Benoı̂t Garbinato

The design of a CORBA group communication service

The common object request broker architecture (CORBA) is becoming a standard for distributed application middleware, and there are increasing needs for enriching the basic functionalities of CORBA. While mechanisms for persistence, transactions, event channels, etc. have been designed and specified for CORBA, no standard support is provided to handle object replication. In this paper we discuss the issue of augmenting CORBA with group communication, which is considered an adequate paradigm to handle replication. We distinguish two main approaches: the integration approach and the service approach. We argue that the service approach is more appropriate to CORBA as it preserves the modularity of the architecture. We describe a proposal for a group communication service and discuss some implementation issues.

Location-based Publish/Subscribe

This paper introduces the concept of location-based publish/subscribe (LPS), which allows mobile ad hoc applications to anonymously communicate with each other, depending on their locations. With this concept, publish/subscribe topics are typically expressed in a dynamic manner including proximity criteria, e.g., I subscribe to all events on topic T published within some range R. We advocate that location-based publish/subscribe is a key programming paradigm for building mobile ad hoc application, and sketch our current implementation, which is based on standard APIs of the Java 2 platform, Micro Edition

An adaptive algorithm for efficient message diffusion in unreliable environments

In this paper, we propose a novel approach for solving the reliable broadcast problem in a probabilistic unreliable model. Our approach consists in first defining the optimality of probabilistic reliable broadcast algorithms and the adaptiveness of algorithms that aim at converging toward such optimality. Then, we propose an algorithm that precisely converges toward the optimal behavior, thanks to an adaptive strategy based on Bayesian statistical inference. We compare the performance of our algorithm with that of a typical gossip algorithm through simulation. Our results show, for example, that our adaptive algorithm quickly converges toward such exact knowledge.

Impact of Scale-free Topologies on Gossiping in Ad Hoc Networks

We show that scale-free topologies have a positive impact on the performance of gossiping algorithms in peer-to-peer overlay networks. This result is important in the context of ad hoc networks, where each node participates in controlling the network topology. Our study shows that, when combined with such topologies, typical gossiping algorithms tend to require fewer messages and experience smaller latency than when combined with other topologies, such as rings or grids. This suggests that the topology control scheme should aim at producing an overlay network that exhibits scale-free characteristics.

A Gambling Approach to Scalable Resource-Aware Streaming

In this paper, we propose a resource-aware solution to achieving reliable and scalable stream diffusion in a probabilistic model, i.e., where communication links and processes are subject to message losses and crashes, respectively. Our solution is resource-aware in the sense that it limits the memory consumption, by strictly scoping the knowledge each process has about the system, and the bandwidth available to each process, by assigning a fixed quota of messages to each process. We describe our approach as gambling in the sense that it consists in accepting to give up on a few processes sometimes, in the hope to better serve all processes most of the time. That is, our solution deliberately takes the risk not to reach some processes in some executions, in order to reach every process in most executions. The underlying stream diffusion algorithm is based on a tree-construction technique that dynamically distributes the load of forwarding stream packets among processes, based on their respective available bandwidths. Simulations show that this approach pays off when compared to traditional gossiping, when the latter faces identical bandwidth constraints.

Design and Implementation of the Pervaho Middleware for Mobile Context-Aware Applications

Context-aware applications offer a great potential for the future of mobile computing. In order to be developed in an optimal way, such applications need appropriate middleware services. This paper introduces Pervaho, an integrated middleware aimed specifically for supporting the development and testing of mobile context-aware applications. To illustrate the use of Pervaho, we walk through the development of a concrete mobile context-aware application and show how it can be elegantly built on top of Pervahos location-based publish/subscribe service. We also illustrate how a specialized mobility testing tool significantly simplifies the process of testing proximity-based semantics. We then present the implementation of Pervaho, which is based on a set of communication protocols geared at mesh networks. Finally, we provide a performance analysis of our implementation.

SpeakUp --- A Mobile App Facilitating Audience Interaction

A dynamic student-teacher interaction during class is an important part of the learning experience. However, in regular class settings and especially in large classrooms, it is a challenging task to encourage students to participate as they tend to be intimidated by the size of the audience. In this paper, in order to overcome this issue, we present SpeakUp, a novel context-aware mobile application supporting the social interactions between speakers and audiences through anonymous messaging and a peer rating mechanism. Context-awarness is achieved by bounding interactions in space and time using location-based authorization and message boards with limited lifetime. Anonymity is used as an icebreaker, so students dare writing down any question that pops in their heads. Peer rating is used to make it easy for teachers to access the most relevant ones and address them. We performed an evaluation with 140 students over five four-hour lessons that indicate that SpeakUp is easy to use and is perceived as useful.

QuoCast: A Resource-Aware Algorithm for Reliable Peer-to-Peer Multicast

This paper presents QuoCast, a resource-aware protocol for reliable stream diffusion in unreliable environments, where processes may crash and communication links may lose messages. QuoCast is resource-aware in the sense that it takes into account memory, CPU, and bandwidth constraints. Memory constraints are captured by the limited knowledge each process has of its neighborhood. CPU and bandwidth constraints are captured by a fixed quota on the number of messages that a process can use for streaming. Both incoming and outgoing traffic are accounted for. QuoCast maximizes the probability that each streamed packet reaches all consumers while respecting their incoming and outgoing quotas. The algorithm is based on a tree-construction technique that dynamically distributes the forwarding load among processes and links, based on their reliabilities and on their available quotas. The evaluation results show that the adaptiveness of QuoCast to several contraints provides better reliability when compared to other adaptive approaches.

Improving Neighbor Detection for Proximity-Based Mobile Applications

In this paper, we consider the problem of improving the detection of a device by another device in mobile ad hoc networks, given a maximum amount of time that they remain in proximity of each other. Our motivation lies in the emergence of a new trend of mobile applications known as proximity-based mobile applications which enable a user to communicate with other users in some defined range and for a certain amount of time. The highly dynamic nature of these applications makes neighbor detection time-constrained, i.e., even if a device remains in proximity for a limited amount of time, it should be detected with a high probability as a neighbor. To address this problem, we perform a realistic simulation-based study in mobile ad hoc networks and we consider three typical urban environments where proximity-based mobile applications are used, namely indoor with hard partitions, indoor with soft partitions and outdoor urban areas. In our study, a node periodically broadcasts a message in order be detected as a neighbor. Thus, we study the effect of parameters that we believe could influence the detection probability, i.e., the transmission power and the time interval between two consecutive broadcasts. More precisely, for each environment, we determine when a change in the value of each of these parameters could lead to an improvement of the neighbor detection and when it hurts. Our experiments show that there exists no unique combination of values of these parameters that maximizes the detection probability in all environments. Accordingly, for each environment, we present the combination that maximizes the detection probability in that environment.