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更新时间:2010-3-9:  来源:毕业论文
智能电表集中抄表系统入户子系统 第6页
Object technology has been extensively used in the design and subsequent implementation of all the constituent subsystems described in this paper. The steps of meta-class abstraction have been applied at all stages in the continuing life cycle of the system’s architectural framework. This has been particularly true of the early stages of the framework. It has subsequently been found that building systems in this way enables the inevitable change in customer requirements to be rapidly and effectively addressed.
8. Conclusions
In conclusion, it can be seen that new methods and approaches to software development can dramatically reform important aspects of network planning and
management. PC power and the rapid development of PC-based, modular software tools, sharing core data with larger systems, is a quick and effective way to improve planning productivity. Productivity increases by a factor of between 10 and 200 have been achieved from ‘smart’ PC-based tools developed relatively quickly and cheaply within BT. Such tools also allow the simultaneous consideration of all the elements of ‘total’ network performance, and optimal balances of function, reliability and cost can be achieved using advanced optimisation techniques. The relatively low cost and high speed of development of these tools calls into question the need for extensive re-engineering analyses of existing processes, where the danger is ‘paralysis by analysis’, and challenges the cost-efficiency of ‘big systems’. It is often more effective to rapidly synthesise a new automated process, by developing a small application and testing its effect, before moving on to treat the next obvious productivity problem.
If the key requirements of modularity and data-sharing are adhered to, the result will be a cohesive set of network planning tools, offering massive planning productivity improvements, the better integration of network planning and management, and the guarantee of optimally designed, high-performance networks.
Acknowledgements
The authors would  like to thank Danny Poon and John Tindle (Sunderland University) and Steve Brewis, Tony Conway and Colin Birchenall (BT) for their collaborative efforts which assisted the delivery of the GenOSys planning tool. The efforts of the GenOSys, TASC and BECS build teams are also appreciated.
References
1 Adams E K and Willetts K J: ‘The lean communications provider’, McGraw-Hill (1996).
2 Mellis J: ‘Systematic approaches to network infrastructure planning and performance modelling’, BT Technol J, 14, No 2, pp 87—94 (April 1996).
3 Mellis J: ‘Plant and people: the influence of human factors in telecommunications network performance’, Telektronikk,  93,  1, pp 128—135 (1997)
4 Redstall R M, Mardani R and Mellis J: ‘OMNI — an object-based model of the access network infrastructure’, BT Technol J, 14, No 2, pp 95—100 (April 1996).
5 Tindle J, Brewis S J and Ryan H M: ‘Advanced simulation and optimisation of the telecommunications network’, BT Technol J,  14, No 2, pp 140—146 (April 1996).
6 Paul H and Tindle J: ‘Passive optical network planning,’ BT Technol J, 14, No 2, pp 110—115  (April 1996).
7 Goldberg D E: ‘Genetic algorithms in search, optimization and machine learning’, Addison-Wesley Publishing Co,  pp 59—122 (1989).
8 BT: ‘Access Narrowband Greenfield Planning Rules’, internal document (1997).

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