Performance analysis of data scheduling algorithms for multi‐item requests in multi‐channel broadcast environments

Li, Kai; Lee, Victor C. S.

doi:10.1002/dac.1098

Cited by 16 publications

(11 citation statements)

References 22 publications

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“…K. Liu et al [21] presented the DUP algorithm which considers both the urgencies of queries and data items, and the DUP algorithm always broadcasts the most urgent data item which is required in the most urgent query. A much more comprehensive discussion on recent research results can be found in [22]. Lv et al introduced the concept of profit into the broadcast schedule and proposed an efficient scheduling algorithm in [23] which always choose the data item with highest profit to be broadcast at each time unit.…”

Section: Related Workmentioning

confidence: 98%

“…A time-critical request is associated with a deadline imposed by either the application or the user, the result of a request is useful only if all the required data items can be received before the deadline. 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.…”

Section: Introductionmentioning

confidence: 99%

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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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Section: Related Workmentioning

confidence: 98%

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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“…Wireless technologies, such as radio frequency identification and GPS, have been applied for facilitating instructional processes by creating a highly interactive environment [7,8]. A system was developed to support the foreign language learning.…”

Section: Applied Technologies In U-learning Environmentsmentioning

confidence: 99%

Intelligent route generation: discovery and search of correlation between shared resources

Yen

Huang

et al. 2012

Int J Communication

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Sharing information and resources on the Internet has become an important activity for education. The use of ubiquitous devices makes it possible for learning participants to be engaged in an open and connected social environment, and also allows the learning activities to be performed at any time and any place. In this study, the discovery of correlation among shared resources is concentrated. A hypothetical scenario is considered that the information, such as photos and thoughts, is applicable to be shared with implicit context (i.e., geographical information) by learners through a practical implementation, PadSCORM, on a mobile device. Two major contributions are achieved. First, the correlations among resources are determined through usage experiences mining and geographical information adjustment. It then assists learners in filtering out redundant information by highlighting the significance of resources. Second, an intelligent searching algorithm is proposed to visualize adaptive routes to facilitate search process and to enrich the learning activity. The empirical experiments revealing the feasibility and performance (e.g., accuracy and effectiveness) are conducted in the universities in North Taiwan.Social network analysis concentrates on the discovery of implicit correlation via the explicit exchange of resources among participants. The participant, including the human user and/or object,

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“…However, this solution is infeasible in a business environment. Although a router can schedule the transmission of each file, the schedule does not indicate the value of the file to the business (Liu and Lee 2010). For example, the system cannot determine whether a non-urgent file sent by the Chief Executive Officer is more important than an urgent file sent by a project manager.…”

Section: Introductionmentioning

confidence: 96%

Optimal services for content delivery based on business priority

Liang

Luh

2013

Journal of the Chinese Institute of Engineers

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In a content-delivery system, connections are viewed as resources for sending files. However, the growing business needs of large-scale networks require an effective content-delivery service for transferring files. Since connections are sparse resources, prioritizing connections is essential for efficiently delivering urgent files and regular files based on various business priorities. This study presents a loss function as a performance index for a content-delivery service. The proposed loss function was applied to a sample content-delivery system to derive the average number of regular files in the retry group, the probability of failure to transfer a regular file in the first attempt, and the probability of failure to transmit urgent files. Additionally, the loss was associated with the decreased number of reserve connections under regular hours and peak hours. The experimental results show that the proposed model finds the optimal number of reserve connections for sending high-and low-priority files, and a manager can increase the service rate to ensure that losses are tolerable when delivering urgent files. Finally, the relative probabilities of blocked urgent files and blocked regular files are used as an indicator of efficiency in reserving connections.

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Performance analysis of data scheduling algorithms for multi‐item requests in multi‐channel broadcast environments

Cited by 16 publications

References 22 publications

A Novel Scheduling Algorithm for Supporting Periodic Queries in Broadcast Environments

A Novel Scheduling Algorithm for Supporting Periodic Queries in Broadcast Environments

Intelligent route generation: discovery and search of correlation between shared resources

Optimal services for content delivery based on business priority

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