%the risk of corporate security holes (31%)and the high price of Could Computing services (27.8%).
%Most of the upgrades in European cable networks already took place by 2011, while VDSL coverage doubled in the last three years.
which supports multiple computing clouds from different service providers operating on coexisting heterogeneous virtual networks
By decoupling service providers from infrastructure providers and by integrating computing clouds with virtual networks the In-Network clouds introduce flexibility for change.
This implies that the Orchestration Plane may use very local knowledge to deserve a real time control as well as a more global knowledge to manage some long-term processes like planning. 2. 3 Virtualisation Plane Overview Virtualisation hides the physical characteristics 14,16 of the computing
Autonomic service provisioning on In-Network Clouds (Service Computing Clouds. 4 Conclusion This work has presented the design of an open software networked infrastructure (In-Network Cloud) that enables the composition of fast and guaranteed services in an efficient manner,
and Sándor Imre Budapest University of Technology and Economics department of Telecommunications Mobile Communication and Computing Laboratory Mobile Innovation Centre Magyar Tudosok krt. 2, H-1117
From Autonomic Computing to Autonomic Networking: an Architectural Perspective. In: Proc. of 5th IEEE Workshop on Engineering of Autonomic and Autonomous Systems (EASE 2008),
/PECES PERVASIVE Computing in Embedded systems, FP7, http://www. ict-peces. eu/Semsorgrid4env Semantic Sensor Grids for Rapid Application Development for Environmental Management, FP7
, users, contents, services, network resources, computing resources, device characteristics) via virtualization and data mining functionalities; the metadata produced in this way are then input of intelligent cognitive modules
6) The modularity of the Cognitive Manager functionalities allows their ranging from very simple SW/HW/computing implementations,
which are worthwhile with respect to the increased SW/HW/computing complexity. The following section shows an example of application of the above-mentioned concepts.
IEEE International Conference on Peer-to-peer Computing P2p 2010, Delft, The netherlands (August 2010) 7. Bindal, R.,Cao, P.,Chan, W.,Medval, J
9th International Conference on Peer-to-peer Computing (P2p'09), Seattle, USA (September 2009) 9. The Smoothit Project:
MPTCP is an extension for end-hosts it doesn't require an upgrade to the routing system;
The operator upgrades its traffic management box so that it drops Conex traffic with a lower probability.
Only one party has to upgrade, ie the combined CDN-ISP. The Content providers and consumers don't know about Conex.
Therefore the ISP needs to upgrade two things. Firstly its traffic management box: it needs to do occasional auditing spot-checks,
There is no need to coordinate end users all having to upgrade. Every user can immediately use the new (virtualised) software,
Cloud computing, for instance, is built on shared resources and computing environments, offering virtualized environments to individual tenants
however, we are now witnessing the emergence of new and unprecedented models for service-oriented computing for the Future Internet:
Metrics can be used directly for computing risks (e g.,, probability of threat occurrence) or indirectly (e g.,
Proceedings of the 11th IEEE International Enterprise Distributed Object Computing Conference, WASHINGTON DC, USA, p. 253.
and our main motivation is to take into account the security policies while computing an orchestration. The AVANTSSAR Platform, for example, implements an idea presented in 11 to automatically generate a mediator.
and service-oriented access to virtualized computing, data storage and network resources as well as higher level services.
the SNIA Cloud storage Technical Working group or the OGF Open Clouds Computing Interface Working group. Trust and security are regarded often as an afterthought in this context,
inter alia with regard to upgrades and patches, quick procurement services, avoidance of vendor lock ins, and legacy modernization 18.
, trusted computing 21 or computations on outsourced data 20. Trustworthy Clouds Underpinning the Future Internet 215 3. 3 Failures of the Cloud Management Systems Due to the highly automated nature of the cloud management systems
Another source of failure stems from the fact that large-scale computing clouds are built often using low-cost commodity hardware that fails (relatively) often.
A more practical solution is to use Trusted Computing to verify correct policy enforcement 6. Trusted computing instantiation as proposed by the Trusted Computing Group (TCG) uses secure hardware to allow a stakeholder
Hence, a computing cloud may use the services of a storage cloud. Unlike local data centers residing in a single country
Trustworthy Clouds Underpinning the Future Internet 219 5 Outlook The Path Ahead Cloud computing is not new it constitutes a new outsourcing delivery model that aims to be closer to the vision of true utility computing.
Proceedings of the 41st annual ACM symposium on Theory of computing, Bethesda, MD, USA. STOC'09, pp. 169 178.
Proceedings of the 3rd international conference on Trust and trustworthy computing, Berlin, Germany, June 21-23,2010.
In the cloud users and businesses can buy computing resources (e g.,, servers, services, applications) provided by the cloud
and solutions for a significant upgrade of the federated testbed environment that was used. The chapter by Zseby et al. entitled Multipath Routing Experiments in Federated Testbeds demonstrates the practical usefulness of federation and virtualisation in heterogeneous testbeds.
As a result of this use case a new feature for Panlab was developed called Federation Computing Interface (FCI) API
As a result to accomplish the needs of this experiment was the development of a new feature of Panlab's framework called Federation Computing Interface (FCI) API.
and how Panlab framework is able by means of Federation Computing Interface API to managed resource.
and Operating the Experiment The scenario during the experiment utilizes the Federation Computing Interface (FCI) API that Panlab provides 5. Federation Computing Interface (FCI) is an API for accessing resources of the federation.
net/trac/wiki/RADL 5. Federation Computing Interface (FCI), http://trac. panlab. net/trac/wiki/FCI Multipath Routing Slice Experiments in Federated
Proceedings of the 2nd International Conference on Autonomic Computing and Communication systems, pp. 1 6 (2008) 21.
The autonomic computing edge: Can you CHOP UP autonomic computing? IBM Corporation (2008) 30. Prehofer, C.,Bettstetter, C.:
Self-organization in Communication Networks: Principles and Design Paradigms. IEEE Communications Magazine 43 (7), 78 85 (2005) 31.
Pervasive and Mobile Computing 2, 65 84 (2006) 6. Chen, H.,Wu, H.,Tzeng, N.:
Indeed, IT resources are processing data that should be transferred from the user's premises or from the data repository to the computing resources.
In case of inefficiency of the underlying infrastructure, the control plane is able to request the upgrade or downgrade of the virtual resources,
and Reality of Delivering Computing as the 5th Utility. In: Proceedings of the 2009 9th IEEE/ACM International Symposium on Cluster Computing and the Grid, WASHINGTON DC, USA.
CCGRID'09, p. 1. IEEE Computer Society Press, Los Alamitos (2009), doi: 10.1109/CCGRID. 2009.97 20 Mintotalpower:
The autonomic computing edge: Can you CHOP UP autonomic computing? Whitepaper IBM developerworks (March 2008), http://www. ibm. com/developer works/autonomic/library/ac-edge4/4. Theilmann, W.,Winkler, U
.,Happe, J.,Magrans de Abril, I.:Managing on-demand business applications with hierarchical service level agreements.
IEEE Int'l Conference on Services Computing, July 2010, pp. 602 609 (2010) 6. Berners-Lee, T.:
IEEE Internet Computing 12 (5), 13 15 (2008) 16. Phuoc, D. L.,Polleres, A.,Hauswirth, M.,Tummarello, G.,Morbidoni, C.:
and ensuring a satisfactory level of Qos for the end users (by appropriating resources to network upgrades etc).
The first topic concerns the resources of telecom operators and service providers such as networks, switching, computing and data cen 404 Part VIII:
One of the key developments in this respect is the use of advanced communication and computing infrastructure as part of the Smart Grid.
and focuses on heavy computing services dedicated to data centers powered completely by green energy, from a large abundant reserve of natural resources in Canada, Europe and the US.
and similar emerging forms of distributed, open computing will push forward new forms of innovation such as,
from Cloud computing to Social media, to Service-oriented Computing, from Business Process Engineering to semantic technologies and mash-up.
and remotely manage computing resources: this approach aims at delivering scalable IT resources over the Internet,
The computational resources of a FINES are maintained in the Computing Cloud, and are linked recursively to compose complex FINERS starting from simpler ones.
and maintaining large scale computing solutions simply interacting with a familiar (though technologically enhanced) business reality.
the heaviest computing services are dedicated to virtual data centers powered completely by green energy from a large abundant reserve of natural resources,
many computing centers are not so close to green energy sources. Thus, green energy distributed network is an emerging technology,
such as hand-held devices, home PCS), the heaviest computing services will be dedicated to data centers powered completely by green energy.
electrical energy is treated by an inverter/charger in order to produce an appropriate output current for computing and networking devices.
The VMS are used to run user applications, particularly heavy-computing services. Based on this testbed network, experiments and research are performed targeting cloud management algorithms and optimization of the intermittently-available renewable energy sources.
which is a new software platform specific for dealing with the delivery of computing infrastructure 5. Figure 3 compares the layered architecture of the GSN with a general architecture of a cloud comprising four layers.
and iv) Turning off computing resources at the original node. Indeed, solutions for the migration of simple applications have been provided by many ICT operators in the market.
The whole network is considered as a set of clouds of computing resources which is managed using the Iaas Framework 5. The Iaas Framework include four main components:
Whilst most of cloud management solutions in the market focus particularly on computing resources, Iaas Framework components can be used to build network virtualized tools 6 10,
It focuses on the latest advancements in mobile and pervasive computing, wireless networks, middleware and agent technologies as they become embedded into the physical spaces of cities.
IEEE PERVASIVE computing, April-June (2007) 18. Panlab Project, Pan European Laboratory Infrastructure Implementation, http://www. panlab. net/fire. html 19.
The substance of this upgrade though is situated in a great range of differences from country to country or integration groups,
especially SMES, for example, intensive computing facilities, experimental platforms (e g. agro-materials platform, chemical and physical analysis services.
which were aimed at implementing new facilities concerning intensive computing with SMES in the region. The project was successful in meeting its scientific goals (through establishing an Interuniversity Computation Centre involving all universities in the region)
Maria Angela Ferrario1, Zoltán Bajmócy2, 3, Will Simm1, Stephen Forshaw1. 1 Lancaster University, School of Computing and Communications, Lancaster, UK 2 University of Szeged
Rethink User Computing Change Focus from Platform to User...96 5. 3. 3 Step 3:
Shorten the Time Frame for New Computing Approach Adoption...97 5. 3. 4 Step 4:
on the other hand,(ii) a reduce function that merges all intermediate values associated with the same intermediate key 41.6 1 Big data the open source computing framework Hadoop have received a growing interest
Proceedings of the 6th international conference on pervasive computing and applications, pp 363 366 40.
which will be investigated in details in this Chapter. 2. 1 Introduction The development of cloud computing started years ago with the emergence of grid computing.
Grid computing can be explained as the allocation of several computer systems in a parallel structure to solve one problem 1. Cloud computing is similar to Grid
and specialized software applications 2. It is the latest development in the computing models that performs computing functions on multilevel virtualization and abstraction by integrating many IT resources.
Defined as the process that enables the user to utilize computing capabilities, such as server using time and data storage, automatically and without human interaction. 2. Broad network access,
which is an approach for computing that is based on degrees of truth rather than the usual true
This project will be achieved by leveraging cloud computing technologies in the government data centers of the National Computing and Information Agency (NCIA.
Cloud computing is simply about an innovative IT model for providing an ondemand network access to a shared pool of configurable computing resources such as networks, servers and software applications.
Proceedings of international conference on advanced computing and communications and informatics, pp 470 476 12.
company Kleiner Perkins Caufield Byers, in two Computing Cycles (i e. smartphones, and tablets cycles respectively) we are entering, faster than before, a third Computing Cycle of‘‘Wearables/Drivables/Flyables/Scannables''devices 2. Considering smartphones and tablets,
as reported by Infoworld 3, in 2013 a research company such as, e g.,, IDC has predicted that tablet shipments will hit 229.3 million units in 2013,
Rethink User Computing Change Focus from Platform to User The traditional approaches and practices of users'profiles management are not suitable any more in nowadays work environments because of today's complex computing landscape
They need to develop a user-centered strategy designed to optimize the computing experience and keep the user as productive as possible on any platform,
and visibility that the company needs to securely deliver the right computing resources for users 14.5.3.3 Step 3:
Shorten the Time Frame for New Computing Approach Adoption Many of the consumer technologies that are already in use by enterprises are advancing very fast.
the future of enterprise mobile computing. White Pap Dell, Dell Headquarter Round Rock, pp 3 14 6. Docherty J (2009) Consumerisation of IT:
and computing assets that are shared by the company in addition to the services shared by the other parties in the world 4. Thus, the individual services,
Moreover, it provided a description for the crowdsourcing concept as well as the incentives and rewards in social computing.
Scekic O, Truong H-L, Dustdar S (2013) Incentives and rewarding in social computing. Commun ACM 56:72 82. doi:
5-Share, Review, and Upgrade; 6-Establish and Implement) they provide a light perspective to complement
with the goal of creating the next generation of computing interfaces. It is a company of designers
multi-screen, multi-device computing environments. The core technology platform, called g-speak, enables applications to run across multiple screens and multiple devices.
so it happens to be a very sensitive topic. 10.7 Noldus Face Reader Noldus Face Reader 8 is an affective computing tool designed to capture
and affective computing (Noldus Face Reader). Furthermore, the selection has shown a majority of digital innovations coming from US based companies (among them a‘‘big''player such as Starbucks),
Computing interfaces, 194 Confidentiality, 28 Consumerization, 89,90 92,95, 98,99, 102,104, 109 Critical success factors (CSFS), 152 Cross organizational collaboration (COC
method (FDM), 35 GGENERAL definition of information (GDI), 4 Generation Z, 4 Grid computing, 23 HHADOOP, 7, 28 Hybrid cloud, 34
and cloud computing. Computing is turning ubiquitous, and digital experiences span devices. Billions of sensors, screens and devices in conference rooms, living rooms, cars, phones, parks and many other spaces are forming a vast network
This computing power will digitize nearly everything in society, and will derive insights from all of the data being generated by interactions among people,
In this world, soft connectivity will be centred increasingly in human-computing interfaces that empower individuals and take full advantage of hard connectivity when planned properly.
Next, cities need to facilitate digital infrastructure to support human-computing interfaces that empower individuals.
These include the emergence of cloud and mobile computing, the growth of big data and analytics,
and developing a platform optimizing computing to scaling applications and decoupling them from the server or data center in
the main features of big data (quantity, speed, variety) are technical properties that depend not on the data themselves but on the evolution of computing, storage,
Sensors and computing are used to capture and monitor seismic data, borehole activity, environmental readings, weather, production utilization, storage capacity, spot pricing (trading), transportation, inventory levels, demand and forecasts,
and distributing computing and analytical capabilities throughout the network, particularly at the edge. Specifically, these are:
Distributing computing and storage. Efficient distribution will require moving the ability to analyze data only in the data center to add processing at the edge (or near the edge) of the network,
devices, computing, storage, analytics, and control systems. But although IP networks are primed to support the expansion of big data and the Ioe,
resulting in the need to move computing close to the network edge in a distributed intelligence architecture.
Constraints on the technological limits of electrical efficiency and on computer memory and processing already pose limits to computing and data analysis.
Other challenges include determining how virtualized computing environments may support a reallocation of computing resources.
But today, with the advent of vast arrays of computing power, we increasingly rely on data processed by others,
the rapid growth of mobile computing; and, more recently, the addition of sensor data (data derived from devices that sense their environment) to the mix have pushed all the boundaries of how we think about data and its uses.
and these activities have become more common and more efficient with the availability of modern computing.
but instead on the evolution of computing, storage, and processing technologies. 11 What may look like big data today will not likely be as big in the near future.
and their information technology (IT) usage. 29 Another study has shown that the use of Internet computing tools can also help firms reach decisions more efficiently, across a broad range of industries,
R is a free software programming language and software environment for statistical computing and graphics. The R language is used widely among statisticians and data miners for developing statistical software and data analysis.
It does not include equipment with some embedded computing abilities such as mobile cellular phones, personal digital assistants (PDAS), or TV SETS.
Business Ready Infrastructure (BRI) Service as a smart sourcing alternative to utility computing; and the first hosted pay-by-use Enterprise Systems Management Framework, called MTAASTM.
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