Richard Yang

Sprite: a simple, cheat-proof, credit-based system for mobile ad-hoc networks

Mobile ad hoc networking has been an active research area for several years. How to stimulate cooperation among selfish mobile nodes, however, is not well addressed yet. In this paper, we propose Sprite, a simple, cheat-proof, credit-based system for stimulating cooperation among selfish nodes in mobile ad hoc networks. Our system provides incentive for mobile nodes to cooperate and report actions honestly. Compared with previous approaches, our system does not require any tamper-proof hardware at any node. Furthermore, we present a formal model of our system and prove its properties. Evaluations of a prototype implementation show that the overhead of our system is small. Simulations and analysis show that mobile nodes can cooperate and forward each others messages, unless the resource of each node is extremely low.

A Theory of Network Localization

In this paper, we provide a theoretical foundation for the problem of network localization in which some nodes know their locations and other nodes determine their locations by measuring the distances to their neighbors. We construct grounded graphs to model network localization and apply graph rigidity theory to test the conditions for unique localizability and to construct uniquely localizable networks. We further study the computational complexity of network localization and investigate a subclass of grounded graphs where localization can be computed efficiently. We conclude with a discussion of localization in sensor networks where the sensors are placed randomly

Rigidity, computation, and randomization in network localization

We provide a theoretical foundation for the problem of network localization in which some nodes know their locations and other nodes determine their locations by measuring the distances to their neighbors. We construct grounded graphs to model network localization and apply graph rigidity theory to test the conditions for unique localizability and to construct uniquely localizable networks. We further study the computational complexity of network localization and investigate a subclass of grounded graphs where localization can be computed efficiently. We conclude with a discussion of localization in sensor networks where the sensors are placed randomly.

General AIMD congestion control

Instead of the increase-by-one decrease-to-half strategy used in TCP for congestion window adjustment, we consider the general case such that the increase value and decrease ratio are parameters. That is, in the congestion avoidance state, the window size is increased by /spl alpha/ per window of packets acknowledged and it is decreased to /spl beta/ of the current value when there is congestion indication. We refer to this window adjustment strategy as general additive increase multiplicative decrease (GAIMD). We present the (mean) sending rate of a GAIMD flow as a function of /spl alpha/, /spl beta/, loss rate, mean round-trip time, mean timeout value, and the number of packets acknowledged by each ACK. We conducted extensive experiments to validate this sending rate formula. We found the formula to be quite accurate for a loss rate of up to 20%. We also present a simple relationship between /spl alpha/ and /spl beta/ for a GAIMD flow to be TCP-friendly, that is, for the GAIMD flow to have approximately the same sending rate as a TCP flow under the same path conditions. We present results from simulations in which TCP-friendly GAIMD flows (/spl alpha/=0.31, /spl beta/=7/8) compete for bandwidth with TCP Reno flows and with TCP SACK flows, on a DropTail link as well as on a RED link. We found that the GAIMD flows were highly, TCP-friendly. Furthermore, with /spl beta/ at 7/8 instead of 1/2, these GAIMD flows have reduced rate fluctuations compared to TCP flows.

Batch rekeying for secure group communications

Many emerging web and Internet applications are based on a group communications model. Thus, securing group communications is an important Internet design issue. The key graph approach has been proposed for group key management. Key tree and key star are two important types of key graphs. Previous work has been focused on individual rekeying, i.e., rekeying after each join or leave request. In this paper, we first identify two problems with individual rekeying: inefficiency and an out-of-sync problem between keys and data. We then propose the use of periodic batch rekeying which can improve efficiency and alleviate the out-of-sync problem. We devise a marking algorithm to process a batch of join and leave requests. We then analyze the key server’s processing cost for batch rekeying. Our results show that batch rekeying, compared to individual rekeying, saves server cost substantially. We also show that when the number of requests in a batch is not large, the best key tree degree is four; otherwise, key star (a special key tree with root degree equal to group size) outperforms small-degree key trees.

On selfish routing in internet-like environments

A recent trend in routing research is to avoid inefficiencies in network-level routing by allowing hosts to either choose routes themselves (e.g., source routing) or use overlay routing networks (e.g., Detour or RON). Such approaches result in selfish routing, because routing decisions are no longer based on system-wide criteria but are instead designed to optimize host-based or overlay-based metrics. A series of theoretical results showing that selfish routing can result in suboptimal system behavior have cast doubts on this approach. In this paper, we use a game-theoretic approach to investigate the performance of selfish routing in Internet-like environments based on realistic topologies and traffic demands in our simulations. We show that in contrast to theoretical worst cases, selfish routing achieves close to optimal average latency in such environments. However, such performance benefits come at the expense of significantly increased congestion on certain links. Moreover, the adaptive nature of selfish overlays can significantly reduce the effectiveness of traffic engineering by making network traffic less predictable

Optimizing cost and performance for multihoming

Multihoming is often used by large enterprises and stub ISPs to connect to the Internet. In this paper, we design a series of novel smart routing algorithms to optimize cost and performance for multihomed users. We evaluate our algorithms through both analysis and extensive simulations based on realistic charging models, traffic demands, performance data, and network topologies. Our results suggest that these algorithms are very effective in minimizing cost and at the same time improving performance. We further examine the equilibrium performance of smart routing in a global setting and show that a smart routing user can improve its performance without adversely affecting other users.

Network localization in partially localizable networks

Knowing the positions of the nodes in a network is essential to many next generation pervasive and sensor network functionalities. Although many network localization systems have recently been proposed and evaluated, there has been no systematic study of partially localizable networks, i.e., networks in which there exist nodes whose positions cannot be uniquely determined. There is no existing study which correctly identifies precisely which nodes in a network are uniquely localizable and which are not. This absence of a sufficient uniqueness condition permits the computation of erroneous positions that may in turn lead applications to produce flawed results. In this paper, in addition to demonstrating the relevance of networks that may not be fully localizable, we design the first framework for two dimensional network localization with an efficient component to correctly determine which nodes are localizable and which are not. Implementing this system, we conduct comprehensive evaluations of network localizability, providing guidelines for both network design and deployment. Furthermore, we study an integration of traditional geographic routing with geographic routing over virtual coordinates in the partially localizable network setting. We show that this novel cross-layer integration yields good performance, and argue that such optimizations will be likely be necessary to ensure acceptable application performance in partially localizable networks.

Reliable group rekeying: a performance analysis

In secure group communications, users of a group share a common group key. A key server sends the group key to authorized new users as well as performs group rekeying for group users whenever the key changes. In this paper, we investigate scalability issues of reliable group rekeying, and provide a performance analysis of our group key management system (called keygem) based upon the use of key trees. Instead of rekeying after each join or leave, we use periodic batch rekeying to improve scalability and alleviate out-of-sync problems among rekey messages as well as between rekey and data messages. Our analyses show that batch rekeying can achieve large performance gains. We then investigate reliable multicast of rekey messages using proactive FEC. We observe that rekey transport has an eventual reliability and a soft real-time requirement, and that the rekey workload has a sparseness property, that is, each group user only needs to receive a small fraction of the packets that carry a rekey message sent by the key server. We also investigate tradeoffs between server and receiver bandwidth requirements versus group rekey interval, and show how to determine the maximum number of group users a key server can support.

COPE: traffic engineering in dynamic networks

Traffic engineering plays a critical role in determining the performance and reliability of a network. A major challenge in traffic engineering is how to cope with dynamic and unpredictable changes in traffic demand. In this paper, we propose COPE, a class of traffic engineering algorithms that optimize for the expected scenarios while providing a worst-case guarantee for unexpected scenarios. Using extensive evaluations based on real topologies and traffic traces, we show that COPE can achieve efficient resource utilization and avoid network congestion in a wide variety of scenarios.