在無線感測網路之中，覆蓋問題是一個被廣泛探討的議題，然而，要同時考慮覆蓋及感測器之間的電量平衡仍然是一大挑戰。本論文的主要是希望在監控目標區域使用最少數量的感測器即可達成監控之目的，同時使整體網路的生命週期能夠盡量延長。為了要延長網路的壽命，因此，提出一套提出了聯合覆蓋和能量平衡機制，使每顆感測器的電量消耗能夠平均，進而延長整體網路的壽命。此算法主要由三個階段組成：第一階段，計算每環節內感測器的數量，且計算能夠覆蓋目標監控區域感測器的數量。第二階段，計算傳輸時，感測器所耗費的電量，且為了讓電量較低的感測器能夠減緩能量消耗，將尚未喚醒的感測器排入監控的工作，來平衡整的工作量。第三階段，將能夠互相通訊的感測器設為群組。基於最佳距離和退避技術，在傳感器及其鄰居之間實現全分佈式調度算法，以最大限度地提高網絡使用壽命，實現全覆蓋，並延長網絡使用壽命，同時在環中轉發數據包。
最後，將與其他論文作法的模擬比較，可以看出，本論文提出的機制在網路壽命和能量平衡程度方面優於現有的研究。

Coverage is an important issue that has been widely discussed in wireless sensor networks (WSNs). However, it is still a big challenge to achieve both purposes of full coverage and energy balance. This paper considers the area coverage problem for a WSN in which the number the used sensors is minimal within concentric rings of proportional width, where the goal is to guarantee energy balance within the entire monitored region and aim to achieve full coverage at all times. To prolong the network lifetime, a Joint Coverage and Energy Balance mechanism is proposed as a tool for determining the power levels of each ring in order to add additional sensors responsible for replenishing the network. Creating a perpetual environmental network able to monitor and cover the desired area with controlled and balanced energy capability is relevant due to it being a novelty on the field, to our best knowledge. The proposed mechanism mainly consists of three phases.
In the first phase, each ring calculates the number of sensors and the coverage area responsible for monitoring the area of interest is also calculated. In the second phase, the copious amount of energy wasted transferring packets among rings is dealt with. The energy availability and energy consumption levels among rings are calculated and additional sensors are added to the network with the purpose of replenishing the energy levels. In the last phase, the sensors further aggregate into several groups making use of sensing capabilities, communication range and constraints. Based on optimal distance and backoff techniques, a totally distributed scheduling algorithm is implemented among sensors and their neighbors for maximizing network lifetime to achieve full coverage and perpetuate the lifetime of our network while forwarding data packets among rings. 
Performance evaluation and analysis reveal that the proposed mechanism outperforms the existing studies in terms of the network lifetime and the degree of energy balance.

Contents
List of Figures	V
List of Tables	VI
Chapter 1. Introduction	- 1 -
1.1 Motivation for a Wireless Sensor Network	- 1 -
1.2. Definitions and Background	- 2 -
1.2.1 Sensors and sensing	- 2 -
1.2.2 Sensor Classification	- 5 -
1.2.3 Wireless Sensor Networks	- 6 -
1.3. Challenges and Constraints	- 8 -
1.3.1 Routing	- 8 -
1.3.2 Energy	- 8 -
1.3.3 Wireless Networking	- 9 -
1.3.4 Real world applications	- 10 -
Chapter 2. Related Works	- 12 -
2.1 Coverage	- 12 -
2.2 Energy Balance	- 14 -
2.3 Power Consumption	- 14 -
Chapter 3. Problem Statement	- 16 -
3.1 Network Model	- 17 -
3.2 Coverage Phase	- 20 -
3.2.1 Coverage area explanation	- 21 -
3.3 Energy Balance Phase	- 25 -
3.3.1 Energy availability comparison	- 28 -
3.3.2 Energy consumption	- 29 -
3.4 Node Scheduling Component	- 32 -
Chapter 4. Performance Analysis	- 40 -
4.1	Summary	- 42 -
Chapter 5 Conclusion	- 44 -
References	- 46 -

List of Figures
Fig.1. Human body senses	- 3 -
Fig 2. Data collection and actuation	- 4 -
Fig.3. Monitored region with three neighboring sensors in Optimal Deployment	- 18 -
Fig 4. Network environment and element description	- 19 -
Fig. 5. Triangle area illustration	- 22 -
Fig. 6. Network system with energy comparison, group selection (G1,G2, G3) and distinct ring lifetimes.	- 31 -
Fig. 7. Full coverage achieved	- 33 -
Fig. 8. Proximity constraint illustration.	- 33 -
Fig. 9. Overlay constraint illustration.	- 34 -
Fig. 10. Sensor categorization according to distance	- 36 -
Fig.11.Totally distributed Backoff Scheduling	- 39 -
Fig. 12. Energy consumption representation graph	- 41 -
Fig. 13. Energy availability representation graph	- 42 -

List of Tables
Table 1. Classification and examples of sensors	- 5 -
Table 2 Simulation Parameters used in this paper	- 40 -

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