A review on DISC 2005, the 19th International Symposium on Distributed Computing

DISC is an international symposium on the theory, design, analysis, implementation and application of distributed systems and networks. The well-known International Symposium on Distributed Computing is organized annually in cooperation with the European Association for Theoretical Computer Science (EATCS). This is a review on the 19th International Symposium on Distributed Computing, which took place in Kraków, Poland, on September 26--29, 2005. The proceedings of DISC 2005 are published by Springer, as volume 3724 of the Lecture Notes in Computer Science (LNCS) series. The conference website can be found at www.mimuw.edu.pl/~disc2005.Postprint (published version

Topics in Distributed Algorithms: On Wireless Networks, Distributed Storage and Streaming

Distributed algorithms are executed on a set of computational instances. Werefer to these instances as nodes. Nodes are runningconcurrently and are independent from each other. Furthermore, they have their own instructions and information. In this context, the challenges are to show thatthe algorithm is correct, regardless of computational, or communication delaysand to show bounds on the usage of communication.We are especially interested the behaviour after transient faults and underthe existence of Byzantine nodes.This thesis discusses fundamental communication models for distributed algorithms. These models are implementing abstract communication methods. First, we address medium access control for a wireless medium with guaranteeson the communication delay. We discuss time division multiple access(TDMA) protocols for ad-hoc networks and we introduce an algorithm that creates aTDMA schedule without using external references for localisation, or time. We justify our algorithm by experimental results.The second topic is the emulation of shared memory on message passingnetworks. Both, shared memory and message passing are basic interprocessorcommunication models for distributed algorithms. We are providing a way ofemulating shared memory on top of an existing message passing network underthe presence of data corruption and stop-failed nodes. Additionally, we ensurethe privacy of the data that is stored in the shared memory. The third topic looks into streaming algorithms and optimisation. We study the problem of sorting a stream ofvehicles on a highway with severallanes so that each vehicle reaches its target lane. We look into optimality interms of minimising the number of move operations, as well as, minimising the length of the output stream. We present an exact algorithm for the case oftwo lanes and show that NP-Hardness for a increasing number of lanes

Local majorities, coalitions and monopolies in graphs: a review

AbstractThis paper provides an overview of recent developments concerning the process of local majority voting in graphs, and its basic properties, from graph theoretic and algorithmic standpoints

Efficient Passive Clustering and Gateways selection MANETs

Passive clustering does not employ control packets to collect topological information in ad hoc networks. In our proposal, we avoid making frequent changes in cluster architecture due to repeated election and re-election of cluster heads and gateways. Our primary objective has been to make Passive Clustering more practical by employing optimal number of gateways and reduce the number of rebroadcast packets

LVMM: The Localized Vehicular Multicast Middleware - a Framework for Ad Hoc Inter-Vehicles Multicast Communications

This thesis defines a novel semantic for multicast in vehicular ad hoc networks (VANETs) and it defines a middleware, the Localized Vehicular Multicast Middleware (LVMM) that enables minimum cost, source-based multicast communications in VANETs. The middleware provides support to find vehicles suitable to sustain multicast communications, to maintain multicast groups, and to execute a multicast routing protocol, the Vehicular Multicast Routing Protocol (VMRP), that delivers messages of multicast applications to all the recipients utilizing a loop-free, minimum cost path from each source to all the recipients. LVMM does not require a vehicle to know all other members: only knowledge of directly reachable nodes is required to perform the source-based routing

An Approach Based on Particle Swarm Optimization for Inspection of Spacecraft Hulls by a Swarm of Miniaturized Robots

The remoteness and hazards that are inherent to the operating environments of space infrastructures promote their need for automated robotic inspection. In particular, micrometeoroid and orbital debris impact and structural fatigue are common sources of damage to spacecraft hulls. Vibration sensing has been used to detect structural damage in spacecraft hulls as well as in structural health monitoring practices in industry by deploying static sensors. In this paper, we propose using a swarm of miniaturized vibration-sensing mobile robots realizing a network of mobile sensors. We present a distributed inspection algorithm based on the bio-inspired particle swarm optimization and evolutionary algorithm niching techniques to deliver the task of enumeration and localization of an a priori unknown number of vibration sources on a simplified 2.5D spacecraft surface. Our algorithm is deployed on a swarm of simulated cm-scale wheeled robots. These are guided in their inspection task by sensing vibrations arising from failure points on the surface which are detected by on-board accelerometers. We study three performance metrics: (1) proximity of the localized sources to the ground truth locations, (2) time to localize each source, and (3) time to finish the inspection task given a 75% inspection coverage threshold. We find that our swarm is able to successfully localize the present so

Using MapReduce Streaming for Distributed Life Simulation on the Cloud

Distributed software simulations are indispensable in the study of large-scale life models but often require the use of technically complex lower-level distributed computing frameworks, such as MPI. We propose to overcome the complexity challenge by applying the emerging MapReduce (MR) model to distributed life simulations and by running such simulations on the cloud. Technically, we design optimized MR streaming algorithms for discrete and continuous versions of Conway’s life according to a general MR streaming pattern. We chose life because it is simple enough as a testbed for MR’s applicability to a-life simulations and general enough to make our results applicable to various lattice-based a-life models. We implement and empirically evaluate our algorithms’ performance on Amazon’s Elastic MR cloud. Our experiments demonstrate that a single MR optimization technique called strip partitioning can reduce the execution time of continuous life simulations by 64%. To the best of our knowledge, we are the first to propose and evaluate MR streaming algorithms for lattice-based simulations. Our algorithms can serve as prototypes in the development of novel MR simulation algorithms for large-scale lattice-based a-life models.https://digitalcommons.chapman.edu/scs_books/1014/thumbnail.jp