José Ferreira de Rezende

Joint Adoption of QoS Schemes for MPEG Streams

Abstract.Indiscriminated packet discards strongly degrade the quality perceived by end users of MPEG video transmissions. This paper investigates different Quality of Service (QoS) schemes and the tradeoffs of jointly adopting such schemes to improve the delivery quality of an MPEG stream. From an analytical model, we evaluate the impact of frame losses on the quality of MPEG streams and on the waste of network resources. Our assessment considers issues such as the use of redundancy by applying a Forward Error Correction (FEC) scheme to tolerate losses, the changing of the compression factor in MPEG encoding, the unequal protection of MPEG frames in a Differentiated Services environment, and how to evaluate the impact of network losses onto application quality. Results provide predicted bounds on the quality to be expected by end users as well as guidelines on how to take the best advantage from the joint adoption of the investigated QoS schemes.

Improving the accuracy of measurement-based geographic location of internet hosts

Location-aware applications take into account from where the users are accessing and thereby can offer novel functionalities in the Internet. This paper focuses on improving the accuracy of a geographic location service that relies on delay measurements to locate Internet hosts. Host locations are inferred by comparing delay patterns of geographically distributed landmarks, which are hosts with a known geographic location, with the delay pattern of the target host to be located. We deal with two problems that influence the accuracy of the resulting location estimation: (i) the placement of the landmarks and the probe machines that perform the delay measurements; and (ii) how to best measure the similarity between the delay patterns of the landmarks and the one observed for the target host. For the landmark placement problem, we propose a demographic approach to improve the representativeness of each landmark with respect to the hosts to be located. Given a limited number of landmarks, results show that a demographic placement provides closer landmarks and more accurate location estimations for most hosts. Concerning the placement of probe machines, we show that they have to be sparsely placed to avoid gathering redundant data. Furthermore, we define and evaluate three similarity models. Experiments show that other similarity models outperform the commonly adopted Euclidean distance, resulting then in a more accurate geographic location of Internet hosts.

Reflective middleware for wireless sensor networks

Wireless Sensor Networks (WSNs) are distributed systems whose main goal is to collect and deliver data to applications. This paper proposes a reflective, service-oriented middleware for WSN. The middleware provides an abstraction layer between applications and the underlying network infrastructure and it also keeps the balance between application QoS requirements and the network lifetime. It monitors both network and application execution states, performing a network adaptation whenever it is needed. Simulation results show that the network residual energy can be increased in more than 100% when adopting an adaptation strategy, while the application QoS requirement is respected.

Toward a Measurement-Based Geographic Location Service

Location-aware applications require a geographic location service of Internet hosts. We focus on a measurement-based service for the geographic location of Internet hosts. Host locations are inferred by comparing delay patterns of geographically distributed landmarks, which are hosts with a known geographic location, with the delay pattern of the target host to be located. Results show a significant correlation between geographic distance and network delay that can be exploited for a coarse-grained geographic location of Internet hosts.

An efficient heuristic for selecting active nodes in wireless sensor networks

Energy saving is a paramount concern in wireless sensor networks (WSNs). A strategy for energy saving is to cleverly manage the duty cycle of sensors, by dynamically activating different sets of sensors while non-active nodes are kept in a power save mode. We propose a simple and efficient approach for selecting active nodes in WSNs. Our primary goal is to maximize residual energy and application relevance of selected nodes to extend the network lifetime while meeting application-specific QoS requirements. We formalize the problem of node selection as a knapsack problem and adopt a greedy heuristic for solving it. An environmental monitoring application is chosen to derive some specific requirements. Analyses and simulations were performed and the impact of various parameters on the process of node selection was investigated. Results show that our approach outperforms a naive scheme for node selection, achieving large energy savings while preserving QoS requirements.

An underlay strategy for indirect routing

The evolution of the Internet toward ubiquity, mobility, and independence of wired infrastructure requires revising routing in large dynamic clouds. The need for frequent address updates caused by node mobility suggests decoupling the permanent node identifier from its topological address. This paper proposes Tribe, an indirect and scalable routing protocol for self-organizing networks. Tribe provides an anchor-based abstraction, where the communication is split into two phases: location of the destination node and direct communication between source and destination, associated with appropriate addressing schemes. Tribe anchor nodes play the role of rendezvous points and are responsible for translating a nodes identifier into a topology-dependent address. Tribe achieves high scalability by distributing location information among all nodes in the network using peer-to-peer concepts. By managing regions of a logical addressing space, Tribe nodes route in a hop-by-hop basis with small amount of information and communication cost. A qualitative analysis of the Tribe topology and a performance evaluation of the protocol behavior are provided. Tribe raises fundamental issues and triggers a high potential for future work.

Increasing throughput in dense 802.11 networks by automatic rate adaptation improvement

Rate control algorithms for commercial 802.11 devices strongly rely on packet losses for their adaptation. As a result, they give poor performance in dense networks because they are not able to distinguish packet losses related to channel error from packet losses due to collision. In this paper, we evaluate automatic rate adaptation algorithms in IEEE 802.11 dense networks. A certain number of works in the literature address this problem, but they demand modifications of the IEEE standard, or depend on some special feature not available in off-the-shelf devices. In this context, we propose a new automatic rate control algorithm which is simple, easy to implement, standards-compliant, and well-suited for crowded 802.11 networks. Our approach consists of measuring the contention level, inferring the collision probability, and choosing transmission rates which maximize throughput. Results from simulation and real experiments show throughput improvement of up to 100% from our mechanism.

Channel sensing order for cognitive radio networks using reinforcement learning

This work investigates the problem of channel sensing order used by a cognitive multichannel network, where each user is able to perform primary user detection on only one channel at a time. The sensing order indicates the sequence of channels sensed by the secondary users when searching for an available channel. When using an optimal sensing order, the secondary user can find faster a free channel with high quality. Brute-force algorithms may be used to find the optimal sensing order. However, this approach requires great computational effort. Even in scenarios where the secondary user knows the probability of each channel being available, the sensing order where the most available channels are sensed first is not ideal when using adaptive modulation. Therefore, we propose an approach using reinforcement learning to search dynamically for the optimal sensing order. Through simulations, we evaluated our proposal and compared its performance with other mechanisms, and the results obtained are close to the optimal value provided by the brute-force and superior to the other mechanisms in most of the scenarios.

REUSE: A combined routing and link scheduling mechanism for wireless mesh networks

Increasing the capacity of wireless mesh networks has motivated numerous studies. In this context, the cross-layer optimization techniques involving joint use of routing and link scheduling are able to provide better capacity improvements. Most works in the literature propose linear programming models to combine both mechanisms. However, this approach has high computational complexity and cannot be extended to large-scale networks. Alternatively, algorithmic solutions are less complex and can obtain capacity values close to the optimal. Thus, we propose the REUSE algorithm, which combines routing and link scheduling and aims to increase throughput capacity in wireless mesh networks. Through simulations, the performance of the proposal is compared to a developed linear programming model, which provides optimal results, and to other proposed mechanisms in the literature that also deal with the problem algorithmically. We observed higher values of capacity in favor of our proposal when compared to the benchmark algorithms.

Easily-managed and topology-independent location service for self-organizing networks

The need for efficient location mechanisms is an important issue in scalable self-organizing networks. Existing solutions are inherently dependent on the spatial distribution of nodes in the topology. This leads to limitations that go against the principles of self-organization. In this paper, we propose Twins, an easily-managed location service for self-organizing networks. Twins defines a logical multidimensional space that is a strict mathematical representation of the network geographic space. This representation is obtained through Hilbert space-filling curves. The geographic space is used for addressing and routing, while localization is based on the curve. Control messages are routed based on the logical structure while data packets are routed in a hop-by-hop basis with greedy next-hop choice. In this paper, we evaluate the Twins management operations in terms of fairness of space sharing and logical/geographic distances between nodes and their location servers. Our results show that Twins assures a fair distribution of control overhead and scales well with the number of nodes.