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Pipelined heap (priority queue) management for advanced scheduling in high-speed networks
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Source IEEE/ACM Transactions on Networking (TON) archive
Volume 15 ,  Issue 2  (April 2007) table of contents
Pages: 450 - 461  
Year of Publication: 2007
ISSN:1063-6692
Authors
Aggelos Ioannou  Computer Architecture and VLSI Systems Laboratory, Institute of Computer Science, Foundation for Research and Technology-Hellas (FORTH), Heraklion, Crete, GR, Greece and Department of Computer Science, University of Crete, Greece
Manolis G. H. Katevenis  Computer Architecture and VLSI Systems Laboratory, Institute of Computer Science, Foundation for Research and Technology-Hellas (FORTH), Heraklion, Crete, GR, Greece and Department of Computer Science, University of Crete, Greece
Publisher
IEEE Press  Piscataway, NJ, USA
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Downloads (6 Weeks): 9,   Downloads (12 Months): 83,   Citation Count: 3
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DOI Bookmark: 10.1109/TNET.2007.892882

ABSTRACT

Per-flow queueing with sophisticated scheduling is one of the methods for providing advanced quality of service (QoS) guarantees. The hardest and most interesting scheduling algorithms rely on a common computational primitive, implemented via priority queues. To support such scheduling for a large number of flows at OC-192 (10 Gb/s) rates and beyond, pipelined management of the priority queue is needed. Large priority queues can be built using either calendar queues or heap data structures; heaps feature smaller silicon area than calendar queues. We present heap management algorithms that can be gracefully pipelined; they constitute modifications of the traditional ones. We discuss how to use pipelined heap managers in switches and routers and their cost-performance tradeoffs. The design can be configured to any heap size, and, using 2-port 4-wide SRAMs, it can support initiating a new operation on every clock cycle, except that an insert operation or one idle (bubble) cycle is needed between two successive delete operations. We present a pipelined heap manager implemented in synthesizable Verilog form, as a core integratable into ASICs, along with cost and performance analysis information. For a 16 K entry example in 0.13-µm CMOS technology, silicon area is below 10 mm2 (less than 8% of a typical ASIC chip) and performance is a few hundred million operations per second. We have verified our design by simulating it against three heap models of varying abstraction.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Aggelos Ioannou: colleagues
Manolis G. H. Katevenis: colleagues