A Study On Data Broadcast Strategy In Mobile Real Time Database System

The rapid development of wireless communication network makes mobile computing to be reality. The mobile supporting station organizes data which are requested frequently and transmit them to mobile clients by broadcast mode.There are many issues worth to be researched in data broadcasting.It is the primary problem that how to determine data to be broadcasted. The data requested frequently broadcasting in time will satisfied with the needs of many mobile clients. The classic technologies to get frequent elements usually adopt to counting, sketching, quantile and hashing algorithms and the hashing algorithm performs best in time aspect. Based on Bernoulli large number theorem and Markov inequality, the number of frequent element that appeared is estimated by the conflicts of hashing. It makes the error to be fallen in the scope that be permitted that use a large number of hashing functions and hashing tables. Multi-hashing makes full use of the computing ability of multi-core CPUs which are popular at present. Adding hashing functions can raise the precision, but hardly increase the time.It is the most benefit which mobile clients obtained from broadcast to take the most data available by the least time and power consumed. For the benefits of mobile clients the data broadcast scheduling adopts to priority scheme and adjusts the weights of data deadline, requested frequency and reach time. The scheduling is satisfied with the data request success ratio firstly, and then trades off average access time and average tuning time. With the implement of scheduling, the data requests of the same clients are arranged to responsed at adjacent broadcast frames as much as possible. The structure of data organization appends hot data indicators. When mobile clients listen the broadcast channel, they may download all kinds of hot data according to their power. The hit rate of cache is increased and the load of uplink channel is decreased, so as to reduce average access time. The throughput of broadcast system is improved. Indexing technology is hardly studied when data access is skew in real time system. On one hand indexing considers the probability of data accessed, on the other hand indexing needs to satisfy data real-time constraints, and meanwhile, the time complexity of arithmetic computing for indexing must be low. The nearly optimal binary index tree NOBIT is based on the idea of static optimal search tree. We introduce real-time weight when it deals with nodes probabilities weight so as to quickly construct a binary index tree with nearly optimal performance. The search process of NOBIT is similar to binary search, and its average time complexity is O(logN). The NOBIT considers the probability of accessed data and data which are accessed frequently are put into the front part of broadcast sequence so that average tuning time is shortened. Meanwhile, the NOBIT takes the real-time constraints of accessed data into account and data with rigid time constraints also are put into the front part of broadcast sequence so that success rate of data requested is improved.