## 2 Literature Review
### Routing for Mobile Agent  
One of the most critical problems to solve in mobile-based applications is the migration path of mobile agents, that is, the choice of routing. For instance, network management may involve frequent operations by multiple mobile agents. Each mobile agent moves through the network on a designated path to collect information for further processing. The agent returns the result to the management station so that it can follow up. If the mobile agent selects a bad traverse order, this affects the operational efficiency, increases the system response time, increases network traffic, and even leads to operational abnormalities. While advances in sensor technology have made it possible to achieve a \"quantity-to-mass\" by using large numbers of inexpensive compact sensors in very complex situations, we must apply new computing technologies to meet the theoretical and methodological challenges. Communication requires consumption of limited energy available in sensor nodes, while large numbers of sensors often have different forms of data. Selecting only the most needed information becomes key. [PERSON] (2016) proposed mobile agent-based distributed sensor networks distributed to leaf nodes. The purpose reducing network resource consumption (mainly bandwidth) and risk of intentional monitoring by enemies. In this network configuration, the processing unit dispatches mobile agents with executable data synthesis instructions. The mobile agents selectively access leaf node sensors along the specified path and progressively fuse the data. Sensor nodes, also called leaf nodes, are the basic data collection units in mobile agent routing sensor networks ([PERSON], 2016). Sensor nodes have several channels, and multiple sensors connect to them. Base stations send sensor nodes to collect diverse types of measurement data in the external environment, such as sound, vibrating, and infrared. The sampling subsystem controls data acquisition and transfers collected data to the main system for processing. Nodes detect the signals energy in each channel individually and process data at the analog front end. Mobile agents move between sensor nodes in the network, sequentially integrate the local data with the desired resolution, and send the result to the first processing unit. Due to intermittent failures or energy-saving considerations, some sensor nodes may be off or dormant, to be re-awakened when necessary. The sensor finds its longitude and latitude from its Global Position System (GPS) module. The embedded Radio Frequency (RF) modem in sensor nodes reduce network energy requirements (Sensor, 2016). Different clusters select different network members to avoid interference. The message transmission relies not only on the physical distance between two sensor nodes, but also on communication bandwidth, data packet loss rate, and length of the transmitted message (including partially integrated data and mobile proxy code). Figure 5 shows a simple configuration of a sensor network based on mobile agents. The network has a processing unit, denoted as \(s_{0}\), with \(N=10\) leaf nodes, denoted as \(s_{j}\), and \(i=1,\ 2,\ldots N\), one of them closed. The sensor node space travels in a monitoring area, and each node collects measurement data in the environment. The sensor node \(s_{j}\) detects the signal energy expressed by \(e_{i}\), and \(i=1,\ 2,\ldots N\). The time taken by the sensor node \(s_{i}\) to collect data is \(t_{i,acq}\), and the time consumed by the processing data is \(t_{i,proc}\). The signal bandwidth of the wireless communication link with distance \(d_{i,j}\) between sensor nodes \(s_{i}\) and \(s_{j}\) is W bit and the operating frequency is \(d_{i,j}\) Hz. Due to intermittent errors, some sensor nodes may be temporarily off, such as the sensor \(s_{9}\) in the figure. The purpose of the route is to find a path for the mobile agent that satisfies the required detection accuracy with minimal energy consumption and path loss.