Wireless Multimedia Sensor Networks (WMSNs) is inherited and developed from the traditional Wireless Sensor Networks (WSNs). Quality of service (QoS) has become an important index to evaluate the quality of the WMSNs. This paper discusses the following two aspects. Firstly, we propose a method to handle sudden network congestion–improving the way of key frame transmission, namely increasing the compression ratio of the key frames. The process reduces the video image quality, it can guarantee the continuity of video signal and conform the requirement of people’s daily viewing. Secondly, the paper is discussing to apply the Ant Colony Optimization (ACO) to improve the mathematical model and make it apply to WMSNs. At last, the experiment turns out that the improved ACO can be used in routing and this has certain application value.
AliA.KhelilA.SuriN. and MahmudimaneshM., Adaptive Hybrid Compression for Wireless Sensor Networks [J], Acm Transactions on Sensor Networks11(4) (2015), 1–36.
2.
DeshpandeA. and KaushalD.A, Enhancing the Performance of TCP by Improvising on the Key MANET Routing Protocols [J], International Journal of Latest Research in Science & Technology7(3) (2016), 531–538.
3.
MammadovA. and AbbasovB., A review of protocols related to enhancement of TCP performance in wireless and WLAN networks [C], IEEE International Conference on Application of Information and Communication Technologies, (2014), 1–4.
4.
KeC.H.YangC.Y. and ChenJ.L., A novel mapping mechanism for MPEG-4 video delivery over IEEE 802.11e networks [J], Multimedia Tools & Applications76(4) (2017), 1–13.
5.
MorenoF. and AledoD., The DLMT hardware implementation. A comparative study with the DCT and the DWT[C], Conference on IEEE Industrial Electronics Society, (2012), 1591–1596.
6.
Al-ZoubiH.R., Video Coding and Routing in Wireless Video Sensor Networks [J], Aasri Procedia5(3), (2013), 48–53.
7.
AkyildizI.F.MelodiaT. and ChowdhuryR.K., A survey on wireless multimedia sensor networks [J], Computer Networks51(4) (2007), 921–960.
8.
ParkJ. and JeonB., Parallel transform domain Wyner-Ziv video encoding scheme for standard definition video [C], IEEE International Symposium on Broadband Multimedia Systems and Broadcasting, (2012), 1–4.
9.
GhaboosiK.VemulapalliM.OatesJ. and TangY., Method and apparatus for heterogeneous small cells self-organization in LTE networks based on internet protocol multimedia subsystems [J], 2017, 12–16.
10.
CoboL.QuinteroA. and PierreS., Ant-based routing for wireless multimedia sensor networks using multiple QoS metrics[J], Computer Networks54(17) (2010), 2991–3010.
11.
LiL.L. and WangJ.K., SAR image ship detection based on Ant Colony Optimization[C], International Congress on Image and Signal Processing, (2012), 1100–1103.
12.
RahmanM.A.GhasemaghaeiR.SaddikA.E. and GueaiebW., M-IAR: Biologically Inspired Routing Protocol for Wireless Multimedia Sensor Networks[C], IEEE Instrumentation and Measurement Technology Conference Proceedings, (2008), 1823–1827.
13.
DissanayakeM.B.WorrallS. and FernandoW.A.C., Wyner-Ziv based error correction of non-key frames for low complexity streaming applications[C], IEEE International Conference on Industrial and Information Systems, (2011), 467–471.
14.
HasanM.Z.Al-RizzoH. and Al-TurjmanF., A Survey on Multipath Routing Protocols for QoS Assurances in Real-Time Wireless Multimedia Sensor Networks [J], IEEE Communications Surveys & Tutorials, (2017), (99), 1–1.
15.
KumarN.IqbalR.ChilamkurtiN. et al., An ant based multi constraints QoS aware service selection algorithm in Wireless Mesh Networks [J], Simulation Modelling Practice and Theory19(9) (2011), 1933–1945.
16.
ChoS.YiJ.H.ShresthaB. and SeoC, Multipath routing technique for responding to sniffing attacks in wireless multimedia sensor network environment [J], International Journal of Sensor Networks24(3) (2017), 200.
17.
AnandamuruganS. and AbiramiT., Antipredator Adaptation Shuffled Frog Leap Algorithm to Improve Network Life Time in Wireless Sensor Network [J], Wireless Personal Communications, (2017), 1–12.
18.
EhsanS. and HamdaouiB., A Survey on Energy-Efficient Routing Techniques with QoS Assurances for Wireless Multimedia Sensor Networks [J], IEEE Communications Surveys & Tutorials14(2) (2012), 265–278.
19.
PudlewskiS. and MelodiaT., On the Performance of Compressive Video Streaming for Wireless Multimedia Sensor Networks [C], IEEE International Conference on Communications, (2010), 1–5.
20.
SharmaS.MishraR. and SinghK., A Review on Wireless Network Security[C], International Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness, Springer, Berlin, Heidelberg, (2013), 668–681.
21.
LeishmanT.G.GreenD.G. and PaperinG., Dual phase evolution-a mechanism for self-organization and optimization [C], Asia-Pacific Worksop on Intelligent and Evolutionary Systems, (2007), 1–8.
22.
ShenY.C.ChengH.P.LuoJ.C.LinY.H. and WuJ.L., Efficient Real-Time Distributed Video Coding by Parallel Progressive Side Information Regeneration [J], IEEE Sensors Journal17(6) (2017), 1872–1883.
23.
LvY.LiuY.ChenW.ShengX. and HanY., A Twice Ant Colony Algorithm Based on Simulated Annealing for Solving Multi-constraints QoS Unicast Routing [J], Advances in Information Sciences & Service Sciences5(1) (2013), 167–175.
24.
KuangZ.F. and ChenZ.G., Multicast Routing Algorithm with QoS Constraints in Cognitive Wireless Mesh Networks [J], Journal of Software23(11) (2014), 3029–3044.
25.
LiZ. and ShiQ., An QoS Algorithm Based on ACO for Wireless Sensor Network [C], IEEE International Conference on High PERFORMANCE Computing and Communications & 2013 IEEE International Conference on Embedded and Ubiquitous Computing, (2013), 1671–1674.
