Real-time Broadcast System Research Articles

Design & Implementation of Real-Time Broadcast System of Urban Public Transport Crowding Index Based on the Internet of Things

Real-time broadcast system of public transport crowding index belongs to the broadcast system of urban public transport environment in ITS. The remaining seats and vehicle weight of the bus can effectively reflect the current crowding of public transport. This paper proposes a real-time broadcast system about the crowding index in public transport based on the Internet of things. The system can be divided into four submodules: wireless sensor network node, Sink node, terminal analysis and evaluation system and site display platform.Operating datas in public transport collected by wireless sensor networking node are sent to terminal analysis and evaluation system by GPRS wireless communication mode. This system can help people choose the best travel route. It may be helpful for managers to make a better traffic assignment.

Scheduling on-demand broadcast with timing constraints

In a distributed system, broadcasting is an efficient way to dispense data in certain highly dynamic environments. While there are several well-known on-line broadcast scheduling strategies that minimize wait time, there has been little research that considers on-demand broadcasting with timing constraints. One application which could benefit from a strategy for on-demand broadcast with timing constraints is a real-time database system. Scheduling strategies are needed in real-time databases that identify which data item to broadcast next in order to minimize missed deadlines. The scheduling decisions required in a real-time broadcast system allow the system to be modeled as a Markov Decision Process (MDP). In this paper, we analyze the MDP model and determine that finding an optimal solution is a hard problem in PSPACE. We propose a scheduling approach, called Aggregated Critical Requests (ACR), which is based on the MDP formulation and present two algorithms based on this approach. ACR is designed for timely delivery of data to clients in order to maximize the reward by minimizing the deadlines missed. Results from trace-driven experiments indicate the ACR approach provides a flexible strategy that can outperform existing strategies under a variety of factors.

Providing Data Items with Time Constraints in Multi-Channel Broadcasting Environments

In a mobile computing system, users carrying portable devices can access database services from any location without requiring a fixed position in the networking environment. Some examples of strategies supported by databases in mobile computing include location dependent queries, long-lived transactions that require migration of data into the portable devices, form-based transactions, and online information report. Within a mobile computing environment, the need for a realtime database management model is strong, because one of the basic requirements in mobile data management is to provide real-time response to transactions of the underlying strategies. However, the resource constraints of mobile computing systems make it difficult to satisfy timing requirements of supported strategies. Low bandwidth, unreliable wireless links, and frequent disconnections increase the overhead of communication between mobile hosts and fixed hosts of the system. There are many situations in which we need to incorporate real-time constraints in broadcasting systems for mobile environments. In this paper, we study broadcast scheduling strategies for pushbased broadcast with timing constraints in the form of deadlines. Unlike previously proposed scheduling algorithms for broadcast systems which aim to minimize the mean access time, our goal is to identify scheduling algorithms for broadcast systems that ensure requests meet their deadlines. We present a study of the performance of traditional real-time strategies and mobile broadcasting strategies, and demonstrate that traditional realtime algorithms do not always perform the best in a mobile environment. We propose a multichannel model based on pushbased real-time broadcast system and also provide an efficient scheduling algorithm, called dynamic adjustment with time constraint (DATC), which is designed for timely delivery of data to mobile clients.

Forward of Special Issue on “Mobile System, Agent Technology, and Web Services”

Forward of Special Issue on “Mobile System, Agent Technology, and Web Services”

Pull-based broadcasting with timing constraints

The rapid growth in wireless and mobile computing has resulted in an increase in applications that would benefit from a broadcast system that considers timing constraints. Previously proposed scheduling algorithms for broadcast systems aim to minimize the mean access time, while our goal in this paper is to identify scheduling algorithms for broadcast systems that ensure requests meet their deadlines. We consider a pull-based approach in which users send explicit requests for data to a server. There are several well-known scheduling algorithms for real-time systems in non-mobile environments, and previous work in real-time mobile systems has utilized these scheduling algorithms to minimize missed deadlines. However, we demonstrate that traditional real-time algorithms do not always perform the best in a mobile environment and may perform worse than some non-real-time strategies. In this paper, we present a model of a pull-based real-time broadcast system and an analysis of the system as a Markov decision process (MDP). We also propose an efficient scheduling algorithm, called aggregated critical requests-β (ACR-β), which is designed for timely delivery of data to mobile clients. Our results indicate that ACR-β outperforms existing algorithms when timing constraints and the benefits of broadcasting are considered.