POWER CONTROL: THE ENERGY-ORIENTED PERSPECTIVE in .NET framework

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POWER CONTROL: THE ENERGY-ORIENTED PERSPECTIVE
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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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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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POWER CONTROL PROTOCOLS FOR WIRELESS AD HOC NETWORKS
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r Minimize Cost/Packet. In order to maximize the lifetime of all nodes in the network, metrics other than energy consumed/packet need to be used. The paths selected when using these metrics should be such that nodes with depleted energy reserves do not lie on many paths. r Minimize Maximum Node Cost. This metric ensures that node failure is delayed. Unfortunately, there is no way to implement this metric directly in a routing protocol. However, minimizing the cost/node does signi cantly reduce the maximum node cost in the network. The early energy-aware routing algorithms are based on shortest path algorithms. Instead of using delay or hop counts as the link metrics, energy-oriented link metrics such as signal strength [60], battery energy level at each node [61, 62], power level [63 65], and energy consumption per transmission [9, 66] are used in these algorithms. The link condition and power level of nodes are exchanged periodically in order to keep these metrics up-to-date. In this way, energy consumption for routes can be minimized. However, certain nodes in the network may drain energy out faster than other nodes since these nodes may lie on many paths. Therefore, energy consumption must be balanced among nodes to increase network lifetime. Chang and Tassiulas [16, 17] formulate the problem of maximizing the lifetime of network as a linear programming problem. By solving the optimization problem, the network lifetime can be maximized. However, the optimal solutions either are not distributed or induce signi cant computational and communication overhead. Chang and Tassiulas [17] also propose a heuristic based on shortest path routing. The link cost is proportional to the energy consumed per packet and is inversely proportional to the normalized resident battery energy at sender and receiver. The battery status of nodes should be broadcast periodically in order to keep the link cost up-to-date. Simulation results show that the heuristic can approximate the maximum network lifetime if the frequency of information update is large enough. Zussman and Segall [18] formulate the energy-ef cient anycast problem that follows the method in references 16 and 17, and they propose an iterative algorithm to obtain the optimal solution. The energy-aware routing algorithms discussed above do not directly interact with power control, although power control is always used in the MAC layer to further reduce the energy consumption by decreasing the transmission power. An alternative is to incorporate power control directly into routing algorithm [64, 65]. This method requires that each source can put the transmit power level PTX at a suitable format eld in the transmitted packet. It also requires that the radio transceiver can measure the received signal strength PRX . With these two values, the node that received the packet can estimate the link attenuation. Upon the received signal power, the node can adjust its transmit power to the remote node by PTX = PTX PRX + SR + Secth Here SR is the minimum power level required for correct packet reception, and Secth is a power margin introduced to take into account channel and interference
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