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Software defined networking (SDN) is used to provide as a centralized control with a flexible and scalable network. Also, SDN is provisioned for the communication systems of the next generation. OpenFlow is treated as a leading standard that defines the interface between the control plane and the physical network (data plane). Formaintaining the flexibility for the various network applications, software...
Neural networks are widely used in various fields due to their superior learning ability. Concurrent with the increase in their popularity, the rise of Big Data has resulted in increased computational requirements and processing power. To meet the requirements of real-time learning and classification, the process of finding the maximum value proves to be the performance bottleneck, and therefore needs...
OpenFlow, the main protocol for software-defined networking (SDN) advocated by Google, requires multiple flow tables with long and variable rule lengths. For fast packet forwarding, using ternary content-addressable memory (TCAM) as implementation of lookup-table has displayed superior performance in executing the conventional packet classification algorithms. However, applying traditional TCAM designs...
Ternary Content Addressable Memory (TCAM) provides superior table-lookup performance to the conventional search algorithms. However, as word length increases, large-sized TCAM suffers from high power consumption and throughput degradation. This paper presents filter-based dual voltage architecture for long-word TCAM. Without sacrificing throughput and noise immunity, the proposed filter-based dual...
To fit into multiple communication standards, flexible Low-Density Parity-Check (LDPC) decoding is desirable to be implemented in a chip multiprocessor (CMP) system. However, reliability issues, such as soft errors and timing errors, are severer in future advanced CMP systems when CMOS technology scale. Therefore, enhancing error resilience for a CMP system becomes an important design issue. In this...
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