A Method of Multi Protocol Data Distribution in Heterogeneous Network
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摘要: 跨技术通信迅猛发展推动着单一网络向异构无线网络的转变，该转变极大地提高异构无线设备(如Wi-Fi和ZigBee)的高效共存和协作，但也给异构无线网络中的数据分发问题带来了挑战。由于异构网络节点通信范围差异和低占空比节点周期性睡眠的特点，传统数据分发方法不能高效地利用信道资源而导致较低的分发效率。为了解决这些问题，该文提出一种适用于异构网络的并行数据分发方法。通过数据分发时延和能耗定义新的系统损失函数，并证明了损失函数的合理性，利用信标控制的延迟接收数据包的分发策略，从而实现对周期性睡眠的ZigBee网络进行高效数据分发。进一步地，该文根据动态规划的思想，推导出系统的整体能量损耗和时延的最优值。通过仿真实验证明，在考虑时延和能量损耗的前提下，该文的数据分发方法的性能优于传统的数据分发方法。Abstract: The rapid development of cross technology communication promotes the transformation from single network to heterogeneous wireless network, which greatly improves the efficient coexistence and collaboration of heterogeneous wireless devices, but also brings challenges to data distribution in heterogeneous wireless networks. Traditional data distribution schemes are limited by the communication range of a single node and conflict between different network devices, resulting in continuous decline in the efficiency of data distribution. At the same time, they are not suitable for the unique network model of heterogeneous networks. In order to solve these problems, a data distribution method based on multi protocol parallel data transmission in heterogeneous wireless networks is proposed. The key idea is to use the Parallel Multi-protocol Communication (PMC) node as the transmitting node of the ZigBee network, and define a new system COST function to measure the delay and energy penalty of the system. Through adaptive adjustment of the trade-off coefficient in the function, it can depict the data transmission of various requirements. Based on the system COST function, the paper propose a distribution strategy of delayed receiving packets using beacon control that allows ZigBee to choose the appropriate timing to receive data in a heterogeneous network. Furthermore, the paper proves the rationality of the COST function, and then derives the optimal values of the overall energy penalty and time delay of the system based on the idea of dynamic programming. Comprehensive evaluation shows that considering the two design requirements of time delay and energy penalty, the performance of this method is better than traditional data distribution methods.
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Key words:
- Heterogeneous network /
- Raptor code /
- Data distribution /
- Dynamic programming
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表 1 模型求解算法
输入：$Z = \{ {Z_1},{Z_2},{Z_3}, ··· ,{Z_N}\} $, $n$ 输出：${\rm{COST}}$, $I$, $D$ (1) While($Z \ne \varnothing $) (2) 初始化${\rm{COS}}{{\rm{T}}_{{\rm{TMP}}}} = + \infty $，设置$n$为PMC发送的包数 (3) 计算$Z_i^t(v) \times Z_i^U$，并对${\varDelta _{ {\rm{delay} } } }$进行排序 (4) for $i$ in 1 to $N$ (5) for $j$ in 1 to $N - 1$ (6) ${I_{{\rm{tmp}}}} = I \cup \{ {I_j}\;{\rm{to}}\;{I_{\min (N - 1,j + 1)}}\} $ (7) 根据损失代价函数计算COST (8) If ${\rm{COST}} < {\rm{COS}}{{\rm{T}}_{{\rm{TMP}}}}$ (9) ${\rm{COS}}{{\rm{T}}_{{\rm{TMP}}}} = {\rm{COST}}$ $I = I \cup \{ {I_j}\;{\rm{to}}\;{I_{j - i - 1}}\} $ (10) end if (11) end for (12) end for (13) $D = Z - I$ (14) 计算$Z_i^R = Z_i^P + n$ (15) for $i$ in 1 to length of $Z$ (16) If $Z_i^P \ge Z_i^R$ (17) $Z = Z - \{ {Z_i}\} $ (18) end if (19) end for (20) end while 
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