MEM for Arbitrary Exponential Open Networks with Blocking and Multiple Job Classes
7th UK Computer and Telecommunications Performance Engineering Workshop
An Approximate Method for Performance Evaluation of Asynchronous Pipeline Rings
CIT '06 Proceedings of the Sixth IEEE International Conference on Computer and Information Technology
Journal of Systems Architecture: the EUROMICRO Journal
Wireless sensor network survey
Computer Networks: The International Journal of Computer and Telecommunications Networking
FCCM '08 Proceedings of the 2008 16th International Symposium on Field-Programmable Custom Computing Machines
Higher-order distributional properties in closed queueing networks
Performance Evaluation
Performance optimization of open zero-buffer multi-server queueing networks
Computers and Operations Research
Interconnection alternatives for hierarchical monitoring communication in parallel SoCs
Microprocessors & Microsystems
Opportunistic MAC layer design with stochastic Petri Nets for multimedia ad hoc networks
Concurrency and Computation: Practice & Experience - Performance Evaluation of Communications in Distributed Systems and Web-Based Service Architectures
Hybrid dynamic energy and thermal management in heterogeneous embedded multiprocessor SoCs
Proceedings of the 2010 Asia and South Pacific Design Automation Conference
CIT '10 Proceedings of the 2010 10th IEEE International Conference on Computer and Information Technology
Journal of Signal Processing Systems
IEEE Communications Magazine
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Embedded devices have gradually increased the demand for computing performance. In recent years, researches have focused on ways to maximize the performance of embedded multi-core SoC when the hardware consumption is very limited. This paper presents a new queueing network model and performance analysis method for embedded multi-core SoC based on task handling mechanism with priority. To calculate the blocking probability and queueing situation of the implementation for every executing core, finite capacity holding nodes are added to the queueing model, and an equivalent queueing network model is obtained. An adaptive load scheduling algorithm is designed, and the main scheduler is real-time scheduling by blocking and queueing the situation of each core. Common priority FIFO buffer, high-priority FIFO buffer queue, and semi-global FIFO buffer queue are a reasonable distribution. Finally, the approximate iterative algorithm is proposed for evaluating system performance. The experimental results indicate that the adaptive scheduling algorithm significantly improves the balance of task assignment.