本文選題：無線傳感器網(wǎng)絡(luò)　切入點(diǎn)：數(shù)據(jù)壓縮　出處：《中南大學(xué)》2014年碩士論文

【摘要】：能量是無線傳感器網(wǎng)絡(luò)(Wireless Sensor Networks,WSN)極其重要而有限的資源,而節(jié)點(diǎn)絕大部分能量都消耗在無線數(shù)據(jù)通信上,如何高效利用能量是WSN面臨的關(guān)鍵問題�；赪SN監(jiān)測數(shù)據(jù)的時(shí)、空相關(guān)性,數(shù)據(jù)壓縮能有效減少通信數(shù)據(jù)量,是傳感器節(jié)點(diǎn)重要的節(jié)能手段。然而,數(shù)據(jù)壓縮減少通信能耗的同時(shí),節(jié)點(diǎn)的處理能耗也增加。因此,如何極大限度的提高數(shù)據(jù)壓縮的能量收益,是降低系統(tǒng)能耗的關(guān)鍵所在。 數(shù)據(jù)壓縮算法的能效主要涉及能效性評(píng)估方法和能效提高方法。因此,本文主要研究了面向一般硬件平臺(tái)的數(shù)據(jù)壓縮能效評(píng)估方案、數(shù)據(jù)壓縮的源程序級(jí)能耗優(yōu)化方法和具有發(fā)射功耗感知的數(shù)據(jù)壓縮三個(gè)問題。 為了更加客觀有效地評(píng)價(jià)具體數(shù)據(jù)壓縮方法所能實(shí)現(xiàn)的節(jié)能效果,本文在已有評(píng)估準(zhǔn)則的基礎(chǔ)上,給出了硬件因素和算法因素分離的數(shù)據(jù)壓縮算法的能效性評(píng)估方案；為了提高壓縮算法程序運(yùn)行效率,降低算法自身能量消耗,研究并提出了針對(duì)數(shù)據(jù)壓縮算法的程序級(jí)節(jié)能優(yōu)化方法；為了使數(shù)據(jù)壓縮算法在無線發(fā)射功率進(jìn)行調(diào)節(jié)時(shí)仍能保持節(jié)能收益,提出了可適應(yīng)發(fā)射功率變化壓縮算法調(diào)整機(jī)制。 本文通過對(duì)能效性評(píng)估、源程序節(jié)能優(yōu)化和壓縮算法調(diào)整等三個(gè)方面的方法研究、方案設(shè)計(jì)來提高數(shù)據(jù)壓縮的能效性,并以典型節(jié)點(diǎn)的硬件平臺(tái)資源條件為例,通過計(jì)算、測試驗(yàn)證了本文所提方法、方案的可行性和有效性,理論分析計(jì)算和實(shí)驗(yàn)結(jié)果都表明所提出的方法能有效提高無線傳感器節(jié)點(diǎn)的整體節(jié)能效率。圖28副,表18個(gè),參考文獻(xiàn)90篇。
[Abstract]:Energy is an extremely important and limited resource for Wireless Sensor Networks (WSNs) in wireless sensor networks, and most of the energy of nodes is consumed in wireless data communication. How to utilize energy efficiently is a key problem for WSN.Spatial correlation and data compression can effectively reduce the amount of communication data based on WSN, which is an important energy saving method for sensor nodes.However, while data compression reduces communication energy consumption, node processing energy consumption also increases.Therefore, how to greatly improve the energy return of data compression is the key to reduce system energy consumption.The energy efficiency of data compression algorithm is mainly related to energy efficiency assessment and energy efficiency improvement methods.Therefore, this paper mainly studies the energy efficiency evaluation scheme of data compression based on general hardware platform, the optimization method of source code level energy consumption of data compression and the data compression with transmit power sensing.In order to evaluate more objectively and effectively the energy saving effect achieved by specific data compression methods, this paper presents an energy efficiency evaluation scheme of data compression algorithm based on the existing evaluation criteria, in which hardware factors and algorithm factors are separated.In order to improve the efficiency of the compression algorithm program and reduce the energy consumption of the algorithm, a program-level energy saving optimization method for the data compression algorithm is studied and proposed.In order to keep the energy saving benefit of the data compression algorithm when the wireless transmission power is adjusted, the adaptive algorithm adjustment mechanism is proposed.In this paper, the energy efficiency evaluation, the optimization of source code and the adjustment of compression algorithm are studied, and the scheme is designed to improve the energy efficiency of data compression. Taking the resource condition of hardware platform of typical node as an example, the calculation is carried out.The test results show that the proposed method is feasible and effective. The theoretical analysis and experimental results show that the proposed method can effectively improve the overall energy-saving efficiency of wireless sensor nodes.There are 28 pairs of figs, 18 tables and 90 references.
【學(xué)位授予單位】：中南大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TP212.9;TN929.5

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