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Mar 21, Only Introduction of Internet & Websites [email protected] Page 1. TCP/IP: Transmission Control Protocol/Internet Protocol protocols network computer network computer Protocol computer follow 8. IP Address: internet Protocol Address IP address unique numeric network computer. May 27, J.C.S COMPUTER [email protected],com Siraj sir INTERNET bUVjusV gtkjksa yk [kksa Lora= usVodksaZ dk,slk la;qDr usVodZ gS ftlesa izR;sd. Jan 30, In this lesson, we will give a brief overview of the internet, and we will The internet is the largest computer network in the world, connecting.
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Aug 2, Computer Fundamental Notes PDF in Hindi Download और न ही Scan किया गया है| हम शिर्फ़ Internet पर पहले से उप्लाब्थ Link. Internet and Web Page Designing Notes. DCA 2nd Semester Notes in hindi according to Makhanlal Chaturvedi National University of Bhopal. Internet address. Consists of 4 bytes separated by periods. Example: -The R first bytes (R= 1,2,3) correspond to the network address;.
Client-side software can include animations, games , office applications and scientific demonstrations. Through keyword -driven Internet research using search engines like Yahoo! Compared to printed media, books, encyclopedias and traditional libraries, the World Wide Web has enabled the decentralization of information on a large scale.
The Web is therefore a global set of documents , images and other resources, logically interrelated by hyperlinks and referenced with Uniform Resource Identifiers URIs.
URIs symbolically identify services, servers , and other databases, and the documents and resources that they can provide. Web services also use HTTP to allow software systems to communicate in order to share and exchange business logic and data. The Web has enabled individuals and organizations to publish ideas and information to a potentially large audience online at greatly reduced expense and time delay. Publishing a web page, a blog, or building a website involves little initial cost and many cost-free services are available.
However, publishing and maintaining large, professional web sites with attractive, diverse and up-to-date information is still a difficult and expensive proposition. Many individuals and some companies and groups use web logs or blogs, which are largely used as easily updatable online diaries.
Some commercial organizations encourage staff to communicate advice in their areas of specialization in the hope that visitors will be impressed by the expert knowledge and free information, and be attracted to the corporation as a result. Advertising on popular web pages can be lucrative, and e-commerce , which is the sale of products and services directly via the Web, continues to grow. Online advertising is a form of marketing and advertising which uses the Internet to deliver promotional marketing messages to consumers.
It includes email marketing, search engine marketing SEM , social media marketing, many types of display advertising including web banner advertising , and mobile advertising. In , Internet advertising revenues in the United States surpassed those of cable television and nearly exceeded those of broadcast television.
When the Web developed in the s, a typical web page was stored in completed form on a web server, formatted in HTML , complete for transmission to a web browser in response to a request. Over time, the process of creating and serving web pages has become dynamic, creating a flexible design, layout, and content.
Websites are often created using content management software with, initially, very little content. Contributors to these systems, who may be paid staff, members of an organization or the public, fill underlying databases with content using editing pages designed for that purpose while casual visitors view and read this content in HTML form.
There may or may not be editorial, approval and security systems built into the process of taking newly entered content and making it available to the target visitors. Communication Email is an important communications service available on the Internet. The concept of sending electronic text messages between parties in a way analogous to mailing letters or memos predates the creation of the Internet.
Emails can be cc-ed to multiple email addresses. Internet telephony is another common communications service made possible by the creation of the Internet. The idea began in the early s with walkie-talkie -like voice applications for personal computers.
In recent years many VoIP systems have become as easy to use and as convenient as a normal telephone. The benefit is that, as the Internet carries the voice traffic, VoIP can be free or cost much less than a traditional telephone call, especially over long distances and especially for those with always-on Internet connections such as cable or ADSL and mobile data.
Interoperability between different providers has improved and the ability to call or receive a call from a traditional telephone is available. Simple, inexpensive VoIP network adapters are available that eliminate the need for a personal computer. Voice quality can still vary from call to call, but is often equal to and can even exceed that of traditional calls.
Remaining problems for VoIP include emergency telephone number dialing and reliability. Currently, a few VoIP providers provide an emergency service, but it is not universally available. This voltage is then coupled with a capacitor to accumulate a charge, which then powers up the tag chip. The tag can then produce a small magnetic field that encodes the signal to be transmitted, and this can be picked up by the reader.
The tag also has a dipole antenna on which an alternating potential difference appears and it is powered up. It can then use this power to transmit messages. RFID technology is being used in various applications such as supply chain management, access control, identity authentication, and object tracking. The RFID tag is attached to the object to be tracked and the reader detects and records its presence when the object passes by it.
In this manner, object movement can be tracked and RFID can serve as a search engine for smart things. For access control, an RFID tag is attached to the authorized object. For example, small chips are glued to the front of vehicles.
When the car reaches a barricade on which there is a reader, it reads the tag data and decides whether it is an authorized car. If yes, it opens automatically.
The low level data collected from the RFID tags can be transformed into higher level insights in IoT applications [ 42 ]. There are many user level tools available, in which all the data collected by particular RFID readers and data associated with the RFID tags can be managed.
The high level data can be used to draw inferences and take further action. Actuators Let us look at some examples of actuators that are used in the Internet of Things. An actuator is a device, which can effect a change in the environment by converting electrical energy into some form of useful energy.
Some examples are heating or cooling elements, speakers, lights, displays, and motors. The actuators, which induce motion, can be classified into three categories, namely, electrical, hydraulic, and pneumatic actuators depending on their operation. Hydraulic actuators facilitate mechanical motion using fluid or hydraulic power. Pneumatic actuators use the pressure of compressed air and electrical ones use electrical energy.
As an example, we can consider a smart home system, which consists of many sensors and actuators. Preprocessing As smart things collect huge amount of sensor data, compute and storage resources are required to analyze, store, and process this data.
The most common compute and storage resources are cloud based because the cloud offers massive data handling, scalability, and flexibility. But this will not be sufficient to meet the requirements of many IoT applications because of the following reasons [ 43 ]. Their changing location makes it difficult to communicate with the cloud data center because of changing network conditions across different locations. Latency sensitive applications, which need real time responses, may not be feasible with this model.
Also, the communication may be lossy due to wireless links, which can lead to unreliable data. They thus cannot afford to communicate all the time. To solve the problem of mobility, researchers have proposed mobile cloud computing MCC [ 44 ].
But there are still problems associated with latency and power. MCC also suffers from mobility problems such as frequently changing network conditions due to which problems such as signal fading and service degradation arise.
As a solution to these problems, we can bring some compute and storage resources to the edge of the network instead of relying on the cloud for everything.
This concept is known as fog computing [ 11 , 45 ] also see Section 2. The fog can be viewed as a cloud, which is close to the ground. Data can be stored, processed, filtered, and analyzed on the edge of the network before sending it to the cloud through expensive communication media. The fog and cloud paradigms go together. Both of them are required for the optimal performance of IoT applications.
A smart gateway [ 13 ] can be employed between underlying networks and the cloud to realize fog computing as shown in Figure 7.
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Figure 7: Smart gateway for preprocessing. The features of fog computing [ 11 ] are as follows: 1 Low latency: less time is required to access computing and storage resources on fog nodes smart gateways. This is beneficial as context awareness is an important feature of IoT applications.
Multiple fog nodes need to be deployed in distributed geographical areas in order to provide services to mobile devices in those areas. The tasks performed by a smart gateway [ 46 ] are collecting sensor data, preprocessing and filtering collected data, providing compute, storage and networking services to IoT devices, communicating with the cloud and sending only necessary data, monitoring power consumption of IoT devices, monitoring activities and services of IoT devices, and ensuring security and privacy of data.
Some applications of fog computing are as follows [ 10 , 11 ]: 1 Smart vehicular networks: smart traffic lights are deployed as smart gateways to locally detect pedestrians and vehicles through sensors, calculate their distance and speed, and finally infer traffic conditions. This is used to warn oncoming vehicles. These sensors also interact with neighboring smart traffic lights to perform traffic management tasks. For example, if sensors detect an approaching ambulance, they can change the traffic lights to let the ambulance pass first and also inform other lights to do so.
The data collected by these smart traffic lights are locally analyzed in real time to serve real time needs of traffic management. Further, data from multiple gateways is combined and sent to the cloud for further global analysis of traffic in the city. This is done in order to switch automatically to alternative sources of energy such as solar and wind power.
This balancing can be done at the edge of the network using smart meters or microgrids connected by smart gateways. These gateways can analyze and process data. They can then project future energy demand, calculate the availability and price of power, and supply power from both conventional and alternative sources to consumers. Communication As the Internet of Things is growing very rapidly, there are a large number of heterogeneous smart devices connecting to the Internet.
IoT devices are battery powered, with minimal compute and storage resources. Because of their constrained nature, there are various communication challenges involved, which are as follows [ 19 ]: 1 Addressing and identification: since millions of smart things will be connected to the Internet, they will have to be identified through a unique address, on the basis of which they communicate with each other.
For this, we need a large addressing space, and a unique address for each smart object. Therefore, we need a solution that facilitates communication with low power consumption. This stack is very complex and demands a large amount of power and memory from the connecting devices.
The IoT devices can also connect locally through non-IP networks, which consume less power, and connect to the Internet via a smart gateway. Therefore, their applications are limited to small personal area networks.
Personal area networks PAN are being widely used in IoT applications such as wearables connected to smartphones. For increasing the range of such local networks, there was a need to modify the IP stack so as to facilitate low power communication using the IP stack. Near Field Communication NFC Near Field Communication [ 47 — 49 ] is a very short range wireless communication technology, through which mobile devices can interact with each other over a distance of few centimeters only.
All types of data can be transferred between two NFC enabled devices in seconds by bringing them close to each other. This technology is based on RFID. It uses variations in the magnetic field to communicate data between two NFC enabled devices.
NFC operates over a frequency band of There are two modes of operation: active and passive. In the active mode, both the devices generate magnetic fields, while in the passive mode, only one device generates the field and the other uses load modulation to transfer the data. The passive mode is useful in battery powered devices to optimize energy use. One benefit of the requirement of close proximity between devices is that it is useful for secure transactions such as payments.
Consequently, almost all smartphones in the market today are NFC enabled. Different sensor nodes need to interact with each other wirelessly. So, they cannot be used in many applications, where a large area needs to be monitored through many sensor nodes deployed in diverse locations.
A wireless sensor network WSN consists of tens to thousands of sensor nodes connected using wireless technologies. They collect data about the environment and communicate it to gateway devices that relay the information to the cloud over the Internet.
The communication between nodes in a WSN may be direct or multihop. The sensor nodes are of a constrained nature, but gateway nodes have sufficient power and processing resources. The popular network topologies used in a WSN are a star, a mesh, and a hybrid network. There are clearly a lot of protocols that can be used in IoT scenarios. Let us discuss the design of a typical IoT network protocol stack with the most popular alternatives. The Internet Protocol for Smart Objects IPSO Alliance has published various white papers describing alternative protocols and standards for the layers of the IP stack and an additional adaptation layer, which is used for communication [ 51 — 54 ] between smart objects.
The IEEE It supports low power communication along with low cost and short range communication. In the case of such resource constrained environments, we need a small frame size, low bandwidth, and low transmit power. Transmission requires very little power maximum one milliwatt , which is only one percent of that used in WiFi or cellular networks.
This limits the range of communication. Because of the limited range, the devices have to operate cooperatively in order to enable multihop routing over longer distances.
As a result, the packet size is limited to bytes only, and the rate of communication is limited to kbps. The coding scheme in IEEE The protocol also supports short bit link addresses to decrease the size of the header, communication overheads, and memory requirements [ 55 ]. Readers can refer to the survey by Vasseur et al. IPv6 is considered the best protocol for communication in the IoT domain because of its scalability and stability.
Such bulky IP protocols were initially not thought to be suitable for communication in scenarios with low power wireless links such as IEEE This standard defines an adaptation layer between the The choice of IPv6 is because of the large addressing space available in IPv6. IPv6 headers are not small enough to fit within the small byte MTU of the Hence, squeezing and fragmenting the packets to carry only the essential information is an optimization that the adaptation layer performs.
Specifically, the adaptation layer performs the following three optimizations in order to reduce communication overhead [ 55 ]: i Header compression 6loWPAN defines header compression of IPv6 packets for decreasing the overhead of IPv6. Some of the fields are deleted because they can be derived from link level information or can be shared across packets. On the other hand, the maximum size of a frame in IEEE Therefore, we need to fragment the IPv6 packet.
This is done by the adaptation layer. The network layer is responsible for routing the packets received from the transport layer. For such networks, RPL is an open routing protocol, based on distance vectors. It describes how a destination oriented directed acyclic graph DODAG is built with the nodes after they exchange distance vectors.
A set of constraints and an objective function is used to build the graph with the best path [ 53 ]. The objective function and constraints may differ with respect to their requirements.
For example, constraints can be to avoid battery powered nodes or to prefer encrypted links. The objective function can aim to minimize the latency or the expected number of packets that need to be sent. The making of this graph starts from the root node. The root starts sending messages to neighboring nodes, which then process the message and decide whether to join or not depending upon the constraints and the objective function.
Subsequently, they forward the message to their neighbors. In this manner, the message travels till the leaf nodes and a graph is formed. Now all the nodes in the graph can send packets upwards hop by hop to the root. We can realize a point to point routing algorithm as follows. We send packets to a common ancestor, from which it travels downwards towards leaves to reach the destination. To manage the memory requirements of nodes, nodes are classified into storing and nonstoring nodes depending upon their ability to store routing information.
When nodes are in a nonstoring mode and a downward path is being constructed, the route information is attached to the incoming message and forwarded further till the root. The root receives the whole path in the message and sends a data packet along with the path message to the destination hop by hop.
But there is a trade-off here because nonstoring nodes need more power and bandwidth to send additional route information as they do not have the memory to store routing tables. TCP is not a good option for communication in low power environments as it has a large overhead owing to the fact that it is a connection oriented protocol. Therefore, UDP is preferred because it is a connectionless protocol and has low overhead.
The application layer is responsible for data formatting and presentation. However, HTTP is not suitable in resource constrained environments because it is fairly verbose in nature and thus incurs a large parsing overhead. It is used in most IoT applications [ 56 , 57 ]. Unlike HTTP, it incorporates optimizations for constrained application environments [ 50 ]. Other supported features are built in header compression, resource discovery, autoconfiguration, asynchronous message exchange, congestion control, and support for multicast messages.
There are four types of messages in CoAP: nonconfirmable, confirmable, reset nack , and acknowledgement. For reliable transmission over UDP, confirmable messages are used [ 58 ].
The response can be piggybacked in the acknowledgement itself. Clients can publish or subscribe to a topic. This communication takes place through the broker whose job is to coordinate subscriptions and also authenticate the client for security. Moreover, it uses text for topic names, which increases its overhead.
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The topic names are replaced by topic IDs, which reduce the overheads of transmission. Topics do not need registration as they are preregistered. Messages are also split so that only the necessary information is sent. Further, for power conservation, there is an offline procedure for clients who are in a sleep state. Messages can be buffered and later read by clients when they wake up.
Clients connect to the broker through a gateway device, which resides within the sensor network and connects to the broker. It has a relatively shorter range and consumes lower energy as compared to competing protocols.
The BLE protocol stack is similar to the stack used in classic Bluetooth technology. It has two parts: controller and host. The physical and link layer are implemented in the controller. The functionalities of upper layers are included in the host [ 62 ]. BLE is not compatible with classic Bluetooth. Let us look at the differences between classic Bluetooth and BLE [ 63 , 64 ]. The main difference is that BLE does not support data streaming. Instead, it supports quick transfer of small packets of data packet size is small with a data rate of 1 Mbps.
There are two types of devices in BLE: master and slave.
The master acts as a central device that can connect to various slaves. Let us consider an IoT scenario where a phone or PC serve as the master and mobile devices such as a thermostat, fitness tracker, smart watch, or any monitoring device act as slaves. In such cases, slaves must be very power efficient. Therefore, to save energy, slaves are by default in sleep mode and wake up periodically to receive packets from the master.
In classic Bluetooth, the connection is on all the time even if no data transfer is going on. BLE supports low duty cycle requirements as its packet size is small and the time taken to transmit the smallest packet is as small as 80 s.
An experiment conducted by Siekkinen et al. The energy efficiency of BLE is 2. It consumes lower power than a traditional WiFi device and also has a longer range. This is why this protocol is suitable for Internet of Things applications. Let us look at the specifications of the IEEE This standard was developed to deal with wireless sensor network scenarios, where devices are energy constrained and require relatively long range communication.
IEEE Because of the relatively lower frequency, the range is longer since higher frequency waves suffer from higher attenuation. We can extend the range currently 1 km by lowering the frequency further; however, the data rate will also be lower and thus the tradeoff is not justified. Zigbee was developed by the Zigbee alliance, which works for reliable, low energy, and cheap communication solutions.
The range of Zigbee device communication is very small 10— meters. The details of the network and application layers are also specified by the Zigbee standard.
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Unlike BLE, the network layer here provides for multihop routing. A FFD node can additionally act as a router. Zigbee supports star, tree, and mesh topologies. The routing scheme depends on the topology. The framework for communication and distributed application development is provided by the application layer. APOs are spread over the network nodes. These are pieces of software, which control some underlying device hardware examples: switch and transducer.
It is responsible for secure communication between the Application Objects. These features can be used to create a large distributed application. The two are very different but merging them has many advantages.
That is why its integration with WSN is very useful. These sensor tags sense data from the environment and then the RFID reader can read this sensed data from the tag. In such cases, simple RFID protocols are used, where there is only single hop communication. RFID sensing technologies can be further classified on the basis of the power requirement of sensor tags as explained earlier in the section on RFIDs active and passive see Section 5. To extend its capabilities, the sensor tag is equipped with a wireless transceiver, little bit of Flash memory, and computational capabilities such that it can initiate communication with other nodes and wireless devices.
The nodes can in this fashion be used to form a wireless mesh network. In such networks, sensor tags can communicate with each other over a large range via intermediate hops. With additional processing capabilities at a node, we can reduce the net amount of data communicated and thus increase the power efficiency of the WSN.
The readers are equipped with wireless transceivers and microcontrollers so that they can communicate with each other and therefore, the tag data can reach a reader, which is not in the range of that tag. It takes advantage of multihop communication of wireless sensor network devices. The data from all the RFID readers in the network ultimately reaches a central gateway or base station that processes the data or sends it to a remote server.
These kinds of integrated solutions have many applications in a diverse set of domains such as security, healthcare, and manufacturing. Let us now discuss some of the most common technologies in this area. Narrow band IoT: it is a technology made for a large number of devices that are energy constrained. It is thus necessary to reduce the bit rate. Sigfox: it is one more protocol that uses narrow band communication 10 MHz. It uses free sections of the radio spectrum ISM band to transmit its data.
Instead of 4G networks, Sigfox focuses on using very long waves. Thus, the range can increase to a kms. Because of this the energy for transmission is significantly lower 0. Again the cost is bandwidth. It can only transmit 12 bytes per message, and a device is limited to messages per day. This is reasonable for many kinds of applications: submarine applications, sending control emergency codes, geolocation, monitoring remote locations, and medical applications.
Weightless: it uses a differential binary phase shift keying based method to transmit narrow band signals.
To avoid interference, the protocol hops across frequency bands instead of using CSMA. It supports cryptographic encryption and mobility. Along with frequency hopping, two additional mechanisms are used to reduce collisions. The downlink service uses time division multiple access TDMA and the uplink service uses multiple subchannels that are first allocated to transmitting nodes by contacting a central server.
Some applications include smart meters, vehicle tracking, health monitoring, and industrial machine monitoring. Neul: this protocol operates in the sub-1 GHz band. It uses small chunks of the TV whitespace spectrum to create low cost and low power networks with very high scalability.
It has a 10 km range and uses the Weightless protocol for communication. It targets wide area network applications and is designed to be a low power protocol. Its data rates can vary from 0. It was designed to serve as a standard for long range IoT protocols. It thus has features to support multitenancy, enable multiple applications, and include several different network domains. These lightweight protocols need to be able to carry application messages, while simultaneously reducing power as far as possible.
It defines the communication protocol between a server and a device. The devices often have limited capabilities and are thus referred to as constrained devices. The main aims of the OMA protocol are as follows: 1 Remote device management. All the protocols in this class treat all the network resources as objects. Such resources can be created, deleted, and remotely configured. These devices have their unique limitations and can use different kinds of protocols for internally representing information.
It is an application layer protocol that allows constrained nodes such as sensor motes or small embedded devices to communicate across the Internet. It is ideally suited for small devices because of its low overhead and parsing complexity and reliance on UDP rather than TCP. Middleware Ubiquitous computing is the core of the Internet of Things, which means incorporating computing and connectivity in all the things around us.
Interoperability of such heterogeneous devices needs well-defined standards. But standardization is difficult because of the varied requirements of different applications and devices. For such heterogeneous applications, the solution is to have a middleware platform, which will abstract the details of the things for applications.
That is, it will hide the details of the smart things. It should act as a software bridge between the things and the applications. It needs to provide the required services to the application developers [ 20 ] so that they can focus more on the requirements of applications rather than on interacting with the baseline hardware.
To summarize, the middleware abstracts the hardware and provides an Application Programming Interface API for communication, data management, computation, security, and privacy.
The challenges, which are addressed by any IoT middleware, are as follows: [ 20 , 71 , 72 ]. Interoperability is of three types: network, semantic, and syntactic. Network interoperability deals with heterogeneous interface protocols for communication between devices.
It insulates the applications from the intricacies of different protocols. Syntactic interoperability ensures that applications are oblivious of different formats, structures, and encoding of data. Semantic interoperability deals with abstracting the meaning of data within a particular domain. It is loosely inspired by the semantic web. In the Internet of Things, the infrastructure is mostly dynamic. The devices have to announce their presence and the services they provide. The solution needs to be scalable because the devices in an IoT network can increase.
Most solutions in this domain are loosely inspired by semantic web technologies. In addition, typically APIs are provided to discover devices based on their capabilities. Finally, any IoT middleware needs to perform load balancing, manage devices based on their levels of battery power, and report problems in devices to the users.
Moreover, IoT applications need to scale due to ever increasing requirements. This should be managed by the middleware by making required changes when the infrastructure scales.
It is necessary to analyze all of this data in great detail. As a result a lot of big data algorithms are used to analyze IoT data. Moreover, it is possible that due to the flimsy nature of the network some of the data collected might be incomplete. It is necessary to take this into account and extrapolate data by using sophisticated machine learning algorithms.
Security and privacy issues need to be addressed in all such environments.
The middleware should have built in mechanisms to address such issues, along with user authentication, and the implementation of access control. Most of the sensor data is analyzed and stored in a centralized cloud. It is necessary for IoT middleware to seamlessly run on different types of clouds and to enable users to leverage the cloud to get better insights from the data collected by the sensors. The context can subsequently be used for providing sophisticated services to users.
There are many middleware solutions available for the Internet of Things, which address one or more of the aforementioned issues. All of them support interoperability and abstraction, which is the foremost requirement of middleware. Middlewares can be classified as follows on the basis of their design [ 72 ]: 1 Event based: here, all the components interact with each other through events.
Each event has a type and some parameters. Events are generated by producers and received by the consumers. A service oriented middleware views resources as service providers. It abstracts the underlying resources through a set of services that are used by applications. There is a service repository, where services are published by providers. The consumers can discover services from the repository and then bind with the provider to access the service. Service oriented middleware must have runtime support for advertising services by providers and support for discovering and using services by consumers.
HYDRA [ 23 ] is a service oriented middleware. It incorporates many software components, which are used in handling various tasks required for the development of intelligent applications. Hydra also provides semantic interoperability using semantic web technologies. It supports dynamic reconfiguration and self-management. The database can then be queried by the applications using a query language.
There are easy to use interfaces for extracting data from the database. This approach has issues with scaling because of its centralized model. It incorporates devices with different data formats and ontologies and ties all of them together in a common framework. The framework is used for exchanging data between diverse types of devices.
For a common semantic format, we need to have adapters for communication between devices because; for each device, we need adapters to map standards to one abstract standard [ 73 ]. In such a semantic middleware [ 74 ], a semantic layer is introduced, in which there is a mapping from each resource to a software layer for that resource.Another novel IoT device, which has a lot of promise are monitoring patches that are pasted on the skin.
Interoperability of such heterogeneous devices needs well-defined standards. The preprocessing layer performs filtering, processing, and analytics of sensor data. Actions Shares. The Internet Governance Forum meets for the first time.