Broadcast program generation for unordered queries with data replication

Huang, Jiun-Long; Chen, Ming-Syan

doi:10.1145/952532.952704

Cited by 30 publications

(8 citation statements)

References 5 publications

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“…As the above description of indexing, indexing technique is currently divided into two types: first, a large number of existing studies suggest that index and data items are intermixed each other to be broadcast at same broadcast channel [12]; second, the broadcast channels are simply divided into index channel and data channel [8,13]. They play different roles in data broadcast that index channel is responsible for broadcasting index structure, while data channel is responsible for broadcasting data items.…”

Section: Related Workmentioning

confidence: 99%

“…It is well known that the goal of indexing technique is to reduce access time. Various schemes are directly proposed to improve the performance of wireless data broadcast, all of which adopt alphabetic Huffman Tree, hashing table, tree and exponential indexing [8,9,13,14,15,16,17]. [7] firstly proposed an allocation model in server side through considering access frequencies of data items, data item's lengths, and bandwidth of different channels.…”

Section: Related Workmentioning

confidence: 99%

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On-line Data Retrieval Algorithm with Restart Strategy in Wireless Networks

Luan

2014

JNW

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Data retrieval is an efficient scheme for data dissemination in mobile computing, and its primary goal is to improve the waiting time and save the energy of mobile devices. Existing data retrieval algorithms are developed at the basis of a-priori knowledge of wireless data broadcast. In practical, they are not suitable for on-line data retrieval where the knowledge is not known. In this paper, we study on-line data retrieval problem with Las Vegas strategy of randomized algorithm, called as LVDR, and reduce the competitive rate of this problem, , where is the number of channels and is the length of broadcast cycle. Thus, we observe that different schemes of choosing channel will generate the different efficiencies in randomized algorithm. Therefore, we propose another scheme introduced restart strategy to execute the other retrieval sequences of choosing channels when the client may not retrieve the requested data item in certain time, called as LVDR-RS. In addition, we adopt Markov chain to predict the optimal restart cycle for each requested data item. Through analysis, we obverse that the competitive rate is closely related with the number of restarts and restart cycle, .

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

On-line Data Retrieval Algorithm with Restart Strategy in Wireless Networks

Luan

2014

JNW

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“…Then, a content selection scheme [40] is presented to overcome the shortage in [41]. The broadcast program for ordered queries is generated with data replication [42], and [43] is for unordered queries. In addition, [13] proposes a polynomial-time deterministic algorithm to achieve the lower bounds of average access time for a pair of two files.…”

Section: Related Workmentioning

confidence: 99%

Online Scheduling Sequential Objects with Periodicity for Dynamic Information Dissemination

Chen

2009

IEEE Trans. Knowl. Data Eng.

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The scalability of data broadcasting has been manifested by prior studies on the base of the traditional data management systems where data objects, mapped to a pair of state and value in the database, are independent, persistent, and static against simple queries. However, many modern information applications spread dynamic data objects and process complex queries for retrieving multiple data objects. Particularly, the information servers dynamically generate data objects that are dependent and can be associated into a complete response against complex queries. Accordingly, the study in this paper considers the problem of scheduling dynamic broadcast data objects in a clients-providers-servers system from the standpoint of data association, dependency, and dynamics. Since the data broadcast problem is NP-hard, we derive the lower and the upper bounds of the mean service access time. In light of the theoretical analyses, we further devise a deterministic algorithm with several gain measure functions for the approximation of schedule optimization. The experimental results show that the proposed algorithm is able to generate a dynamic broadcast schedule and also minimize the mean service access time to the extent of being very close to the theoretical optimum.

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“…The authors in [22] proposed a greedy algorithm to solve the dependent data broadcasting problem for a single channel. In view of the poor performance of adopting a greedy algorithm for multiple channels, Huang and Chen adopted the concept of a genetic algorithm to solve the dependent data broadcasting problem for multiple channels [11], [5], [7].…”

Section: Related Workmentioning

confidence: 99%

“…Moreover, the broadcast program allows a data item to appear in different broadcast channels simultaneously. Such a replication issue is addressed in [11].…”

Section: Introductionmentioning

confidence: 99%

On Channel Allocation for Heterogeneous Data Broadcasting

Tsai

Hung²,

Chen

2009

IEEE Trans. on Mobile Comput.

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In recent years, data broadcasting has become a promising technique in designing a mobile information system with power conservation, high scalability, and high bandwidth utilization. However, prior research topics in data broadcasting are mainly based on the assumption that the disseminated data items are of the same size. Motivated by the fact that various kinds of data objects may be disseminated in advanced information systems, we explore in this paper the problem of generating broadcast programs in a heterogeneous data broadcasting environment, in which disseminated data items can be of different sizes. Given the broadcast database and the number of channels, we first derive the analytical model of the heterogeneous data broadcasting to obtain the average waiting time of mobile users and prove the allocation problem as an NP-complete problem. In order to solve such problem, we propose a two-phase architecture to perform channel allocation. Algorithm Dimension Reduction Partitioning (DRP) is employed to perform rough allocation to derive the satisfactory solutions, whereas mechanism Cost-Diminishing Movement Selection (CDMS) is used for fine allocation to achieve local optimum solutions. In addition to the two-phase architecture, we also propose algorithm GA-CDMS according to the concept of hybrid genetic algorithm for comparison purposes. GA-CDMS can perform global search more accurately and efficiently than the conventional genetic algorithm GA, and the suboptimum that GA-CDMS achieves will be very close to the optimal solution. In order to validate the two-phase allocation algorithm DRP-CDMS, several experiments are conducted. In these experiments, we consider the important issues such as accuracy, scalability, diversity and efficiency. From the experimental results, we show that the proposed two-phase channel allocation is very practical in performing an effective channel allocation with high efficiency in a heterogeneous broadcasting environment.

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Broadcast program generation for unordered queries with data replication

Cited by 30 publications

References 5 publications

On-line Data Retrieval Algorithm with Restart Strategy in Wireless Networks

On-line Data Retrieval Algorithm with Restart Strategy in Wireless Networks

Online Scheduling Sequential Objects with Periodicity for Dynamic Information Dissemination

On Channel Allocation for Heterogeneous Data Broadcasting

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