Scaling high-quality, cost-efficient query evaluation is critical to search system performance. Although partial indexes reduce query processing times, result quality may be jeopardized due to exclusion of relevant non-local documents. Selectively forwarding queries between geographically distributed search sites may help. The basic idea of query forwarding is that after a local site receives a query, it determines non-local sites to forward the query to and returns an aggregation of the local and non-local results. Nevertheless, electricity costs remain substantial sources of operating expenses. We present a hybrid rank-energy query forwarding model termed "RESQ." The novel contribution is to simultaneously consider both ranking quality and spatially-temporally varying energy prices when making forwarding decisions. Experiments with a large-scale query log, publicly-available electricity price data, and real search site locations demonstrate that query forwarding under RESQ achieves the result scalability of partial indexes with the cost savings of energy-aware approaches (e.g., an 87% ranking guarantee with a 46% savings in energy costs).

Selective query forwarding is a promising technique to help scale high-quality and cost-efficient query evaluation in distributed search systems. The basic idea is simple. After a local site receives a query, it determines non-local sites to forward the query to and returns an aggregation of local and non-local results. We introduce "RESQ", a hybrid rank-energy selective query forwarding model. The novel contribution of RESQ is to simultaneously consider both ranking quality and energy costs when making forwarding decisions. Using a large-scale query log and publicly-available energy price time series, we demonstrate the ability of RESQ forwarding to achieve favorable tradeoffs between the possibility of returning high ranking query results and savings in temporally- and spatially-varying energy prices.

We transform the 3D underwater sensor network (USN) localization problem into its 2D counterpart by employing sensor depth information and a simple projection technique. We first prove that a nondegenerative projection preserves network localizability. We then prove that given a network and a constant k, all of the geometric k-lateration localization methods are equivalent. Based on these results, we design a purely distributed bilateration localization scheme for 3D USNs termed as underwater sensor positioning (USP). Through extensive simulations, we show that USP has the following nice features: (1) improved localization capabilities over existing 3D methods, (2) low storage and computation requirements, (3) predictable and balanced communication overhead, and (4) robustness to errors from the underwater environment.

We develop a rate adaptation scheme for 802.11 networks termed SRC that is based on a novel combination of sequential hypothesis testing and short-term loss ratios. The underlying design of SRC represents a fundamental departure from previous rate adjustment strategies that employ fixed-size observation windows and seemingly-intuitive rate increase guidelines. Through extensive simulation results, SRC is shown to be robust to dynamic characteristics of the wireless channel and to significantly increase network throughput over existing mainstream rate adaptation solutions. SRC does not require any type of specialized hardware or modifications to the existing 802.11 standard.

We study the localization problem in sparse 3D underwater sensor networks. Considering the fact that depth information is typically available for underwater sensors, we transform the 3D underwater positioning problem into its two- dimensional counterpart via a projection technique and prove that a non-degenerative projection preserves network localizability. We further prove that given a network and a constantk, all of the geometrick-lateration localization methods are equivalent. Based on these results, we design a purely distributed localization framework termed USP. This framework can be applied with any ranging method proposed for 2D terrestrial sensor networks. Through theoretical analysis and extensive simulation, we show that USP preserves the localizability of the original 3D network via a simple projection and improves localization capabilities when bilateration is employed. USP has low storage and computation requirements, and predictable and balanced communication overhead.

We develop a practical and comprehensive hybrid rogue access point (AP) detection framework for commodity Wi- Fi networks. It is the first scheme that combines the distributed wireless media surveillance and the centralized wired end socket level traffic "fingerprinting" The former is designed not only to detect various types of rogue APs, but also to discover suspicious activities so as to prevent the adversaries from turning victim APs into rogue devices. Moreover, the socket level traffic fingerprinting helps our frame work to achieve a finer granularity on rogue AP detection among the existing schemes. This framework has the following nice properties: i) it requires neither specialized hardware nor modification to existing standards; ii) the proposed mechanism greatly improves the rogue AP detection probability so that network resilience is improved; iii) it provides a cost-effective solution to Wi-Fi network security enhancement by incorporating free but mature software tools; iv) it can protect the network from adversaries capable of using customized equipment and/or violating the IEEE 802.11 standard; v) its open architecture allows extra features to be easily added on in the future. Our analysis and evaluation demonstrate that this hybrid rogue AP protection framework is capable of reliably revealing rogue devices and preempting potential attacks.

We examine a widely accepted myth about passive listening in wireless networks, and give a detailed description of how to achieve real "passive listening." Then we develop a lightweight intrusion management system called LIMS for commodity Wi-Fi networks. Our system employs novel techniques to increase network resilience to passive and active attacks that could reveal the WEP/WPA-PSK shared key. LIMS has the following nice properties: i) it requires neither specialized hardware nor modification to existing security protocols (e.g, WEP and WPA); ii) the proposed mechanism can be integrated with an access point in a plugin manner; iii) it provides a cost-effective security enhancement to Wi-Fi networks by incorporating free but mature software tools; iv) it has the ability to prevent a certain class of DoS attacks.

We first give a comprehensive taxonomy of rouge access points (APs), which includes a new class of rouge APs never addressed in the literature before. Then, we propose an efficient rogue AP protection system termed as RAP for commodity Wi-Fi networks. In RAP, novel techniques are introduced to detect rouge APs and to improve network resilience. Our system has the following nice properties: i) it requires neither specialized hardware nor modification to existing standards; ii) the proposed mechanism can be integrated with an AP in a plugin manner; iii) it provides a cost-effective security enhancement to Wi-Fi networks by incorporating free but mature software tools; iv) it can protect the network from adversaries capable of using customized equipment and violating the IEEE 802.11 standard.

New improved upper and lower bounds on the maximum size of a symmetric or arbitrary conflict-avoiding code of length n = 4 m for three active users are proved. Furthermore, direct constructions for optimal conflict-avoiding codes of length n = 4 m and m equiv 2 (mod 4) for three active users are provided.