標題: | 在行動隨意網路中利用群集與情境資訊的服務發現 Service Discovery using Cluster and Context Information in Mobile Ad Hoc Networks |
作者: | 潘律甫 Pan, Lu-Fu 羅濟群 Lo, Chi-Chun 資訊管理研究所 |
關鍵字: | 隨意網路;服務發現;情境資訊;MANET;Service Discovery Protocol;Context Information |
公開日期: | 2013 |
摘要: | 隨著動態網路與行動隨意網路(MANET)的發展,服務發現(Service Discovery)機制在行動隨意網路中可進行資源和服務的共享,因此,如何在行動節點的電力和儲存能力有限的情況下,快速發現正確可用服務的服務發現機制足以影響整個行動隨意網路系統的效能。GSD (Group-based Service Discovery Protocol)為隨意網路中典型的服務發現協定,但是有太多的冗餘封包傳送造成大量的網路傳輸量(Network Overhead),為了改善這個情況,本論文提出了一個基於群集與情境資訊的隨意網路發現機制: Context Node enhanced Group-based Service Discovery Protocol (CNGSD),利用群集的型式搭配群組資訊來達到需求封包轉送、增加服務發現的效率與減少冗餘封包的傳送。此外透過情境資訊能夠讓使用者取得更適合的服務,本論文利用NS-3進行實驗模擬,模擬結果顯示了CNGSD與GSD的比較,CNGSD具有較好的服務發現效能,平均少了71.2%網路傳輸量;回應時間也比較快,平均加速了44.5%。 With growing of dynamic networks and mobile ad hoc network (MANET), service discovery is prerequisite part in pervasive environment. It can share the resources and services of MANET. In the case of limited power and storage capacity of the mobile node, an effective mechanism for discovering service affects the performance of the system. GSD (Group-based Service Discovery Protocol) is a typical service discovery protocol in MANET, but it creates enormous network overhead due to redundant packet transmission. In this paper, a cluster-based and context information service discovery approach: Context Node enhanced Group-based Service Discovery Protocol (CNGSD) is proposed. In form of clustering with group information leads to intelligence forwarding the request packets, increase performance of service discovery, and reduce redundant disseminative packets. Besides, clients can get better service matching by using context information. In this paper, we use GSD as benchmark and compare with CNGSD in NS-3. Simulation results show that our approach has better performance than GSD with an average 71.2% less network overhead. The response time also accelerated with an average of 44.5%. |
URI: | http://140.113.39.130/cdrfb3/record/nctu/#GT070053411 http://hdl.handle.net/11536/71549 |
顯示於類別: | 畢業論文 |