命名數(shù)據(jù)網(wǎng)絡(luò)中基于局部請求相似性的協(xié)作緩存路由機制
doi: 10.11999/JEIT140246
基金項目:
國家973計劃項目(2012CB315901),國家自然科學(xué)基金(61372121)和國家863計劃項目(2011AA01A103)資助課題
Collaborative Caching and Routing Scheme Based on Local Request Similarity in Named Data Networking
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摘要: 該文針對命名數(shù)據(jù)網(wǎng)絡(luò)(Named Data Networking, NDN)應(yīng)答內(nèi)容的高效緩存和利用問題,依據(jù)內(nèi)容請求分布的局域相似特征,提出一種協(xié)作緩存路由機制。緩存決策時,將垂直請求路徑上的冗余消除和水平局域范圍內(nèi)的內(nèi)容放置進行有效結(jié)合。垂直方向上,提出基于最大內(nèi)容活躍因子的路徑緩存策略,確定沿途轉(zhuǎn)發(fā)對應(yīng)的最大熱點請求區(qū)域;水平方向上,采用一致性Hash協(xié)同緩存思想,實現(xiàn)應(yīng)答內(nèi)容的局域定向存儲。路由查找時,將局域節(jié)點緩存引入到路由轉(zhuǎn)發(fā)決策中,依據(jù)內(nèi)容活躍等級動態(tài)執(zhí)行局域緩存查找,增大內(nèi)容請求就近響應(yīng)概率。該機制減小了內(nèi)容請求時延和緩存冗余,提高了緩存命中率,以少量額外的代價換取了內(nèi)容請求開銷的大幅下降,仿真結(jié)果驗證了其有效性。
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關(guān)鍵詞:
- 互聯(lián)網(wǎng) /
- 命名數(shù)據(jù)網(wǎng)絡(luò)(NDN) /
- 內(nèi)容路由 /
- 緩存策略 /
- 請求相似性
Abstract: How to efficiently cache and take advantage of largely distributed copies poses challenges to the retrieval process of Named Data Networking (NDN). On the basis of similarity in local request, a collaborative caching and routing scheme is proposed. In the scheme, redundancy elimination in vertical requesting path and collaborative cache in horizontal local scope are effectively combined on the caching decision-making. In the vertical direction, the similar community which has the highest active value along the content delivery path is calculated based on the path caching strategy. In the horizontal direction, consistent Hash-caching is implemented to fulfill the oriented cache for the requested data in the vicinity. When a retrieve is requested, the proposed scheme dynamically performs the local lookup according to the content popularity by introduction of the local cache factor into the routing process. The simulation results show that the scheme can decrease the request latency, reduce the cache redundancy, and achieve higher cache hit ratio by comparison with existing methods.-
Key words:
- Internet /
- Named Date Networking (NDN) /
- Content-based routing /
- Caching strategy /
- Request similarity
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