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One of the challenges of elded systems is failure to keep the As-Maintained con guration baseline current. This commonly occurs when budgets are reduced or priorities are focused on other activities. Unfortunately, some organizations have a view that if an activity doesn t help the bottom line or accomplish a mission, it must not be worth investing resources. So, MISSION SYSTEM Users and System Developers ask: Do we invest money in the actual system to get more capability or in maintaining system baselines in lock step Generally, the capability argument wins. As a result, there may be a discrepancy between the physical MISSION SYSTEM and its baselines. Once a system is developed, delivered, and accepted, a key question is: WHO maintains the product baseline for elded systems Systems often go through a series of major upgrades over their useful service life. Each improvement or upgrade may be performed internally or externally by a new System Developer contract. The challenge for User and Acquirer to ultimately answer is: HOW do we assure the developer that the baseline con guration documentation identically matches the improved or upgraded, As-Maintained system As a User SE, you will be expected to answer this question and vouch for the integrity of the As-Maintained Product Baseline. Maintaining the currency of the Product Baseline is important not only for the existing elded systems but also for future production runs. Some systems are elded in low quantities as trial runs to assess consumer feedback in the marketplace. After the initial trials, production contracts may be released for large quantities. Some markets may saturate quickly or, if your organization is lucky, enjoy system production over several years. These production runs may involve a single production contractor or multiple contractors; the baseline integrity challenges, however, are the same.



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Planning of next generation systems includes several focus areas: Focus Area 5: Perform and maintain a gap analysis. Focus Area 6: Bound and partition the problem and solution spaces. Focus Area 7: Formulate and develop new capability requirements.

Figure 7.6. Accuracy of the model to capture interactions. This graph shows the observed number of packet drops and the accuracy of the model in predicting these drops. (b) Effectiveness of scheduling formulation. This graph compares the throughput observed in simulation by (i) most stable routes predicted by DSR (ii) routes obtained from interference-aware formulation, and (iii) routes obtained from an interference- and scheduling-aware formulation. (Figure 7.6 represents the results presented in reference 31.)

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at every level of the project do not share and reflect this confidence. If people are trying to transfer onto the project, that indicates people have confidence it will succeed. If people are transferring off the project or leaving the company, that indicates people have no confidence and expect it to fail.

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As MISSION SYSTEM and SUPPORT SYSTEM data are collected and analyzed, a repository of knowledge is established. So, what do you do with all this data Despite its title, this could be simply a single page for management with a brief rationale depicting the current gap and gap projections over time. The OPERATING ENVIRONMENT element of most systems is often highly competitive and may range from benign or adversarial. Depending on the overall organizational mission, competitors and adversaries will continually improve and upgrade their system capabilities. Regardless of your organization s operating domain, the marketplace, military environment, space environment, and medical environment are dynamic and continually change in response to MISSION SYSTEM changes. For some systems survival or convenience means changing, either by necessity due to component or obsolescence accordance cost of maintenance, in accord with marketplace trends and demands. Thus, operational capability and performance gaps emerge between your existing system and those of competitors and adversaries. This in turn forces investment to improve existing system performance or develop new systems, products, and services.

MICS-based formulation to estimate the effect of the low-level interactions of the MAC protocol. The study also estimates the fraction of packet drops that occurs at each link due to ineffective handshake of the MAC protocol. Such a metric is similar to the ETX metric which captures the amount of packet losses. The integration of such MAC modeling with routing formulations provides a more accurate globally aware routing model and is a challenging and important research goal. Kolar and Abu-Ghazaleh [31] also performed a global scheduling and interference-aware (SIA) routing and measured the performance gains. SIA was implemented by rst getting the best route from the Interference-aware formulation (IA Routes) from the basic MCF linear program model [52]. Then, the packet losses at different links were estimated using the scheduling model discussed above. The links that had the highest con icts were mutually excluded by adding further constraints into the LP formulation; the extended model is then re-executed. These steps were repeated until the solution converged or the number of runs exceeded a predetermined threshold, at which time the best routes found are used. Figure 7.6b compares general IA routes proposed in reference 52 with SIA routes. The IA routes work on the Protocol model of interference which assumes a constant interference range. The performance is reported normalized to the performance of the traditional routes obtained using the best DSR routes. It can be seen that the SIA routes perform better than the IA routes. The effectiveness of the scheduling formulations can be seen in high contention areas; as described above in Figure 7.1 in Section 7.4.1, it is in that area that scheduling plays a higher role in determining link capacity. It can be seen in Figure 7.6b that SIA advantages are more pronounced under higher

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