Worst-case delay analysis of Variable Bit-Rate flows in network-on-chip with aggregate scheduling

Jafari, Roozbeh; Jantsch, Axel; Lu, Jiwen

doi:10.1109/date.2012.6176457

Cited by 4 publications

(14 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The algorithm with all stages, including details of inter-router ESC step, is presented in Appendix. Now, we can obtain LUDB from end-to-end ESC according to the proposed theorem for calculating delay bounds [3]. We have automated our proposed analytical approach as a tool for worst-case performance analysis.…”

Section: B Inter-router Escmentioning

confidence: 99%

“…As depicted in the figure, T HoL (f1,r) is equal to the maximum delay for passing packets of flow f 2 in the buffer. According to [1], the maximum delay for flow f j is bounded by Equation (3).…”

Section: Fig 4 An Example Of Buffer Sharingmentioning

confidence: 99%

“…1) Delay Optimization: As mentioned before, decision variables in the proposed optimization problems are the weights on shared channels. Due to shared channels in VOPD application, 20 weights are formulated in the optimizations as a weight vector W defined as follows: W = w (6,3,0,4) , w (10,2,0,0) , w (14,0,0,2) , w (13,3,0,2) , w (12,0,0,2) , w (9,4,0,0) , w (4,3,0,4) , w (4,0,0,2) , w (8,2,0,0) , w (8,4,0,2) , w (6,2,0,4) , w (10,4,0,0) , w (14,3,0,2) , w (13,1,0,2) , w (12,3,0,2) , w (9,3,0,0) , w (4,0,0,4) , w (4,4,0,2) , w (8,…”

Section: A Vopd Applicationmentioning

confidence: 99%

“…Due to shared channels in the MMS application, weight vector W consisting of 37 weights is defined as below: W = w (16,1,0,0) , w (15,3,0,2) , w (15,0,0,2) , w (5,3,0,0) , w (14,4,0,2) , w (19,1,0,2) , w (18,4,0,2) , w (18,3,0,2) , w (13,2,0,4) , w (23,3,0,0) , w (14,1,0,4) , w (10,2,0,4) , w (1,0,0,4) , w (1,3,0,…”

Section: B Mutlimedia Applicationmentioning

confidence: 99%

“…Therefore, the first important consideration is to derive the LUDB for a given communication flow. To this end, based on the Network Calculus theory [1], we have presented and proved required theorems in [2] [3]. We then presented a methodology [4] to consider resource sharing scenarios and also derive end-toend Equivalent Service Curve (ESC) and LUDB by applying the proposed theorems.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Weighted Round Robin Configuration for Worst-Case Delay Optimization in Network-on-Chip

Jafari

Jantsch

2016

IEEE Trans. VLSI Syst.

View full text Add to dashboard Cite

Abstract-We propose an approach for computing the endto-end delay bound of individual variable bit-rate flows in a FIFO multiplexer with aggregate scheduling under Weighted Round Robin (WRR) policy. To this end, we use network calculus to derive per-flow end-to-end equivalent service curves employed for computing Least Upper Delay Bounds (LUDBs) of individual flows. Since real time applications are going to meet guaranteed services with lower delay bounds, we optimize weights in WRR policy to minimize LUDBs while satisfying performance constraints. We formulate two constrained delay optimization problems, namely, Minimize-Delay and Multiobjective optimization. Multi-objective optimization has both total delay bounds and their variance as minimization objectives. The proposed optimizations are solved using a genetic algorithm. A Video Object Plane Decoder (VOPD) case study exhibits 15.4% reduction of total worst-case delays and 40.3% reduction on the variance of delays when compared with round robin policy. The optimization algorithm has low run-time complexity, enabling quick exploration of large design spaces. We conclude that an appropriate weight allocation can be a valuable instrument for delay optimization in on-chip network designs.

show abstract

Section: B Inter-router Escmentioning

confidence: 99%

Section: Fig 4 An Example Of Buffer Sharingmentioning

confidence: 99%

Section: A Vopd Applicationmentioning

confidence: 99%

Section: B Mutlimedia Applicationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Weighted Round Robin Configuration for Worst-Case Delay Optimization in Network-on-Chip

Jafari

Jantsch

2016

IEEE Trans. VLSI Syst.

View full text Add to dashboard Cite

show abstract

Worst‐Case Analysis of Tandem Queueing Systems Using Network Calculus

Bouillard

Stea

2015

Quantitative Assessments of Distributed Systems

View full text Add to dashboard Cite

Exact Worst-Case Delay in FIFO-Multiplexing Feed-Forward Networks

Bouillard

Stea

2015

IEEE/ACM Trans. Networking

View full text Add to dashboard Cite

In this paper we compute the actual worst-case endto-end delay for a flow in a feed-forward network of FIFOmultiplexing service curve nodes, where flows are shaped by piecewise-affine concave arrival curves, and service curves are piecewise affine and convex. We show that the worst-case delay problem can be formulated as a mixed integer-linear programming problem, whose size grows exponentially with the number of nodes involved. Furthermore, we present approximate solution schemes to find upper and lower delay bounds on the worst-case delay. Both only require to solve just one linear programming problem, and yield bounds which are generally more accurate than those found in the previous work, which are computed under more restrictive assumptions.

show abstract

Worst-case delay analysis of Variable Bit-Rate flows in network-on-chip with aggregate scheduling

Cited by 4 publications

References 6 publications

Weighted Round Robin Configuration for Worst-Case Delay Optimization in Network-on-Chip

Weighted Round Robin Configuration for Worst-Case Delay Optimization in Network-on-Chip

Worst‐Case Analysis of Tandem Queueing Systems Using Network Calculus

Exact Worst-Case Delay in FIFO-Multiplexing Feed-Forward Networks

Contact Info

Product

Resources

About