Special Issue "Distributed Systems and Mobile Computing"

A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Artificial Intelligence".

Deadline for manuscript submissions: closed (31 May 2021).

Printed Edition Available!
A printed edition of this Special Issue is available here.

Special Issue Editor

Dr. Giovanni Viglietta
E-Mail Website
Guest Editor
Japan Advanced Institute of Science and Technology (JAIST), Nomi, Ishikawa 923-1292 Japan
Interests: distributed computing; swarm robotics; computational geometry; combinatorial game theory
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Special Issue Information

Dear Colleagues,

The MDPI journal Information is inviting submissions to a Special Issue on "Distributed Systems and Mobile Computing".

Recent years have witnessed a rapid development of the field of Distributed Computing by Mobile Entities, whose concern is the study of systems of autonomous computational entities that are capable of sensing and moving within the environment they inhabit. With a great variety of applications, from swarms of mobile robots to sensor networks, from autonomous intelligent vehicles to crawlers and viruses on the Web, the theoretical research in this area intersects Distributed Computing with the fields of Computational Geometry, Graph Theory, Combinatorics, and Control Theory.

This Special Issue aims to provide a forum for the presentation and discussion of the latest theoretical and practical advances in the field of Distributed Computing by Mobile Entities.

Topics of interest may include, but are not limited to, the following:

  • Models for mobile robots;
  • Robot motion planning;
  • Distributed graph searching;
  • Mobile agents on dynamic graphs;
  • Continuous protocols for swarm robotics;
  • Computation under restricted visibility;
  • Computing by programmable particles.

Dr. Giovanni Viglietta
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Information is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • moving and computing
  • swarm robotics
  • programmable particles
  • mobile agents

Published Papers (5 papers)

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Research

Article
Time-Optimal Gathering under Limited Visibility with One-Axis Agreement
Information 2021, 12(11), 448; https://doi.org/10.3390/info12110448 - 27 Oct 2021
Viewed by 567
Abstract
We consider the distributed setting of N autonomous mobile robots that operate in Look-Compute-Move (LCM) cycles following the well-celebrated classic oblivious robots model. We study the fundamental problem of gathering N autonomous robots on a plane, which requires all robots to meet at [...] Read more.
We consider the distributed setting of N autonomous mobile robots that operate in Look-Compute-Move (LCM) cycles following the well-celebrated classic oblivious robots model. We study the fundamental problem of gathering N autonomous robots on a plane, which requires all robots to meet at a single point (or to position within a small area) that is not known beforehand. We consider limited visibility under which robots are only able to see other robots up to a constant Euclidean distance and focus on the time complexity of gathering by robots under limited visibility. There exists an O(DG) time algorithm for this problem in the fully synchronous setting, assuming that the robots agree on one coordinate axis (say north), where DG is the diameter of the visibility graph of the initial configuration. In this article, we provide the first O(DE) time algorithm for this problem in the asynchronous setting under the same assumption of robots’ agreement with one coordinate axis, where DE is the Euclidean distance between farthest-pair of robots in the initial configuration. The runtime of our algorithm is a significant improvement since for any initial configuration of N1 robots, DEDG, and there exist initial configurations for which DG can be quadratic on DE, i.e., DG=Θ(DE2). Moreover, our algorithm is asymptotically time-optimal since the trivial time lower bound for this problem is Ω(DE). Full article
(This article belongs to the Special Issue Distributed Systems and Mobile Computing)
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Article
On the Distributed Construction of Stable Networks in Polylogarithmic Parallel Time
Information 2021, 12(6), 254; https://doi.org/10.3390/info12060254 - 19 Jun 2021
Viewed by 550
Abstract
We study the class of networks, which can be created in polylogarithmic parallel time by network constructors: groups of anonymous agents that interact randomly under a uniform random scheduler with the ability to form connections between each other. Starting from an empty [...] Read more.
We study the class of networks, which can be created in polylogarithmic parallel time by network constructors: groups of anonymous agents that interact randomly under a uniform random scheduler with the ability to form connections between each other. Starting from an empty network, the goal is to construct a stable network that belongs to a given family. We prove that the class of trees where each node has any k2 children can be constructed in O(logn) parallel time with high probability. We show that constructing networks that are k-regular is Ω(n) time, but a minimal relaxation to (l,k)-regular networks, where l=k1, can be constructed in polylogarithmic parallel time for any fixed k, where k>2. We further demonstrate that when the finite-state assumption is relaxed and k is allowed to grow with n, then k=loglogn acts as a threshold above which network construction is, again, polynomial time. We use this to provide a partial characterisation of the class of polylogarithmic time network constructors. Full article
(This article belongs to the Special Issue Distributed Systems and Mobile Computing)
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Article
Clustering Optimization of LoRa Networks for Perturbed Ultra-Dense IoT Networks
Information 2021, 12(2), 76; https://doi.org/10.3390/info12020076 - 10 Feb 2021
Viewed by 1058
Abstract
Long Range (LoRa) communication is widely adapted in long-range Internet of Things (IoT) applications. LoRa is one of the powerful technologies of Low Power Wide Area Networking (LPWAN) standards designed for IoT applications. Enormous IoT applications lead to massive traffic results, which affect [...] Read more.
Long Range (LoRa) communication is widely adapted in long-range Internet of Things (IoT) applications. LoRa is one of the powerful technologies of Low Power Wide Area Networking (LPWAN) standards designed for IoT applications. Enormous IoT applications lead to massive traffic results, which affect the entire network’s operation by decreasing the quality of service (QoS) and minimizing the throughput and capacity of the LoRa network. To this end, this paper proposes a novel cluster throughput model of the throughput distribution function in a cluster to estimate the expected value of the throughput capacity. This paper develops two main clustering algorithms using dense LoRa-based IoT networks that allow clustering of end devices according to the criterion of maximum served traffic. The algorithms are built based on two-common methods, K-means and FOREL. In contrast to existing methods, the developed method provides the maximum value of served traffic in a cluster. Results reveal that our proposed cluster throughput model obtained a higher average throughput value by using a normal distribution than a uniform distribution. Full article
(This article belongs to the Special Issue Distributed Systems and Mobile Computing)
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Article
Robot Evacuation on a Line Assisted by a Bike
Information 2021, 12(1), 28; https://doi.org/10.3390/info12010028 - 12 Jan 2021
Viewed by 724
Abstract
Two robots and a bike are initially placed at the origin of an infinite line. The robots are modelled as autonomous mobile agents whose communication capabilities are either in the wireless or face-to-face model, while the bike neither can move nor communicate on [...] Read more.
Two robots and a bike are initially placed at the origin of an infinite line. The robots are modelled as autonomous mobile agents whose communication capabilities are either in the wireless or face-to-face model, while the bike neither can move nor communicate on its own. Thus, the bike is not autonomous but rather requires one of the robots to ride it. An exit is placed on the line at distance d from the origin; the distance and direction of the exit from the origin is unknown to the robots. Only one robot may ride the bike at a time and the goal is to evacuate from the exit in the minimum time possible as measured by the time it takes the last robot to exit. The robots can maintain a constant walking speed of 1, but when riding the bike they can maintain a constant speed v>1 (same for both robots). We develop algorithms for the evacuation of the two robots from the unknown exit and analyze the evacuation time defined as the time it takes the second robot to evacuate. In the wireless model we present three algorithms: in the first the robots move in opposite direction with max speed, in the second with a specially selected “optimal” speed, and in the third the robot imitates the biker (i.e., robot riding the bike). We also give three algorithms in the Face-to-Face model: in the first algorithm the robot pursues the biker, in the second the robot and the biker use zig-zag algorithms with specially chosen expansion factors, and the third algorithm establishes a sequence of specially constructed meeting points near the exit. In either case, the optimality of these algorithms depends on v>1. We also discuss lower bounds. Full article
(This article belongs to the Special Issue Distributed Systems and Mobile Computing)
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Article
A Multi-Objective Optimization Problem on Evacuating 2 Robots from the Disk in the Face-to-Face Model; Trade-Offs between Worst-Case and Average-Case Analysis
Information 2020, 11(11), 506; https://doi.org/10.3390/info11110506 - 29 Oct 2020
Viewed by 566
Abstract
The problem of evacuating two robots from the disk in the face-to-face model was first introduced by Czyzowicz et al. [DISC’2014], and has been extensively studied (along with many variations) ever since with respect to worst-case analysis. We initiate the study of the [...] Read more.
The problem of evacuating two robots from the disk in the face-to-face model was first introduced by Czyzowicz et al. [DISC’2014], and has been extensively studied (along with many variations) ever since with respect to worst-case analysis. We initiate the study of the same problem with respect to average-case analysis, which is also equivalent to designing randomized algorithms for the problem. In particular, we introduce constrained optimization problem 2EvacF2F, in which one is trying to minimize the average-case cost of the evacuation algorithm given that the worst-case cost does not exceed w. The problem is of special interest with respect to practical applications, since a common objective in search-and-rescue operations is to minimize the average completion time, given that a certain worst-case threshold is not exceeded, e.g., for safety or limited energy reasons. Our main contribution is the design and analysis of families of new evacuation parameterized algorithms which can solve 2EvacF2F, for every w for which the problem is feasible. Notably, the worst-case analysis of the problem, since its introduction, has been relying on technical numerical, computer-assisted calculations, following tedious robot trajectory analysis. Part of our contribution is a novel systematic procedure, which given any evacuation algorithm, can derive its worst- and average-case performance in a clean and unified way. Full article
(This article belongs to the Special Issue Distributed Systems and Mobile Computing)
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