Yingxin Jiang

Face-to-Face Proximity Estimation Using Bluetooth On Smartphones

The availability of “always-on” communications has tremendous implications for how people interact socially. In particular, sociologists are interested in the question if such pervasive access increases or decreases face-to-face interactions. Unlike triangulation which seeks to precisely define position, the question of face-to-face interaction reduces to one of proximity, i.e., are the individuals within a certain distance? Moreover, the problem of proximity estimation is complicated by the fact that the measurement must be quite precise (1-1.5 m) and can cover a wide variety of environments. Existing approaches such as GPS and Wi-Fi triangulation are insufficient to meet the requirements of accuracy and flexibility. In contrast, Bluetooth, which is commonly available on most smartphones, provides a compelling alternative for proximity estimation. In this paper, we demonstrate through experimental studies the efficacy of Bluetooth for this exact purpose. We propose a proximity estimation model to determine the distance based on the RSSI values of Bluetooth and light sensor data in different environments. We present several real world scenarios and explore Bluetooth proximity estimation on Android with respect to accuracy and power consumption.

RIPPS: Rogue Identifying Packet Payload Slicer Detecting Unauthorized Wireless Hosts Through Network Traffic Conditioning

Wireless network access has become an integral part of computing both at home and at the workplace. The convenience of wireless network access at work may be extremely beneficial to employees, but can be a burden to network security personnel. This burden is magnified by the threat of inexpensive wireless access points being installed in a network without the knowledge of network administrators. These devices, termed <it>Rogue Wireless Access Points</it>, may allow a malicious outsider to access valuable network resources, including confidential communication and other stored data. For this reason, wireless connectivity detection is an essential capability, but remains a difficult problem. We present a method of detecting wireless hosts using a local RTT metric and a novel packet payload slicing technique. The local RTT metric provides the means to identify physical transmission media while packet payload slicing conditions network traffic to enhance the accuracy of the detections. Most importantly, the packet payload slicing method is transparent to both clients and servers and does not require direct communication between the monitoring system and monitored hosts.

WiiLab: Bringing together the Nintendo Wiimote and MATLAB

It is often a daunting task for engineering students to learn programming. Learning by playing has proven to be an effective way to engage students at nearly all levels of the curriculum. In this work, we will describe how we developed modules for teaching MATLAB to freshmen engineers through the use of the Nintendo Wiimote and motion capture. Through the work of a summer REU project, we developed and prototyped a unified set of C# and MATLAB libraries for Windows entitled WiiLab. In particular, the work focused on creating an easy-to-use API that largely abstracted the complexity of interacting with the Wiimote. In the work, we describe several laboratory modules developed for WiiLab and experiences from using the Wiimote in a four hundred student freshmen engineering course.

JumboGen: dynamic jumbo frame generation for network performance scalability

Network line speeds have increased at a significant rate. Unfortunately, network performance has not been able to keep pace with increases in line speed. This is due to the majority of packets being less than or equal to 100 bytes in addition to network routers not being able to scale well with the increased number of packets. In this paper we present our solution, JumboGen, an approach that will allow for a higher utilization of larger packet sizes on a domain-wise basis. Through simulations and experimentation, we show that the dynamic creation of jumbo packets decreases the number of packets processed by core routers and does not have an adverse impact on link utilization or fairness. The final result of JumboGen is a reduction in the number of packets seen by core routers which directly improves network scalability.

Granularity Aware (m, k) Queue Management for Real-time Media Servers

Real-time media servers are becoming increasingly important as the Internet supports more and more multimedia applications. In order to meet these ever increasing demands, real-time media servers will be responsible for supporting a large number of clients with a wide range of QoS requirements. While techniques such as aggregation of state information for scalability have been proposed in the literature such as with Differentiated Services, the per-stream effects of such aggregation are poorly understood. In this paper, we explore the effects of aggregated state information and propose a granularity aware (m, k) queue management (GAQM) which improves control over the tradeoff between scalability/granularity and QoS performance. Specifically, we identify the necessity of balancing aggregation groups according to critical characteristics such as relative deadlines. We present detailed examples of GAQM and evaluate our work through simulation studies.

A distributed traffic control scheme based on edge-centric resource management

The correct admission of flows in the Differentiated Services (DiffServ) environment is critical to provide stable and predictable quality of service (QoS) to the end user. Without a scalable and precise admission control scheme, the service provider is faced with either over-provisioning the network or accepting periods of best-effort like behavior. In this paper, we propose a novel approach for admission control that exploits the unique architectural aspects of DiffServ. Through the use of periodic heartbeats emanating from edge routers to probe the network state on the available egress paths, edge routers are able to quickly conduct admission control with a tunable degree of precision. In this paper, we detail our approach, Edge-centric Resource Management (ERM), and conduct detailed simulation studies regarding the effectiveness of the approach.

Effects of Low-Quality Computation Time Estimates in Policed Schedulers

Researchers conducting computer simulations can often provide estimates of computation time for a given type of simulation, which may be used by the compute cluster to aid in resource allocation and scheduling. However, the low quality of these estimates can cause deadline misses and unpredictable behavior. This problem is exacerbated on complex compute resources, clusters, and grids. Past-deadline jobs may be killed to provide resources for others, but the effect on the throughput of whole batches not fully understood. In this paper, we examine models for simple job schedulers and examine the quality of the deadline guarantee given. Simulation results based on actual runtimes are provided and discussed

Save for Later: A Technique for Improving End-to-End Mesh Network Performance

Due to fading and node mobility, packet loss in wireless networks is prevalent and unavoidable. Significant research has been conducted to improve the quality of wireless networks. Compared to other wireless networks, the backbone of a wireless mesh network (WMN) tends to be a relatively static topology and thus link error is likely to be transient rather than permanent. This paper proposes a technique, Save For Later (SFL), that leverages such transience to improve the performance of WMNs. SFL is a link-layer enhancement that allows an intermediate mesh router to temporarily save failed transmissions due to the high probability that a later successful transmission will convey that the failure is transient in nature. The paper develops a stochastic model to analyze the steady state throughput of a TCP bulk data transfer under SFL. Finally, the paper shows through simulation and analytical results that SFL elegantly improves the performance of WMNs in terms of throughput and flow fairness.

End-wise admission control delegation for effective end-to-end quality of service

Despite the significant body of research that has been conducted on quality of service (QoS), the notion of a dominant approach to end-to-end (E2E) QoS remains elusive. Beyond the ever present issue of deployment, the complexity and limited speed of resource negotiation arising from per-hop or per-domain interactions limit the general utility of the existing approaches. In this paper, we propose a novel approach to make significant strides in practical end-to-end QoS by leveraging the over-provisioned nature of the core and cooperative interactions amongst end autonomous systems. Our approach, E3AC (End-wise delegation for End-to-End Admission Control), provides a framework for catalyzing QoS amongst end ISPs while dramatically reducing the setup latency for QoS negotiations

Fast Admission Control for Short TCP Flows

Over the last decade, numerous admission control schemes have been studied to allocate network resources. Although per-flow control schemes can provide guaranteed QoS, such schemes face scalability issues in large networks due to the tremendous number of flows present. While aggregation-based approaches such as Differentiated Services relieve the storage of state in the core, admission control of flows, especially short-lived flows, is still a serious bottleneck. To that end, we propose an admission control scheme, Fast Admission for Short Flows (FASF), that enables accelerated admission control at the edge rather than via centralized or in-path mechanisms. FASF not only reduces the burden on admission control by largely distributing the dominant resource requests (i.e. short-lived flows), but also improves flow completion time and hence network goodput.