To promote commercial deployment of multihop wireless networks, the research/industry communities must develop new theories and protocols for flexible traffic engineering in these networks in order to support diverse user applications. This paper studies an important traffic engineering problemhow to support fair bandwidth allocation among all end-to-end flows in a multihop wireless networkwhich, in a more precise term, is to achieve the global maxmin fairness objective in bandwidth allocation. There exists no distributed algorithm for this problem in multihop wireless networks using IEEE 802.11 DCF. We have two major contributions. The first contribution is to develop a novel theory that maps the global maxmin objective to four local conditions and prove their equivalence. The second contribution is to design a distributed rate adjustment protocol based on those local conditions to achieve the global maxmin objective through fully distributed operations. Comparing with the prior art, our protocol has a number of advantages. It is designed for the popular IEEE 802.11 DCF. It replaces per-flow queueing with per-destination queueing. It achieves far better fairness (or weighted fairness) among end-to-end flows.

Liang Zhang;Wen Luo;式刚 陈;Ying Jian

Journal of Parallel and Distributed Computing

2012-3

Modeling worm propagation has been an important research subject in the Internet-worm research community. An accurate analytical propagation model allows us to study the spreading speed and traffic pattern of a worm under an arbitrary set of worm/network parameters, which is often computationally too intensive for simulations. More importantly, it gives us an insight into the impact of each worm/network parameter on the propagation of the worm and the effectiveness of a potential defense mechanism that is designed to control some of those parameters. Traditionally, most modeling work in the area concentrates on the relatively simple random-scanning worms. However, worm technologies have advanced rapidly in recent years. By enabling close coordination among all infected hosts, the permutation-scanning worms minimize the duplication of effort when scanning the whole Internet address space. They propagate much faster, and more importantly, can be much more stealthy than the random-scanning worms. Modeling these worms, however, remains a challenge to date. This paper proposes a mathematical model that precisely characterizes the propagation patterns of the permutation-scanning worms. The analytical framework captures the interactions among all infected hosts by a series of inter-dependent differential equations, which together present the overall behavior of the worm. We use simulations to verify the numerical results from the model, and demonstrate how the model can be used to study the impact of various worm/network parameters on the propagation.

Parbati Kumar Manna;式刚 陈;Sanjay Ranka

2008

An Internet worm automatically replicates itself to vulnerable systems and may infect hundreds of thousands of servers across the Internet. It is conceivable that the cyber-terrorists may use a wide-spread worm to cause major disruption to our Internet economy. While much recent research concentrates on propagation models, the defense against worms is largely an open problem. We propose a distributed anti-worm architecture (DAW) that automatically slows down or even halts the worm propagation. New defense techniques are developed based on behavioral difference between normal hosts and worm-infected hosts. Particulary, a worm-infected host has a much higher connection-failure rate when it scans the Internet with randomly selected addresses. This property allows DAW to set the worms apart from the normal hosts. We propose a temporal rate-limit algorithm and a spatial rate-limit algorithm, which makes the speed of worm propagation configurable by the parameters of the defense system. DAW is designed for an Internet service provider to provide the anti-worm service to its customers. The effectiveness of the new techniques is evaluated analytically and by simulations.

式刚 陈;Yong Tang

2004

Per-flow counting for big network data streams is a fundamental problem in various network applications such as traffic monitoring, load balancing, capacity planning, etc. Traditional research focused on designing compact data structures to estimate flow sizes from the beginning of the data stream (i.e., landmark window model). However, for many applications, the most recent elements of a stream are more significant than those arrived long time ago, which gives rise to the sliding window model. In this paper, we consider per-flow counting over the sliding window model, and propose two novel solutions, ACE and S-ACE. Instead of allocating a separate data structure for each flow, both solutions utilize the counter sharing idea to reduce memory footprint, so they can be implemented in on-chip SRAMs in modern routers to keep up with the line speed. ACE has to reset the sliding window periodically to give precise estimates, while S-ACE based on a novel segment design can achieve persistently accurate estimates. Our extensive simulations as well as experimental evaluations based on real network traffic trace demonstrate that S-ACE can achieve fast processing speed and high measurement accuracy even with a very tight memory.

You Zhou;Yian Zhou;式刚 陈;Youlin Zhang

2017-7-5

Traditional networks rely on aggregate routing and decentralized control to achieve scalability. On the contrary, software-defined networks achieve near optimal network performance and policy-based management through per-flow routing and centralized control, which, however, face scalability challenge due to: 1) limited ternary content addressable memory and on-die memory for storing the forwarding table and 2) per-flow communication/computation overhead at the controller. This paper presents a novel hybrid switching (HS) design, which integrates traditional switching and software-defined networking (SDN) switching for the purpose of achieving both scalability and optimal performance. We show that the integration also leads to unexpected benefits of making both types of switching more efficient under the hybrid design. We also design the general optimization framework via HS and propose an approximation algorithm for load-balancing optimization as a case study. Testing and numerical evaluation demonstrate the superior performance of HS when comparing with the state-of-The-Art SDN design.

Hongli Xu;河 黄;式刚 陈;Gongming Zhao;刘生 黄

IEEE/ACM Transactions on Networking

2018-2

Data dissemination is a key problem that bottlenecks the wide application of Wireless Sensor Network (WSN). In this paper, a novel data dissemination scheme – Logarithmic Spiral Data Dissemination (LSDD) – is proposed. In LSDD, data advertisements are disseminated following a spiral-like path, which involve only a small fraction of nodes in a sensor network. By exploiting nice features of spiral, this scheme scales well for large sensor networks while prolonging the network lifetime. In numerical analysis and simulations, we show the distinct merits of LSDD as follows: lower dissemination cost (O√n) compared to that of flooding-based schemes (O(n)), controllable topology by spiral parameters, excellent scalability, and good fault tolerance. We evaluate the extra delay caused by LSDD as a trade-off for its advantages, which is shown to be within a tolerable range.

Yang Sun;Guangbin Fan;式刚 陈

International Journal of Ad Hoc and Ubiquitous Computing

2007

Traditional systems for monitoring and diagnosing patients’ health conditions often require either dedicated medical devices or complicated system deployment, which incurs high cost. The networking research community has recently taken a different technical approach of building health-monitoring systems at relatively low cost based on wireless signals. However, the RF signals carry various types of noise and have time-varying properties that often defy the existing methods in more demanding conditions with other body movements, which makes it difficult to model and analyze the signals mathematically. In this paper, we design a novel wireless system using commercial off-the-shelf RFID readers and tags to provide a general and effective means of measuring bodily oscillation rates, such as the hand tremor rate of a patient with Parkinson’s disease. Our system includes a series of noise-removal steps, targeting at noise from different sources. More importantly, it introduces two sliding window-based methods to deal with time-varying signal properties from channel dynamics and irregular body movement. The proposed system can measure bodily oscillation rates of multiple persons simultaneously, even when the individuals are moving. Extensive experiments show that our system can produce accurate measurement results with errors less than 0.3 oscillations per second when it is applied to monitor hand tremor.

Youlin Zhang;式刚 陈;You Zhou;玉光 方

2018-12-6

With the capability of infecting hundreds of thousands of hosts, worms represent a major threat to the Internet. The defense against Internet worms is largely an open problem. This paper investigates two important problems. Can a localized defense system detect new worms that were not seen before and, moreover, capture the attack packets? How to identify polymorphic worms from the normal background traffic? We have two major contributions here. The first contribution is the design of a novel double-honeypot system, which is able to automatically detect new worms and isolate the attack traffic. The second contribution is the proposal of a new type of position-aware distribution signatures (PADS), which fit in the gap between the traditional signatures and the anomaly-based systems. We propose two algorithms based on Expectation-Maximization (EM) and Gibbs Sampling for efficient computation of PADS from polymorphic worm samples. The new signature is capable of handling certain polymorphic worms. Our experiments show that the algorithms accurately separate new variants of the MSBlaster worm from the normal-traffic background.

Yong Tang;式刚 陈

Proceedings - IEEE INFOCOM

2005

Measuring traffic volume in a road system has important applications in transportation engineering. The connected vehicle technologies integrate wireless communications and computers into transportation systems, allowing wireless data exchanges between vehicles and road-side equipment, and enabling large-scale, sophisticated traffic measurement. This paper investigates the problem of persistent traffic measurement, which was not adequately studied in the prior art, particularly in the context of intelligent vehicular networks. We propose three estimators for privacy-preserving persistent traffic measurement: one for point traffic, one for point-to-point traffic, and another for three-point traffic. After that, we present a general framework to measure persistent traffic that go through more than three locations. The estimators are mathematically derived from the join result of traffic records, which are produced by the electronic roadside units with privacy-preserving data structures. We evaluate our estimation methods using simulations based on both real transportation traffic data and synthetic data. The numerical results demonstrate the effectiveness of the proposed methods in producing high measurement accuracy and allowing accuracy-privacy tradeoff through parameter setting.

Yu E. Sun;河 黄;式刚 陈;Hongli Xu;Kai Han;Yian Zhou

IEEE Transactions on Mobile Computing

2019-7-1

Traditional radio frequency identification (RFID) technologies allow tags to communicate with a reader but not among themselves. By enabling peer communications between nearby tags, the emerging networked tags represent a fundamental enhancement to today's RFID systems. They support applications in previously infeasible scenarios where the readers cannot cover all tags due to cost or physical limitations. This paper is the first study on identifying state-free networked tags, which is a basic, fundamental function for most tagged systems. To prolong the lifetime of networked tags and make identification protocols scalable to large systems, energy efficiency and time efficiency are most critical. Our investigation reveals that the traditional contention-based protocol design will incur too much energy overhead in multihop tag systems. Surprisingly, a reader-coordinated design that serializes tag transmissions performs much better. In addition, we show that load balancing is important in reducing the worst case energy cost to the tags, and we present a solution based on serial numbers. We also show that, by leveraging the request aggregation and transmission pipelining techniques, the time efficiency of serialized ID collection can be greatly improved.

Min Chen;式刚 陈;You Zhou;Youlin Zhang

IEEE/ACM Transactions on Networking

2017-6