In this paper, we aim to find a robust network formation strategy that can adaptively evolve the network topology against network dynamics in a distributed manner. We consider a network coding deployed wireless ad hoc network where source nodes are connected to terminal nodes with the help of intermediate nodes. We show that mixing operations in network coding can induce packet anonymity that allows the inter-connections in a network to be decoupled. This enables each intermediate node to consider complex network inter-connections as a node-environment interaction such that the Markov decision process (MDP) can be employed at each intermediate node. The optimal policy that can be obtained by solving the MDP provides each node with optimal amount of changes in transmission range given network dynamics (e.g., the number of nodes in the range and channel condition). Hence, the network can be adaptively and optimally evolved by responding to the network dynamics. The proposed strategy is used to maximize long-term utility, which is achieved by considering both current network conditions and future network dynamics. We define the utility of an action to include network throughput gain and the cost of transmission power. We show that the resulting network of the proposed strategy eventually converges to stationary networks, which maintain the states of the nodes. Moreover, we propose to determine initial transmission ranges and initial network topology that can expedite the convergence of the proposed algorithm. Our simulation results confirm that the proposed strategy builds a network which adaptively changes its topology in the presence of network dynamics. Moreover, the proposed strategy outperforms existing strategies in terms of system goodput and successful connectivity ratio.
Network formation strategies for dynamic network conditions in conventional routing schemes have been widely studied in the context of a self-organizing network. Protocols for self-organization of wireless sensor networks where there exists a large number of static nodes with energy constraints are described in @cite_26 . @cite_39 , an emergency communication system based on UAV-assisted self-organizing network is considered. In this work, UAVs are used as a strong relay node to form a relay network in the air, and the nodes on the ground formed a self-organizing network automatically with the help of UAVs. @cite_3 , a dynamic topology control that prolongs the lifetime of a wireless sensor network is proposed based on a non-cooperative game.
@cite_26 @cite_3 @cite_39
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Emergency Communication System (ECS) becomes more and more important for certain emergency situations such as the affected mountainous areas, temporary battlefield, or filed of fire. Self-organizing network is proverbially adopted by ECS due to its flexible and robust architecture. However, the moving range and mode of mobile node in self-organizing network, especially mobile gateway, constrain the coverage and adaptability of self-organizing network in ECS. In this paper, we design an ECS based on UAV-assisted self-organizing network, which helps nodes on the ground form a self-organizing network automatically. In addition, the system adopts UAV as strong relay nodes to form relay network in the air. We also add some humanized functions in the system to adapt to the needs of different environment, which includes positioning and messages pushing service. The proposed ECS can be easily deployed in the emergency environment and owes high communication efficiency. We present a suite of algorithms for self-organization of wireless sensor networks in which there is a scalably large number of mainly static nodes with highly constrained energy resources. The protocols further support slow mobility by a subset of the nodes, energy-efficient routing, and formation of ad hoc subnetworks for carrying out cooperative signal processing functions among a set of the nodes. Wireless Sensor Networks consisting of nodes with limited power are deployed to gather useful information from the field. In WSNs it is critical to collect the information in an energy efficient manner. Ant Colony Optimization, a swarm intelligence based optimization technique, is widely used in network routing. A novel routing approach using an Ant Colony Optimization algorithm is proposed for Wireless Sensor Networks consisting of stable nodes. Illustrative examples, detailed descriptions and comparative performance test results of the proposed approach are included. The approach is also implemented to a small sized hardware component as a router chip. Simulation results show that proposed algorithm provides promising solutions allowing node designers to efficiently operate routing tasks. In this paper, we investigate a communication system in which unmanned aerial vehicles (UAVs) are used as relays between ground-based terminals and a network base station. We develop an algorithm for optimizing the performance of the ground-to-relay links through control of the UAV heading angle. To quantify link performance, we define the ergodic normalized transmission rate (ENTR) for the links between the ground nodes and the relay, and derive a closed-form expression for it in terms of the eigenvalues of the channel correlation matrix. We show that the ENTR can be approximated as a sinusoid with an offset that depends on the heading of the UAV. Using this observation, we develop a closed-form expression for the UAV heading that maximizes the uplink network data rate while keeping the rate of each individual link above a certain threshold. When the current UAV relay assignments cannot meet the minimum link requirements, we investigate the deployment and heading control problem for new UAV relays as they are added to the network, and propose a smart handoff algorithm that updates node and relay assignments as the topology of the network evolves.