Ayalvadi Ganesh

Secure routing for structured peer-to-peer overlay networks

Structured peer-to-peer overlay networks provide a substrate for the construction of large-scale, decentralized applications, including distributed storage, group communication, and content distribution. These overlays are highly resilient; they can route messages correctly even when a large fraction of the nodes crash or the network partitions. But current overlays are not secure; even a small fraction of malicious nodes can prevent correct message delivery throughout the overlay. This problem is particularly serious in open peer-to-peer systems, where many diverse, autonomous parties without preexisting trust relationships wish to pool their resources. This paper studies attacks aimed at preventing correct message delivery in structured peer-to-peer overlays and presents defenses to these attacks. We describe and evaluate techniques that allow nodes to join the overlay, to maintain routing state, and to forward messages securely in the presence of malicious nodes.

The effect of network topology on the spread of epidemics

Many network phenomena are well modeled as spreads of epidemics through a network. Prominent examples include the spread of worms and email viruses, and, more generally, faults. Many types of information dissemination can also be modeled as spreads of epidemics. In this paper we address the question of what makes an epidemic either weak or potent. More precisely, we identify topological properties of the graph that determine the persistence of epidemics. In particular, we show that if the ratio of cure to infection rates is larger than the spectral radius of the graph, then the mean epidemic lifetime is of order log n, where n is the number of nodes. Conversely, if this ratio is smaller than a generalization of the isoperimetric constant of the graph, then the mean epidemic lifetime is of order e/sup na/, for a positive constant a. We apply these results to several network topologies including the hypercube, which is a representative connectivity graph for a distributed hash table, the complete graph, which is an important connectivity graph for BGP, and the power law graph, of which the AS-level Internet graph is a prime example. We also study the star topology and the Erdos-Renyi graph as their epidemic spreading behaviors determine the spreading behavior of power law graphs.

Peer-to-peer membership management for gossip-based protocols

Gossip-based protocols for group communication have attractive scalability and reliability properties. The probabilistic gossip schemes studied so far typically assume that each group member has full knowledge of the global membership and chooses gossip targets uniformly at random. The requirement of global knowledge impairs their applicability to very large-scale groups. In this paper, we present SCAMP (Scalable Membership protocol), a novel peer-to-peer membership protocol which operates in a fully decentralized manner and provides each member with a partial view of the group membership. Our protocol is self-organizing in the sense that the size of partial views naturally converges to the value required to support a gossip algorithm reliably. This value is a function of the group size, but is achieved without any node knowing the group size. We propose additional mechanisms to achieve balanced view sizes even with highly unbalanced subscription patterns. We present the design, theoretical analysis, and a detailed evaluation of the basic protocol and its refinements. Simulation results show that the reliability guarantees provided by SCAMP are comparable to previous schemes based on global knowledge. The scale of the experiments attests to the scalability of the protocol.

Probabilistic reliable dissemination in large-scale systems

The growth of the Internet raises new challenges for the design of distributed systems and applications. In the context of group communication protocols, gossip-based schemes have attracted interest as they are scalable, easy to deploy, and resilient to network and process failures. However, traditional gossip-based protocols have two major drawbacks: 1) they rely on each peer having knowledge of the global membership; and 2) being oblivious to the network topology, they can impose a high load on network links when applied to wide-area settings. In this paper, we provide a theoretical analysis of gossip-based protocols which relates their reliability to key system parameters (the system size, failure rates, and number of gossip targets). The results provide guidelines for the design of practical protocols. In particular, they show how reliability can be maintained while alleviating drawback by: 1) providing each peer with only a small subset of the total membership information and drawback; and 2) organizing members into a hierarchical structure that reflects their proximity according to some network-related metric. We validate the analytical results by simulations and verify that the hierarchical gossip protocol considerably reduces the load on the network compared to the original, non-hierarchical protocol.

Network awareness and failure resilience in self-organizing overlay networks

The growth of peer-to-peer applications on the Internet motivates interest in general purpose overlay networks. The construction of overlays connecting a large population of transient nodes poses several challenges. First, connections in the overlays should reflect the underlying network topology, in order to avoid overloading the network and to allow god application performance. Second, connectivity among active nodes of the overlay should be maintained, even in the presence of high failure rates or when a large proportion of nodes are not active. Finally, the cost of using the overlay should be spread evenly among peer nodes for fairness reasons as well as for the sake of application performance. To preserve scalability, we seek solutions to these issues that can be implemented in a fully decentralized manner and rely on local knowledge from each node. In this paper, we propose an algorithm called the localizer which addresses these three key challenges. The localizer refines the overlay in a way that reflects geographic locality so as to reduce network overload. Simultaneously, it helps to evenly balance the number of neighbors of each node in the overlay, thereby sharing the load evenly as well as improving the resilience to random node failures or disconnections. The proposed algorithm is presented and evaluated in the context of an unstructured peer-to-peer overlay network produced using the Scamp protocol. We provide a theoretical analysis of the various aspects of the algorithm. Simulation results based on a realistic network topology model confirm the analysis and demonstrate the localizer efficiency.

Efficient epidemic-style protocols for reliable and scalable multicast

Epidemic-style (gossip-based) techniques have recently emerged as a scalable class of protocols for peer-to-peer reliable multicast dissemination in large process groups. These protocols provide probabilistic guarantees on reliability and scalability. However, popular implementations of epidemic-style dissemination are reputed to suffer from two major drawbacks: (a) (Network Overhead) when deployed on a WAN-wide or VPN-wide scale they generate a large number of packets that transit across the boundaries of multiple network domains (e.g., LANs, subnets, ASs), causing an overload on core network elements such as bridges, routers, and associated links; (b) (Lack of Adaptivity) they impose the same load on process group members and the network even under reduced failure rates (viz., packet losses, process failures). lit this paper we report on the (first) comprehensive set of solutions to these problems. The solution is comprised of two protocols: (1) a hierarchical gossiping protocol, and (2) an adaptive multicast dissemination framework that allows use of any gossiping primitive within it. These protocols work within a virtual peer-to-peer hierarchy called the Leaf Box hierarchy. Processes can be allocated in a topologically aware manner to the leaf boxes of this structure, so that (1) and (2) produce low traffic across domain boundaries in the network. In the interests of space, this paper focuses on a detailed discussion and evaluation (through simulations) of only the hierarchical gossiping protocol. We present an overview of the adaptive dissemination protocol and its properties.

Performance Analysis of Contention Based Medium Access Control Protocols

This paper studies the performance of contention based medium access control (MAC) protocols. In particular, a simple and accurate technique for estimating the throughput of the IEEE 802.11 DCF protocol is developed. The technique is based on a rigorous analysis of the Markov chain that corresponds to the time evolution of the back-off processes at the contending nodes. An extension of the technique is presented to handle the case where service differentiation is provided with the use of heterogeneous protocol parameters, as, for example, in IEEE 802.11e EDCA protocol. Our results provide new insights into the operation of such protocols. The techniques developed in the paper are applicable to a wide variety of contention based MAC protocols.

Congestion pricing and user adaptation

The problem of sharing bandwidth in a communication network has been the focus of much research aimed at guaranteeing an appropriate quality of service to users. This is particularly challenging in an environment with a great diversity of users and applications, which makes it difficult, if not impossible, to tightly constrain user attributes and requirements. This motivates shifting the burden of rate allocation from the network to the end-systems. We propose a decentralized scheme for user adaptation and study its dynamics. The proposed scheme uses congestion prices as a mechanism for providing both feedback and incentives to end-systems.

Spontaneous Emergence of Multiple Drug Resistance in Tuberculosis before and during Therapy

The emergence of drug resistance in M. tuberculosis undermines the efficacy of tuberculosis (TB) treatment in individuals and of TB control programs in populations. Multiple drug resistance is often attributed to sequential functional monotherapy, and standard initial treatment regimens have therefore been designed to include simultaneous use of four different antibiotics. Despite the widespread use of combination therapy, highly resistant M. tb strains have emerged in many settings. Here we use a stochastic birth-death model to estimate the probability of the emergence of multidrug resistance during the growth of a population of initially drug sensitive TB bacilli within an infected host. We find that the probability of the emergence of resistance to the two principal anti-TB drugs before initiation of therapy ranges from 10−5 to 10−4; while rare, this is several orders of magnitude higher than previous estimates. This finding suggests that multidrug resistant M. tb may not be an entirely “man-made” phenomenon and may help explain how highly drug resistant forms of TB have independently emerged in many settings.

On the race of worms, alerts, and patches

We provide an analytical framework for evaluating the performance of automatic patching systems. We use it to quantify the speed of patch or alert dissemination required for worm containment. Motivated by scalability and trust issues, we consider a hierarchical system where network hosts are organized into subnets, each containing a patch server (termed superhost). Patches are disseminated to superhosts through an overlay connecting them and, after verification, to end hosts within subnets. The analytical framework accommodates a variety of overlays through the novel abstraction of a minimum broadcast curve. It also accommodates filtering of scans across subnets. The framework provides quantitative estimates that can guide system designers in dimensioning automatic patching systems. The results are obtained mathematically and verified by simulation.