本文選題：邊緣計(jì)算 + 云計(jì)算�。� 參考：《計(jì)算機(jī)研究與發(fā)展》2017年05期

【摘要】：隨著物聯(lián)網(wǎng)的快速發(fā)展和4G/5G無線網(wǎng)絡(luò)的普及,萬物互聯(lián)的時(shí)代已經(jīng)到來,網(wǎng)絡(luò)邊緣設(shè)備數(shù)量的迅速增加,使得該類設(shè)備所產(chǎn)生的數(shù)據(jù)已達(dá)到澤字節(jié)(ZB)級(jí)別.以云計(jì)算模型為核心的集中式大數(shù)據(jù)處理時(shí)代,其關(guān)鍵技術(shù)已經(jīng)不能高效處理邊緣設(shè)備所產(chǎn)生的數(shù)據(jù),主要表現(xiàn)在:1)線性增長的集中式云計(jì)算能力無法匹配爆炸式增長的海量邊緣數(shù)據(jù);2)從網(wǎng)絡(luò)邊緣設(shè)備傳輸海量數(shù)據(jù)到云中心致使網(wǎng)絡(luò)傳輸帶寬的負(fù)載量急劇增加,造成較長的網(wǎng)絡(luò)延遲;3)網(wǎng)絡(luò)邊緣數(shù)據(jù)涉及個(gè)人隱私,使得隱私安全問題變得尤為突出;4)有限電能的網(wǎng)絡(luò)邊緣設(shè)備傳輸數(shù)據(jù)到云中心消耗較大電能.為此,以邊緣計(jì)算模型為核心的面向網(wǎng)絡(luò)邊緣設(shè)備所產(chǎn)生海量數(shù)據(jù)計(jì)算的邊緣式大數(shù)據(jù)處理應(yīng)運(yùn)而生,其與現(xiàn)有以云計(jì)算模型為核心的集中式大數(shù)據(jù)處理相結(jié)合,即二者相輔相成,應(yīng)用于云中心和網(wǎng)絡(luò)邊緣端的大數(shù)據(jù)處理,較好地解決了萬物互聯(lián)時(shí)代大數(shù)據(jù)處理中所存在的上述問題.邊緣計(jì)算中的"邊緣"是個(gè)相對(duì)的概念,指從數(shù)據(jù)源到云計(jì)算中心數(shù)據(jù)路徑之間的任意計(jì)算資源和網(wǎng)絡(luò)資源.邊緣計(jì)算的基本理念是將計(jì)算任務(wù)在接近數(shù)據(jù)源的計(jì)算資源上運(yùn)行.首先系統(tǒng)地介紹邊緣計(jì)算的概念和原理;其次,通過現(xiàn)有研究工作為案例(即云計(jì)算任務(wù)遷移、視頻分析、智能家居、智慧城市、智能交通以及協(xié)同邊緣),實(shí)例化邊緣計(jì)算的概念;最后,提出邊緣計(jì)算領(lǐng)域所存在的挑戰(zhàn).該文希望能讓學(xué)界和產(chǎn)業(yè)界了解和關(guān)注邊緣計(jì)算,并能夠啟發(fā)更多的學(xué)者開展邊緣式大數(shù)據(jù)處理時(shí)代邊緣計(jì)算模型的研究.
[Abstract]:With the rapid development of the Internet of things and the popularity of 4G/5G wireless network, the age of interconnection of all things has arrived, and the number of network edge devices has increased rapidly, which makes the data generated by this kind of devices have reached the level of ZB. In the era of centralized big data processing based on cloud computing model, its key technology can no longer efficiently handle the data generated by edge devices. The linear growth of centralized cloud computing capabilities can't match the explosive growth of massive edge data.) the transmission of massive data from network edge devices to the cloud center results in a sharp increase in the load of network bandwidth. The network edge data involves personal privacy, which makes the privacy security problem more prominent. 4) the network edge devices with limited power consumption consume a large amount of power to transmit data to the cloud center. Therefore, the edge big data processing based on the edge computing model, which is oriented to the massive data computing generated by the network edge devices, is combined with the existing centralized big data processing based on the cloud computing model. That is to say, they complement each other and are applied to the big data processing in the cloud center and the edge of the network, which solves the above problems in the big data processing in the age of interconnection of all things. "Edge" in edge computing is a relative concept, which refers to arbitrary computing resources and network resources from data sources to cloud computing center data paths. The basic idea of edge computing is to run computing tasks on computing resources close to the data source. First, the concept and principle of edge computing are introduced systematically. Secondly, through the existing research work as a case (i.e. cloud computing task migration, video analysis, smart home, smart city, The concept of intelligent traffic and collaborative edge computing is instantiated. Finally, the challenges in the field of edge computing are presented. This paper hopes to make the academic and industry understand and pay attention to edge computing, and can inspire more scholars to study edge computing model in the era of edge big data processing.
【作者單位】： 韋恩州立大學(xué)計(jì)算機(jī)科學(xué)系;安徽大學(xué)計(jì)算機(jī)科學(xué)與技術(shù)學(xué)院;
【基金】：國家自然科學(xué)基金面上項(xiàng)目(61572001) 安徽大學(xué)2016年博士科研啟動(dòng)經(jīng)費(fèi)項(xiàng)目(J01003214)~~
【分類號(hào)】：TP3

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