Pierre Leone

Energy optimal data propagation in wireless sensor networks

We propose an algorithm to compute the optimal parameters of a probabilistic data propagation algorithm for wireless sensor networks (WSN). The probabilistic data propagation algorithm we consider was introduced in previous work, and it is known that this algorithm, when used with adequate parameters, balances the energy consumption and increases the lifespan of the WSN. However, we show that in the general case achieving energy balance may not be possible. We propose a centralized algorithm to compute the optimal parameters of the probabilistic data propagation algorithm, and prove that these parameters maximize the lifespan of the network even when it is not possible to achieve energy balance. Compared to previous work, our contribution is the following: (a) we give a formal definition of an optimal data propagation algorithm: an algorithm maximizing the lifespan of the network. (b) We find a simple necessary and sufficient condition for the data propagation algorithm to be optimal. (c) We constructively prove that there exists a choice of parameters optimizing the probabilistic data propagation algorithm. (d) We provide a centralized algorithm to compute these optimal parameters, thus enabling their use in a WSN. (e) We extend previous work by considering the energy consumption per sensor, instead of the consumption per slice, and propose a spreading technique to balance the energy among sensors of a same slice. The technique is numerically validated by simulating a WSN accomplishing a data monitoring task and propagating data using the probabilistic data propagation algorithm with optimal parameters.

Optimal data gathering paths and energy-balance mechanisms in wireless networks

This paper studies the data gathering problem in wireless networks, where data generated at the nodes has to be collected at a single sink. We investigate the relationship between routing optimality and fair resource management. In particular, we prove that for energy-balanced data propagation, Pareto optimal routing and flow maximization are equivalent, and also prove that flow maximization is equivalent to maximizing the network lifetime. We algebraically characterize the network structures in which energy-balanced data flows are maximal. Moreover, we algebraically characterize communication links which are not used by an optimal flow. This leads to the characterization of minimal network structures supporting the maximal flows. We note that energy-balance, although implying global optimality, is a local property that can be computed efficiently and in a distributed manner. We suggest online distributed algorithms for energy-balance in different optimal network structures and numerically show their stability in particular setting. We remark that although the results obtained in this paper have a direct consequence in energy saving for wireless networks they do not limit themselves to this type of networks neither to energy as a resource. As a matter of fact, the results are much more general and can be used for any type of network and different types of resources.

Near optimal geographic routing with obstacle avoidance in wireless sensor networks by fast-converging trust-based algorithms

Geographic routing scales well in sensor networks, mainly due to its stateless nature. Still, most of the algorithms are concerned with finding some path, while the optimality of the path is difficult to achieve. In this paper we are presenting a novel geographic routing algorithm with obstacle avoidance properties. It aims at finding the optimal path from a source to a destination when some areas of the network are unavailable for routing due to low local density or obstacle presence. It locally and gradually with time (but, as we show, quite fast) evaluates and updates the suitability of the previously used paths and ignores non optimal paths for further routing. By means of extensive simulations, we are comparing its performance to existing state of the art protocols, showing that it performs much better in terms of path length thus minimizing latency, space, overall traffic and energy consumption.

An adaptive blind algorithm for energy balanced data propagation in wireless sensors networks

In this paper, we consider the problem of energy balanced data propagation in wireless sensor networks and we generalise previous works by allowing realistic energy assignment. A new modelisation of the process of energy consumption as a random walk along with a new analysis are proposed. Two new algorithms are presented and analysed. The first one is easy to implement and fast to execute. However, it needs a priori assumptions on the process generating data to be propagated. The second algorithm overcomes this need by inferring information from the observation of the process. Furthermore, this algorithm is based on stochastic estimation methods and is adaptive to environmental changes. This represents an important contribution for propagating energy balanced data in wireless sensor netwoks due to their highly dynamic nature.

Order conditions and symmetry for two-step hybrid methods

In this study of two-step hybrid methods for second-order equations of the type y″ = f(y), we apply P-series [Hairer, E., Lubich, C. and Wanner, G. (2002). Geometric Numerical Integration Structure-Preserving Algorithms for Ordinary Differential Equations. Springer Series in Computational Mathematics.] to formalise the approach of Chan [Chan, R. P. K. (2002). Two-step hybrid methods. Internal Publication.] to the order conditions, and present two characterizations of symmetry. Although order conditions can be obtained through the classical theory for the Nyström methods, it is of interest to derive particular simpler formulas for the class of two-step hybrid methods in order to facilitate the search for high-order methods. Moreover, the approach proves useful in analysing the symmetry of the hybrid methods.

Stochastic Models and Adaptive Algorithms for Energy Balance in Sensor Networks

We consider the important problem of energy balanced data propagation in wireless sensor networks and we extend and generalize previous works by allowing adaptive energy assignment. We consider the data gathering problem where data are generated by the sensors and must be routed toward a unique sink. Sensors route data by either sending the data directly to the sink or in a multi-hop fashion by delivering the data to a neighbouring sensor. Direct and neighbouring transmissions require different levels of energy consumption. Basically, the protocols balance the energy consumption among the sensors by computing the adequate ratios of direct and neighbouring transmissions. An abstract model of energy dissipation as a random walk is proposed, along with rigorous performance analysis techniques. Two efficient distributed algorithms are presented and analyzed, by both rigorous means and simulation. The first one is easy to implement and fast to execute. The protocol assumes that sensors know a-priori the rate of data they generate. The sink collects and processes all these information in order to compute the relevant value of the protocol parameter. This value is transmitted to the sensors which individually compute their optimal ratios of direct and neighbouring transmissions. The second protocol avoids the necessary a-priori knowledge of the data rate generated by sensors by inferring the relevant information from the observation of the data paths. Furthermore, this algorithm is based on stochastic estimation methods and is adaptive to environmental changes.

Geographic Routing with Early Obstacles Detection and Avoidance in Dense Wireless Sensor Networks

Existing geographic routing algorithms for sensor networks are mainly concerned with finding a path toward a destination, without explicitly addressing the impact of obstacles on the routing performance. When the size of the communication voids is increased, they might not scale well with respect to the quality of paths, measured in terms of hop count and path length. This paper introduces a routing algorithm with early obstacle detection and avoidance. The routing decisions are based on path optimality evaluation, made at the node level, gradually over time. We implement our algorithm and evaluate different aspects: message delivery performance, topology control overhead and algorithm convergence time. The simulation findings demonstrate that our algorithm manages to improve significantly and quite fast the path quality while keeping the computational complexity and message overhead low. The algorithm is fully distributed, and uses only limited local network knowledge.

Localization algorithm for wireless ad-hoc sensor networks with traffic overhead minimization by emission inhibition

Widely used positioning systems like GPS are not a valid solution in large networks with small size, low cost sensors, due both to their size and their cost. Thus, new solutions for localization awareness are emerging, commonly based on the existence of a few references spread into the network. We propose a localization algorithm to reduce the number of transmitting nodes. The algorithm relies on self selecting nodes for location information disclosure. Each node makes a decision based on its proximity to the nodes in the area covered only by two of the references used for its own localization. We analyze different aspects of the location awareness propagation problem: communication overhead, redundant transmissions, network coverage.

Self-stabilizing TDMA Algorithms for Dynamic Wireless Ad-hoc Networks

In dynamic wireless ad hoc networks (DynWANs), autonomous computing devices set up a network for the communication needs of the moment. These networks require the implementation of a medium access control (MAC) layer. We consider MAC protocols for DynWANs that need to be autonomous and robust as well as have high bandwidth utilization, high predictability degree of bandwidth allocation, and low communication delay in the presence of frequent topological changes to the communication network. Recent studies have shown that existing implementations cannot guarantee the necessary satisfaction of these timing requirements. We propose a self-stabilizing MAC algorithm for DynWANs that guarantees a short convergence period, and by that, it can facilitate the satisfaction of severe timing requirements, such as the above. Besides the contribution in the algorithmic front of research, we expect that our proposal can enable quicker adoption by practitioners and faster deployment of DynWANs that are subject changes in the network topology.

Chameleon-MAC: adaptive and self-algorithms for media access control in mobile ad hoc networks

In mobile ad hoc networks (MANETs) mobile nodes do not have access to a fixed network infrastructure and they set up a communication network by themselves. MANETs require implementation of a wireless Medium Access Control (MAC) layer. Existing MAC algorithms that consider no mobility, solve the problem of eventually guaranteeing every node with a share of the communications bandwidth. In the context of MANETs, we ask: Is there an efficient MAC algorithm when mobility is considered? MANETs are subject to transient faults, from which self-stabilizing systems can recover. The self-stabilization design criteria, and related concepts of self-*, liberate the application designer from dealing with low-level complications, and provide an important level of abstraction. Whereas stabilization criteria are important for the development of autonomous systems, adaptation is imperative for coping with a variable environment. Adapting to a variable environment requires dealing with a wide range of practical issues, such as relocation of mobile nodes and changes to the motion patterns. This work proposes the design and proof of concept implementation of an adapted MAC algorithm named CHAMELEON-MAC, which is based on a self-stabilizing algorithm by Leone et al., and uses self-* methods in order to further adapt its behavior according to the mobility characteristics of the environment. Moreover, we give an extensive treatment of the aspects and parameters that can bring the algorithm into the practical realm and we demonstrate documented behavior on real network studies (MICAz 2.4 GHz motes) as well as using simulation (TOSSIM [32]), showing improved overhead and fault-recovery periods than existing algorithms. We expect that these advantages, besides the contribution in the algorithmic front of research, can enable quicker adoption by practitioners and faster deployment.