Swarm Robotics

Collectively working robot teams can solve a problem more efficiently than a single robot, while also providing robustness and flexibility to the group. Swarm robotics model is a key component of a cooperative algorithm that controls the behaviors and interactions of all individuals. The robots in the swarm should have some basic functions, such as sensing, communicating, and monitoring, and satisfy the following properties

Editorial: Special Issue “Swarm Robotics”

Swarm robotics is the study of how to coordinate large groups of relatively simple robots through the use of local rules so that a desired collective behavior emerges from their interaction [...

Using Service Clustering and Self-Adaptive MOPSO-CD for QoS-Aware Cloud Service Selection

AbstractA promising way to effectively manage the composition of services in a heterogeneous and dynamic environment is to make workflow management able to self-adapt at runtime to react to changes in its environment by autonomously reconfiguring itself. Most of the proposed methodologies address this issue as a QoS-aware service selection problem in which a web service broker can dynamically select the “right” service that takes part in the composition, and adaptively change the bound service when the delivered QoS has changed.In this paper, we propose a self-organizing framework that uses a service clustering based discovery approach to effectively and efficiently support the selection of services in which runtime changes in the QoS of the services are taken into account. Two bio-inspired algorithms are designed to support a QoS-aware dynamic service selection mechanism. An ant-based clustering algorithm enhanced with a template mechanism that guides the artificial ants to move data items to construct and maintain a specific topology is adopted as a method for efficient service discovery. As a consequence, services can dynamically be discovered in a shorter time and with lower network traffic. To select the actual concrete services that best meet the user QoS requirements a Self-Adaptive Multi-Objective Particle Swarm Optimization Algorithm using crowding distance technique (MOPSO-CD) is executed using the topological map generated by the ant algorithm. In the end, simulation results show the effectiveness of the method proposed

Designing Parallel Models of Soil Contamination by the CARPET Language

This paper describes the main features of the CARPET language and its practical use for programming three-dimensional models of the contamination of soils developed in the CABOTO project. CARPET is a high-level language based on the cellular automata model, which supports rapid prototyping of a large number of applications in science and engineering. A CARPET implementation has been used for programming cellular algorithms in the CAMEL parallel system. The CAMEL (Cellular Automata environMent for systEms modeLing) system is a parallel implementation of a software environment for the simulation and modeling of complex systems based on cellular automata. CAMEL offers the computing power of a parallel computer although hiding, by the CARPET language, the architecture issues to a user. The CARPET language allows the design of parallel programs for describing the actions of thousands of simple active interacting agents that might simulate the behavior of very complex systems. Keywords: Par..

A High-Level Language for Programming Cellular Algorithms on Parallel Machines

This paper describes CARPET, a parallel programming language based on the cellular automata model. A CARPET implementation has been used for programming cellular algorithms in the CAMEL parallel environment. CAMEL is an environment designed to support the development of high performance applications in science and engineering. It offers the computing power of a highly parallel computer, hiding the architecture issues from a user. By CARPET a user might write programs to describe the actions of thousands of simple active agents interacting locally, then the CAMEL system allows a user to observe the global complex evolution that arises from all the local interactions. 1 Introduction Currently available high performance computing systems can be exploited to efficiently support applications in science and engineering. However, the lack of high-level languages, tools, and application-development environments does not allow to program parallel algorithms that are portable, efficient and exp..

A High-Level Cellular Programming Model for Massively Parallel Processing

Cellular automata are used for designing highperformance applications in many areas. This paper describes CARPET, a high-level programming language based on the cellular automata model. CARPET is a programming language designed to support the development of parallel high performance software. It exploits the computing power of a highly parallel computer releasing a user from using explicit parallel constructs. A CARPET implementation has been used for programming cellular algorithms in the CAMEL parallel environment. By CARPET a user might write programs to describe the actions of thousands of simple active agents interacting locally, then the CAMEL environment allows a user to observe the global complex evolution that arises from their parallel execution and their local interactions. 1. Introduction A model of parallel computation represents an abstract machine designed to separate the concerns of program development from those of effective parallel execution. In fact, a model acts a..

CARPET: A Programming Language for Parallel Cellular Processing

In this paper we describe CARPET, a parallel programming language based on the cellular automata model. CARPET is the language used for programming cellular algorithms in the CAMEL environment. CAMEL is an environment designed to support the development of high performance applications in science and engineering. It offers the computing power of a highly parallel computer, hiding the architecture issues from a user. The system can be used both as a tool to model dynamic complex phenomena and as a computational model for parallel processing. By CARPET a user might write programs to describe the actions of thousands of simple active agents interacting locally, then the CAMEL system allows a user to observe the global complex evolution that arises from all the local interactions. 1 Introduction Massively parallel computing can be very useful to engineers and scientists. However, the lack of models and tools that simply and automatically allow the exploitation of parallelism in complex en..