Resources
- Identity Use Cases & Scenarios.
- FIDIS Deliverables.
- Identity of Identity.
- Interoperability.
- Profiling.
- Forensic Implications.
- HighTechID.
- D3.1: Overview on IMS.
- D3.2: A study on PKI and biometrics.
- D3.3: Study on Mobile Identity Management.
- D3.5: Workshop on ID-Documents.
- D3.6: Study on ID Documents.
- D3.7: A Structured Collection on RFID Literature.
- D3.8: Study on protocols with respect to identity and identification – an insight on network protocols and privacy-aware communication.
- D3.9: Study on the Impact of Trusted Computing on Identity and Identity Management.
- D3.10: Biometrics in identity management.
- D3.11: Report on the Maintenance of the IMS Database.
- D3.15: Report on the Maintenance of the ISM Database.
- D3.17: Identity Management Systems – recent developments.
- D12.1: Integrated Workshop on Emerging AmI Technologies.
- D12.2: Study on Emerging AmI Technologies.
- D12.3: A Holistic Privacy Framework for RFID Applications.
- D12.4: Integrated Workshop on Emerging AmI.
- D12.5: Use cases and scenarios of emerging technologies.
- D12.6: A Study on ICT Implants.
- D12.7: Identity-related Crime in Europe – Big Problem or Big Hype?.
- D12.10: Normality Mining: Results from a Tracking Study.
- Privacy and legal-social content.
- Mobility and Identity.
- Other.
- IDIS Journal.
- FIDIS Interactive.
- Press & Events.
- In-House Journal.
- Booklets
- Identity in a Networked World.
- Identity R/Evolution.
Energy Supplies
One of the basic requirements for ambient intelligence or ubiquitous computing support is the availability of electric energy for objects in the environments. How can these embedded and partially mobile sensors, actuators or micro processors be supplied with electric energy? Certainly cabling them in a traditional way is not an acceptable solution; costs will be very high and mobility of cabled devices is limited. In this context two approaches are of importance [Bizer et al. (2006: 65)]:
Reducing the energy consumption of these devices so that traditional sources of energy can be used over a longer period.
Finding new or more efficient ways for energy supply of these devices
The first approach can be achieved by more integrated and efficient micro processors (section ) and more efficient programming. In addition to more efficiency in internal code, the use of more efficient wireless communication and routing protocols is an important task in reduction of energy consumption [Bizer et al. (2006: 66)].
In the context of new and more efficient ways for energy supply, the following approaches seem to be very important:
Improved rechargeable batteries based on a higher energy density compared to today’s solutions: this could prolong recharge cycles for mobile and fixed components.
“Energy Harvesting” [Satyanarayanan (2005)]: using motion, differences in temperature or sound waves energy can be extracted from the environment and used for energy supply mainly of mobile devices.
Fuel cells: using different type of fuel such as hydrogen, methanol or methane, the chemical energy of the fuel is directly concerted into electric energy with an efficiency of up to 70%.
Hydrogen is not a primary energy carrier, i.e. it is not a natural energy resource and needs to be synthesised from water using electric energy. In this context methanol receives more attention as a renewable and natural energy resource. Different prototypes of methanol fuel cells as energy sources for notebooks are already available. But energy efficiency is still a problem, as only 50% efficiency seems to be achievable today for this type of fuel cell. As a consequence heat from the fuel cells, for integrated systems such as a notebook, is still a problem. In addition these types of fuel cells are still quite heavy (around 1.7 kg). It can be expected that with the development of improved membrane materials for fuel cells energy density and efficiency can be improved significantly in near future.
New and more efficient ways of energy supply for ICT are a basic technology for AmI and thus indirectly influence identity management in ambient intelligent environments. In European Member States in general, research in energy supply in the public sector seems mainly to be focused on renewable energies and improving energy efficiency. Such research for systems and devices in AmI environments currently seems to be driven mainly by private organisations (see examples in this chapter).
Smart Materials
According to a definition given by McCloskey (2004) smart materials are “non-living material systems that achieve adaptive behaviour”. Examples of smart materials are compound materials using piezo-electric fibres or polymers that are electrically or magnetically active. Other examples are shape memory alloys (SMA), i.e. metals that after being deformed return back to their original shape when heated. Micro-electro-mechanic systems (MEMS) are also understood as smart materials. They are combinations of e.g. sensors or actuators or other electric circuits integrated on a computer chip. MEMS are used, for example, in the wings of aircrafts to detect and measure the degree of deformation.
Smart materials may play a major role in the context of new sensors and actuators in AmI. Actuators and data from these sensors may be subject to identity management in ambient intelligent environments.
Public research institutions seem to play a major role in research in smart materials as well in Europe as the USA. The European Union actively supports projects in the context of smart materials.
Networking & Communication
The levels of interaction that may occur between the user and the technology within the AmI context is shown in the “MultiSphere Reference Model” ().
Figure : A visualisation of the MultiSphere Reference Model [WWRF (2001)] showing various layers of interaction desirable in the AmI scenario
Although this model aims primarily at putting issues and ideas of wireless communications in context, from such models the following interaction levels can be identified [Riva (2001)]:
Body area network (BAN) connecting sensors, chips or devices attached to the body/clothes or implanted in the body (distance: <1 meter)
Personal area network (PAN) consisting of personal and/or shared devices or peripherals (distance: <10 meters)
Local area network (LAN) for the nomadic access to fixed and mobile networks, and to the Internet (distance: <100 meters)
Wide area network (WAN) for the access and routing with full mobility (worldwide access)
The ‘Cyberworld’ where users and intelligent agents interact (virtual)
To fulfil the current vision of AmI, it is necessary that fluid communication between these layers is realised through the use of interoperable hardware and software standards and protocols.
‘Body-centric’ wireless communications is a new and developing field which refers to human-self and human to human networking through the use of wearable and implantable sensors. Existing technologies which allow portable devices to connect are typically based on PAN standards such as 802.11x or on Bluetooth. Neither of these are spectrum efficient for BANs in that most of the radio energy becomes directed away from the body when the radio antenna is placed close to the skin. As such BAN is an area where standards are only now starting to be defined.
Grid Computing
Building, providing and maintaining the infrastructure required to support the AmI environment will be an extremely difficult task. Both functional (related to the specific system operation) and non-functional (security, scalability, performance, robustness, availability, reliability, licence issues, etc) requirements of an AmI system pose strict demands on the computational and communication resources and in general on the underlying infrastructure. However, the promising results of the feverish research in the field of Grid Computing in combination with the on-going efforts of its wider adoption in industry and business indicate that the infrastructure required for AmI is actually on the way and, thus, the implementation of AmI systems with strong real-time, security or reliability requirements or large-scale AmI systems may not be that distant.
As grid computing is an emerging technology, many approaches to define it exist. In an effort to capture the different aspects of grid computing in one definition, Ian Foster [Foster et al (2002)] defines the Grid as a system that “coordinates resources that are not subject to centralised control using standard, open, general-purpose protocols and interfaces to deliver nontrivial qualities of service”. This definition goes beyond defining the Grid as simply an infrastructure delivering the power of multiple computational resources to a single user-point for a specific application by uniting these resources (pools of storage systems, processing units and networks) into a single system. The Grid has thus no central administrative control but involves the integration and coordination of users and resources of different control domains based on standards, seamless and open protocols and interfaces dealing with issues such as, authentication, authorisation, service level agreement establishment, resource discovery, negotiation, reservation and service execution, for the delivery of various qualities of service, including requirements concerning response time, availability, throughput and security. According to Berman, Fox and Hey [Bergman et al (2003)] “Grid infrastructure will provide us with the ability to dynamically link together resources as an ensemble to support the execution of large-scale, resource-intensive, and distributed applications”. Thus, the vision of the Grid is the provision of global – if possible - infrastructure for scientific, business, managerial, governmental and commercial purposes, as well as daily activities.
Initially the idea behind the Grid was the exploitation of idle computational cycles. Based on the observation that most computers remain idle for almost 90% of a typical day, the Grid was seen as the technological solution to the problem of the widely distributed unused computing capacity. Grid computing is regarded to be the future of Semantic Web, the next step in distributed networking. The Grid may include systems which are geographically dispersed, belonging to different organisations, running different operating systems on heterogeneous hardware platforms. The user, however, should be able to have uniform access to these resources; in other words, the Grid is presented as a single large virtual computer.
| Electrical Power Grid | The Grid |
Transparency | No need to worry about how or where the electrical power you are using is generated. | No need to worry about what computer/s is used to process your request or where the data it requires is. The middleware is responsible for assigning the submitted task to the resource which is more suitable for performing it (in terms of availability, workload and the quality of service requested by the user, etc.) and will work the best possible way to locate and retrieve the data needed. |
Pervasiveness | Electricity is widely accessible and accessing it requires only a standard wall socket. | No special requirements for accessing the Grid exist. Different platforms, such as desktop computers, laptops, PDAs and mobile phones, will be able to access the Grid resources simply through a web browser. |
Any access point serves | At any socket the electrical appliance is connected to it will get the electricity it requires for operating. | Any computer connecting to the Grid will be served by it as if it were a local machine. |
Utility | Electricity is provided as a service: you request for electricity and it is provided to you, and you are charged for what you use. | The Grid is envisaged to be a service which will simply provide resources based on the request. The charging will also be based on the use of the Grid and the quality of service requested. |
Infrastructure | The underlying infrastructure is called “the power grid”. It includes power stations, transmission stations and power-lines among others in order to link together different kinds of power plants with homes, factories, etc. | The infrastructure that is required for the provision of the above services is called “the Grid”. It includes personal computers, servers, databases, networks, linked together. |
Table : Electrical Power Grid and the Grid analogy
In general, the term infrastructure is used to describe a technology that lies under the application being used and the service provided and is taken for granted when these operations are performed. When making a phone call, the callers are not concerned with the switches, the repeaters and the general underlying network that connects the transmitter with the receiver. The Internet allows the communication among different, geographically dispersed devices. Similarly, the Grid must be able to provide on-demand access to computing, and thus be widely deployed. The latter, however, requires that the Grid infrastructure must be simple and provide more functionality than the underlying Internet at the same time.
Grid computing, as a term, was initially adopted in order to capture the vision of scientists and researchers to make computer power as easy to access as electricity through the electric power grid. Potentially it must involve every protocol and computer technology that already exists with its scope thus being extremely wide. summarises the similarities in the core idea and operation of the electrical power grid and the Grid [Chetty et al. (2002)].
Grid Classification
In an effort to classify the applications that will take advantage of the Grid by running on it, Allen et al. identified an initial list of categories of Grid applications with the classification criterion being the main driving reason for using the Grid [Allen et al. (2003)]. According to this classification scheme, the categories of Grid applications are the following:
Community-centric
Such applications are used in a collaborative environment and thus involve and require various interactions among people or communities. Such a collaborative environment could be scientists and engineers cooperating to design and produce a new vehicle or a smart surveillance system processing input from various geographically dispersed cameras and microphones.
Data-centric
These Grid applications require storage, management, mining and transfer of large amounts of data between distributed and/or heterogeneous databases. Examples of such applications include DNA analysis applications and weather monitoring based on processing of data received by sensors placed on various locations around the globe.
Computation-centric
The applications in this category are the common computationally demanding applications, such as weather forecasting, climate modelling, world economy modelling, and earthquake simulation. For years the limitation of computational resources has been forcing scientists and engineers to intentionally omit important factors affecting these models so that these applications produce a result in reasonable time. This leads to a compromise in the precision and thus the reliability of the produced models.
Interaction-centric
One of the strongest requirements of these applications is responsiveness due to real-time user interaction which in turn requires robust and effective real-time data processing and analysis. Examples of such applications include the submission of orders by customers and their processing and monitoring by suppliers and distributors in supply chain management and online gaming applications.
Having functionality as the classification criterion, the following categories of the Grid exist:
The Computational Grid
It embodies the initial idea behind the Grid. Its main aim is to speed up the applications by sharing their processing needs to several computational resources (processing units, memory units, disks) and coordinating them.
The Data/Information Grid
This type of Grid focuses on the controlled data access, sharing and management. The data may be heterogeneous, distributed and of large amount. A Data Grid offers great advantages to data-intensive applications including performance and security improvement.
The Equipment Grid
It links together different types of equipment, including telescopes, cameras, microphones, health monitoring devices, and other sensors and devices.
The Enterprise Grid
This type of Grid integrates all the above mentioned Grids. Every user of the Enterprise Grid is able to get from the Grid the resources his applications require any time he uses them as if his applications are being processed locally. It provides prompt access to available information and executes computationally demanding applications in a reasonable time requiring the least possible intervention of IT experts during the resource provision and system operation.
Another Grid classification based on the scale of the Grid divides the Grids into Cluster Grids, Enterprise Grids, Utility Computing and Community Grids. More specifically:
Cluster Grids
The resources shared in Cluster Grids are physically located in the same place and are mainly used inside companies for resource coordination, workload balancing and backup mechanisms.
Enterprise Grids
The resources are physically distributed within the company and the applications using them are operating behind the corporate firewall.
Utility Computing
The resources are provided by a third party service provider who hosts and manages the Grid application and the Grid resources. These resources may be provided to more than one organisation, whereas the organisations are paying for their use based on the charging scheme which has been agreed between them and the service provider.
Community or Partner Grids
This type of Grid involves the collaboration of various organisations which all share resources based on predefined agreements forming what is called a Virtual Organisation (VO), a term better described in section .
The Semantic Grid
The Semantic Grid is the projection of Semantic Web in the grid computing area. It is an effort to apply the main principles of Semantic Web to the Grid. The Semantic Grid was initiated by the need of having a description of the information in the Web so that it is more easily and efficiently discovered and retrieved. This need was not satisfied by HTML which is a mark-up language focusing on formatting and not tagging content. According to the semantic grid group, the semantic grid is “an extension of the current grid in which information and services are given well-defined meaning, better enabling computers and people to work in cooperation”. Similarly with the Semantic Web, the Semantic Grid includes a detailed description of the services and the resources in the Grid, which allows for a more efficient service and resource discovery. Moreover, grid resources and output of grid applications can be connected and integrated and useful and intelligent associations of data can be produced. Such an example could be searching texts for a word as well as audio files which contain this word.
The Mobile Grid
In an effort to address the issue of mobility, a requirement posed by many applications, and thus, leverage the large set of mobile users, research has also been focused on the Mobile Grid. The Grid, while providing services to the users, must be able to deal with issues of network handovers concerning both the users and the resources. Thus, it must be adaptable and able to dynamically configure the services, the resources, the network and the security. [Litke et al. (2004)] The Mobile Grid could be the extended grid infrastructure that could support the provision of location-based services. In the Mobile Grid, users can be mobile with their location changing often or rarely, leading to a need of instant knowledge of the user’s new location and related context. The simplest example could be a user wanting to download a file. If his current location is much closer to a computer storing this file than the previous one, then the Grid should be able to adjust to the new context. In the case of a mobile resource, which could be either a computational resource or an expert (such as a doctor or a teacher), the Grid must be able to either update the system with the new location of the resources, so that access to that resources is still possible, or locate a new resource satisfying the user’s requirements.
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