无线传感网中混合业务下的触发式流控制算法

无线传感器网络中,节点所具有的能量和通信能力等都十分有限,如何设计有效的协议及算法,利用有限的资源高效地完成诸多任务,成为无线传感器网络设计所面临的一大挑战.考虑接收容量模型,研究了无线传感器网络在节点接收容量和能量联合受限情况下,面向混合业务时的效用公平流控制问题,并针对传统对偶分解算法存在着收敛速度慢、步长不易调节、通信负荷大等缺陷,进一步提出了基于事件触发的分布式求解算法.理论分析与仿真验证均表明:使用事件触发算法时,传感节点的平均广播周期比使用对偶分解算法时大很多,大幅度降低了无线传感器网络节点间的通信量,减少了网络的通信开销.仿真结果显示:与对偶分解算法相比,分布式事件触发算法具有收敛速度快、对网络规模扩展的适应性强等优势;与传统的速率公平流控制机制相比,所提的效用公平流控制模型能够更加适应弹性与非弹性业务共存的网络场景.

Event Triggered-Based Flow Control Algorithm for Mixed Traffic in Wireless Sensor Networks

In wireless sensor networks, nodes commonly have limited energy and communication ability. Desiging efficient protocols and algorithms to complete various tasks efficiently with limited resources has become a challenge in wireless sensor networks. Considering the receiver capacity and mixed traffic in wireless sensor networks, this paper investigate the utility fair flow control problem with joint power and receiver capacity constraints. Since conventional dual decomposition algorithms often have drawbacks such as slow convergence, difficult adjustment of stepsize and large communication overhead, this paper proposes an event-triggered distributed algorithm for the flow control problem studied in this paper. Both theoretical analysis and simulation results show that the average broadcast period of sensor nodes when using event triggered distributed algorithm is longer than that of dual decomposition. Compared with the dual decomposition algorithm, this event triggered distributed algorithm reduces the amount of information exchange among nodes, decreases the communication overhead in wireless sensor networks greatly. The simulation results also show that the event triggered distributed algorithm has a much faster convergence than the dual decomposition algorithm and the former has better scalability to the network size. Additionally, compared with the conventional rate fair flow control mechanism, the utility fair flow control model can better cater for the networks scene with a mix of elastic and inelastic traffic.