Application acceleration for wireless and mobile data networks

This work studies application acceleration for wireless and mobile data networks. The problem of accelerating application can be addressed along multiple dimensions. The first dimension is advanced network protocol design, i.e., optimizing underlying network protocols, particulary transport layer protocol and link layer protocol. Despite advanced network protocol design, in this work we observe that certain application behaviors can fundamentally limit the performance achievable when operating over wireless and mobile data networks. The performance difference is caused by the complex application behaviors of these non-FTP applications. Explicitly dealing with application behaviors can improve application performance for new environments. Along this overcoming application behavior dimension, we accelerate applications by studying specific types of applications including Client-server, Peer-to-peer and Location-based applications. In exploring along this dimension, we identify a set of application behaviors that significantly affect application performance. To accommodate these application behaviors, we firstly extract general design principles that can apply to any applications whenever possible. These design principles can also be integrated into new application designs. We also consider specific applications by applying these design principles and build prototypes to demonstrate the effectiveness of the solutions. In the context of application acceleration, even though all the challenges belong to the two aforementioned dimensions of advanced network protocol design and overcoming application behavior are addressed, application performance can still be limited by the underlying network capability, particularly physical bandwidth. In this work, we study the possibility of speeding up data delivery by eliminating traffic redundancy present in application traffics. Specifically, we first study the traffic redundancy along multiple dimensions using traces obtained from multiple real wireless network deployments. Based on the insights obtained from the analysis, we propose Wireless Memory (WM), a two-ended AP-client solution to effectively exploit traffic redundancy in wireless and mobile environments. Application acceleration can be achieved along two other dimensions: network provision ing and quality of service (QoS). Network provisioning allocates network resources such as physical bandwidth or wireless spectrum, while QoS provides different priority to different applications, users, or data flows. These two dimensions have their respective limitations in the context of application acceleration. In this work, we focus on the two dimensions of overcoming application behavior and Eliminating traffic redundancy to improve application performance. The contribution of this work is as follows. First, we study the problem of application acceleration for wireless and mobile data networks, and we characterize the dimensions along which to address the problem. Second, we identify that application behaviors can significantly affect application performance, and we propose a set of design principles to deal with the behaviors. We also build prototypes to conduct system research. Third, we consider traffic redundancy elimination and propose a wireless memory approach.Ph.D.Committee Chair: Sivakumar, Raghupathy; Committee Member: Ammar, Mostafa; Committee Member: Fekri, Faramarz; Committee Member: Ji, Chuanyi; Committee Member: Ramachandran, Umakishor

Enhancing Intrusion Detection System with proximity information

Intrusion Detection Systems (IDSes) proposed to identify or prevent the wide spread of worms can be largely classified as signature-based or anomaly-based. Modern worms are often sufficiently intelligent to hide their activities and evade anomaly detection, rendering existing IDSes (particularly signature-based) less effective. We propose PAIDS, a proximity-assisted IDS approach for identifying the outbreak of unknown worms. Operating on an orthogonal dimension with existing IDSes, PAIDS can work collaboratively with existing IDSes for better performance. Trace-driven evaluation indicates that PAIDS has high detection rates and low false-positive rates. We also build a prototype with Google Maps APIs and libpcap library

Dynamic layer management in super-peer architectures

The emerging peer-to-peer (P2P) model has recently gained a significant attention due to its high potential of sharing various resources among networked users. Super-peer unstructured P2P systems have been found very effective by dividing the peers into two layers, super-layer and leaf-layer, in which message flooding is only conducted among super-layer. However, current super-peer systems do not employ any effective layer management schemes, which means the transient and low-capacity peers are allowed to act as super-peers. Moreover, the lack of an appropriate size ratio maintenance mechanism on super-layer to leaf-layer makes the system’s search performance far from being optimal. We propose a Dynamic Layer Management algorithm, DLM, which can maintain the optimal layer size ratio, and adaptively adjust peers between super-layer and leaf-layer. DLM is completely distributed in the sense that each peer decides to be a super-peer or a leaf peer independently without the global knowledge. DLM could effectively help a super-peer P2P system maintain the optimal layer size ratio, and designate peers with relatively long lifetime and large capacities as super-peers, and the peers with short lifetime and low capacities as leaf-peers under highly dynamic network situations. We demonstrate that the quality of a super-peer system is significantly improved under DLM scheme by comprehensive simulations. 1

Improving Energy Efficiency of Location Sensing on Smartphones

Location-based applications have become increasingly popular on smartphones over the past years. The active use of these applications can however cause device battery drain owing to their powerintensive location-sensing operations. This paper presents an adaptive location-sensing framework that significantly improves the energy efficiency of smartphones running location-based applications. The underlying design principles of the proposed framework involve substitution, suppression, piggybacking, and adaptation of applications ’ location-sensing requests to conserve energy. We implement these design principles on Android-based smartphones as a middleware. Our evaluation results show that the design principles reduce the usage of the power-intensive GPS (Global Positioning System) by up to 98 % and improve battery life by up to 75%