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A classification of emerging and traditional grid systems
The grid has evolved in numerous distinct phases. It started in the early ’90s as a model of metacomputing in which supercomputers share resources; subsequently, researchers added the ability to share data. This is usually referred to as the first-generation grid. By the late ’90s, researchers had outlined the framework for second-generation grids, characterized by their use of grid middleware systems to “glue” different grid technologies together. Third-generation grids originated in the early millennium when Web technology was combined with second-generation grids. As a result, the invisible grid, in which grid complexity is fully hidden through resource virtualization, started receiving attention. Subsequently, grid researchers identified the requirement for semantically rich knowledge grids, in which middleware technologies are more intelligent and autonomic. Recently, the necessity for grids to support and extend the ambient intelligence vision has emerged. In AmI, humans are surrounded by computing technologies that are unobtrusively embedded in their surroundings.
However, third-generation grids’ current architecture doesn’t meet the requirements of next-generation grids (NGG) and service-oriented knowledge utility (SOKU).4 A few years ago, a group of independent experts, arranged by the European Commission, identified these shortcomings as a way to identify potential European grid research priorities for 2010 and beyond. The experts envision grid systems’ information, knowledge, and processing capabilities as a set of utility services.3 Consequently, new grid systems are emerging to materialize these visions. Here, we review emerging grids and classify them to motivate further research and help establish a solid foundation in this rapidly evolving area
JXTA-Overlay: a P2P platform for distributed, collaborative, and ubiquitous computing
With the fast growth of the Internet infrastructure and the use of large-scale complex applications in industries, transport, logistics, government, health, and businesses, there is an increasing need to design and deploy multifeatured networking applications. Important features of such applications include the capability to be self-organized, be decentralized, integrate different types of resources (personal computers, laptops, and mobile and sensor devices), and provide global, transparent, and secure access to resources. Moreover, such applications should support not only traditional forms of reliable distributing computing and optimization of resources but also various forms of collaborative activities, such as business, online learning, and social networks in an intelligent and secure environment. In this paper, we present the Juxtapose (JXTA)-Overlay, which is a JXTA-based peer-to-peer (P2P) platform designed with the aim to leverage capabilities of Java, JXTA, and P2P technologies to support distributed and collaborative systems. The platform can be used not only for efficient and reliable distributed computing but also for collaborative activities and ubiquitous computing by integrating in the platform end devices. The design of a user interface as well as security issues are also tackled. We evaluate the proposed system by experimental study and show its usefulness for massive processing computations and e-learning applications.Peer ReviewedPostprint (author's final draft
Towards Developing Grid-based Portals for E-Commerce on-Demand Services on a Utility Computing Platform
Trends and current practices in the design and development of grid-enabled portals(GeP) reveal the need to identify and
fulfill certain additional relevant requirements in order to build applicable and usable grid-enabled portals for evolving
computing platforms such as the utility computing (UC). This paper reports an investigation of the minimum relevant
additional requirements that must be fulfilled to attain effective GeP design for UC. A GeP prototype for the Grid-based
Utility Infrastructure for Small, Micro, and Medium Enterprises (SMME) Enabling Technology (GUISET) initiative – a
UC platform was developed, and an analytic evaluation experiment undertaken in the study to elicit these additional
requirements using a set of benchmark requirements (standards) revealed that it fulfilled the minimum requirements to be
suitable for UC context. The result of the study underlines the need for more controlled experiments in portal prototyping
in order to foster the practice of GeP design for UC
Managing a Fleet of Autonomous Mobile Robots (AMR) using Cloud Robotics Platform
In this paper, we provide details of implementing a system for managing a
fleet of autonomous mobile robots (AMR) operating in a factory or a warehouse
premise. While the robots are themselves autonomous in its motion and obstacle
avoidance capability, the target destination for each robot is provided by a
global planner. The global planner and the ground vehicles (robots) constitute
a multi agent system (MAS) which communicate with each other over a wireless
network. Three different approaches are explored for implementation. The first
two approaches make use of the distributed computing based Networked Robotics
architecture and communication framework of Robot Operating System (ROS) itself
while the third approach uses Rapyuta Cloud Robotics framework for this
implementation. The comparative performance of these approaches are analyzed
through simulation as well as real world experiment with actual robots. These
analyses provide an in-depth understanding of the inner working of the Cloud
Robotics Platform in contrast to the usual ROS framework. The insight gained
through this exercise will be valuable for students as well as practicing
engineers interested in implementing similar systems else where. In the
process, we also identify few critical limitations of the current Rapyuta
platform and provide suggestions to overcome them.Comment: 14 pages, 15 figures, journal pape
Mobile Computing in Digital Ecosystems: Design Issues and Challenges
In this paper we argue that the set of wireless, mobile devices (e.g.,
portable telephones, tablet PCs, GPS navigators, media players) commonly used
by human users enables the construction of what we term a digital ecosystem,
i.e., an ecosystem constructed out of so-called digital organisms (see below),
that can foster the development of novel distributed services. In this context,
a human user equipped with his/her own mobile devices, can be though of as a
digital organism (DO), a subsystem characterized by a set of peculiar features
and resources it can offer to the rest of the ecosystem for use from its peer
DOs. The internal organization of the DO must address issues of management of
its own resources, including power consumption. Inside the DO and among DOs,
peer-to-peer interaction mechanisms can be conveniently deployed to favor
resource sharing and data dissemination. Throughout this paper, we show that
most of the solutions and technologies needed to construct a digital ecosystem
are already available. What is still missing is a framework (i.e., mechanisms,
protocols, services) that can support effectively the integration and
cooperation of these technologies. In addition, in the following we show that
that framework can be implemented as a middleware subsystem that enables novel
and ubiquitous forms of computation and communication. Finally, in order to
illustrate the effectiveness of our approach, we introduce some experimental
results we have obtained from preliminary implementations of (parts of) that
subsystem.Comment: Proceedings of the 7th International wireless Communications and
Mobile Computing conference (IWCMC-2011), Emergency Management: Communication
and Computing Platforms Worksho
Addressing the Challenges in Federating Edge Resources
This book chapter considers how Edge deployments can be brought to bear in a
global context by federating them across multiple geographic regions to create
a global Edge-based fabric that decentralizes data center computation. This is
currently impractical, not only because of technical challenges, but is also
shrouded by social, legal and geopolitical issues. In this chapter, we discuss
two key challenges - networking and management in federating Edge deployments.
Additionally, we consider resource and modeling challenges that will need to be
addressed for a federated Edge.Comment: Book Chapter accepted to the Fog and Edge Computing: Principles and
Paradigms; Editors Buyya, Sriram
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