# Matching of Energy Provisions in Multihop Wireless Infra-Structures
## 2 Related Work  
Energy efficiency in wireless networks has attracted many studies. There is an extensive body of research on energy efficient networking and communication in wireless networks, including energy efficient radio and devices [16; 20; 21], MAC protocols and sleep control [22; 23], routing, clustering and data aggregations [14; 15; 17; 18; 24], as well as transport control [25; 26], and local recovery mechanism [27; 28; 29]. In these works, local energy efficiency at nodes and routes are typically considered. The energy sources and supplies are typically uniform for nodes in a network. Energy charging and supply methods for networks with green energy supplies have been studied in [7; 8]. Reference [8] has modelled an energy buffer as a \(G/G/1/\infty\) queue and a \(G/G/1/N\) queue. Based on the model, an resource management scheme is proposed to balance traffic load across the mesh network. A solar powered WLAN mesh network is introduced in [7]. With a target of minimizing the enough resource allocation to the solar-powered WLAN, Genetic Algorithm (GA)-based resource assignment is utilized based on the information of input load profile, and historical solar radiation data. These studies focus more on energy resource management at individual nodes than the global combination of energy resource in the networks. Prolonging network lifetime has been extensively studied in data centric sensor networks. The methods include energy aware routing, energy efficient MAC, relay nodes deployments, and clustering, [12; 15; 18; 19; 22; 30]. On the other hand, these methods mainly rely on special features in sensor networks such as aggregation of small sensing data, and low cost nodes. A minimum cost node and energy deployment scheme for heterogeneous sensor networks with a lifetime constraint is proposed in [31]. The study considered a heterogeneous sensor network that has three components: sensors, cluster heads, and aircraft sinks. To ensure a certain data collection cycle by aircraft, sensors and cluster heads are designed with minimum cost using efficient node deployment parameters for density and energy of sensor and cluster head nodes. A joint approach of energy provision and node placement for sensor networks is introduced in [32]. This paper has a target of prolonging network lifetime. It considers a sensor network that allows hierarchical nodes types, such as sensor nodes, fixed relay nodes, freely deployed relay nodes. Furthermore, more energy can be provided to relay nodes. Based on this network structure, the paper proposed optimal relay node placement and energy provision with linear programming. The approach enables best position setting for freely deployable relay nodes, resulting in long network lifetime. An energy aware provision scheme in a solar powered WLAN mesh network is introduced in [7]. This paper has a target of minimizing the enough resource allocation in a wireless mesh network that has a sustainable energy support system with solar panel, charge controller, and battery. Based on the information of input load profile, and historical solar radiation data, a GA algorithm is proposed to optimize the resource assignment. A lifetime optimization scheme using variable batteries in sensor networks is introduced in [33]. This paper has a target of achieving long network lifetime by counterbalancing of non-uniform energy consumption. The sensor network has a basic application of sensor data dissemination and data gathering at a sink node. With a focus on ring area sensor network topology, the paper proposed two deployment approaches. In the first approach, battery capacity at sensor nodes are variably allocated according to the estimated energy consumption based on the number of sensing data transmitted and received at nodes in the ring regions. The second approach is based on non-uniform node deployment in different ring regions. Summarizing, the related studies mentioned above make progress in the analysis of resource optimization in wireless networks.