Journal Article

Fully persistent B-trees

  • Gerth Stølting Brodal
  • Spyros Sioutas
  • Konstantinos Tsakalidis
  • Kostas Tsichlas

We present efficient fully persistent B-trees in the I/O model with block size B that support range searches on t reported elements at any accessed version of size n in O ( log B ⁡ n + t / B ) I/Os and updates at any accessed version in O ( log B ⁡ n + log 2 ⁡ B ) amortized I/Os, using O ( m / B ) disk blocks after m updates. This improves both the query and update I/O-efficiency of the previous fully persistent B-trees of Lanka and Mays (ACM SIGMOD ICMD 1991). To achieve the result, we introduce an implementation for ephemeral B-trees that supports searches and updates in O ( log B ⁡ n ) I/Os, using O ( n / B ) blocks, where moreover every update makes a worst-case constant number of modifications to the structure. We make these B-trees fully persistent using an I/O-efficient method for full persistence, inspired by the node-splitting method of Driscoll et al. (JCSS 1989). Interesting in its own right, the method is generic enough to be applied to any external memory pointer-based data structure with maximum in-degree d i n and out-degree O ( B ), where every node occupies a constant number of blocks on disk. For a user-specified parameter π = Ω ( d i n ), we achieve O ( π B + log 2 ⁡ π ) I/O-overhead per access to a field of an ephemeral block and amortized O ( π B + log 2 ⁡ π + d i n π log 2 ⁡ B ) I/O-overhead and O ( 1 / B ) block space-overhead per modification to the ephemeral structure.

TCS Journal 2014 Journal Article

Dynamic 3-sided planar range queries with expected doubly-logarithmic time

  • Gerth Stølting Brodal
  • Alexis C. Kaporis
  • Apostolos N. Papadopoulos
  • Spyros Sioutas
  • Konstantinos Tsakalidis
  • Kostas Tsichlas

The Priority Search Tree is the classic solution for the problem of dynamic 2-dimensional searching for the orthogonal query range of the form [ a, b ] × ( − ∞, c ] (3-sided rectangle). It supports all operations in logarithmic worst case complexity in both main and external memory. In this work we show that the update and query complexities can be improved to expected doubly-logarithmic, when the input coordinates are being continuously drawn from specific probability distributions. We present three pairs of linear space solutions for the problem, i. e. a RAM and a corresponding I/O model variant: (1) First, we improve the update complexity to doubly-logarithmic expected with high probability, under the most general assumption that both the x- and y-coordinates of the input points are continuously being drawn from a distribution whose density function is unknown but fixed. (2) Next, we improve both the query complexity to doubly-logarithmic expected with high probability and the update complexity to doubly-logarithmic amortized expected, by assuming that only the x-coordinates are being drawn from a class of smooth distributions, and that the deleted points are selected uniformly at random among the currently stored points. In fact, the y-coordinates are allowed to be arbitrarily distributed. (3) Finally, we improve both the query and the update complexity to doubly-logarithmic expected with high probability by moreover assuming the y-coordinates to be continuously drawn from a more restricted class of realistic distributions. All data structures are deterministic and their complexity's expectation is with respect to the assumed distributions. They comprise combinations of known data structures and of two new data structures introduced here, namely the Weight Balanced Exponential Tree and the External Modified Priority Search Tree.

SODA Conference 2012 Conference Paper

Fully persistent B-trees

  • Gerth Stølting Brodal
  • Konstantinos Tsakalidis
  • Spyros Sioutas
  • Kostas Tsichlas

We present I/O-efficient fully persistent B-Trees that support range searches at any version in O (log B n + t/B ) I/Os and updates at any version in O (log B n + log 2 B ) amortized I/Os, using space O ( m/B ) disk blocks. By n we denote the number of elements in the accessed version, by m the total number of updates, by t the size of the query's output, and by B the disk block size. The result improves the previous fully persistent B-Trees of Lanka and Mays by a factor of O (log B m ) for the range query complexity and O (log B n ) for the update complexity. To achieve the result, we first present a new B-Tree implementation that supports searches and updates in O (log B n ) I/Os, using O ( n/B ) blocks of space. Moreover, every update makes in the worst case a constant number of modifications to the data structure. We make these B-Trees fully persistent using an I/O-efficient method for full persistence that is inspired by the node-splitting method of Driscoll et al. The method we present is interesting in its own right and can be applied to any external memory pointer based data structure with maximum in-degree d in bounded by a constant and out-degree bounded by O ( B ), where every node occupies a constant number of blocks on disk. The I/O-overhead per modification to the ephemeral structure is O ( d in log 2 B ) amortized I/Os, and the space overhead is O ( d in /B ) amortized blocks. Access to a field of an ephemeral block is supported in O (log 2 d in ) worst case I/Os.

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