Weijia Jia

Vertex Cover

Recently, there has been increasing interest and progress in lowering the worst-case time complexity for well-known NP-hard problems, particularly for the Vertex Cover problem. In this paper, new properties for the Vertex Cover problem are indicated, and several simple and new techniques are introduced, which lead to an improved algorithm of time O(kn+1.2852k) for the problem. Our algorithm also induces improvement on previous algorithms for the Independent Set problem on graphs of small degree.

Rendezvous design algorithms for wireless sensor networks with a mobile base station

Recent research shows that significant energy saving can be achieved in wireless sensor networks with a mobile base station that collects data from sensor nodes via short-range communications. However, a major performance bottleneck of such WSNs is the significantly increased latency in data collection due to the low movement speed of mobile base stations. To address this issue, we propose a rendezvous-based data collection approach in which a subset of nodes serve as the rendezvous points that buffer and aggregate data originated from sources and transfer to the base station when it arrives. This approach combines the advantages of controlled mobility and in-network data caching and can achieve a desirable balance between network energy saving and data collection delay. We propose two efficient rendezvous design algorithms with provable performance bounds for mobile base stations with variable and fixed tracks, respectively. The effectiveness of our approach is validated through both theoretical analysis and extensive simulations.

Complete optimal deployment patterns for full-coverage and k-connectivity (k≤6) wireless sensor networks

In this paper, we propose deployment patterns to achieve full coverage and three-connectivity, and full coverage and five-connectivity under different ratios of sensor communication range (denoted by Rc) over sensing range (denoted by Rs) for wireless sensor networks (WSNs). We also discover that there exists a hexagon-based universally elemental pattern which can generate all known optimal patterns. The previously proposed Voronoi-based approach can not be applied to prove the optimality of the new patterns due to their special features. We propose a new deployment-polygon based methodology, and prove their optimality among regular patterns when Rc/Rs ≥ 1. We conjecture that our patterns are globally optimal to achieve full coverage and three-connectivity, and full coverage and five-connectivity, under all ranges of Rc/Rs. With these new results, the set of optimal patterns to achieve full coverage and k-connectivity (k≤6) is complete, for the first time.

Rendezvous Planning in Wireless Sensor Networks with Mobile Elements

Recent research shows that significant energy saving can be achieved in wireless sensor networks by using mobile elements (MEs) capable of carrying data mechanically. However, the low movement speed of MEs hinders their use in data-intensive sensing applications with temporal constraints. To address this issue, we propose a rendezvous-based approach in which a subset of nodes serve as the rendezvous points (RPs) that buffer data originated from sources and transfer to MEs when they arrive. RPs enable MEs to collect a large volume of data at a time without traveling long distances, which can achieve a desirable balance between network energy saving and data collection delay. We develop two rendezvous planning algorithms, RP-CP and RP-UG. RP-CP finds the optimal RPs when MEs move along the data routing tree while RP-UG greedily chooses the RPs with maximum energy saving to travel distance ratios. We design the rendezvous-based data collection protocol that facilitates reliable data transfers from RPs to MEs in presence of significant unexpected delays in ME movement and network communication. Our approach is validated through extensive simulations.

Traceback of DDoS Attacks Using Entropy Variations

Distributed Denial-of-Service (DDoS) attacks are a critical threat to the Internet. However, the memoryless feature of the Internet routing mechanisms makes it extremely hard to trace back to the source of these attacks. As a result, there is no effective and efficient method to deal with this issue so far. In this paper, we propose a novel traceback method for DDoS attacks that is based on entropy variations between normal and DDoS attack traffic, which is fundamentally different from commonly used packet marking techniques. In comparison to the existing DDoS traceback methods, the proposed strategy possesses a number of advantages - it is memory nonintensive, efficiently scalable, robust against packet pollution, and independent of attack traffic patterns. The results of extensive experimental and simulation studies are presented to demonstrate the effectiveness and efficiency of the proposed method. Our experiments show that accurate traceback is possible within 20 seconds (approximately) in a large-scale attack network with thousands of zombies.

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.

Optimal Deployment Patterns for Full Coverage and

In this paper, we study deployment patterns to achieve full coverage and <i>k</i> -connectivity <i>(k</i> ≤ 6) under different ratios of the sensor communication range (denoted by <i>R</i>_c) to the sensing range (denoted by <i>R</i>_s) for homogeneous wireless sensor networks (WSNs). In particular, we propose new patterns for 3- and 5-connectivity. We also discover that there exists a hexagon-based universally elemental pattern that can generate all known optimal patterns. The previously proposed Voronoi-based approach cannot be applied to prove the optimality of the new patterns due to their special features. We propose a new deployment-polygon-based methodology. We prove the optimality of deployment patterns to achieve 3-connectivity, 4-connectivity, and 5-connectivity for certain ranges of <i>R</i>_c/<i>R</i>_s, respectively, and prove the optimality of deployment patterns to achieve 6-connectivity under all ranges of <i>R</i>_c/<i>R</i>_s.

k

Vehicular networks are experiencing rapid growth and evolution under the increasing demand of vehicular traffic management and ubiquitous network connectivity. In particular, the amount of information to be downloaded from the roadside-deployed gateways is dramatically increasing. Infected by high mobility, intermittent connectivity, and unreliability of the wireless channel, it is challenging to satisfy the need for massive data transmission in vehicular networks. In this paper, we propose a novel protocol called vehicular cooperative media access control (VC-MAC), which utilizes the concept of cooperative communication tailored for vehicular networks, particularly for gateway-downloading scenarios. VC-MAC leverages the broadcast nature of the wireless medium to maximize the system throughput. Spatial diversity and user diversity are exploited by concurrent cooperative relaying to overcome the unreliability of the wireless channel in vehicular networks. We theoretically analyze the selection of an optimal relay set using a weighted independent set (WIS) model and then design a backoff mechanism to select the optimal relays in a distributed manner. We have carried out extensive simulations to demonstrate that VC-MAC effectively enhances cooperative information downloading and significantly increases the system throughput compared with existing strategies.

-Connectivity

Research shows that significant energy saving can be achieved in wireless sensor networks by using mobile elements (MEs) capable of carrying data mechanically. However, the low movement speed of MEs hinders their use in data-intensive sensing applications with temporal constraints. To address this issue, we propose a rendezvous-based approach in which a subset of nodes serve as the rendezvous points (RPs) that buffer data originated from sources and transfer to MEs when they arrive. RPs enable MEs to collect a large volume of data at a time without traveling long distances, which can achieve a desirable balance between network energy saving and data collection delay. We develop two rendezvous planning algorithms, RP-CP and RP-UG. RP-CP finds the optimal RPs when MEs move along the data routing tree while RP-UG greedily chooses the RPs with maximum energy saving to travel distance ratios. We design the rendezvous-based data collection protocol that facilitates reliable data transfers from RPs to MEs in presence of significant unexpected delays in ME movement and network communication. Our approach is validated through extensive simulations.

(k \leq 6)

Recently, there have been increasing interests and progresses in lowering the worst case time complexity for well-known NP-hard problems, in particular for the VERTEX COVER problem. In this paper, new properties for the VERTEX COVER problem are indicated and several new techniques are introduced, which lead to a simpler and improved algorithm of time complexity O(kn + 1:271kk2) for the problem. Our algorithm also induces improvement on previous algorithms for the INDEPENDENT SET problem on graphs of small degree.