Link Weight Function Research Articles

Wireless ultraviolet cooperative unmanned aerial vehicle formation communication link maintenance method.

A stable formation communication network can improve the task efficiency of a unmanned aerial vehicle (UAV) cluster. Aiming at the topology construction of the UAV formation communication network, combined with the optimal rigid graph theory, we design a three-dimensional UAV formation communication network generation algorithm based on the optimal rigid graph. We construct a new link weight function by introducing node residual energy and communication path loss to reduce the overall energy consumption of formation. Aiming at the problem that the communication link of the UAV is interrupted when the formation network is moving, a UAV communication beam tracking and holding method based on a multiple-input multiple-output (MIMO) structure and position prediction is designed. Simulation results show that the network topology constructed by the UAV formation communication network generation algorithm has a good average node degree, and effectively improves the network connectivity and communication fault tolerance. Compared with the tracking and holding algorithm based on the received signal strength, the beam tracking and holding algorithm significantly reduces the number of link interruptions, and the communication success holding rate can be basically maintained at about 90%.

Topology Control Algorithm of Underwater Sensor Network Based on Potential-Game and Optimal Rigid Sub-Graph

Aiming at the problems of unbalanced energy consumption, redundant links, short life cycle in underwater sensor networks, a topology control algorithm for underwater wireless sensor networks based on potential-game and optimal rigid sub-graph is proposed. Firstly, based on the potential game theory, the topology control model of underwater sensor network is constructed, which considers network coverage, connectivity, transmission energy consumption, end-to-end delay, transmission success rate, node residual energy and so on. It is proved that the model is an ordinal potential game and has a Nash equilibrium solution. Then, the link weight function of node load and node residual energy is introduced, and the redundant links in the network are eliminated by using the principle of optimal rigid sub-graph. Simulation experiments and contrast analysis show that compared with other network models, the network topology model constructed in this paper has lowed node load and stronger energy balance, prolongs the life cycle of the network and more conforms to the underwater environment.

A Game Theory Based Clustering Protocol to Support Multicast Routing in Cognitive Radio Mobile Ad Hoc Networks

The frequent movement of nodes in cognitive radio mobile ad hoc networks (CRAHNs) causes challenges in scalability, stability, channel sensing and channel access problems that can be solved by using clustering technique. Game theory is a feasible approach to solve such problems by casting clustering problems as distributed optimization problems. The main contributions of this article are as follows. Firstly, we propose a minimum connected weighted inner edge spanning tree (MWIEST) game to find an approximate solution of a MWIEST problem in CRAHNs. In this game, a link-weight function of each link is designed based on a combination of link-stability and link-connectivity ratio functions. Secondly, we prove that the MWIEST game is an exact potential game that exists at least one Nash equilibrium ( NE ) point which is an approximate solution of the MWIEST problem. Besides, we also prove that best responses ( BR s) of the game converge to a NE in finite iterations. Thirdly, based on the MWIEST game, we propose four algorithms including the node information exchange (NIE), the best response selection (BRS), the intermediate nodes selection (INS) and the forming cluster (FC). Specifically, the algorithms NIE, BRS and INS provide a set of intermediate nodes (SetIN) which supports the FC algorithm to form clusters. Finally, we propose the game theory based clustering (GBC) protocol which is combination of the FC algorithm and the proposed cluster maintenance algorithm to construct high stable clusters supporting multicast routing in CRAHNs. Moreover, each obtained cluster includes most members having the same receiving channel which avoids the affected regions of licensed channels. For the performance evaluation, we implement the GBC protocol in OMNET++ platform to demonstrate its performance improvement over the state-of-the-art protocols in terms of network stability and control overheads.

Scalable Adaptive Group Communication for Collaboration Framework of Cloud-enabled Robots

Recently, researchers have been exploring the idea of robots that rely on cloud-computing infrastructure to take advantage of processing power and access vast amounts of data. This approach allows a robot to delegate compute-intensive tasks like image recognition, graphical mapping systems and etc. However, the efficient information sharing of cloud-enabled robots is not addressed which is necessary in disseminating real time information. In this paper, a collaboration framework is presented which is designed for information sharing of cloud-enabled robots. Based on attributes, cloud-enabled robots form logical groups to perform information sharing through the Internet. To provide a faster way of disseminating messages, a scalable adaptive group communication (SAGC) is proposed. The logical groups are processed using fuzzy system to employ scalable grouping, and then, the logical links are adjusted by a node link weight function based on Brownian agent to direct the queries to robots with relevant information. The performance evaluation showed that the SAGC had the fastest response to queries compared to other group communication methods.

BANDWIDTH-SENSITIVE ROUTING: FROM INDIVIDUALISM TO COLLECTIVISM

The routing metric is the measure by which a routing protocol chooses paths between pairs of source and destination nodes in the network. Routing metric has a significant impact on the network resource utilization. The most well-known intradomain routing disciplines in today's Internet are the minimum hop count routing (e.g., Routing Information Protocol (RIP)) and the shortest path routing (e.g., Open Shortest Path First (OSPF) and intermediate system to system (IS-IS)). In the former case, the routing metric is the number of hops over the path and in the latter one, the metric is evaluated with respect to an additive link weight function. In this article, we study the impact of these two types of metrics on routing of bandwidth-sensitive traffic in the network. We first argue that the main characteristics of a bandwidth-sensitive routing problem can be captured elegantly through transforming the problem from the networking domain into the sociology area. This model reveals that the minimum hop count is indeed a dominant Individualist view of resource management in the Internet, whereas the shortest-path metric has a collectivist trend. We then propose a novel hybrid metric, which combines the benefit of both sociological systems. Through extensive simulations, we show that our proposed scheme yields much better results, with respect to the number of admitted requests and delay of paths, compared with other well-known counterparts.

A shortest-path-based topology control algorithm in wireless multihop networks

In this paper, we present a shortest-path-based algorithm, called local shortest path(LSP), for topology control in wireless multihop networks. In this algorithm, each node locally computes the shortest paths connecting itself to nearby nodes based on some link weight function, and then it selects all the second nodes on the shortest paths as its logical neighbors in the final topology. Any energy model can be employed in LSP to design the link weight function whose value represents the power consumption required in the transmission along a link. We analytically prove that such a simple algorithm maintains network connectivity and guarantees that the minimal energy path between any two nodes is preserved in the final topology. Simulation results show that LSP can reduce the energy consumption, especially in heterogenous network.