Deciding which queue to join: Some counterexamples
Operations Research
Using name-based mappings to increase hit rates
IEEE/ACM Transactions on Networking (TON)
Source-level IP packet bursts: causes and effects
Proceedings of the 3rd ACM SIGCOMM conference on Internet measurement
Future processors: flexible and modular
CODES+ISSS '05 Proceedings of the 3rd IEEE/ACM/IFIP international conference on Hardware/software codesign and system synthesis
Load balancing for parallel forwarding
IEEE/ACM Transactions on Networking (TON)
A scalable load balancer for forwarding internet traffic: exploiting flow-level burstiness
Proceedings of the 2005 ACM symposium on Architecture for networking and communications systems
Sequence-preserving adaptive load balancers
Proceedings of the 2006 ACM/IEEE symposium on Architecture for networking and communications systems
Using Multi-Core Processors to Support Network Security Applications
FTDCS '08 Proceedings of the 2008 12th IEEE International Workshop on Future Trends of Distributed Computing Systems
Chip Multiprocessor Architecture: Techniques to Improve Throughput and Latency
Chip Multiprocessor Architecture: Techniques to Improve Throughput and Latency
The effect of packet reordering in a backbone link on application throughput
IEEE Network: The Magazine of Global Internetworking
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Load balancing is critical to the performance of parallel processing systems. It is more difficult for network systems such as NIDS and Web Servers, because they must preserve flow order. But traditional flow-based load balancing schemes of network parallel processing systems, such as LLF, cost much resource and introduce lots of communication overhead. With the rapid popularization of multi-core system, it is a good choice to apply NIDS in CMP architecture to achieve higher performance. Some companies have taken the first step. Their scheduling algorithm operates at a custom NIC based on FPGA technology. LLF algorithm can't be used in such environment because it needs much more memory than NIC owns. In this paper, we propose a scheduling scheme that remaps the new arrival flows when the system is unbalanced. To make effective adjustments we design a new triggering policy based on waiting lengths and their difference. Compared with LLF, our algorithm costs about 5% memory to get the same performance.