Satellite-based estimates of groundwater storage variations in large drainage basins with extensive floodplains

This study presents monthly estimates of groundwater anomalies in a large river basin dominated by extensive floodplains, the Negro River Basin, based on the synergistic analysis using multisatellite observations and hydrological models. For the period 2003-2004, changes in water stored in the aquifer is isolated from the total water storage measured by GRACE by removing contributions of both the surface reservoir, derived from satellite imagery and radar altimetry, and the root zone reservoir simulated by WGHM and LaD hydrological models. The groundwater anomalies show a realistic spatial pattern compared with the hydrogeological map of the basin, and similar temporal variations to local in situ groundwater observations and altimetry-derived level height measurements. Results highlight the potential of combining multiple satellite techniques with hydrological modeling to estimate the evolution of groundwater storage.     

Multi-objective K-connected Deployment and Power Assignment in WSNs using a problem-specific constrained evolutionary algorithm based on decomposition

The K-connected Deployment and Power Assignment Problem (DPAP) in WSNs aims at deciding both the sensor locations and transmit power levels, for maximizing the network coverage and lifetime objectives under K-connectivity constraints, in a single run. Recently, it is shown that the Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D) is a strong enough tool for dealing with unconstraint real life problems (such as DPAP), emphasizing the importance of incorporating problem-specific knowledge for increasing its efficiency. In a constrained Multi-objective Optimization Problem (such as K-connected DPAP), the search space is divided into feasible and infeasible regions. Therefore, problem-specific operators are designed for MOEA/D to direct the search into optimal, feasible regions of the space. Namely, a DPAP-specific population initialization that seeds the initial solutions into promising regions, problem-specific genetic operators (i.e. M-tournament selection, adaptive crossover and mutation) for generating good, feasible solutions and a DPAP-specific Repair Heuristic (RH) that transforms an infeasible solution into a feasible one and maintains the MOEA/D’s efficiency simultaneously. Simulation results have shown the importance of each proposed operator and their interrelation, as well as the superiority of the DPAP-specific MOEA/D against the popular constrained NSGA-II in several WSN instances.     

Optimality and stability of the K-hyperline clustering algorithm

K-hyperline clustering is an iterative algorithm based on singular value decomposition and it has been successfully used in sparse component analysis. In this paper, we prove that the algorithm converges to a locally optimal solution for a given set of training data, based on Lloyd’s optimality conditions. Furthermore, the local optimality is shown by developing an Expectation-Maximization procedure for learning dictionaries to be used in sparse representations and by deriving the clustering algorithm as its special case. The cluster centroids obtained from the algorithm are proved to tessellate the space into convex Voronoi regions. The stability of clustering is shown by posing the problem as an empirical risk minimization procedure over a function class. It is proved that, under certain conditions, the cluster centroids learned from two sets of i.i.d. training samples drawn from the same probability space become arbitrarily close to each other, as the number of training samples increase asymptotically.     

An Integer Programming Algorithm for Routing Optimization in IP Networks

Most data networks nowadays use shortest path protocols to route the traffic. Given administrative routing lengths for the links of the network, all data packets are sent along shortest paths with respect to these lengths from their source to their destination.     

Secure and self-stabilizing clock synchronization in sensor networks

In sensor networks, correct clocks have arbitrary starting offsets and nondeterministic fluctuating skews. We consider an adversary that aims at tampering with the clock synchronization by intercepting messages, replaying intercepted messages (after the adversary’s choice of delay), and capturing nodes (i.e., revealing their secret keys and impersonating them). We present an efficient clock sampling algorithm which tolerates attacks by this adversary, collisions, a bounded amount of losses due to ambient noise, and a bounded number of captured nodes that can jam, intercept, and send fake messages. The algorithm is self-stabilizing, so if these bounds are temporarily violated, the system can efficiently stabilize back to a correct state. Using this clock sampling algorithm, we construct the first self-stabilizing algorithm for secure clock synchronization in sensor networks that is resilient to the aforementioned adversarial attacks.     

QoS Filtering and Resource Reservation in an Internet Environment

Multimedia group applications often operate in an environment where the various participants are located on systems and communication links with different capabilities. Mechanisms are required that ensure full-quality media for high-performance workstations but lower-quality media for playout at low-end systems. QoS filters have been proposed as a way to adapt QoS to the user specified level by changing the structure of a media stream in a well defined way. Resource reservation and QoS filter instantiation should be closely integrated since both represent one particular aspect of the provision of individualistic QoS for heterogeneous users in multipeer communications. The Internet reservation protocol RSVP is receiver oriented and allows each receiver to specify its resource requirements. However, no actual mechanisms are defined that adapt the data stream to the receiver specified QoS requirements.In this paper we present an enhanced version of RSVP (called RSVP++) that integrates resource reservation and QoS filter control. In order to achieve this integration we extend the RSVP functional model and define a new QoS service class. RSVP++ can coexist with common RSVP systems, thus, openness and interoperability of the system are ensured.     

Constraint-based deductive model checking

We show that constraint logic programming (CLP) can serve as a conceptual basis and as a practical implementation platform for the model checking of infinite-state systems. CLP programs are logical formulas (built up from constraints) that have both a logical interpretation and an operational semantics. Our contributions are: (1) a translation of concurrent systems (imperative programs) into CLP programs with the same operational semantics; and (2) a deductive method for verifying safety and liveness properties of the systems which is based on the logical interpretation of the CLP programs produced by the translation. We have implemented the method in a CLP system and verified well-known examples of infinite-state programs over integers, using linear constraints here as opposed to Presburger arithmetic as in previous solutions. Published online: 18 July 2001