By Xu Yang, Athman Bouguettaya
Access to cellular companies specializes in tools for gaining access to broadcast established M-services from a number of instant channels. This booklet offers a unique infrastructure that offers a multi-channel broadcast framework for cellular clients to successfully notice and entry composite M-services. Multi-channel algorithms are proposed for successfully gaining access to composite services.
Access to cellular companies presents an in-depth survey of instant info entry and motivates the necessity to deal with cellular companies another way. A instant version of carrier orientated structure (SOA) is usually covered.
Designed for researchers and practitioners who paintings within the normal sector of cellular prone, this e-book is additionally appropriate for advanced-level scholars in desktop science.
Michael P. Papazoglou, Tilburg college, The Netherlands
Fabio Casati, college of Trento, Italy
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The most representative B+ tree based methods are (1,m) indexing and distributed indexing . We only discuss distributed indexing in this section, because it is derived from (1,m) indexing and they have very similar data structure. 1 Data Organization In distributed indexing, every broadcast data item is indexed on its primary key attribute. Indices are organized in B+ tree structure. 1 shows a typical full index tree consisting of 81 data items . 1, each node has three pointers) pointing at its child nodes.
Furthermore, the hashing function itself is included in every data bucket. This obviously increases the broadcast cycle, and thus, the access time. In our method, hashing is used only to partition the broadcast data into a number of partitions. B+ tree technique is then used to index each partition. The hashing function is only stored at the beginning of each partition. Since the number of partitions is a small number compared to the number of all data items, the overhead introduced is much smaller than that in hashing based method.
The requirement for choosing the hashing functions is the ability to generate partitions containing the same approximate size of data items across partitions. We use a two level hashing method to achieve this objective. First, each key field is converted into its integer representation using the ASCII standard. The resulted number is then hashed to the range [1, p]. The optimum scenario is when a hashing function produces partitions with equal size. In this case, we only need to store a hashing value and a hashing function at the beginning of each partition.
Access to Mobile Services by Xu Yang, Athman Bouguettaya