A QoS-aware energy-efficient memetic flower pollination routing protocol for underwater acoustic sensor network

被引:21
|
作者
Sivakumar, V. [1 ]
Rekha, D. [1 ]
机构
[1] Vellore Inst Technol, Sch Comp Sci & Engn, Chennai Campus, Chennai 600127, Tamil Nadu, India
来源
关键词
grant free pattern division multiple access; memetic flower pollination routing; minimum energy broadcast; underwater acoustic sensor network; NODE;
D O I
10.1002/cpe.5166
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Huge number of applications ranging from commercial, scientific, to military applications are recently emerging in Underwater Acoustic Sensor Networks (UWASNs). The major research challenges associated with UWASN includes high energy consumption, large propagation delay, and low available bandwidth due to its acoustic medium. In this paper, Quality of Service (QoS)-aware Energy-Efficient Memetic Flower Pollination Routing (MFPR) has been proposed to identify optimal energy-efficient routing coverage set in underwater. The fitness function for MFP is formulated for Vector-Based Forward (VBF) protocol that allocates the reliable routing path for source node within its routing pipe. The proposed algorithm works in two stages, where Memetic algorithm is responsible for identifying the optimal route cover set and FPA is responsible for switching between local and global pollination to forward packets in reliable path. In addition, the proposed work considers Grant Free Pattern Division Multiple Access (GFPDMA) packets for routing purpose, since it reduces the latency at the time of packet transmission. Hence, this forms QoS-aware routing in UWASN. The proposed MFPR is evaluated in UWASN environment that runs applications with varied QoS requirements. The simulation result shows that the novel proposed method improves the performance of UWASN in terms of high network lifetime, less end-to-end delay, high energy consumption, high packet delivery ratio, and high throughput than existing Quality-of-Service-Aware Evolutionary Routing Protocol (QERP) and Balanced and Multi-objective Optimized Opportunistic Routing (BMOOR) models.
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页数:10
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