Balancing push and pull for data broadcast
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
“Data in your face”: push technology in perspective
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
R × W: a scheduling approach for large-scale on-demand data broadcast
IEEE/ACM Transactions on Networking (TON)
Broadcast on Demand: Efficient and Timely Dissemination of Data in Mobile Environments
RTAS '97 Proceedings of the 3rd IEEE Real-Time Technology and Applications Symposium (RTAS '97)
A Pull-Based Broadcast Algorithm that Considers Timing Constraints
ICPPW '04 Proceedings of the 2004 International Conference on Parallel Processing Workshops
On-demand data broadcasting for mobile decision making
Mobile Networks and Applications
A multi-channel VANET providing concurrent safety and commercial services
Proceedings of the 2nd ACM international workshop on Vehicular ad hoc networks
RTCSA '05 Proceedings of the 11th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications
Time-Critical On-Demand Data Broadcast: Algorithms, Analysis, and Performance Evaluation
IEEE Transactions on Parallel and Distributed Systems
Scheduling real-time requests in on-demand data broadcast environments
Real-Time Systems
On scheduling vehicle-roadside data access
Proceedings of the fourth ACM international workshop on Vehicular ad hoc networks
IPDPS '09 Proceedings of the 2009 IEEE International Symposium on Parallel&Distributed Processing
Efficient processing of requests with network coding in on-demand data broadcast environments
Information Sciences: an International Journal
Supporting real-time multiple data items query in multi-RSU vehicular ad hoc networks (VANETs)
Journal of Systems and Software
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On-demand broadcast is an effective wireless data dissemination technique to enhance system scalability and capability to handle dynamic data access patterns. Previous studies on time-critical on-demand data broadcast were conducted under the assumption that each client requests only one data item at a time. With the rapid growth of time-critical information dissemination services in emerging applications, there is an increasing need for systems to support efficient processing of real-time multi-item requests. Little work, however, has been done. In this paper, we study the behavior of six representative single-item request based scheduling algorithms in time-critical multi-item request environments. The results show that the performance of all algorithms deteriorates when dealing with multi-item requests. We observe that data popularity, which is an effective factor to save bandwidth and improve performance in scheduling single-item requests, becomes a hindrance to performance in multi-item request environments. Most multi-item requests scheduled by these algorithms suffer from a starvation problem, which is the root of performance deterioration. Based on our analysis, a novel algorithm that considers both request popularity and request timing requirement is proposed. The performance results of our simulation study show that the proposed algorithm is superior to other classical algorithms under a variety of circumstances.