http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
- 中文 을 입력하시려면 zhongwen을 입력하시고 space를누르시면됩니다.
- 北京 을 입력하시려면 beijing을 입력하시고 space를 누르시면 됩니다.
RISS 인기검색어
- 검색키워드
- 저자 : Peidong Zhu (검색결과 4 건)
- 무료
- 기관 내 무료
- 유료
-
Scaling Inter-domain Routing System via Path Exploration Aggregation
( Xiaoqiang Wang ),( Peidong Zhu ),( Xicheng Lu ),( Kan Chen ),( Huayang Cao ) 한국인터넷정보학회 2013 KSII Transactions on Internet and Information Syst Vol.7 No.3
One of the most important scalability issues facing the current Internet is the rapidly increasing rate of BGP updates (BGP churn), to which route flap and path exploration are the two major contributors. Current countermeasures would either cause severe reachability loss or delay BGP convergence, and are becoming less attractive for the rising concern about routing convergence as the prevalence of Internet-based real time applications. Based on the observation that highly active prefixes usually repeatedly explore very few as-paths during path exploration, we propose a router-level mechanism, Path Exploration Aggregation (PEA), to scale BGP without either causing prefix unreachable or slowing routing convergence. PEA performs aggregation on the transient paths explored by a highly active prefix, and propagates the aggregated path instead to reduce the updates caused by as-path changes. Moreover, in order to avoid the use of unstable routes, PEA purposely prolongs the aggregated path via as-path prepending to make it less preferred in the perspective of downstream routers. With the BGP traces obtained from RouteViews and RIPE-RIS projects, PEA can reduce BGP updates by up to 63.1%, shorten path exploration duration by up to 53.3%, and accelerate the convergence 7.39 seconds on average per routing event.
-
Modeling and Evaluating Information Diffusion for Spam Detection in Micro-blogging Networks
( Kan Chen ),( Peidong Zhu ),( Liang Chen ),( Yueshan Xiong ) 한국인터넷정보학회 2015 KSII Transactions on Internet and Information Syst Vol.9 No.8
Spam has become one of the top threats of micro-blogging networks as the representations of rumor spreading, advertisement abusing and malware distribution. With the increasing popularity of micro-blogging, the problems will exacerbate. Prior detection tools are either designed for specific types of spams or not robust enough. Spammers may escape easily from being detected by adjusting their behaviors. In this paper, we present a novel model to quantitatively evaluate information diffusion in micro-blogging networks. Under this model, we found that spam posts differ wildly from the non-spam ones. First, the propagations of non-spam posts mostly result from their followers, but those of spam posts are mainly from strangers. Second, the non-spam posts relatively last longer than the spam posts. Besides, the non-spam posts always get their first reposts/comments much sooner than the spam posts. With the features defined in our model, we propose an RBF-based approach to detect spams. Different from the previous works, in which the features are extracted from individual profiles or contents, the diffusion features are not determined by any single user but the crowd. Thus, our method is more robust because any single user`s behavior changes will not affect the effectiveness. Besides, although the spams vary in types and forms, they`re propagated in the same way, so our method is effective for all types of spams. With the real data crawled from the leading micro-blogging services of China, we are able to evaluate the effectiveness of our model. The experiment results show that our model can achieve high accuracy both in precision and recall.
-
Shedding Light on the Use of AS Relationships for Path Inference
Wenping Deng,Wolfgang Mühlbauer,Yuexiang Yang,Peidong Zhu,Xicheng Lu,Bernhard Plattner 한국통신학회 2012 Journal of communications and networks Vol.14 No.3
Autonomous system (AS) business relationships and their inference have been widely studied by network researchers in the past. An important application of inferred AS relationships can be the prediction of AS paths between a source and destination AS within a model. However, besides knowing the topology and inferred AS relationships, AS path prediction within a model needs to be understood in order for us to know how we can derive border gateway protocol (BGP) policies from AS relationships. In this paper, we shed light onto the predictive capabilities of AS relationships by investigating whether they can be translated into BGP policies such that inferred AS paths are consistent with real AS paths, e.g., paths observed from BGP routing tables. Our findings indicate that enforcing constraints such as the well-known valley-free property and the widely assumed preference of customer routes always results in a very low consistency for AS path inference. In addition, this is true irrespective of whether customer,peer, or provider routes are preferred. Apparently, applying such constraints eliminates many “correct” paths that are observed in BGP routing tables and that are propagated in a simple shortest path model where AS relationships are ignored. According to our findings, deriving BGP routing policies for predicting with high accuracy AS paths in a model directly from AS relationships is still difficult.
-
Shedding Light on the Use of AS Relationships for Path Inference
Deng, Wenping,Muhlbauer, Wolfgang,Yang, Yuexiang,Zhu, Peidong,Lu, Xicheng,Plattner, Bernhard The Korea Institute of Information and Commucation 2012 Journal of communications and networks Vol.14 No.3
Autonomous system (AS) business relationships and their inference have been widely studied by network researchers in the past. An important application of inferred AS relationships can be the prediction of AS paths between a source and destination AS within a model. However, besides knowing the topology and inferred AS relationships, AS path prediction within a model needs to be understood in order for us to know how we can derive border gateway protocol (BGP) policies from AS relationships. In this paper, we shed light onto the predictive capabilities of AS relationships by investigating whether they can be translated into BGP policies such that inferred AS paths are consistent with real AS paths, e.g., paths observed from BGP routing tables. Our findings indicate that enforcing constraints such as the well-known valley-free property and the widely assumed preference of customer routes always results in a very low consistency for AS path inference. In addition, this is true irrespective of whether customer, peer, or provider routes are preferred. Apparently, applying such constraints eliminates many "correct" paths that are observed in BGP routing tables and that are propagated in a simple shortest path model where AS relationships are ignored. According to our findings, deriving BGP routing policies for predicting with high accuracy AS paths in a model directly from AS relationships is still difficult.
ScienceON
KISS연관 검색어 추천
이 검색어로 많이 본 자료
활용도 높은 자료
