Opportunistic Routing in Underwater Acoustic Networks Fusing Depth Adjustment and Adaptive Forwarding
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摘要: 针对水声传感器网络路由过程中的空洞问题和数据传输中能效低下的问题，该文提出了融合深度调整和自适应转发的水声网络机会路由(OR-DAAF)。针对路由空洞，区别于传统绕路策略，OR-DAAF提出一种基于拓扑控制的空洞恢复模式算法—利用剩余能量对空洞节点分级，先后调整空洞节点到新的深度以克服路由空洞，恢复网络联通。针对数据传输中的能效低下问题，OR-DAAF提出了转发区域划分机制，通过转发区域的选择自适应转发面积以抑制冗余包，并提出基于加权推进距离，能量和链路质量的多跳多目标路由决策指标，综合考虑区域能量，链路质量和推进距离实现能效平衡。实验数据表明，相比DVOR协议，OR-DAAF的包投递率和生命周期分别提高10%和48.7%，端到端时延减少22%。Abstract: Considering voids in the routing process of underwater acoustic sensor networks and low energy efficiency in data transmission, An Opportunistic Routing fusing Depth Adjustment and Adaptive Forwarding (OR-DAAF) technique is developed. Aiming at routing voids, instead of adopting the traditional detour strategy, OR-DAAF proposes a topology control-based void recovery mode algorithm, which uses the residual energy to grade void nodes and successively adjusts them to the new depth to overcome routing voids and restore network connectivity. Aiming at low energy efficiency in data transmission, OR-DAAF proposes a forwarding area division mechanism that selects the forwarding area to suppress redundant packets. It also puts forward a multi-hop and multi-objective routing decision index based on weighted advance distance, energy and link quality, comprehensively considering regional energy, link quality and advance distance to achieve an energy efficiency balance. Experimental results show that compared with a Doppler VHF omnidirectional range, OR-DAAF improves packet delivery rate by 10% and network lifetime by 48.7%, respectively and reduces delay by 22%.
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表 1 符号集
符号 含义 ${n_i}$ 第i个节点 $ {\text{PF}}{{\text{A}}_i} $, $ {\text{AF}}{{\text{A}}_i} $ ni的主、辅助转发区域 ${\text{N}}{{\text{e}}_i}$, ${\text{Nsn}}{{\text{r}}_i}$ ni的能量、信噪比候选集 ${\text{Npf}}{{\text{a}}_i}$, ${\text{Naf}}{{\text{a}}_i}$ ni的主、辅助转发候选集 $G({n_i})$, $E({n_i})$ ni的邻居数、剩余能量 $\varOmega , \;\varPhi$ ni的两跳邻居集、深度集 $E{{\text{(}}{n_i}{\text{)}}^{{\text{NF}}}}$ ni的邻居集能量 $ {\text{TF}}{{\text{A}}_i} $ ni的综合转发区域 $d_{ {{jk} } }^{ {\text{NF} } }$ nj的所有邻居节点nk到nj的距离 ${(d'_{ {{jk} } })^{ {\text{NF} } } }$ nj的所有邻居节点nk到平面P的距离 
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算法1: 构建候选集 1: for each node ${n_j} \in {N_i}(t)$ 2: if ${n_j} \in {\text{PF}}{{\text{A}}_i}$ 3: then add ${n_j} \to {\text{Npf}}{{\text{a}}_i}$
4: if $E({n_j}) \ge \displaystyle\sum\limits_k {E({n_k})/2G({n_i})}$5: then add $n_{j} \rightarrow {\rm{N} }e_{i}$ 6: if ${\text{SNR} }({n_i},{n_j}) \ge \displaystyle\sum\limits_k { {\text{SNR} }({n_i},{n_k})/2{{G} }({n_i})}$ 7: then add $n_{j} \rightarrow {\rm{Nsnr} }_{i}$ 8: if $[{n_j} \in {\text{Npf} }{ {\text{a} }_i}] \vee [{n_j} \in {\text{N} }{ {{e} }_i}] \vee [{n_j} \in {\text{Nsn} }{ {\text{r} }_i}]$ 9: then add $ n_{j} \rightarrow C(i) $ 10: end for 11: if $C(i) = \varnothing $ the forwarding area is $ {\text{PF}}{{\text{A}}_i} $ 12: then replace $ {\text{PF}}{{\text{A}}_i} $ to $ {\text{TF}}{{\text{A}}_i} $ 13: and switch to Algorithm 1 again 14: else if $C(i) = \varnothing $ the forwarding area is $ {\text{TF}}{{\text{A}}_i} $ 15: switch to the Algorithm 2
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算法 2: 空洞恢复算法 1: if $|\varOmega| > 0$ 2: for $n_{k} \in \varOmega$ 3: if $ E(n)<0.5 E_{\text {mat }} $ 4: then wait $ 2R/{v_0} $ and switch to Algorithm 2 5: else if
$ \left\{\begin{array}{c}\left(x_{D}-x_{i}\right)\left(x_{k}-x_{i}\right)+\left(y_{D}-y_{i}\right)\left(y_{k}-y_{i}\right) \\+\left(z_{D}-z_{i}^{*}\right)\left(z_{k}-z_{i}^{*}\right)>0 \\0<\sqrt{\left(x_{k}-x_{i}\right)^{2}+\left(y_{k}-y_{i}\right)^{2}+\left(z_{k}-z_{i}^{*}\right)^{2}} \\\leq R\end{array}\right\} $6: then $z_{i}^{*} \rightarrow \varPhi$ 7: end if 8: end for 9: $\hat z = \arg {\min _{\forall z_i^* \in \varPhi } }\{ |z_i^* - {z_i}|\}$
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