On the performance of real-time multi-item request scheduling in data broadcast environments

Lee, Victor C. S.; Liu, Kai

doi:10.1016/j.jss.2010.01.034

Cited by 22 publications

(17 citation statements)

References 18 publications

(19 reference statements)

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“…For solving request starvation problem, Chen et al (2008) considered on-demand broadcast with time-critical multi-item requests, and Liu and Lee (2010a) designed a data scheduling scheme for multi-item requests broadcast multiple channels. Chen et al (2010) also proposed another scheme to solve request starvation problem. In multi-channel wireless environment, Liu and Lee (2010b) extended a number of representative scheduling schemes to evaluate their performances in scheduling multi-item requests.…”

Section: Related Workmentioning

confidence: 99%

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On-demand data broadcast with deadlines for avoiding conflicts in wireless networks

Shen

Tian

2015

Journal of Systems and Software

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Section: Related Workmentioning

confidence: 99%

“…Two known research streams on the data scheduling problem are push-based (Yee et al, 2002) and pull-based (Chen et al, 2010) data broadcast. In push-based data broadcast, the server periodically distributes some pre-selected data items at the channels according to a-priori knowledge of clients' requests, such as the access probability.…”

Section: Introductionmentioning

confidence: 99%

On-demand data broadcast with deadlines for avoiding conflicts in wireless networks

Shen

Tian

2015

Journal of Systems and Software

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“…To a large extent, the data placement problem of XML data is similar to that in multi-item contexts [13,14] where mobile clients may request multiple items each time. However, there are some drawbacks of existing data placement approaches in the traditional data broadcast models.…”

Section: Introductionmentioning

confidence: 99%

“…Firstly, the previous work on multi-item placement problems generally assumes that the clients' queries are known in advance [13][14][15][16]. For example, the clients can provide a profile of their interests to the servers [15,16].…”

Section: Introductionmentioning

confidence: 99%

Organizing XML Data in a Wireless Broadcast System by Exploiting Structural Similarity

Qin

Sheng

Wang

et al. 2017

Wireless Pers Commun

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Wireless data broadcast is an efficient way of delivering data of common interest to a large population of mobile devices within a proximate area, such as smart cities, battle fields, etc. In this work, we focus ourselves on studying the data placement problem of periodic XML data broadcast in mobile and wireless environments. This is an important issue, particularly when XML becomes prevalent in today's ubiquitous and mobile computing devices and applications. Taking advantage of the structured characteristics of XML data, effective broadcast programs can be generated based on the XML data on the server only. An XML data broadcast system is developed and a theoretical analysis on the XML data placement on a wireless channel is also presented, which forms the basis of the novel data placement algorithm in this work. The proposed algorithm is validated through a set of experiments. The results show that the proposed algorithm can effectively place XML data on air and significantly improve the overall access efficiency.

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“…For such kind of applications, some real-time broadcast scheduling algorithms have been proposed [14], [6], [22], which take queries' deadlines into account. But unfortunately, almost all the existing real-time broadcast scheduling algorithms only support single data item [2] or one-shot queries [7], [16], and thus can be of low performance, or even not applicable in some practical applications. For example, a stock investor wants to refresh his stock information once every minute to decide whether or not to trade his stock.…”

Section: Introductionmentioning

confidence: 99%

A Novel Scheduling Algorithm for Supporting Periodic Queries in Broadcast Environments

Zhou

2015

IEEE Trans. on Mobile Comput.

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Being a proven efficient approach to answering queries that have common data needs, data broadcast has received much attention in the past decade, especially for dynamic and large-scale data dissemination. An important class of emerging data broadcast applications must monitor multiple data items continuously in order to enable data-driven decision making. For such applications, an important problem that must be addressed is how to disseminate data to periodic continuous queries so that all the requests can be satisfied while the bandwidth utilization is minimized. To our best knowledge, the only known work on this topic is the RM-UO algorithm proposed in [27]. However, the RM-UO algorithm simply utilizes the Sr algorithm introduced in [13] to transform the original queries into 2-harmonic tasks, which would lead to a considerable waste of available bandwidth. In this paper, based on the observation that some queries can be merged to save bandwidth consumption, we propose two merging polices namely Multiple Query Merging (MQM) and Redundant Query Merging (RQM), and show that both can lead to notable bandwidth savings. Further, to disseminate data to periodic continuous queries, we implement a unified scheduling algorithm called UM, which combines both MQM and RQM. Extensive experiments have been conducted to compare our UM algorithm with RM-UO, and the results show that UM outperforms RM-UO considerably in terms of wireless bandwidth consumption and query service ratio.

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On the performance of real-time multi-item request scheduling in data broadcast environments

Cited by 22 publications

References 18 publications

On-demand data broadcast with deadlines for avoiding conflicts in wireless networks

On-demand data broadcast with deadlines for avoiding conflicts in wireless networks

Organizing XML Data in a Wireless Broadcast System by Exploiting Structural Similarity

A Novel Scheduling Algorithm for Supporting Periodic Queries in Broadcast Environments

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