Data Dissemination In Mobile Computing Pdf Download
Keena Wiegert
Energy Efficiency: WSNs are typically powered by batteries or other low-power sources, and so energy efficiency is a crucial consideration in data dissemination. Techniques such as data aggregation, compression, and clustering can be used to reduce the amount of data transmitted and conserve energy.
Reliability: Data dissemination in WSNs must be reliable, meaning that all nodes in the network receive the necessary data without loss or duplication. Techniques such as error detection and correction can be used to ensure reliability.
Scalability: WSNs can range in size from a few nodes to thousands or even millions of nodes. Data dissemination techniques must be scalable to accommodate the number of nodes in the network.
Security: WSNs are vulnerable to security threats, such as eavesdropping, tampering, and denial of service attacks. Techniques such as encryption and authentication can be used to ensure the security of data dissemination.
Adaptability: WSNs must be adaptable to changing conditions in the environment, such as changes in the number and location of nodes, changes in data rates, and changes in network topology. Techniques such as dynamic routing and load balancing can be used to adapt to these changes.
QoS Requirements: In some applications, data dissemination may have Quality of Service (QoS) requirements such as delay, throughput, or reliability. Techniques such as priority scheduling and traffic shaping can be used to ensure that QoS requirements are met.
The data dissemination is a method of distributing or transmitting the statistical or another type of data to the end-users. The data can be in the form of audio, video or any other data services. Organizations use many ways to release data to the public, such as electronic format, CD-ROM and paper publications, i.e., PDF files based on aggregated data. Mobile devices receive output data. A mobile device can select, tune and cache the required data items, which can be used for application programs.
Nowadays, the most popular dissemination method is non-proprietary open systems using internet protocols. There are various communication infrastructures that can be used in data dissemination across any set of interconnected networks. Data is made available in standard open formats.
Some organizations use proprietary databases to disseminate the data in order to protect the sovereignty and copyright of the data. If you use proprietary databases to disseminate the data, it requires specific software for end-users to view the data. This type of transmitted data cannot be open in common open formats. This type of data is first converted into the proprietary data format, and then the organization provides specifically designed software to their user to read the data.
Standards were developed to provide an internationally accepted statistical methodology for the dissemination of statistical data. The 'International Organization for Standardization' (ISO) is an international standard-setting body with many representatives from various national standards organizations.
Communication asymmetry is one of the key aspects of dissemination-based applications. The Communications Asymmetry specifies that the communication capacity or data volume going towards servers-to-clients (also known as downstream direction) is much greater than that in going towards clients-to servers (also known as upstream direction).
Content delivery is always an asymmetric process. it doesn't matter whether it is performed over a symmetric channel such as the internet or over an asymmetric channel, such as a cable television (CATV) network.
The mobile communication between a static computer system and a mobile device is intrinsically asymmetric. A device is always allocated a limited bandwidth because there are a large number of devices that have to access the network. The bandwidth in the downstream direction is much larger than in the upstream direction. It is because mobile devices have limited power resources. It is also a fact that faster data transmission rates for long intervals of time would use greater power dissipation from the devices. The data transmission rates go up to a maximum of 14.4 kbps for both uplink and downlink direction in GSM networks. It is an example of symmetric communication, and this symmetry is maintained because GSM is only used for voice communication.
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With the application of mobile computing, there could be more intelligent ways to sense and collect data, and to reduce the workload of participants. In addition, the scale of data sensing, collection and dissemination could increase. Mobile computing makes full use of various sensing devices, such as smart phones, wireless body sensors, smart sensing devices in manufacturing, and smart meters. These devices, which sense and collect data (on the order of zettabytes in the near future), together with the computing power of mobile devices, develop a new paradigm to data sensing, collection and dissemination. Mobile Computing has emerged as a prospective computing paradigm to pave the way to pervasive computing for mobile and big-data applications.
To ensure intelligent data sensing, data collection and data processing based on mobile computing over the pervasive computing environment, there are some fundamental challenges. Many open issues remain unresolved, such as how to achieve the expected performance for intelligent data sensing, data collection, data processing, and how to ensure the data quality, data reliability, information security and privacy in data collection/dissemination with intelligence. Other relevant aspects should also be studied, such as the computation cost, the platform, tools, service discovery, data management, and analytics for intelligent data collection and dissemination. These unresolved issues have been major research hotspots for many researchers since they are critical to ensuring rigid and efficient applications for intelligent data sensing, collection and dissemination in mobile computing.
To tackle the above issues and challenges, this Special Section in IEEE Access will present innovative solutions and recent advances in the domain of intelligent data sensing, collection and dissemination in mobile computing, which will provide a guide for the application and future research of mobile computing.
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