# Swarm Intelligence Techniques for Mobile Wireless Charging
## 2 Related Works and Comparison
### Energy Provisioning Using MCs in WRSNs  
Recently, the field of wireless rechargeable sensor networks (WRSNs) has witnessed many significant research efforts using a single MC. In [34], authors relied on Powercast technology to prolong the network lifetime of a WSN by constructing a wireless charging queue built on the greedy algorithm. The charging behavior of the MC is considered greedy, since the MC maintains the continuous charging of a sensor-node for a long time before charging another sensor-node. The authors studied the charging problem and proposed several heuristic algorithms to plan the charging activities for the MC (i.e., to determine the sequence of nodes to be charged and the amount of energy to be delivered to the sensor-nodes). This approach exploited a single MC, a robot which is used to deliver energy to where it is needed. Hence, the authors built a proof-of-concept prototype and conducted experiments to evaluate its feasibility and performance in small-scale networks. In [35; 36], the authors proposed a single mobile charging vehicle that periodically visits the network and wirelessly replenishes every sensor-node in the network based on a near-optimal solution. The authors capitalized on the recent breakthrough in wireless energy transfer technology and proposed a scenario where a single mobile charging vehicle periodically visits the network to wirelessly charge each sensor-node. They studied a practical optimization problem, with the aim of maximizing the ratio of the wireless charging vehicle (WCV)'s vacation time over the cycle time, and subsequently, developed a provable near-optimal solution for flow routing, the total cycle time, and the individual charging time at each node. Their numerical results showed that a sensor network operating under their solution could remain operational for a long time. The authors in [37] studied the problem of maximizing the network lifetime of a single MC (subject to the energy capacity of the MC) and designed a heuristic algorithm, called FACT, to address the problem. Their work focused on locating closed charging tours for the MC, as well as designing an energy allocation scheme for the MC in a way that maximized the minimum battery energy of all the sensor-nodes after charging. However, the above techniques exploring a single MC have scalability problems in the way that the techniques are limited in the context of LS-WSNs containing thousands of sensor-nodes. The single-charger technique will not be sustainable for LS-WSN scenarios, since the single MC will require a high amount of movement energy to traverse the whole network and it would have depleted its energy before completing its tour of the network. The implication is that several sensor-nodes will be left energy-hungry, thus leading to high node death rates and, consequently, resulting in a network operational breakdown. This is because a single MC has a limited amount of energy that it can provide, which is not feasible in a highly dense network environment. A single MC may not have enough energy to recharge all the sensor-nodes in a large-scale network scenario on a single tour. On the contrary, the use of multiple MCs will undoubtedly handle this problem and will optimize the energy efficiency of the network. Based on the scalability problem with a single MC in a LS-WSN scenario, the authors in [38; 39] investigated the minimum MC problem (i.e., the number of energy-constrained MCs for rechargeable sensor networks to keep every sensor-node working continuously). The authors in [38] approached the problem firstly by proving its computational hardness and then by proposing the use of approximation algorithms, with proven performance bounds, to address the minimum MCs problem. Conversely, the authors in [39] divided the minimum MCs problem into two _N-P_ hard sub-problems: a Tour Construction Problem (TCP) and a Tour Assignment Problem (TAP). They considered a two-step solution to the problem.