Routing for Wireless Multi-Hop Networks (SpringerBriefs in Computer Science)
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However, the increased per- Similar observations can be made for the remaining contents centage of compressed features is accompanied by a degradation of of Table 3, while all dominant features per node, type of proto- the MSE scores. With regard to Stack 1, the deterioration of MSE is col stack, and feature selection algorithm are highlighted in Fig.
This the length of Pij. By contrast, as illustrated at Fig.
Routing for Wireless Multi-Hop Networks
No other out, geometry, material of the objects and the presence of heavy spatial correlation on the dominant attributes that REC-FSA selects machinery, obstacles, people, mobility. The variation of the MSE can be derived. Shifting towards the dominant features for charac- scores increases as we shift from Stack 1 to Stack 2, and subse- terizing the performance when Stack 2 is deployed, the behavior quently the duration of the network operation expands from 2.
In fact, when FSSA is used, the received sig- from 0. In addition, due to the optimal network behav- Fig. In- the sink node. The remaining features that are chosen by REC-FSA deed, humidity becomes a primary feature for characterizing the are related to the mean and the standard deviation of on-board network performance for the sensor nodes that operate closer to temperature Ti and humidity Hi.
It is also considered important to Dominant features at the industrial environment. The results presented highlight how the differences on layer are characterized as redundant. The improvement on the functionality of Stack 2, which exploits the value of LQI for mak- network performance is accompanied by a homogeneity on the ing routing decisions. Nevertheless, especially for the industrial deployment, ized by limited salience.
With respect to features associated to sor node, when Stack 1 is employed. As such, the dominant fea- herein proposed for constructing the original feature vector, and in tures provided by FSSA are in compliance to the current state of terms of salience and qualitative compression of the reduced pat- the art, which emphasizes both on the impact of multipath and tern of dominant attributes. The herein proposed based design choices .
By contrast, REC-FSA selects features framework for feature selection concentrates on a single aspect that are available on the ith node, related to both the status of of network performance PRRij , however it can serve as a design the sensor node e. Moreover, the structured methodology adopted al- of-the-art on the importance of link quality estimation for net- lows the scalable adaptation of the proposed scheme towards more work performance characterization.
Instead, they highlight that the expanded deployments. Finally, the lightweight nature of REC-FSA similar estimation can be achieved by metrics that are available promotes the real-time character of the proposed feature selection at each node i. Thus, the respective features can be employed scheme. In addition, while in this work we have considered pairwise characterization of 6.
Conclusions and future work redundancy and compression, our future directions link to graph- based models.
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According to methodology with the WSN protocol stacks development, and the anonymous therein presented, an estimation of the SoC can be derived by per- reviewers for their insightful comments. Power consumption and lifetime calculation for IEEE Using the recorded time tcuttoff it takes the battery to the receiving frames from the 1-hop neighbors. As such, Eq. Note  M. Erol-Kantarci, H. Hasenfratz, O. Saukh, C.
Walser, C. Hueglin, M. Fierz, T. Arn, J. Beutel, symbols of channel listening, transmission and reception within a L. Without loss sor nodes, Pervasive Mobile Comput. Poon, B. Lo, M. Yuce, A. Alomainy, Y. Hao, Body sensor networks: In the era related to: a the duration of backoff period, and the clear channel of big data and beyond, Biomed. IEEE Rev. Di Martino, M. Cinque, D. Cotroneo, Automated generation of performance and dependability models for the assessment of wireless sensor networks, acknowledgment frames as a function of the nominal bit rate and Comput.
IEEE Trans. Laukkarinen, J. Suhonen, T. Hamalainen, M. Hannikainen, Pilot studies of for the transmitter - receiver synchronization, d the turn-around wireless sensor networks: Practical experiences, in: Design and Architectures for Signal and Image Processing DASIP , Conference on, , pp. Surmacz, M. Sabicki, B.
Wojciechowski, M. Nikodem, Lessons learned from In each of the three operational modes of the transceiver, the the deployment of wireless sensor networks, in: A. Kwiecie, P.
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Wang, K. Liu, X. Li, Does wireless sensor network scale? For instance, considering the case of the — Min, M. Bhardwaj, S. Cho, N. Ickes, E. Shih, A. Sinha, A. Wang, A. Chan- drakasan, Energy-centric enabling tecumologies for wireless sensor networks, Wireless Commun.
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