End-to-End Energy Efficient Geographic Path Discovery With Guaranteed Delivery in Ad Hoc and Sensor Networks

International audienceWe propose a novel localized routing protocol for wireless sensor networks (WSN) that is energy-efficient and guarantees delivery. We prove that it is constant factor of the optimum for dense networks. To forward a packet, a node $s$ in graph $G$ computes the cost of the energy weighted shortest path (SP) between $s$ and each of its neighbors which are closer to the destination than itself. It then selects node $x$ which minimizes the ratio of the cost of the SP to the progress towards the destination. It then sends the message to the first node on the SP from $s$ to $x$: say node $x'$. Node $x'$ restarts the same greedy routing process until the destination is reached or the routing fails. To recover from failure, our algorithm invokes Face routing that guarantees delivery. This work is the first to optimize energy consumption of Face routing. First, we build a connected dominating set from graph $G$, second we compute its Gabriel graph to obtain the planar graph $G'$. Face routing is applied on $G'$ only to decide which edges to follow in the recovery process. On each edge, greedy routing is used. This two-phase (greedy-Face) End-to-End routing process (EtE) reiterates until the final destination is reached. Simulation results show that EtE outperforms several existing geographical routing on energy consumption metric

Cost over Progress Based Energy Efficient Routing over Virtual Coordinates in Wireless Sensor Networks

International audienceWe propose an energy efficient routing protocol, VCost, for sensor networks. We assume that nodes are unaware of their geographic location thus, VCost assigns virtual coordinates to nodes as follows. Based on the node hop count distances from a set of landmarks, our method computes a distance metric to obtain the node's virtual coordinates. VCost, then uses these coordinates to route packets from node u to node v, in its neighborhood, such that the ratio of the cost to send a message to v to the progress in the routing task towards the destination is minimized. Compared to existing algorithms that use virtual locations, our simulation shows that VCost improves significantly energy consumption and preserves the small percentage of successful routings

Routage multi-flots économe en énergie dans les réseaux de capteurs et actionneurs

International audienceL'introduction d'actionneurs capables de se déplacer sur ordre dans les réseaux de capteurs a permis l'émergence d'un nouveau genre de protocoles de routage. Ceux-ci tirent parti de cette nouvelle possibilité de relocaliser les éléments du réseau pour adapter dynamiquement sa topologie au trafic. Ils vont ainsi faire se déplacer physiquement les nœuds au fur et à mesure du routage afin d'optimiser le coût des transmissions radio. Toutefois, dans les réseaux de capteurs, il y a souvent plusieurs nœuds géographiquement proches pour reporter un même événement à la station de base. Les messages routés empruntent alors différents chemins qui sont physiquement proches, et certains nœuds appartiennent à plusieurs d'entre eux. Ces derniers vont alors sans cesse devoir se relocaliser sur les différents chemins et donc mourir prématurément. En réponse à ce problème, nous proposons PAMAL, le premier protocole de routage qui optimise la topologie réseau et sait tirer avantage des intersections des chemins de routage de manière complètement locale. PAMAL va ainsi provoquer la fusion des chemins de routage qui se croisent, et ce de plus en plus près des sources au cours et du temps. Les résultats de simulations montrent que ce comportement associé à un mécanisme d'agrégation permet d'améliorer la durée de vie du réseau de 37 %

Vers un protocole de routage géographique économe en énergie de bout en bout avec garantie de livraison.

International audienceNous introduisons EtE, le premier protocole de routage géographique qui soit à la fois économe en énergie et garantissant la livraison. EtE combine les points forts de techniques existantes que sont le coût sur progrès et le routage Greedy-Face-Greedy. Les résultats de simulation montrent que EtE présente une consommation énergétique non seulement plus faible que ses concurrents mais également supérieure de seulement 5% de la consommation optimale centralisée

Energy-aware Georouting with Guaranteed Delivery in Wireless Sensor Networks with Obstacles

International audienceWe propose, EtE, a novel end-to-end localized routing protocol for wireless sensor networks that is energy-efficient and guarantees delivery. To forward a packet, a node s in graph G computes the cost of the energy weighted shortest path between s and each of its neighbors in the forward direction towards the destination which minimizes the ratio of the cost of the shortest path to the progress (reduction in distance towards the destination). It then sends the message to the first node on the shortest path from s to x: say node x′. Node x′ restarts the same greedy rout- ing process until the destination is reached or an obstacle is encountered and the routing fails. To recover from the latter scenario, local minima trap, our algorithm invokes an energy-aware Face routing that guarantees delivery. Our work is the first to optimize energy consumption of Face routing. It works as follows. First, it builds a connected dominating set from graph G, second it computes its Gabriel graph to obtain the planar graph G′. Face routing is invoked and applied to G′ only to determine which edges to follow in the recovery process. On each edge, greedy rout- ing is applied. This two-phase (greedy-Face) End-to-End routing process (EtE) reiterates until the final destination is reached. Simulation results show that EtE outperforms several existing geographical routing on en- ergy consumption metric and delivery rate. Moreover, we prove that the computed path length and the total energy of the path are constant factors of the optimal for dense networks

Energy Efficient Multi-Flow Routing in Mobile Sensor Networks.

International audienceControlled mobility is one of the most complex challenges in Wireless Sensor Networks (WSN). Only a few routing protocols consider controlled mobility in order to extend the network lifetime. They are all designed to optimize the physical route topology from a source to a destination. However, there is often more than one sensor which reports an event to the sink in WSN. In existing solutions, this leads to oscillation of nodes which belong to different routes and their premature death. Experiments show that the need of a routing path merge solution is high. As a response we propose the first routing protocol which locates and uses paths crossing to adapt the topology to the network traffic in a fully localized way while still optimizing energy efficiency. Furthermore the protocol makes the intersection to move away from the destination, getting closer to the sources, allowing higher data aggregation and energy saving. Our approach outperforms existing solutions and extends network lifetime up to 37%

Energy-aware Georouting with Guaranteed Delivery in Wireless Sensor Networks with Obstacles

International audienceWe propose, EtE, a novel end-to-end localized routing protocol for wireless sensor networks that is energy-efficient and guarantees delivery. To forward a packet, a node s in graph G computes the cost of the energy weighted shortest path between s and each of its neighbors in the forward direction towards the destination which minimizes the ratio of the cost of the shortest path to the progress (reduction in distance towards the destination). It then sends the message to the first node on the shortest path from s to x: say node x′. Node x′ restarts the same greedy rout- ing process until the destination is reached or an obstacle is encountered and the routing fails. To recover from the latter scenario, local minima trap, our algorithm invokes an energy-aware Face routing that guarantees delivery. Our work is the first to optimize energy consumption of Face routing. It works as follows. First, it builds a connected dominating set from graph G, second it computes its Gabriel graph to obtain the planar graph G′. Face routing is invoked and applied to G′ only to determine which edges to follow in the recovery process. On each edge, greedy rout- ing is applied. This two-phase (greedy-Face) End-to-End routing process (EtE) reiterates until the final destination is reached. Simulation results show that EtE outperforms several existing geographical routing on en- ergy consumption metric and delivery rate. Moreover, we prove that the computed path length and the total energy of the path are constant factors of the optimal for dense networks

An Optimal Flow Admission and Routing Control Policy for Resource Constrained Networks

Overloaded network devices are becoming an increasing problem especially in resource limited networks with the continuous and rapid increase of wireless devices and the huge volume of data generated. Admission and routing control policy at a network device can be used to balance the goals of maximizing throughput and ensuring sufficient resources for high priority flows. In this paper we formulate the admission and routing control problem of two types of flows where one has a higher priority than the other as a Markov decision problem. We characterize the optimal admission and routing policy, and show that it is a state-dependent threshold type policy. Furthermore, we conduct extensive numerical experiments to gain more insight into the behavior of the optimal policy under different systems’ parameters. While dynamic programming can be used to solve such problems, the large size of the state space makes it untractable and too resource intensive to run on wireless devices. Therefore, we propose a fast heuristic that exploits the structure of the optimal policy. We empirically show that the heuristic performs very well with an average reward deviation of 1.4% from the optimal while being orders of magnitude faster than the optimal policy. We further generalize the heuristic for the general case of a system with n (n>2) types of flows

Optimal production and inventory control of multi-class mixed backorder and lost sales demand class models

10.1016/j.ejor.2020.09.009European Journal of Operational Research2911147-16

A Novel Decomposition-Based Method for Solving General-Product Structure Assemble-to-Order Systems

10.1016/j.ejor.2020.03.01