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other landmarks and constructs a vector [(x1 , y1 , h1 ), . . . , (xn , yn , hn )], where xj and yj are the coordinates of landmark j and hj is the distance in hops from vi to vj (j = 1, . . . , n). Landmark vi calculates a value, called the correction, by cvi =

System Performance Specification (SPS)

35 34

(xj xi )2 + (yj yi )2

32 31

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business process or system It also provides a reliable way to estimate development times and budgets Benefits of the Define Design Build Process From the perspective of the CIO and other senior executives who sponsor a system development project, Define-Design-Build is a way to manage project risk In the Define phase small amounts of time and money are spent up front to qualify a business opportunity 5 10 percent of the total project cost If findings warrant, the enterprise then spends only a moderate amount of further time and money in design 15 30 percent of the total project cost In the Design phase, a small, prototype system is created to prove that the opportunity is real and justifies a larger investment The Build phase is where enterprises spend the most of the time and money 60 80 percent of the project total.

CSCI B22 Software Requirements Specification (SRS)





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whose numerator is the sum of Euclidian distances from vi to every other landmark and the denominator is the sum of the number of hops from vi to every other landmark. The ratio represents the average distance of a hop between landmark vi and any other landmark. In a second round of advertisements and controlled network ooding, each landmark vi communicates its correction value cvi to all other nodes. Corrections are collected by each nonlandmark node. For example, the correction for landmark v1 is cv1 = (6 2)2 + (2 5)2 + (5 2)2 + (4 5)2 = 1.04 4+3

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It is the average distance of one hop, according to landmark v1 . Each nonlandmark node ends up with a correction c, received from one of the landmarks. A distance estimate to every landmark is calculated. For every landmark i = 1, . . . , n, the distance is de ned as di = c hi where hi is the number of hops to landmark vi . For the nonlandmark node u, if c = c1 , then d1 = 1.04 2 = 2.08, d2 = 1.04 1 = 1.04, and d3 = 1.04 3 = 3.12. This algorithm has been improved by Langendoen and Reijers [17]. 2.4.4 Area Delimiting Methods The algorithm presented in this section aims at locating the position of nodes, but without examining features of radio signals received from localized nodes. The algorithm, however, assumes that there are a number of nodes that, at the beginning, know their location, either by con guration or by using the GPS. The bounding box algorithm is a method delimiting that area where a node yet to be localized is likely to be logically contained. The bounding box algorithm uses a grid model that divides the area in squares. Positions are given in reference to these squares, numbered using x and y indexes. Wireless communication ranges are also expressed as a number of squares. Hence, the coverage of a node can be expressed as a squared zone. The position of a node, whose location is initially unknown, can be bounded as the intersection of all the squared zones of its position aware neighbors. This information is obtained through advertisements. This procedure, called the bounding box algorithm, was proposed by Simic and Sastry [18]. We present the algorithm in details hereafter.

tions and permutations for every conceivable system in a single chart can be confusing and impractical. You, as a practicing Systems Engineer, need to employ your own mental skills to apply this concept to your own business domain, systems, and applications. Guidepost 25.4 The preceding discussions focused on the individual system design and SITE strategies. Next we integrate these strategies into a model.

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