A robust and integrated Network and Element Management System cdma2000 NMS has been developed using state of the art computing technology to manage the third generation cdma2000 broadband wireless network. The architecture is based on open standards such as CORBA, SNMP, and Java, and the implementation has leveraged many commercial off-the-shelf (COTS) products and proven technologies. The cdma2000 NMS provides access to OA&M capabilities of cdma2000 network elements, including base station controller (BSC), base transceiver station (BTS), mobile switching center (MSC), interworking function (IWF) and selection distribution unit (SDU) with a unified, integrated and Web-enabled graphical presentation. It supports network topology, configuration management, fault management, and performance management. A common management information base is developed for cdma2000 network elements where a common SNMP agent framework is used based on the Ruby architecture (an internal Lucent effort to establish common, reusable architecture and software). The architecture adopts the semantics of the most popular TMN standards within the network elements. These concepts are being implemented as a SNMP management information base (MIB), i.e., for state management and alarm reporting. Interfaces to network elements or other operations support systems can also be achieved easily via CORBA.

Software systems typically contain design and code defects that manifest themselves as software failures at various points during program execution. These software faults can be viewed as causing failures to occur according to some chance mechanism that is often taken to be a Poisson process. Individual per-fault failure sequences (resulting from delayed fault detection and software correction) during test execution were analyzed to determine whether they satisfied Poisson process assumptions. The system analyzed, a large, complex, industrial software system, was executed under a defined operational profile corresponding to a controlled command and autonomous event mix characteristic of the system's actual usage. The failure events, defined as severe, system-wide affecting events attributed to software faults, typically occurred following many cycles of interacting system features in the expected user mode. Execution times between failure events were calculated and then statistically analyzed for conformance to Poisson process assumptions. The results indicated that first-time failure events conformed to the assumptions of a Poisson process and were consistent with a reliability growth Poisson model but that per-fault failure sequences attributed to specific faults tended to violate Poisson assumptions due to failure clustering.>