Jorge Visca

A rule-based distributed system for self-optimization of constrained devices

During the last years there has been a strong research effort on the autonomic communications and self-management paradigms. Following this impulse, the academic community and the industry have proposed several architectures and techniques to allow network devices to make their own configuration decisions. Those proposals often include resource-expensive technologies such as complex inference machines, ontological modeling and probabilistic prediction that may not be suitable for the most pervasive and inexpensive network-enabled devices. This paper addresses this facet of the autonomic systems introducing RAN. This system aims to be a complete rule-based, distributed system specially designed and implemented to enable autonomic behavior on very constrained devices, such as domestic wireless routers with resources as low as 16 MB of RAM and 4 MB of storage memory. The RAN system was developed to serve the objectives of Rural Ambient Networks, a project that targets the so-called Digital Divide deploying low-cost wireless mesh infrastructure in rural communities. In this context, RAN, in autonomic and distributed manners, optimizes the network configuration to minimize the monetary cost that the community has to pay for using the IT infrastructure. Finally, this work presents an evaluation of RAN that shows how it makes possible to perform sophisticated optimization decisions with a very small overhead in terms of CPU and memory.

Self management of rate, power and carrier-sense threshold for interference mitigation in IEEE 802.11 networks

Nowadays, it is common to find IEEE 802.11 networks that are deployed in an unplanned and unmanaged manner. Moreover, because of the low hardware cost and, trying to obtain better coverage and performance, a large number of devices are usually installed in reduced spaces causing high-density deployments. This kind of networks experiment several problems related with the shared nature of the transmission medium. In recent years, different transmit power control mechanisms have been proposed to palliate those problems, however, in some situations, the existing solutions can lead to an starvation problem. In this paper, we present a novel mechanism that manages data rate, transmit power and carrier-sense threshold to reduce this problem.

Self-managed content-based routing for opportunistic networks

Several countries such as Uruguay and Brazil are implementing the well-known One Laptop Per Child Program (OLPC) by which every child that assists to the primary school obtains in property a laptop with wireless capabilities. They carry their laptops from home to school and back every day and, as seen in the experience, they also carry their laptops to parks, community centers etc. This provides a wide platform for the deployment of Disruption Tolerant network applications. This paper presents a self-managed, opportunistic and content-based routing protocol that supports a network of environmental sensors implemented using consumer-grade wireless routers working together with OLPC laptops. We evaluate the impact of the density, diversity and connectivity of the mobile network on the performance of the protocol and we show how it self-configures it parameters to adapt to changing network conditions.

Embedded Rule-based Management for Content-based DTNs

Several countries such as Uruguay and Brazil are implementing the well-known One Laptop Per Child Program (OLPC) by which every child that attend to primary school obtains in property a laptop with wireless capabilities. They carry their laptops from home to school and back every day and, as we observed in our research, they also carry their laptops to parks, community centers etc. That provides a wide platform for opportunistic, delay tolerant, networking applications. This paper presents a lowcost, delay-tolerant, network of sensors implemented embedding high-level decision-making capabilities inside consumer-grade wireless routers working together with the OLPC laptops. The sensors are deployed at the living premises of children in environmentally vulnerable neighborhoods as well as at their schools, parks, etc. The environmental data collected by the sensors is carried to the school by the laptops and from the school to monitoring stations over the Internet. In this system, all the entities in the network are publishers and subscribers of con_guration commands, policy-rules and environmental data, building a exible, self-management solution.

Opportunistic media sharing for mobile networks

Nowadays there is a proliferation of smart devices used for media consumption. Usually, media contents are streamed from a Content Distribution Network (CDN), through a cellular network, which can get overloaded when there is a large number of active users per cell. At the same time the devices, i.e. smartphones, typically possess a set of wireless interfaces such as WiFi and Bluetooth that can be used to communicate with other devices in its proximity. In this work we propose a publish/subscribe, opportunistic network protocol aimed at off-load infrastructure network nodes. It contributes to optimize the cellular network usage among mobile devices and to reduce the costs and energy consumption induced by the reproduction of media that are temporally popular.

Buffer Management in Opportunistic Networking

Opportunistic Networks are a powerful tool for deploying a class of delay tolerant network applications in zones with scarce communications infrastructure. Unfortunately, these networks are highly stochastic and very sensible to changes in the nodes movement patters, as well as to changes in the data-flow patterns. On the other hand, opportunistic algorithms, while conceptually simple, are highly configurable and plastic but, for the same reason, many examples of such networks are notoriously hard to model and simulate. Thus, the algorithms calibration is a challenging task. In this paper, we show how a combination of a synthetic mobility pattern, combined with simulation and a careful implementation permits to identify potentially disruptive behaviors and find solutions. In particular we show how a quite probable mobility pattern (i.e., data-carrying nodes converging to a data receiver simultaneously) has very bad performance when using a wide family of buffer management policies, FIFO among them. Furthermore, we propose and test an alternative buffer management policy which shows very encouraging results.

DEMOS Mobility Model

Uruguay has a countrywide implementation of the One Laptop per Child (OLPC) initiative, locally named Plan Ceibal. Children participant in this project carry their laptops from home to school and back every day, enabling the creation of new applications to take advantage of computers ubiquity, mobility and wireless capabilities. In this context, we are deploying the project Domestic Environment Monitoring with Opportunistic Sensor networks (DEMOS), seeking to use Plan Ceibal laptops as an opportunistic network to obtain, transport, aggregate and communicate environmental information from sensors disseminated in locations close to children neighborhoods. The planning of DEMOS deployment involve several scenarios of variable size and characteristics; the evolution of the prototype over the real networks would impose frequent countrywide software updates to thousands of childrens laptops, among other logistic limitations. Therefore, in order to overcome such difficulties, speed up the project deployment and minimize costs, we are developing a simulation environment which must preserve the real laptops mobility and other essential characteristics in order to deliver accurate results. Gathering mobility traces from Plan Ceibal laptops would involve the installation of extra hardware such as Global Position System (GPS) devices; even if we were able to get sample traces, they would be tight to a particular scenario, limiting the possibility of changing relevant parameters such as number of laptops, size of mobility areas, speed, among others. Since the existing mobility models do not match our deployment characteristics, we are evolving our own DEMOS Mobility Model (DMM). This paper presents the relevant characteristics of DMM and a prototype scenario generator tool for standard network simulators. We are starting to evaluate an opportunistic routing protocol prototype using DMM.

Rate, power and carrier-sense threshold coordinated management for high-density IEEE 802.11 networks

Nowadays, trying to obtain better coverage and performance, and allowed by the low-hardware prices, it is common to deploy a large number of IEEE 802.11 devices in offices, meeting rooms or auditoriums configuring the so called high-density networks. In such a scenario, the shared nature of the transmission medium causes interference problems. Some physical-layer- and link-layer-adaptation mechanisms to palliate those problems have been developed, however, most of them have not been independently implemented and assessed. In this paper, we implement in a simulator some of the existent solutions, compare them in a simulation environment and show that, in some situations, the existing solutions can lead to a starvation problem. Finally, we propose a new mechanism that manages datarate, transmit power and carrier-sense threshold to ameliorate this problem.

A distributed Notification Bus for constrained devices

During the last years there has been a strong research effort on the autonomic communications and self-management paradigms.

Path sampling, a robust alternative to gossiping for opportunistic network routing

Opportunistic Networks have been designed for transmitting data in difficult environments, characterized by high mobility, sporadic connectivity, and constrained resources. To sustain these networks, the literature describes methods such as Epidemic and Spray&Wait, which do not learn from the network behaviour, and Gossiping-based algorithms that collect historical network data to improve efficiency. In this paper, we show that Gossiping-based solutions suffer from pathological behaviour in some simple network scenarios. Under certain conditions almost all the data transmitted by some nodes may get lost in the network, not reaching its destination. To address this problem we have proposed an algorithm that responds in a more robust manner while staying relatively simple. In this work, we show that our algorithm achieves delivery rates comparable to gossiping-based algorithms, while being more robust and providing better fairness. To illustrate this result, we test native implementations of our solution, Path Sampling, and related algorithms on a network simulator.