後來資料收集問題引起了很多關注。資料收集是涉及無線感測器網路壽命的最重要任務之一。已經提出了許多資料收集演算法用於收集連接的無線感測器網路的特定監視區域中的資料。然而，可以改進用於斷開的無線感測器網路（DWSN）的路徑建立以及用於這種資料收集的路徑的效率。本文提出了一種新的DWSN分區段資料獲取機制，構建了一個移動宿路徑，根據感測器節點的密度在每個段中選擇一組合適的資料獲取點，並從負載資料的點中收集資料。所提出的機制旨在實現DWSN中的每個感測器節點的完全連接，並且還均勻地分佈工作負載感測器節點以增加網路壽命。性能結果表明，所提演算法在網路生命週期，能耗，公平指數和效率指標方面優於現有方法。

Latterly Data collection issues have received much attention. Data collection is one of the foremost task that concerns lifetime of wireless sensor networks. Many data collection algorithms have been proposed for collecting data in particular monitoring regions of connected wireless sensor network. However, path establishment for Disconnected Wireless Sensor Network (DWSN) and the efficiency of the paths for such data collection can be improved. This paper proposes a novel Data collection mechanism for partitioned segments in DWSN, which constructs a mobile sink path, selects a set of opportune data collection points in each segment based on the density of sensor nodes and collects data from the points burdened with data. The proposed mechanism is intended to achieve full connectivity of each and every sensor node in the DWSN and also evenly distribute the workload sensor nodes to increase the network lifetime. The performance results demonstrated that the proposed algorithms outperform the existing approaches in terms of network lifetime, energy consumption, fairness index, and efficiency index.

Table of Contents

List of Figures	V
List of Tables	VI
Chapter 1. Introduction	- 1 -
Chapter 2. Related Works	- 5 -
Chapter 3. Problem Statement	- 12 -
3.1 Network Environment	- 12 -
3.2 Problem Formulation	- 15 -
Chapter 4. The Proposed Data Collection Path Algorithm	- 20 -
4.1 External path construction for connecting Segments	- 22 -
       4.1.1Task I: Establishment of the semi trail for Quadrilateral segments…. - 23-
       4.1.2 Task II: Extension of the trail for residual segments…………………-29- 
4.2 Internal path construction for energy balancing	- 32 -
       4.2.1 Task I: Grain course of internal path construction..............................- 32 -
       4.2.2 Task II: Fine course for internal path adjustment……………………- 34 -
Chapter 5. Performance Evaluation	- 37 -
Chapter 6. Conclusions	- 40 -
References	- 41 -
 
List of Figures
Fig. 1. Network environment.	- 21 -
Fig. 2. The example of External mobile sink path.	- 23 -
Fig. 3. The example of Detection of Pivot grid in DWSN.	- 25 -
Fig. 4. The example of Determination of Afferent grids.	- 27 -
Fig. 5. The example of Quadrilateral path construction.	- 28 -
Fig. 6. The example of joining a new segment to the Quadrilateral path.	- 30 -
Fig. 7. Internal path construction of an isolated segment. .	- 33 -
Fig. 8. Various scenarios of fine grid path In and Out.	- 35 -
Fig. 9. Sensor node deployment in an isolated segment..	- 38 -


 
List of Tables
TABLE I	- 11 -
TABLE II	- 14 -
TABLE III- 37 -

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