## 2 Related Work
### Controllable Mobility Aided Routing Protocols  
Some traditional routing protocols proposed for mobile ad hoc networks (e.g., AODV [5], DSR [6], OLSR [7], LAR [22]) and energy-conserving protocols [23; 24] can be applied in MSNs [25]. However, those protocols do not consider controllable mobility as a network parameter when they determine the routes and forward data packets. In contrast, in this paper, our focus is on designing an ad hoc routing architecture that exploits the nodes' controllable mobility. There have been studies that considered controllable mobility in designing routing protocols for MSNs [10, 11, 15, 16]. These protocols first adopt existing multi-hop routing protocols to discover an initial path from a source node to a destination node. Then, nodes on the path except for the source node and the destination node are moved to the positions such that some specific objectives are achieved. For example, the study in [10] showed that the optimal configuration of node positions for energy efficiency can be achieved when all relay nodes are evenly spaced along a line connecting source and destination nodes. In [11], the optimum number of hops for minimizing total transmission power of the route from the source node and the destination node were investigated, and then a routing algorithm called optimal hop count routing (OHCR) was proposed, which is based on the calculated optimum number of hops. The authors further proposed another routing algorithm called MPoPR that minimizes transmission power over progress. After a route between source and destination nodes is discovered, the relay nodes on the route can be moved to their computed optimal positions directly or in rounds to minimize energy consumption. A controllable mobility based geographic routing, CoMNet, was proposed in [15]. CoMNet takes advantages of node mobility to improve routing energy consumption while ensuring network connectivity. Both of transmission cost and mobility cost are optimized in route establishment process. In [16], the nodes's position information was incorporated in the route discovery mechanism of AODV to build the path between source and destination nodes which minimizes the total traveling distance of relay nodes. After the best route is found, the relay nodes of route move to positions which are evenly spaced the straight line connecting source and destination nodes. However, those works differ from ours in that they assume that all nodes in the network are robotic agents, _i.e._, all movements of nodes are controllable. This assumption not only requires a high system cost, but also is not appropriate for applications considered in this paper where considerable number of sensor nodes are carried by unmanned vehicles or humans and cannot be controlled for routing purpose (e.g., search&rescue crew members and a group of unmanned vehicles for surveillance). Moreover, those works focus on minimizing energy consumption for communications. In contrast, maximizing throughput is the major objective of our work, which is important for network applications under consideration (e.g., high-rate sensing and multimedia communications). regular nodes may cooperate with other regular nodes in a given area to track a target, or perform a search&rescue, which leads to the group mobility. On the other hand, the self-propelled robotic node controls its movement based on network status in order to improve the network performance. Once a robotic node decides to move to a target position, it uses an equipped navigation system to travel. For simplicity, in this paper, it is assumed that a robotic node moves towards the target position on a straight line with a given speed. Obstacle avoidance while moving is not a targeted problem of this work, and for this problem existing navigation algorithms [26, 27, 28, 29, 30] can be considered. It is also assumed that mobile sensors are equipped with sensing devices and a video camera to collect information from the monitored area.