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Radiation particles can impact registers or memories creating soft errors. These errors can modify more than one bit causing a Multiple Cell Upset (MCU) which consists of errors in registers or memory cells physically close. These MCUs can affect a single word, producing adjacent bit errors. Hamming codes are commonly used to protect memories or registers from soft errors. However, when multiple errors occur a Hamming code may not detect them. In this letter, Single Error Correction Double Adjacent Error Detection (SEC-DAED) Hamming codes are presented for 16, 32 and 64-bit words. Additionally, Single Error Correction Double Error Detection Triple Adjacent Error Detection (SEC-DED-TAED) codes based on Extended Hamming are presented as well. The enhanced detection is achieved by performing a selective shortening and reordering of the Hamming matrix so adjacent errors result in a syndrome that does not match that of any single error. These codes will help in the detection of MCUs in SRAM memory designs.

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Hamming codes that can correct one error per word are widely used to protect memories or registers from soft errors. As technology scales, radiation particles that create soft errors are more likely to affect more than 1 b when they impact a memory or electronic circuit. This effect is known as a multiple cell upset (MCU), and the registers or memory cells affected by an MCU are physically close. To avoid an MCU from causing more than one error in a given word, interleaving is commonly used in memories. With interleaving, cells that belong to the same logical word are placed apart such that an MCU affects multiple bits but on different words. However, interleaving increases the complexity of the memory device and is not suitable for small memories or content-addressable memories. When interleaving is not used, MCUs can cause multiple errors in a word that may not even be detected by a Hamming code. In this paper, a technique to increase the probability of detecting double and triple adjacent errors when Hamming codes are used is presented. The enhanced detection is achieved by placing the bits of the word such that adjacent errors result in a syndrome that does not match that of any single error. Double and triple adjacent errors are precisely the types of errors that an MCU would likely cause, and therefore, the proposed scheme will be useful to provide error detection for MCUs in memory designs.

Abstract. The goal of ontology-based management is to improve the manageability of network resources through the application of formal ontologies. Prior research work has studied their application to represent the management information definitions, the mapping and merging processes to obtain a semantic integration of those definitions, and the representation of behaviour and policy definitions. Using ontologies allows the additional advantage of integrating, in the same semantic manager, business and service level ontologies with the network management ontology, in a framework for automated management. This integration allows for policy refinement and interoperation between high level policies and low level policies.