Cloud Computing in Bioinformatics

Abstract

Cloud Computing presents a new approach to allow the development of dynamic, distributed and highly scalable software. For this purpose, Cloud Computing offers services, software and computing infrastructure independently through the network. To achieve a system that supports these characteristics, Service-Oriented Architectures (SOA) and agent frameworks exist which provide tools for developing distributed and multi-agent systems that can be used for the establishment of Cloud Computing environments. This paper presents a CISM@ (Cloud computing Integrated into Service-oriented Multi-Agent) architecture set on top of the platforms and frameworks by adding new layers for integrating a SOA and Cloud Computing approach and facilitating the distribution and management of functionalities. CISM@ has been applied to the real case study consisting of the analysis of microarray data and has allowed the efficient management of the allocation of resources to the different system agents.

Integrating Cloud Computing with Next-Generation Telematics for Energy Sustainability in Vehicular Networks

“…These roles have developed to the point where they have been standardized [26]. There have been numerous successful applications of cloud computing including college campus resource management [27], bioinformatics [28], medical information integration [29], land resource information management [30], and so on. The distributed nature of cloud computing offers the ubiquity required to support processing information obtained from large numbers of geographically dispersed vehicles.…”

Intelligent business processes composition based on multi-agent systems

“…These characteristics provide the development of scalable, dynamic and distributed software, representing advantages on the current distributed systems [40]. All this, allows us integrates components as a multi-agent system and SOA (service-oriented architecture, [11][12][13]) to our architecture [41,42]. representing the requirements of the user for which will be generated a diagram according to standard BPMN that models the input, Figure 4.…”

Self-service infrastructure container for data intensive application

“…count= count+1 13: end for 14: while C > 0 do 15: Create virtual machine V count for Type(t) {one VM from each category except last category } 16: C ← C − C count {update available capacity} 17: V ← V V count 18: count= count+1 19: end while 20: Return V Algorithm 2 below shows the pseudo code for the classification using K -Means. The initial cluster K is determined by the available classes of VMs.…”

“…A distributed system enabled by an intelligent agent in [19], data and software sharing using a central repository [18], and a publicly available packaged VM such as Biolinux [16] are already proposed. At extremely large scale, research projects such as CloudBurst [23], CloudBlast [24], and Galaxy [25] provide standard environments and algorithms for analyzing large data generated from scientific experiments.…”

“…Enormous interest surrounds the application of cloud computing to support large scale biological data analysis [2,[18][19][20][21][22]. A distributed system enabled by an intelligent agent in [19], data and software sharing using a central repository [18], and a publicly available packaged VM such as Biolinux [16] are already proposed.…”