## 3 Review of Previous Works
### Active AP Configuration Algorithm for Dual Interfaces
#### 3.3.2 Algorithm Procedure  
The algorithm consists of three phases. The procedure is described as follows:  
1. _First Phase:_ The first phase of the algorithm selects the active APs with the _dual interface_ and their host associations to minimize \(E_{1}\) and maximize \(E_{2}\)[33]. 1. **Preprocessing:** Initially, the APs and the hosts locations are used as inputs of the algorithm. The AP locations are selected manually in the network, taking into account the electrical power supply, the coverage, and user demands. The throughput is estimated using the _throughput estimation model_ in Equation (3) for every possible pair of AP and host. In addition, the 11n interface of an AP is chosen as the initial candidate one for any host. 2. **Initial Solution Generation:**_Greedy algorithm_ is adopted to calculate the initial solution \(E_{1}\)[51]. 3. **Host Association Improvement:** The minimum host throughput and the overall throughput in the network are improved by randomly changing the host association according to the procedure in [22]. 4. **AP Selection Optimization:** This phase optimizes the selection of number of active dual interfaces APs and the AP-host associations in order to further minimize both \(E_{1}\) and \(E_{2}\) using the _local search method_[52]. 5. **Link Speed Normalization:** The fairness criterion will be used if the total expected bandwidth is greater than \(B^{a}\). Next, the speed of the link has been normalized. 6. **Termination Check:** If either of the two interfaces for each current AP is not activated, then activate the interface and apply the _host association improvement_ phase. After that, the algorithm will be terminated and proceed to phase 2 if the minimum throughput constraint of the host is satisfied. If not, proceed to the _AP selection optimization_ phase. 2. _Second Phase:_ The second phase assigns a channel to each active AP interface to minimize \(E_{3}\)[22].  
**Preprocessing:** The interference and delay conditions of the network are illustrated by a graph.  
**Interfered AP Set Generation:** The set of interfering AP interfaces is found for each AP interface.  
**Initial Solution Construction:**_The greedy algorithm_ is adopted to calculate the the initial solution.  
**Solution Improvement by Simulated Annealing:** Simulated annealing (SA) is the probabilistic optimization technique that can be used to improve the solution by gradually adjusting the solution over time. In our proposal, the SA is used to optimize the channel assignment for each interface of every active AP to improve the performance of the network. The SA procedure is used with the constant _temperature_\(T^{SA}\) for the _repeating times_\(R^{SA}\), where \(T^{SA}\) and \(R^{SA}\) are given as the algorithm parameters.  
**Third Phase:** The third phase averages the loads among the different channels in order to minimize \(E_{3}\)[22].  
**Initialization:** The AP flag is initialized with \(0(=OFF)\) in every AP. This flag is used to prevent the re-processing of the same AP again.  
**AP Selection:** One OFF flag AP is chosen to move its associated host to a different AP to which a different channel is assigned.  
**Host Selection:** One associated host with the selected AP is selected to perform the AP movement.  
**Change Application:** Finally, the new associated AP is selected for that host.