In the IP multicast model, a set of hosts can be aggregated into a group of hosts with one address, to which any host can send. However, Internet TV, distance learning, file distribution and other emerging large-scale multicast applications strain the current realization of this model, which lacks a basis for charging, lacks access control, and is difficult to scale. This paper proposes an extension to IP multicast to support the channel model of multicast and describes a specific realization called EXPlicitly REquested SingleSource (EXPRESS) multicast. In this model, a multicast channel has exactly one explicitly designated source, and zero or more channel subscribers. A single protocol supports both channel subscription and efficient collection of channel information such as subscriber count. We argue that EXPRESS addresses the aforementioned problems, justifying this multicast service model in the Internet.

Wireless sensor networks are an emerging area of research interest with a number of compelling potential applications. By architecting sensor networks as virtual databases, we can provide a well-understood nonprocedural programming interface suitable to data management, allowing the community to realize sensornet applications rapidly. We argue here that in order to achieve an energy-efficient and useful implementation, query processing operators should be implemented within the sensor network, and that approximate query results will play a key role. We observe that innetwork implementations of database operators require novel data-centric routing mechanisms, as well as a reconsideration of traditional network and database interface layering.

So far, sensor network broadcast protocols assume a trustworthy environment. However, in safety and missioncritical sensor networks this assumption may not be valid and some sensor nodes might be adversarial. In these environments, malicious sensor nodes can deprive other nodes from receiving a broadcast message. We call this attack a Denial-of-Message Attack (DoM). In this paper, we model and analyze this attack, and present countermeasures. We present SIS, a Secure Implicit Sampling scheme that permits a broadcasting base station to probabilistically detect the failure of nodes to receive its broadcast, even if these failures result from an attacker motivated to induce these failures undetectably. SIS works by eliciting authenticated acknowledgments from a subset of nodes per broadcast, where the subset is unpredictable to the attacker and tunable so as to mitigate acknowledgment implosion on the base station. We use a game-theoretic approach to evaluate this scheme in the face of an optimal attacker that attempts to maximize the number of nodes it denies the broadcast while remaining undetected by the base station, and show that SIS significantly constrains such an attacker even in sensor networks exhibiting high intrinsic loss rates. We also discuss extensions that permit more targeted detection capabilities. 1.

In this paper we propose an efficient on-line estimation algorithm for determining the size of a dynamic multicast group. By using diffusion approximation and Kalman filter, we derive an estimator that minimizes the mean square of the estimation error. As opposed to previous studies, where the size of the multicast group is supposed to be fixed throughout the estimation procedure, we consider a dynamic estimation scheme that updates the estimation at every observation step. The robustness of our estimator to violation of the assumptions under which it has been derived is addressed via simulations. Further validations of our approach are carried out on real audio traces.

Feedback from multicast group members is vital for many multicast protocols. In order to avoid feedback implosion in very large groups feedback algorithms with well behaved scaling-properties must be chosen. In this paper we analyse the performance of three typical feedback algorithms described in the literature. Apart from the basic trade-o between feedback latency and response duplicates we especially focus on the algorithms' sensitivity to the quality of the group size estimation. Based on this analysis we propose a generalized framework for feedback algorithms and especially give recommendations for the choice of well behaved feedback mechanisms that are suitable for very large groups.

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As the size of distributed systems keeps growing, the peer to peer communication paradigm has been identified as the key to scalability. Peer to peer overlay networks are characterized by their self-organizing capabilities, resilience to failure and fully decentralized control. In a peer to peer overlay, no entity has a global knowledge of the system. As much as this property is essential to ensure the scalability, monitoring the system under such circumstances is a complex task. Yet, estimating the size of the system is a core functionality for many distributed applications to parameter setting or monitoring purposes. In this paper, we propose a comparative study between three algorithms that estimate in a fully decentralized way the size of a peer to peer overlay. Candidate approaches are generally applicable irrespective of the underlying structure of the peer to peer overlay. The paper reports the head to head comparison of estimation system size algorithms. The simulations have been conducted using the same simulation framework and inputs and highlight the differences in cost and accuracy of the estimation between the algorithms both in static and dynamic settings. I.

This work presents a thorough investigation of the structure of multicast trees cut from the Internet and power-law topologies. Based on both generated topologies and real Internet data, we characterize the structure of such trees and show that they obey the rank-degree power law; that most high degree tree nodes are concentrated in a low diameter neighborhood; and that the sub-tree size also obeys a power law.

We propose two novel on-line estimation algorithms to determine the size of a dynamic multicast group. We first use a Wiener filter to derive an optimal estimator for the membership size of the session in case the join process is Poisson and the lifetime of participants is distributed exponentially. We next develop the best first-order linear filter from which we derive an estimator that holds for any lifetime distribution. We apply this approach to the case where the lifetime distribution is hyperexponential. Both estimators hold under any tra#c regime. Applying both estimators on real traces corresponding to video sessions, we find that both schemes behave well, one of which performs slightly better than the other in some cases. We further provide guidelines on how to tune the parameters involved in both schemes in order to achieve high quality estimation while simultaneously avoiding feedback implosion.

In this article, we address the problem of counting the number of peers in a peer-to-peer system. This functionality has proven useful in the design of several peer-to-peer applications. However, it is delicate to achieve when nodes are organised in an overlay network, and each node has only a limited, local knowledge of the whole system. In this paper, we propose a generic technique, called the Sample&Collide method, to solve this problem. It relies on a sampling sub-routine which returns randomly chosen peers. Such a sampling sub-routine is of independent interest. It can be used for instance for neighbour selection by new nodes joining the system. We use a continuous time random walk to obtain such samples. The core of the method consists in gathering random samples until a target number of redundant samples are obtained. This method is inspired by the “birthday paradox” technique of Bawa et al. (Estimating aggregates on a peer-to-peer network, Technical Report, Department of Computer Science, Stanford University), upon which it improves by achieving a target variance with fewer samples. We analyse the complexity and accuracy of the proposed method. We illustrate in particular how expansion properties of the overlay affect its performance. We use simulations to