隨著5G網路技術的快速發展，對於無線感測器網路需求不斷增長，他能夠收集、儲存和處理環境訊息，並有著低功耗、低成本、小尺寸、動態組網等特性。近年來在物聯網中，基於能量採集的無線感測器網路受到關注，而能源供應可能是來自太陽能、海洋能、水力、風力或是地熱等再生能源，但收集到的能量可能供不應求，因此我們額外加上一顆常規電池作為輔助能源。而常規電池的壽命也是有限的，為了研究能源消耗和常規電池的壽命之間的關係，我們定義了另外的效能指標“常規能耗比”。基於上述機制，我們進一步考慮了封包可能的屬性，包括非佔先優先權、無耐性，並且為了更貼近真實情形，將封包的抵達程序假設為批次抵達程序。為了簡化計算，我們假設批次抵達包括同時間到達一個封包或是兩個封包。此外，我們研究了兩種情境：（1）僅有一個節點；（2）一個由三節點相連而成的網路。我們透過四維的馬可夫鏈推導出解析模型的平衡方程式，透過迭代演算法得出穩態機率分佈和計算各項效能指標，再研究不同參數對於系統效能的影響。最後，我們使用C語言來撰寫電腦模擬程式，且在大部分的研究案例中，解析結果與模擬結果相當接近。

With the rapid development of 5G network technology, the demand for Wireless sensor networks (WSNs) continues to grow. Wireless sensor networks are capable of collecting, storing, and processing environmental information, with features such as low power consumption, low cost, small size, and dynamic networking. In recent years, Energy Harvesting-based WSNs have gained attention in the context of the Internet of Things (IoT). The energy supply for these networks may come from renewable sources such as solar energy, ocean energy, hydro energy, wind energy, or geothermal energy. However, the collected energy may not always meet the demand. To address this issue, we introduce an additional regular battery as an auxiliary energy source. The regular battery lifetime is also limited. In order to study the relationship between energy consumption and the lifetime of the regular battery, we define an additional performance metric called "regular energy consumption ratio (RECR)." Based on the aforementioned mechanisms, we further consider the possible attributes of packets, including non-preemptive priority and impatience, and for a more realistic scenario, we assume the packet arrival process to be a batch arrival process. For simplicity, we assume that a batch includes the arrival of one or two packets at a time. Additionally, we study two scenarios: (1) a system with a single node, and (2) a network composed of three interconnected nodes. We derive the balance equations of the analytical model through a four-dimensional Markov chain. We obtain the steady-state probability distribution and calculate various performance metrics using iterative algorithms. We then investigate the impact of different parameters on the system's performance. Finally, we use the C language to write the simulation programs and in the majority of research cases, the analytical results are in good agreement with the simulation results.

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