在共享式無線感測網路中之有效資料收集方法

現今為了有效地降低網路部署的成本，會以多個應用共用一個無線感測網路來減少感測器的使用，我們稱此為共享式無線感測網路。在共享式無線感測網路中，每一個感測器已不如傳統無線感測網路僅專屬於單一應用，它們必須負責來自於不同應用的任務，因此工作量將會隨著共享的應用數量而增加，另外，在現今的應用中，有許多是使用錄相機感測器去獲得環境中更豐富的資訊，通常是需要一段時間連續性的感測資料，相較於以往單一時間點的資料收集，這將大幅增加感測器的工作量，對於電量有限的感測器而言，容易消耗更多的電量，進一步有可能降低無線感測網路的生命週期，為了解決工作量增加的問題，感測資料應該被應用共享並被有效率的收集，以減少感測器的工作量，因此，在本篇論文中，我們提出了一個近似演算法，盡可能的減少感測器所需要收集的資料量，同時共享這些感測資料以因應不同應用的需求，我們所提出的方法已證明是一個(4logn+1)-近似演算法，它對於資源有限的感測器而言是較無負擔的，因為它的時間複雜度為O(n^2)，可在多項式時間內完成，及空間複雜度僅有O(n)；在實驗上，我們調整不同參數以產生不同類型的例子，及在這些例子上執行我們提出的近似演算法，將其結果與一個貪婪演算法做比較，亦證明我們的方法在不同狀況下皆優於此貪婪演算法，更有效的降低感測器所需要收集的資料量。

關鍵字

共享式無線感測網路；資料收集；區間感測問題

並列摘要

Shared wireless sensor network is a popular solution nowadays for reducing deployment cost. Sensors in it are shared to multiple applications. Meanwhile, they suffer more workload to satisfy more tasks from these applications. Fortunately, sharing data to multiple tasks is useful to decrease workload, as long as a shared sensor can collect data efficiently. Our study focuses on interval sampling problem, each task in which need a continuous interval of data sampling during its tasks duration. It is different from the data collect problem in the past studies, which only need single data sampling for each task. We design a light weight algorithm to collect data efficiently for a sensor. The time complexity and memory complexity of it are O(n^2) and O(n), respectively, and it has a theoretic bound, which is 4logn+1. The effectiveness of our algorithm is proved in theoretical analysis. The experimental results also show that our algorithm outperforms the greedy algorithm proposed by [11] on different types of instances.

並列關鍵字

shared wireless sensor networks ； data collection ； interval sampling problem

參考文獻

[1] Bhattacharya, S., Saifullah, A., Chenyang Lu, Roman, G., "Multi-Application Deployment in Shared Sensor Networks Based on Quality of Monitoring," in IEEE RTAS, 2010.

[2] Stefano Basagni, Ladislau Blni, Petrika Gjanci, Chiara Petrioli, Cynthia A. Phillips, Damla Turgut, "Maximizing the Value of Sensed Information in Underwater Wireless Sensor Networks via an Autonomous Underwater Vehicle," in Proceedings of IEEE INFOCOM, 2014.

[3] Haofu Han, Jiadi Yu, Hongzi Zhu , Yingying Chen, Jie Yang, Yanmin Zhu, Xue Guangtao, Minglu Li, "SenSpeed: Sensing Driving Conditions to Estimate Vehicle Speed in Urban Environments," in Proceedings of IEEE INFOCOM, 2014.

[4] Ian F. Akyildiz, Tommaso Melodia, and Kaushik R. Chowdhury. "A survey on wireless multimedia sensor networks." Computer networks 51.4 (2007): 921-960.

[7] Yitao Hu, Jiao Tong, Xinbing Wang, Xiaoying Gan, "Critical Sensing Range for Mobile Heterogeneous Camera Sensor Networks," in Proceedings of IEEE INFOCOM, 2014.

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在共享式無線感測網路中之有效資料收集方法

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