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Another interesting result is that MAC layer is insensitivity to the choice of routes; that is, the optimal MAC protocol does not depend on the choice of routes Bhatia and Kodialam [15] consider the joint scheduling, routing, and power control design for power-ef cient communication in wireless multihop networks The overall problem is formulated as an optimization problem with nonlinear objective function and nonlinear constraints, and the derived solution is a performance-guaranteed polynomial time approximation algorithm for jointly solving these three problems The authors rst consider the joint scheduling and power control problem under given ow rates and xed routes They assume the Additive White Gaussian Noise (AWGN) channel in the physical layer, and rate-power function is R = W log2 (1 + NPW ) Thus, 0 the joint scheduling and power control problem is also the problem of joint scheduling and rate adaptation.



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Although we have not covered it in this chapter, some programs begin work from a very abstract Statement of Objectives (SOO) rather than an SPS. Where this is the case, spiral development is employed to reiterate the V-Model for incremental builds intended to mature knowledge about the SYSTEM requirements. We will discuss this topic in 27 on system development Models.





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In summary, the preceding discussions provide the basis with which to establish the guiding principles that govern system design, integration, and veri cation strategy practices. Principle 25.1 System design is a highly iterative, collaborative, and multi-level process with each level dependent on maturation of higher level speci cation and design decisions. Principle 25.2 A system design solution is not contractually complete until it is veri ed as compliant with its Acquirer approved System Performance Speci cation (SPS). Technically it is not complete until all latent defects are removed, but most systems exist between these two extremes. Principle 25.3 The number of latent defects in the elded system is a function of the thoroughness of the effort time and resources spent on system integration, test, and evaluation (SITE).

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First they get the minimum power levels and data rates required to support the ow rates However, this does not guarantee that we will nd a link schedule to satisfy the obtained solution Thus, a scale factor is computed to scale-up the data rates, in order to nd a schedule that support the given ow rate Therefore, the algorithm is a near-optimal approximation algorithm that consumes more energy, and the authors prove that they can approximate the optimal solution by a factor of 3 By appropriate transformation of the original optimization problem, the original problem can be transformed into a Quadratically Constrained Programming problem [56] with only ow rates as the optimization variables The transformed problem can be solved in polynomial time for example, using the interior point method.

During our discussion of the system design, integration, and veri cation strategy, we described the SE design strategy that analyzes, allocates, and ows down System Performance Speci cation (SPS) requirements through multiple levels of abstraction to various item development speci cations and item architectural designs. Next we described a strategy for integrating each of the procured or developed items into successively higher levels of integration. At each level each item s capabilities and levels of performance are to be veri ed against their respective speci cations. 1. The SE process strategy provides a multi-level model for allocating and owing down SPS requirements to lower levels of abstraction. 2. Unlike the Waterfall Model, the SE Process strategy accommodates simultaneous, multi-level design activities including Preliminary Design activities. 3. Whereas a design at any level may be formally baselined to promote stability for lower level decision making, a design at any level is still subject to formal change management modi cation through the end of formal acceptance for delivery. 4. The SE design strategy includes multiple control points to verify and validate decisions prior to commitment to the next level of design activities. 5. The SITE Process implements a strategy that enables us to integrate and verify lower level components into successively higher levels until the system is fully assembled and veri ed. 6. The SITE Process strategy includes breakout points to implement corrective actions that often lead back to the SE Design Process. 7. Corrective actions may require revision of lower level speci cations, redesign, rework of components, or retraining of test operators to correct for design aws and errors, de ciencies, discrepancies, etc.

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8. The integration of the System Design Process and SITE Process strategies produces what we refer to as the V-Model of system development. 9. The V-Model, which represents a common model used on many programs, may be performed numerous times, especially in situations such as spiral development to evolve requirements to maturity.

The authors also propose an iterative algorithm based on the Frank Wolfe method [57], which is ef cient in practice and has the nice property that it can be computed in distributed way In each iteration, the optimal routing policy is shortest path routing..

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