wireless sensor networks are the new generation of networks that typically are formed great numbers of nodes and the communications of these nodes are done as wireless. the main goal of these networks is collecting data from neighboring environment of network sensors. since the sensor nodes are battery operated and there is no possibility of charging or replacing the batteries, the lifetime of ...

This paper proposes an extension of the Gravitational Search Algorithm (GSA) to multiobjective optimization problems. The new algorithm, called Non-dominated Sorting GSA (NSGSA), utilizes the non-dominated sorting concept to update the gravitational acceleration of the particles. An external archive is also used to store the Pareto optimal solutions and to provide some elitism. It also guides t...

Gravitational search algorithm (GSA) is a swarm intelligence optimization algorithm that shares many similarities with evolutionary computation techniques. However, the GSA is driven by the simulation of a collection of masses which interact with each other based on the Newtonian gravity and laws of motion. Inspired by the classical GSA and quantum mechanics theories, this work presents a novel...

In this paper, we give a status report of a real-world application scenario that uses two distinct types of workflow within the Triana problem solving environment: serial scientific workflow for the data processing of gravitational waves signals; and the distributed workflows that dynamically map to the virtual Grid overlay of Triana services. We briefly describe the Triana distribution mechani...

We will prepare for, carry out, and report on a search for burst-like events of gravitational wave origin in data to be collected in an Engineering Run that will have coincident data from operating interferometers at both Hanford and Livingston (hereinafter referred to as the Science Analysis Challenge or SAC). By “burst-like events” (hereinafter “bursts”) we refer in the most general sense to ...

Meta-heuristic search algorithms are developed to solve optimization problems. Such algorithms are appropriate for global searches because of their global exploration and local exploitation abilities. Swarm intelligence (SI) algorithms comprise a branch of meta-heuristic algorithms that imitate the behavior of insects, birds, fishes, and other natural phenomena to find solutions for complex opt...

Multiple Travelling Salesman Problem (mTSP) is one of the most popular and widely used combinatorial optimization problems in the operational research. Many complex problems can be modeled and solved by the mTSP. To solve the mTSP, deterministic algorithms cannot be used as the mTSP is an NP-hard optimization problem. Hence, heuristics approaches are usually applied. In this paper, the Gravitat...