基于博弈论的分布式水声通信网络功率分配算法

针对水下多节点通信网络节点生存时间短、服务质量差等问题,提出了一种基于博弈论的分布式功率分配算法。首先,在效用函数中考虑网络的整体干扰水平,优化网络的SINR水平,改善网络的服务质量。其次,进一步地将节点剩余能量引入到效用函数中,使剩余能量较低时节点减小发射功率,从而提高节点生存时间。所构建的博弈模型纳什均衡点具有存在性与唯一性。最后,通过仿真验证该算法能够延长节点寿命,优化系统SINR,提高节点能量效率。      

An energy‐efficient clustering and multipath routing for mobile wireless sensor network using game theory

Most of the current generation sensor nodes of mobile wireless sensor network (MWSN) are designed to have heterogeneous mobility to adapt itself in the applied environment. Energy optimization in MWSN with heterogeneous mobility is very challenging task. In this paper, a heterogeneous game theoretical clustering algorithm called mobile clustering game theory–1 (MCGT‐1) is proposed for energy optimization in a heterogeneous mobile sensor environment. Energy optimization is achieved through energy‐efficient cluster head election and multipath routing in the network. A heterogeneous clustering game is modelled with varying attributes and located an asymmetric equilibrium condition for a symmetric game with mixed strategies. The real‐time parameters, namely, predicted remaining energy, distance between a base station and nodes, distance between nodes, and mobility speed, were used to calculate the probability to elect the cluster head (CH). The efficient multipath routing is achieved through prior energy prediction strategy. It has mitigated the generation of “hot spots,” reducing its delay and improving the overall residual energy of the network. Simulation results showed that the average lifetime of MCGT‐1 has increased by 6.33 %, 13.1% and 14.2% and the PDR has improved by 4.8%,11.8%, and 17.2% than MCGT, LEACH‐ME and LEACH‐M respectively. The hot spot delay is reduced to 0.063025 seconds, improving the efficiency of the network.     

基于博弈的协作路由算法

协作虚拟多输入多输出（VMIMO）传输是一种有效的无线传输性能优化技术。将物理层协作VMIMO技术和网络层路由选择技术相结合,设计跨层VMIMO路由选择方案可以利用VMIMO的分集增益,显著地降低网络传输能耗。如何设计VMIMO协作路由协议抵抗无线网络的自私节点和欺骗行为,保证高数据转发率和低传输能耗成为路由设计中的重大挑战。为了提高自私网络的VMIMO路由性能,提出了一种基于重复路由博弈的VMIMO协作路由算法。该算法将网络划分成多个Group、Group间使用VMIMO传输数据。将Group间路由选择过程建模为重复路由博弈过程。为了提高数据转发的成功率,提出适用度函数评估节点参与数据分组转发的信誉。以此为基础,提出基于适用度的路由选择子算法和路由转发子算法。理论证明所提重复路由博弈可达到帕累托最优。仿真实验结果表明本算法可以促进自私节点相互合作,可获得较高的数据转发率,较好地减少数据传输时延以及能量消耗。     

一种基于贝叶斯博弈的传感器网络分簇算法

提出了一种基于贝叶斯博弈的无线传感器网络分簇算法.算法将无线传感器网络节点的簇头选择抽象为一个多人的博弈过程,节点之间通过不完全信息的静态博弈实现簇头的合理分布.算法在支付函数的设计时充分考虑了节点能耗和路径损耗等因素,因此通过博弈该算法能实现簇头的合理分布.仿真结果表明,算法在保证数据传输实时性的前提下可使网络能耗更加稳定、能量分布更加均匀,有效地延长网络生命周期.     

移动WSNs中一种覆盖空洞的修复算法

基于无线传感网络的应用依赖于节点对监测区域的可靠覆盖.由于能耗殆尽或故障,节点感测能力可能失效,形成覆盖空洞区域.为此,提出基于模糊推理系统(FIS)的修复节点选取(FISS)算法.FISS算法采用自适应感测半径调整策略,利用节点的移动修复覆盖空洞.将节点的剩余能量和覆盖重叠率作为FIS的输入,并由FIS估计节点成为修...     

异构蜂窝网络中基于Stackelberg博弈的能效优化算法

设备到设备(Device To Device,D2D)通信允许移动终端无需通过基站而进行直接通信。为提高蜂窝系统能效,引入D2D通信共享频谱资源形成异构蜂窝网络。本文将D2D通信的能效优化问题转化为博弈收益最大化问题,并提出了一种基于Stackelberg博弈的分布式功率控制算法。针对系统模型中存在的跨层干扰以及层内干扰,该算法建立了干扰价格系数与D2D对发送功率之间的函数关系,并求解出给定干扰价格系数下D2D对最佳发送功率的闭合表达式。仿真结果表明所提算法能够在最大化基站端蜂窝用户收益的基础上有效提高D2D对的总能效。      

An energy‐efficient utility‐based distributed data routing scheme for heterogenous sensor networks

A utility‐based distributed data routing algorithm is proposed and evaluated for heterogeneous wireless sensor networks. It is energy efficient and is based on a game‐theoretic heuristic load‐balancing approach. It runs on a hierarchical graph arranged as a tree with parents and children. Sensor nodes are considered heterogeneous in terms of their generated traffic, residual energy and data transmission rate and the bandwidth they provide to their children for communication. The proposed method generates a data routing tree in which child nodes are joined to parent nodes in an energy‐efficient way. The principles of the Stackelberg game, in which parents as leaders and children as followers, are used to support the distributive nature of sensor networks. In this context, parents behave cooperatively and help other parents to adjust their loads, while children act selfishly. Simulation results indicate the proposed method can produce on average more load‐balanced trees, resulting in over 30% longer network lifetime compared with the cumulative algorithm proposed in the literature. Copyright © 2014 John Wiley & Sons, Ltd.     

Virtual Game-Based Energy Balanced Topology Control Algorithm for Wireless Sensor Networks

In topology control (TC), game theory is an efficient approach to analyze the conflicting objectives of nodes to enable the topology with certain global properties in the presence of selfish nodes. But in many existing game-based TC algorithms, every node has to make others aware of its changes by transmitting the control information repeatedly, which results in much unnecessary energy waste and network lifetime reduction. To solve the problem, the concept of virtual game is introduced, which virtualizes the game process to avoid the repeated information exchange in the game process. In addition, considering that unbalanced distribution of energy consumption also restricts the network lifetime, a distributed Virtual Game-based Energy Balanced TC algorithm (VGEB) with incomplete information is proposed, which is mathematically analyzed. The analysis results show that the TC virtual game is a potential game and the virtual game algorithm can converge to the state of Nash Equilibrium, which is Pareto Optimal. Moreover, VGEB can easily construct the topology with a low information complexity of O(n) and the induced topology can maintain the network connectivity, where n is the number of nodes in network. Simulation results demonstrate that VGEB can effectively balance the nodes’ energy consumption, greatly reduce the energy waste in the game process and has many other attractive topological features.     

能量采集型无线传感器网络的高能效路由算法

在能量采集型无线传感器网络中,虽然有能量吸收,但是因能量依然非常珍贵,如何优化路由协议,提高能量利用率,延长网络寿命仍然是值得研究的问题.为求解高能效的路由,提出了一种采用遗传算法的高能效路由算法,建立考虑节点的吸收能量、剩余能量、消耗能量和浪费能量的适应函数,用遗传算法寻找全局最优路径.将该适应函数与3种其他适应函数作对比,其他3种适应函数分别为只考虑路径能耗最小的适应函数,考虑路径能耗与路径上节点的吸收能量、剩余能量的适应函数以及考虑路径能耗与网络中所有节点的浪费能量的适应函数.采用遗传算法解出4种路由,通过仿真分析可知,所提出的路由算法能量利用效率最高.     

基于博弈论功率控制的串行干扰消除算法

无线网络实现串行干扰消除算法可以提高网络吞吐量,在采用串行干扰消除算法的无线网络系统中,如何控制节点间传输功率使系统效用最大化是一个NP-Hard难题。针对此问题提出非合作博弈算法来解决节点间的传输功率控制,提出了串行干扰消除算法功率控制的非合作博弈,证明了纳什均衡,所提算法可以获得较高的无线网络吞吐量,仿真实验证实了分析结果并展示了算法的优越性。     

一种基于博弈论的无线传感器网络拓扑控制算法

无线传感器网络对节能有着很高的要求,拓扑控制能够优化网络拓扑,提高无线信道的空间复用率,是提高无线传感器网络能量效率的有效方法.文中提出了-种基于博弈论的无线传感器网络拓扑控制算法,设计了-个与节点度和发射功率有关的收益函数,使拓扑控制博弈存在纳什均衡,网络总收益函数最大,网络的能量效率最高.     

认知无人机辅助边缘通信的能效优化

针对无人机辅助边缘通信中的频谱资源紧缺与无人机能量受限问题,研究了最大化该场景下无人机认知通信的能量效率问题.首先,构建了无人机辅助边缘节点的认知通信网络模型;其次,提出了一种最大化无人机能效的算法,通过联合优化无人机的认知通信感知时间、飞行速度和通信距离阈值,显著提升了无人机认知通信过程中的能效;最后,通过仿真实验对...     

Distributed fuzzy logic based energy‐aware and coverage preserving unequal clustering algorithm for wireless sensor networks

In an energy‐constrained wireless sensor networks (WSNs), clustering is found to be an effective strategy to minimize the energy depletion of sensor nodes. In clustered WSNs, network is partitioned into set of clusters, each having a coordinator called cluster head (CH), which collects data from its cluster members and forwards it to the base station (BS) via other CHs. Clustered WSNs often suffer from the hot spot problem where CHs closer to the BS die much early because of high energy consumption contributed by the data forwarding load. Such death of nodes results coverage holes in the network very early. In most applications of WSNs, coverage preservation of the target area is a primary measure of quality of service. Considering the energy limitation of sensors, most of the clustering algorithms designed for WSNs focus on energy efficiency while ignoring the coverage requirement. In this paper, we propose a distributed clustering algorithm that uses fuzzy logic to establish a trade‐off between the energy efficiency and coverage requirement. This algorithm considers both energy and coverage parameters during cluster formation to maximize the coverage preservation of target area. Further, to deal with hot spot problem, it forms unequal sized clusters such that more CHs are available closer to BS to share the high data forwarding load. The performance of the proposed clustering algorithm is compared with some of the well‐known existing algorithms under different network scenarios. The simulation results validate the superiority of our algorithm in network lifetime, coverage preservation, and energy efficiency.     

一种基于网格划分的水下传感器网络多维优化部署策略

针对水下无线传感器网络节点的部署问题,提出一种基于网格划分的多维优化部署策略。首先,将所需探测水下环境划分成相同规格的网格;然后,综合考虑网络节点数量、网络覆盖率、网络冗余度、网络生存率等指标,构建多目标优化数学模型;最后,采用遗传算法对多维优化部署策略加以实现并进行仿真分析。结果显示：所提策略能够有效地减少部署节点数量,提高网络覆盖率和生存效率,降低网络能耗。     

Pricing for enabling forwarding in self-configuring ad hoc networks

The assumption that all nodes cooperate to relay packets for each other may not be realistic for commercial wireless ad hoc networks. An autonomous (selfish) node in a wireless network has two disincentives for forwarding for others: energy expenditure (real cost) and possible delays for its own data (opportunity cost). We introduce a mechanism that "fosters cooperation through bribery" in the context of forwarding in ad hoc networks. Using a microeconomic framework based on game theory, we design and analyze a pricing algorithm that encourages forwarding among autonomous nodes by reimbursing forwarding. Taking a joint network-centric and user-centric approach, the revenue maximizing network and utility (measured in bits-per-Joule) maximizing nodes interact through prices for channel use, reimbursements for forwarding, transmitter power control, as well as forwarding and destination preferences. In a three-node (two-sources, one-access-point) network, the network converges to an architecture that induces forwarding only when the network geometries are such that forwarding is likely to increase individual benefits (network revenue and node utilities). For other geometries, the network converges to architectures that do not favor forwarding. We then generalize to a multinode network, where it is seen that the nodes' willingness to forward decrease for large ratios of the average internodal distance to the smallest distance between the access point and any source node. Pricing with reimbursement generally improves the network aggregate utility (or aggregate bits-per-Joule), as well as utilities and revenue compared with the corresponding pricing algorithm without reimbursement.     

基于节点休眠的水下无线传感器网络覆盖保持分簇算法

为有效延长水下无线传感器网络的生命周期、保持网络覆盖率,该文提出一种基于节点休眠的覆盖保持分簇算法。首先计算网络节点的覆盖冗余度,并对覆盖冗余度高的节点执行休眠策略,然后以网络覆盖率及节点能耗均衡性为目标,采用多目标算法进行求解,再利用TOPSIS法从非支配解集中选出较优解,当有节点死亡时,通过唤醒策略保持网络覆盖率。仿真结果表明,与目前较好的网络规划算法相比,该文算法能够更好地降低网络能耗,延长网络生命周期并保持网络对环境的覆盖率。     

基于认知无线电的新型非合作功率控制博弈算法

从认知无线电技术特性出发,在干扰温度门限的限制条件下,提出了基于新的代价函数功率控制博弈论算法,以有效地提高认知用户的信干噪比。根据信道状况、吞吐量最大化和功率限制的需求,将功率控制问题转化为一个干扰受限的多约束非线性规划问题。结合博弈论和最优化理论,证明了其纳什均衡的存在性和唯一性,给出了该模型的分布式求解算法。仿真实验表明,该算法可以有效提高认知用户的QoS和系统性能,充分利用无线资源。     

无线传感器网络中簇首选择算法研究

传统的低功耗自适应集簇分层型协议（LEACH）算法在选择簇首时未能考虑到节点剩余能量对网络寿命的影响,使得簇首分布不够合理。为了克服该问题,在完全分布式成簇算法（HEED）协议的基础上,设计了一种根据节点剩余能量选择簇首的算法。在该算法中,剩余能量越大的节点越有可能成为簇首,进而承担更多数据传输责任,能量消耗更加平均,增强了算法的健壮性。仿真结果证实,提出的算法可以有效提高网络能量的使用效率,减少功耗,延长网络生存时间。     

An Energy Efficient Autonomous Method for Coverage Optimization in Wireless Multimedia Sensor Networks

In this paper, a distributed method for coverage optimization of random deployed WMSNs utilizing motility and mobility capabilities of nodes, is proposed. The aims followed by the method are first, maximizing the coverage ratio by minimizing both the covered overlapping areas, and the coverage holes after random deployment, and second, enhancing energy efficiency of the coverage optimization procedure, by minimizing the needed rotations and specially movements, comparing with the previous schemes. To these aims, the most appropriate location and orientation of the nodes are calculated round by round considering all the possible nested compositions of rotation and movement. But, rotating and moving the nodes are performed after terminating the algorithm rounds and achieving the decisive results. So, the proposed method does not impose the overhead of trial and error of rotation or relocation on the network nodes. The performance of the proposed approach has been compared with the previous works for different network configurations; simulation results show that the proposed approach outperforms the previous schemes in terms of both coverage ratio and energy efficiency.     

无线传感器网络能量异构分簇算法的研究

在无线传感器网络能量异构环境下对低功耗自适应的分簇算法(Low Energy Adaptive Clustering Hierarchy,LEACH)与稳定选举协议(Stable Election Protocol,SEP)算法进行了分析,针对其存在的不足提出了一种改进的方案。在簇头选举过程中提高了剩余能量高、距离基站较近节点当选为簇头的概率,同时对当选为簇头的节点设定能量阈值,避免能量过低的节点当选为簇头。仿真结果表明,改进后的算法较好地均衡了网络中节点的能量消耗,有效地提高了网络中能量的利用效率,并且极大地延长了网络正常工作的生命周期。