Cellular Digital Packet Data (CDPD)

Computer Engineering electronics Engineering Civil Engineering

Cellular Digital Packet Data (CDPD) systems offer one of the most advanced means of wireless data transmission technology. Generally used as a tool for business, CDPD holds promises for improving law enforcement communications and operations. As technologies improve, CDPD may represent a major step toward making our nation a wireless information society. While CDPD technology is more complex than most of us care to understand. In this age of information, no one needs to be reminded of speed but also accuracy in the storage, retrieval and transmission of data. The CDPD network is a little one year old and already is proving to be a hot digital enhancement to the existing phone network. CDPD transmits digital packet data at 19.2 Kbps, using idle times between cellular voice calls on the cellular telephone network. CDPD technology represents a way for law enforcement agencies to improve how they manage their communications and information systems. For over a decade, agencies around the world have been experimenting with placing Mobile Data Terminals(MDT) in their vehicles to enhance officer safety and efficiency. Early MDT's transmits their information using radio modems. In this case data could be lost in transmission during bad weather or when mobile units are not properly located in relation to transmission towers. More recently MDT's have transmitted data using analog cellular telephone modems. This shift represented an improvement in mobile data communications, but systems still had flaw which limited their utility. Since the mid-1990, computer manufacturers and the telecommunication industry have been experimenting with the use of digital cellular telecommunications as a wireless means to transmit data. The result of their effort is CDPD systems. These systems allow users to transmit data with a higher degree of accuracy, few service interruptions, and strong security. In addition CDPD technology represents a way for law enforcement agencies to improve how they manage their communications and information systems. This results in the capacity for mobile users to enjoy almost instantaneous access to information. Optimized Distributed Association Rule Mining Algorithm - ODAM With the explosive growth of information sources available on the World Wide Web, it has become increasingly necessary for users to utilize automated tools in find the desired information resources, and to track and analyze their usage patterns. Association rule mining is an active data mining research area. However, most ARM algorithms cater to a centralized environment. In contrast to previous ARM algorithms, ODAM is a distributed algorithm for geographically distributed data sets that reduces communication costs. Recently, as the need to mine patterns across distributed databases has grown, Distributed Association Rule Mining (D-ARM) algorithms have been developed. These algorithms, however, assume that the databases are either horizontally or vertically distributed. In the special case of databases populated from information extracted from textual data, existing D-ARM algorithms cannot discover rules based on higher-order associations between items in distributed textual documents that are neither vertically nor horizontally distributed, but rather a hybrid of the two. Modern organizations are geographically distributed. Typically, each site locally stores its ever increasing amount of day-to-day data. Using centralized data mining to discover useful patterns in such organizations' data isn't always feasible because merging data sets from different sites into a centralized site incurs huge network communication costs. Data from these organizations are not only distributed over various locations but also vertically fragmented, making it difficult if not impossible to combine them in a central location. Distributed data mining has thus emerged as an active subarea of data mining research. A significant area of data mining research is association rule mining. Unfortunately, most ARM algorithms focus on a sequential or centralized environment where no external communication is required. Distributed ARM algorithms, on the other hand, aim to generate rules from different data sets spread over various geographical sites; hence, they require external communications throughout the entire process. DARM algorithms must reduce communication costs so that generating global association rules costs less than combining the participating sites' data sets into a centralized site. However, most DARM algorithms don't have an efficient message optimization technique, so they exchange numerous messages during the mining process. We have developed a distributed algorithm, called Optimized Distributed Association Mining, for geographically distributed data sets. ODAM generates support counts of candidate itemsets quicker than other DARM algorithms and reduces the size of average transactions, data sets, and message exchanges. Existing Method The Data mining Algorithms can be categorized into the following : loading..