Feng-Yuan Ren

Bio: Feng-Yuan Ren is an academic researcher from Tsinghua University. The author has contributed to research in topics: Network processor & TCP acceleration. The author has an hindex of 3, co-authored 3 publications receiving 59 citations. Previous affiliations of Feng-Yuan Ren include Intel.

Effective Data Aggregation Supported by Dynamic Routing in Wireless Sensor Networks

Abstract: Data aggregation is an main method to conserve energy in wireless sensor network (WSN) Prior work on data aggregation protocols are generally based on static routing schemes, such as tree-based, cluster-based or chain-based routing schemes Although they can save energy to some extent, in dynamic scenarios where the source nodes are changing frequently, they will not only incur high overhead to continuously reconstruct the routing but also can not reduce the communication overhead effectively Our work aims to design an effective data aggregation mechanism supported by dynamic routing (DASDR) which can adapt to different scenarios without incurring much overhead Enlightened by the concept of potential field in the discipline of physics, the dynamic routing in DASDR is designed based on two potential fields: depth potential field which guarantees packets reaching the sink at last and queue potential field which makes packets more spatially convergent and thus data aggregation will be more efficient Simulation results show that DASDR is more effective in energy savings as well as scales well with regard to the network size

AntiWorm NPU-based Parallel Bloom Filters for TCP/IP Content Processing in Giga-Ethernet LAN

Abstract: TCP/IP protocol suite carries most application data in Internet. TCP flow retrieval has more security meanings than the IP packet payload. Hence, monitoring the TCP flow has more strength than only monitoring the IP packet payload in the AntiWorm system. The main idea of this paper is to use the flexibility and high performance of network processors to scan TCP flow for locating worm's binary codes, and cut off their propagation. A stateful TCP flow inspection engine is implemented based on IXP network processor, which can monitor about 512K flows. The performance issues about IXP network processors are evaluated and collected, and an analysis is made for further optimizing the system performance. The system is also demonstrated and proved by using the Internet traces and real assaults of Worms. Software Package TCPScanner 1.0 is also given as a software release of the research

AntiWorm NPU-based Parallel Bloom filters in Giga-Ethernet LAN

Abstract: In this paper, an AntiWorm system based on the Intel IXP Network Processor was implemented using the Parallel Bloom filters technique. The AntiWorm system consists of two components: Bloom filters and Exact Matching engines. The Parallel Bloom filters can identify the suspicious traffic quickly and effectively, and then dispatch them to Exact Matching engines for further investigation. Both the principles and the implementation of the AntiWorm system are introduced in detail. With the consideration of the system performance parameters, two feasible implementation solutions are investigated and the advantages and disadvantages are also compared. The selections of configuration parameters of the AntiWorm system are also discussed. A hash scheme based on MD5's function is proposed for implementing fast hash functions. To test the performance of the AntiWorm system, such as throughput and delay, some experiments are carried out with different simulated traffic condition. The internal statistics of IXP network processor are also collected and analyzed for optimizing the system performance. To demonstrate the operation of the AntiWorm system, assaults by Worm Blaster are used in the test bed, and the experimental results prove the effectiveness of the AntiWorm system. The Software Package WormDetector1.0 is also provided as a software release from the research.

Data Aggregation in Wireless Sensor Networks: Previous Research, Current Status and Future Directions

Abstract: Wireless sensor networks (WSNs) consist of large number of small sized sensor nodes, whose main task is to sense the desired phenomena in a particular region of interest. These networks have large number of applications such as habitat monitoring, disaster management, security and military etc. Sensor nodes are very small in size and have limited processing capability as these nodes have very low battery power. WSNs are also prone to failure, due to low battery power constraint. Data aggregation is an energy efficient technique in WSNs. Due to high node density in sensor networks same data is sensed by many nodes, which results in redundancy. This redundancy can be eliminated by using data aggregation approach while routing packets from source nodes to base station. Researchers still face trouble to select an efficient and appropriate data aggregation technique from the existing literature of WSNs. This research work depicts a broad methodical literature analysis of data aggregation in the area of WSNs in specific. In this survey, standard methodical literature analysis technique is used based on a complete collection of 123 research papers out of large collection of 932 research papers published in 20 foremost workshops, symposiums, conferences and 17 prominent journals. The current status of data aggregation in WSNs is distributed into various categories. Methodical analysis of data aggregation in WSNs is presented which includes techniques, tools, methodology and challenges in data aggregation. The literature covered fifteen types of data aggregation techniques in WSNs. Detailed analysis of this research work will help researchers to find the important characteristics of data aggregation techniques and will also help to select the most suitable technique for data aggregation. Research issues and future research directions have also been suggested in this research literature.

CATT: potential based routing with content caching for ICN

Abstract: Information Centric Networking (ICN) has shown possibilities to solve several problems of the Internet. At the same time, some problems need to be tackled in order to advance this promising architecture. In this paper we address two of the problems, namely routing and content caching. For the routing, we introduce the Potential Based Routing (PBR) to achieve several design goals such as availability, adaptability, diversity, and robustness. In addition, we examine the performance of a random caching policy which can be a promising candidate for ICN. The integrated system of both PBR and a caching policy is named the Cache Aware Target idenTification (CATT). Simulation results demonstrate that PBR with replications located on less than 1% of total nodes can achieve a near optimal routing performance (close to the shortest path routing) even though a request message is randomly forwarded.

Darknet as a Source of Cyber Intelligence: Survey, Taxonomy, and Characterization

Abstract: Today, the Internet security community largely emphasizes cyberspace monitoring for the purpose of generating cyber intelligence. In this paper, we present a survey on darknet. The latter is an effective approach to observe Internet activities and cyber attacks via passive monitoring. We primarily define and characterize darknet and indicate its alternative names. We further list other trap-based monitoring systems and compare them to darknet. Moreover, in order to provide realistic measures and analysis of darknet information, we report case studies, namely, Conficker worm in 2008 and 2009, Sality SIP scan botnet in 2011, and the largest amplification attack in 2014. Finally, we provide a taxonomy in relation to darknet technologies and identify research gaps that are related to three main darknet categories: deployment, traffic analysis, and visualization. Darknet projects are found to monitor various cyber threat activities and are distributed in one third of the global Internet. We further identify that Honeyd is probably the most practical tool to implement darknet sensors, and future deployment of darknet will include mobile-based VOIP technology. In addition, as far as darknet analysis is considered, computer worms and scanning activities are found to be the most common threats that can be investigated throughout darknet; Code Red and Slammer/Sapphire are the most analyzed worms. Furthermore, our study uncovers various lacks in darknet research. For instance, less than 1% of the contributions tackled distributed reflection denial of service (DRDoS) amplification investigations, and at most 2% of research works pinpointed spoofing activities. Last but not least, our survey identifies specific darknet areas, such as IPv6 darknet, event monitoring, and game engine visualization methods that require a significantly greater amount of attention from the research community.

Q-Learning-Based Data-Aggregation-Aware Energy-Efficient Routing Protocol for Wireless Sensor Networks

Abstract: The energy consumption of the routing protocol can affect the lifetime of a wireless sensor network (WSN) because tiny sensor nodes are usually difficult to recharge after they are deployed. Generally, to save energy, data aggregation is used to minimize and/or eliminate data redundancy at each node and reduce the amount of the overall data transmitted in a WSN. Furthermore, energy-efficient routing is widely used to determine the optimal path from the source to the destination, while avoiding the energy-short nodes, to save energy for relaying the sensed data. In most conventional approaches, data aggregation and routing path selection are considered separately. In this study, we consider the degrees of the possible data aggregation of neighbor nodes when a node needs to determine the routing path. We propose a novel Q-learning-based data-aggregation-aware energy-efficient routing algorithm. The proposed algorithm uses reinforcement learning to maximize the rewards, defined in terms of the efficiency of the sensor-type-dependent data aggregation, communication energy and node residual energy, at each sensor node to obtain an optimal path. We used sensor-type-dependent aggregation rewards. Finally, we performed simulations to evaluate the performance of the proposed routing method and compared it with that of the conventional energy-aware routing algorithms. Our results indicate that the proposed protocol can successfully reduce the amount of data and extend the lifetime of the WSN.