Feilong Tang

Discriminating DDoS Attacks from Flash Crowds Using Flow Correlation Coefficient

Distributed Denial of Service (DDoS) attack is a critical threat to the Internet, and botnets are usually the engines behind them. Sophisticated botmasters attempt to disable detectors by mimicking the traffic patterns of flash crowds. This poses a critical challenge to those who defend against DDoS attacks. In our deep study of the size and organization of current botnets, we found that the current attack flows are usually more similar to each other compared to the flows of flash crowds. Based on this, we proposed a discrimination algorithm using the flow correlation coefficient as a similarity metric among suspicious flows. We formulated the problem, and presented theoretical proofs for the feasibility of the proposed discrimination method in theory. Our extensive experiments confirmed the theoretical analysis and demonstrated the effectiveness of the proposed method in practice.

A Distance-Based Directional Broadcast Protocol for Urban Vehicular Ad Hoc Network

The topology of a vehicular ad hoc network (VANET) changes rapidly due to high-speed movement of vehicles, so traditional mobile ad hoc network (MANET) broadcast protocol may not work efficiently in VANET. This paper proposes a distance-based broadcast protocol called Efficient Directional Broadcast (EDB) for VANET using directional antennas. In EDB, only the furthest receiver is responsible to forward the packet in the opposite direction where the packet arrives. Besides, a directional repeater located at the intersection helps disseminating the packets to the vehicles on other road segments of different directions. We evaluate the performance of EDB based on a real mobility model generated by live GPS data of taxis in the city of Shanghai. The result shows that EDB is effective and favorable for VANET.

A chain-cluster based routing algorithm for wireless sensor networks

Wireless sensor networks (WSNs) are an emerging technology for monitoring physical world. Different from the traditional wireless networks and ad hoc networks, the energy constraint of WSNs makes energy saving become the most important goal of various routing algorithms. For this purpose, a cluster based routing algorithm LEACH (low energy adaptive clustering hierarchy) has been proposed to organize a sensor network into a set of clusters so that the energy consumption can be evenly distributed among all the sensor nodes. Periodical cluster head voting in LEACH, however, consumes non-negligible energy and other resources. While another chain-based algorithm PEGASIS (power- efficient gathering in sensor information systems) can reduce such energy consumption, it causes a longer delay for data transmission. In this paper, we propose a routing algorithm called CCM (Chain-Cluster based Mixed routing), which makes full use of the advantages of LEACH and PEGASIS, and provide improved performance. It divides a WSN into a few chains and runs in two stages. In the first stage, sensor nodes in each chain transmit data to their own chain head node in parallel, using an improved chain routing protocol. In the second stage, all chain head nodes group as a cluster in a self- organized manner, where they transmit fused data to a voted cluster head using the cluster based routing. Experimental results demonstrate that our CCM algorithm outperforms both LEACH and PEGASIS in terms of the product of consumed energy and delay, weighting the overall performance of both energy consumption and transmission delay.

LABERIO: Dynamic load-balanced Routing in OpenFlow-enabled Networks

In data center networks, how to balance workloads is a key issue with the fast growth of network applications. Open Flow protocol, which is a competitive candidate for solving the problem, provides each user the programmatic control for specific flows, so as to determine their paths through a network. However, existing solutions based on Open Flow only try to find a static routing path during initialization step while the static routing path often suffers from poor performance since the network configuration may change during the data transmission. To solve the problem, this paper proposes LABERIO, a novel path-switching algorithm, to balance the traffic dynamically during the transmission. Experiments on two kinds of network architectures demonstrate that LABERIO outperform other typical load balancing algorithms like Round Robin and LOBUS by reducing up to 13% transmission time.

Towards Context-Aware Workflow Management for Ubiquitous Computing

Ubiquitous computing is a user-centric distributed computing paradigm, allowing users to access to their preferred services even while moving around. To make such a vision a reality, context-aware workflow management is one of key issues because the context of ubiquitous applications is highly varying. In this paper, we propose a context model for intelligent campus navigation applications, then present a context-adaptive workflow management algorithm which can dynamically adjust workflow execution policies in terms of current context information. Moreover, we model the workflow management algorithm in Petri nets. Our context model and workflow management algorithm may be easily extended to other ubiquitous applications with a little change on context structure.

A Joint Design for Distributed Stable Routing and Channel Assignment Over Multihop and Multiflow Mobile Ad Hoc Cognitive Networks

Data communication in mobile ad hoc cognitive networks (MACNets) significantly suffers from link instability and channel interference. The availability and stability of each link in MACNets highly depends on not only the relative movement of neighbor nodes but also the adjacent communication among primary nodes and among cognitive nodes. In multihop and multiflow MACNets, this problem becomes even worse because multiple links potentially interfere with each other. In this paper, we propose a cross-layer distributed approach, called mobility-prediction-based joint stable routing and channel assignment (MP-JSRCA), to maximize the network throughput by jointly selecting stable routes and assigning channels avoiding inter- and intra-flow interferences based on mobility prediction. To quantitatively measure the communication quality of links, we propose a new metric data transmission cost (DTC) that captures node mobility, impact to primary nodes, and channel conflict among cognitive nodes. In our MP-JSRCA, each relay node selects the best link with the smallest DTC as the next hop, within a specified sector region towards the destination. NS2-based simulation results demonstrate that our MP-JSRCA algorithm significantly improves network throughput, and the higher degree of interference MACNets experience, the more improvement can be achieved.

A Transaction Model for Grid Computing

In Grid environment, transaction must have the abilities to coordinate both short-lived operations and long-lived business activities, which can not directly be supported by traditional distributed transaction mechanisms. This paper introduces a transaction model based on agent technologies to satisfy these requirements. The model can coordinate both Atomic transaction and Compensation transaction. The agents shield users from complex transaction process. For two types of transactions, we respectively analyze the coordination mechanisms and provide corresponding algorithms. We also discuss the implementation of this model and propose a security solution.

Wireless Mesh Sensor Networks in Pervasive Environment: a Reliable Architecture and Routing Protocol

Wireless mesh sensor network (WMSN) merges advantages of wireless mesh networks and wireless sensor networks, especially on scalability, robustness and balanced energy dissipation. Routing in WMSNs faces with more challenges than that in traditional sensor networks on account of multiple sink nodes and the mobility of nodes. This paper focuses on two challenging problems. Firstly, we propose a reliable architecture of WMSNs by deploying multiple mobile mesh nodes in each sensor network to collect sensed data, which improves the scalability and performance of WMSNs. Also, we design a routing protocol characteristic to WMSNs. The routing protocol aims at maximizing the lifetime of sensor networks by reducing total energy consumption of a sensor network, as well as balancing energy usage among sensor nodes.

Mobility Prediction Based Joint Stable Routing and Channel Assignment for Mobile Ad Hoc Cognitive Networks

Link instability and channel interference cause significant performance degradation to mobile ad hoc cognitive networks (MACNets). Existing work designs routing and assigns channels separately or does not consider mobility prediction and channel vacation to primary nodes. In this paper, we investigate how to jointly optimize route setup and channel assignment. Firstly, we propose an integrated data transmission cost (IDTC) to quantitatively measure the communication quality of links. This novel routing metric IDTC integratively considers 1) node mobility, 2) co-channel interference among primary and cognitive nodes, 3) relay workload on a specified channel, and 4) distance between the relay and the destination node. We, then, design channel assignment algorithms that completely avoid the interference with primary nodes and minimize the conflict to cognitive nodes. Finally, we propose a joint stable routing and channel assignment (J-SRCA) protocol based on mobility prediction for the network throughput maximization. In our J-SRCA, each link selected hop by hop is simultaneously assigned an interference-avoiding channel during a route setup. NS2-based simulation results demonstrate that our J-SRCA significantly improves various network performance, and the higher interference degree cognitive networks experience, the more improvement our J-SRCA will bring to the networks.

Transaction Management for Reliable Grid Applications

Transaction management in Grids is responsible for ensuring the reliable execution of inherently distributed Grid applications. Grid transaction management is different from existing distributed transaction models because Grid resources are highly autonomous, dynamic and heterogeneous. This paper proposes a Grid transaction service (GridTS) and coordination algorithms that manage short-lived and long-lived Grid transactions respectively, providing reliability support for Grid applications. Unlike existing long-lived transaction models that require application programmers to develop compensating transactions, the GridTS can automatically generate compensating transactions during the execution of long-lived Grid transactions. The feasibility of GridTS and the effectiveness of proposed coordination algorithms are demonstrated through simulation studies.