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Now let s suppose that we have the system shown in Figure 26.5. The SYSTEM consists of PRODUCTS 1 and 2. PRODUCT 1, a large, complex design, consists of SUBSYSTEMs 1 and 2. PRODUCT 2, a simpler design, consists of hardware con guration item (HWCI) 21 and computer software con guration item (CSCI) 21. We apply the SE Process Model to each entity as illustrated by the boxes. Application of the SE Process Model to each entity continues until the SE design is mature and ready to commit to implementation. Figure 26.6 illustrates the state of the system design solution at completion. Here we see a multi-level framework that depicts the horizontal work ow progression over time. Vertically, the Requirements, Operations, Behavioral, and Physical Domain Solutions are decomposed into various levels of abstraction. Collectively the framework graphically illustrates a system, which by de nition, is the integration of multiple levels of capabilities to a higher level purpose that is greater than their individual capabilities.



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System Performance Specification (SPS)

(F,2) (G,2)

26

Where: Where: R = Requirements Solution Domain R = Requirements Solution Domain O = Operations Solution Domain O = Operations Solution Domain BB = Logical Solution Domain = Logical Solution Domain PP = Physical Solution domain = Physical Solution domain Requirements Allocation, Flow Down, & Linking





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for example, power-controlled MAC protocol (Section 11.3.1). Energy conservation gained in this approach is due to the reduction of transmit power to the minimum necessary power level for reliable transmission. Nodes in wireless ad hoc networks serve as relaying nodes for other nodes requiring communication. Therefore, the routing protocol will affect the energy consumption of nodes by next-hop node selection in the network. This motivates the design of energyaware routing, which aims to prolong the network lifetime or conserve energy for nodes. Generally, there are two categories, minimum energy routing and maximizing network lifetime routing. The former one intends to minimize the energy consumed for a single source-destination communication, and the latter one intends to extend the network lifetime by proper traf c distribution. Combined with transmission power control, energy-aware routing can further reduce the energy consumption of terminals. Power-ef cient topology control is another approach to reduce energy consumption. By choosing the transmit power carefully, the ad hoc network maintains a moderate connectivity, and it conserves energy with a lower power level. Inspired by the non-negligible energy consumption of nodes in idle mode in ad hoc networks, power management schemes are proposed to save energy wasted in idle mode. Nodes in network turn off their radio when there is no data to send or receive. In this section, we discuss the energy-oriented power control problem in terms of these issues. The main objective is to reduce energy consumption of nodes and prolong the lifetime of networks. Throughput and delay are second objectives in such approaches.

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However, using the JAD rules, project teams with the appropriate mix of business and technical people can come up with competent system designs every time A basic set of JAD ground rules is shown in the following list: Attendance of all team members is expected If any team member cannot be at a JAD session, then reschedule the session Check your baggage at the door Everyone has a stack of problems and personal issues Leave them out of the JAD session Start and end sessions on time Everyone is busy these days so treat the time spent in JAD sessions as valuable and respect people s schedules..

13 Requirements Allocation, 15

System System Performance Performance Specification Specification (SPS) (SPS) 5 PRODUCT PRODUCT Item Item Development Development Specification Specification

11.5.1 Energy-Aware Routing The rst generation of routing protocols in ad hoc networks are essentially minimum hop routing protocols (MHRP) that do not consider energy ef ciency as the main goal. While energy conservation becomes a major concern for the ad hoc network, many energy-aware routing algorithms have been proposed in recent years. Singh et al. [59] propose several metrics for energy-aware routing: r Minimize Energy Consumed/Packet. In this way, the total energy consumption of this network is minimized. However, it may cause some nodes to drain energy out faster since it tends to route packet around areas of congestion in the network. r Maximize Time to Network Partition. Given a network topology, there exists a minimal set of nodes, the removal of which will cause the network to partition. The routes between these two partitions must go through one of these critical nodes. A routing procedure therefore must divide traf c among these nodes to maximize the lifetime of the network. r Minimize Variance in Node Power Levels. The intuition behind this metric is that all nodes in the ad hoc network are of equal importance, and no node must be penalized more than any other nodes. This metric ensures that all the nodes in the network remain up and running together.

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