Moussab/ORKG-training-evaluation-set huggingface dataset:
Research field: Science
Title: Energy-efficient communication protocol for wireless microsensor networks
Abstract: Wireless distributed microsensor systems will enable the reliable monitoring of a variety of environments for both civil and military applications. In this paper, we look at communication protocols, which can have significant impact on the overall energy dissipation of these networks. Based on our findings that the conventional protocols of direct transmission, minimum-transmission-energy, multi-hop routing, and static clustering may not be optimal for sensor networks, we propose LEACH (Low-Energy Adaptive Clustering Hierarchy), a clustering-based protocol that utilizes randomized rotation of local cluster based station (cluster-heads) to evenly distribute the energy load among the sensors in the network. LEACH uses localized coordination to enable scalability and robustness for dynamic networks, and incorporates data fusion into the routing protocol to reduce the amount of information that must be transmitted to the base station. Simulations show the LEACH can achieve as much as a factor of 8 reduction in energy dissipation compared with conventional outing protocols. In addition, LEACH is able to distribute energy dissipation evenly throughout the sensors, doubling the useful system lifetime for the networks we simulated.
Extracted statement — Inter-cluster topology: direct
Research field: Science
Title: On the Effectiveness of Direct Shipping Strategy for the One-Warehouse Multi-Retailer R-Systems
Abstract: We consider the problem of integrating inventory control and vehicle routing into a cost-effective strategy for a distribution system consisting of one depot and many geographically dispersed retailers. All stock enters the system through the depot and is distributed to the retailers by vehicles of limited constant capacity. We assume that each one of the retailers faces a constant, retailer specific, demand rate and that inventory is charged only at the retailers but not at the depot. We provide a lower bound on the long run average cost over all inventory-routing strategies. We use this lower bound to show that the effectiveness of direct shipping over all inventory-routing strategies is at least 94% whenever the Economic Lot Size of each of the retailers is at least 71% of vehicle capacity. The effectiveness deteriorates as the Economic Lot Sizes become smaller. These results are important because they provide useful guidelines as to when to embark into the much more difficult task of finding cost-effective routes. Additional advantages of direct shipping are lower in-transit inventory and ease of coordination.
Extracted statement — outing: direct
Research field: Science
Title: Fully Loaded Direct Shipping Strategy in One Warehouse/NRetailer Systems without Central Inventories
Abstract: In this paper, we consider one warehouse/multiple retailer systems with transportation costs. The planning horizon is infinite and the warehouse keeps no central inventory. It is shown that the fully loaded direct shipping strategy is optimal among all possible shipping/allocation strategies if the truck capacity is smaller than a certain quantity, and a bound is provided for the general case.
Extracted statement — outing: direct
Research field: Science
Title: The Stochastic Inventory Routing Problem with Direct Deliveries
Abstract: Vendor managed inventory replenishment is a business practice in which vendors monitor their customers' inventories, and decide when and how much inventory should be replenished. The inventory routing problem addresses the coordination of inventory management and transportation. The ability to solve the inventory routing problem contributes to the realization of the potential savings in inventory and transportation costs brought about by vendor managed inventory replenishment. The inventory routing problem is hard, especially if a large number of customers is involved. We formulate the inventory routing problem as a Markov decision process, and we propose approximation methods to find good solutions with reasonable computational effort. Computational results are presented for the inventory routing problem with direct deliveries.
Extracted statement — outing: direct
Research field: Science
Title: Energy-efficient communication protocol for wireless microsensor networks
Abstract: Wireless distributed microsensor systems will enable the reliable monitoring of a variety of environments for both civil and military applications. In this paper, we look at communication protocols, which can have significant impact on the overall energy dissipation of these networks. Based on our findings that the conventional protocols of direct transmission, minimum-transmission-energy, multi-hop routing, and static clustering may not be optimal for sensor networks, we propose LEACH (Low-Energy Adaptive Clustering Hierarchy), a clustering-based protocol that utilizes randomized rotation of local cluster based station (cluster-heads) to evenly distribute the energy load among the sensors in the network. LEACH uses localized coordination to enable scalability and robustness for dynamic networks, and incorporates data fusion into the routing protocol to reduce the amount of information that must be transmitted to the base station. Simulations show the LEACH can achieve as much as a factor of 8 reduction in energy dissipation compared with conventional outing protocols. In addition, LEACH is able to distribute energy dissipation evenly throughout the sensors, doubling the useful system lifetime for the networks we simulated.
Extracted statement — Method: Distributed
Research field: Science
Title: A clustering scheme for hierarchical control in multi-hop wireless networks
Abstract: In this paper we present a clustering scheme to create a hierarchical control structure for multi-hop wireless networks. A cluster is defined as a subset of vertices, whose induced graph is connected. In addition, a cluster is required to obey certain constraints that are useful for management and scalability of the hierarchy. All these constraints cannot be met simultaneously for general graphs, but we show how such a clustering can be obtained for wireless network topologies. Finally, we present an efficient distributed implementation of our clustering algorithm for a set of wireless nodes to create the set of desired clusters.
Extracted statement — Method: Distributed
Research field: Science
Title: Distributed clustering in ad-hoc sensor networks: a hybrid, energy-efficient approach
Abstract: Prolonged network lifetime, scalability, and load balancing are important requirements for many ad-hoc sensor network applications. Clustering sensor nodes is an effective technique for achieving these goals. In this work, we propose a new energy-efficient approach for clustering nodes in ad-hoc sensor networks. Based on this approach, we present a protocol, HEED (hybrid energy-efficient distributed clustering), that periodically selects cluster heads according to a hybrid of their residual energy and a secondary parameter, such as node proximity to its neighbors or node degree. HEED does not make any assumptions about the distribution or density of nodes, or about node capabilities, e.g., location-awareness. The clustering process terminates in O(1) iterations, and does not depend on the network topology or size. The protocol incurs low overhead in terms of processing cycles and messages exchanged. It also achieves fairly uniform cluster head distribution across the network. A careful selection of the secondary clustering parameter can balance load among cluster heads. Our simulation results demonstrate that HEED outperforms weight-based clustering protocols in terms of several cluster characteristics. We also apply our approach to a simple application to demonstrate its effectiveness in prolonging the network lifetime and supporting data aggregation.
Extracted statement — Method: Distributed
Research field: Science
Title: WSN16-5: Distributed Formation of Overlapping Multi-hop Clusters in Wireless Sensor Networks
Abstract: Clustering is a standard approach for achieving efficient and scalable performance in wireless sensor networks. Most of the published clustering algorithms strive to generate the minimum number of disjoint clusters. However, we argue that guaranteeing some degree of overlap among clusters can facilitate many applications, like inter-cluster routing, topology discovery and node localization, recovery from cluster head failure, etc. We formulate the overlapping multi-hop clustering problem as an extension to the k-dominating set problem. Then we propose MOCA; a randomized distributed multi-hop clustering algorithm for organizing the sensors into overlapping clusters. We validate MOCA in a simulated environment and analyze the effect of different parameters, e.g. node density and network connectivity, on its performance. The simulation results demonstrate that MOCA is scalable, introduces low overhead and produces approximately equal-sized clusters.
Extracted statement — Method: Distributed
Research field: Science
Title: SEP: A Stable Election Protocol for clustered heterogeneous wireless sensor networks
Abstract: We study the impact of heterogeneity of nodes, in terms of their energy, in wireless sensor networks that are hierarchically clustered. In these networks some of the nodes become cluster heads, aggregate the data of their cluster members and transmit it to the sink. We assume that a percentage of the population of sensor nodes is equipped with additional energy resources—this is a source of heterogeneity which may result from the initial setting or as the operation of the network evolves. We also assume that the sensors are randomly (uniformly) distributed and are not mobile, the coordinates of the sink and the dimensions of the sensor field are known. We show that the behavior of such sensor networks becomes very unstable once the first node dies, especially in the presence of node heterogeneity. Classical clustering protocols assume that all the nodes are equipped with the same amount of energy and as a result, they can not take full advantage of the presence of node heterogeneity. We propose SEP, a heterogeneous-aware protocol to prolong the time interval before the death of the first node (we refer to as stability period), which is crucial for many applications where the feedback from the sensor network must be reliable. SEP is based on weighted election probabilities of each node to become cluster head according to the remaining energy in each node. We show by simulation that SEP always prolongs the stability period compared to (and that the average throughput is greater than) the one obtained using current clustering protocols. We conclude by studying the sensitivity of our SEP protocol to heterogeneity parameters capturing energy imbalance in the network. We found that SEP yields longer stability region for higher values of extra energy brought by more powerful nodes.
Extracted statement — Method: Distributed
Research field: Science
Title: A clustering method for energy efficient routing in wireless sensor networks
Abstract: Low-Energy Adaptive Clustering Hierarchy (LEACH) is one of the most popular distributed cluster-based routing protocols in wireless sensor networks. Clustering algorithm of the LEACH is simple but offers no guarantee about even distribution of cluster heads over the network. And it assumes that each cluster head transmits data to sink over a single hop. In this paper, we propose a new method for selecting cluster heads to evenly distribute cluster heads. It avoids creating redundant cluster heads within a small geographical range. Simulation results show that our scheme reduces energy dissipation and prolongs network lifetime as compared with LEACH.
Extracted statement — Method: Distributed
Research field: Science
Title: Distance based thresholds for cluster head selection in wireless sensor networks
Abstract: Central to the cluster-based routing protocols is the cluster head (CH) selection procedure that allows even distribution of energy consumption among the sensors, and therefore prolonging the lifespan of a sensor network. We propose a distributed CH selection algorithm that takes into account the distances from sensors to a base station that optimally balances the energy consumption among the sensors. NS-2 simulations show that our proposed scheme outperforms existing algorithms in terms of the average node lifespan and the time to first node death.
Extracted statement — Method: Distributed
Research field: Science
Title: An energy efficient hierarchical clustering algorithm for wireless sensor networks
Abstract: A wireless network consisting of a large number of small sensors with low-power transceivers can be an effective tool for gathering data in a variety of environments. The data collected by each sensor is communicated through the network to a single processing center that uses all reported data to determine characteristics of the environment or detect an event. The communication or message passing process must be designed to conserve the limited energy resources of the sensors. Clustering sensors into groups, so that sensors communicate information only to clusterheads and then the clusterheads communicate the aggregated information to the processing center, may save energy. In this paper, we propose a distributed, randomized clustering algorithm to organize the sensors in a wireless sensor network into clusters. We then extend this algorithm to generate a hierarchy of clusterheads and observe that the energy savings increase with the number of levels in the hierarchy. Results in stochastic geometry are used to derive solutions for the values of parameters of our algorithm that minimize the total energy spent in the network when all sensors report data through the clusterheads to the processing center.
Extracted statement — Method: Distributed
Research field: Science
Title: TASC: topology adaptive spatial clustering for sensor networks
Abstract: The ability to extract topological regularity out of large randomly deployed sensor networks holds the promise to maximally leverage correlation for data aggregation and also to assist with sensor localization and hierarchy creation. This paper focuses on extracting such regular structures from physical topology through the development of a distributed clustering scheme. The topology adaptive spatial clustering (TASC) algorithm presented here is a distributed algorithm that partitions the network into a set of locally isotropic, non-overlapping clusters without prior knowledge of the number of clusters, cluster size and node coordinates. This is achieved by deriving a set of weights that encode distance measurements, connectivity and density information within the locality of each node. The derived weights form the terrain for holding a coordinated leader election in which each node selects the node closer to the center of mass of its neighborhood to become its leader. The clustering algorithm also employs a dynamic density reachability criterion that groups nodes according to their neighborhood's density properties. Our simulation results show that the proposed algorithm can trace locally isotropic structures in non-isotropic network and cluster the network with respect to local density attributes. We also found out that TASC exhibits consistent behavior in the presence of moderate measurement noise levels
Extracted statement — Method: Distributed
Research field: Science
Title: Topology-controlled adaptive clustering for uniformity and increased lifetime in wireless sensor networks
Abstract: Owing to the dynamic nature of sensor network applications the adoption of adaptive cluster-based topologies has many untapped desirable benefits for the wireless sensor networks. In this study, the authors explore such possibility and present an adaptive clustering algorithm to increase the network's lifetime while maintaining the required network connectivity. The proposed scheme features capability of cluster heads to adjust their power level to achieve optimal degree and maintain this value throughout the network operation. Under the proposed method a topology control allows an optimal degree, which results in a better distributed sensors and well-balanced clustering system enhancing networks' lifetime. The simulation results show that the proposed clustering algorithm maintains the required degree for inter-cluster connectivity on many more rounds compared with hybrid energy-efficient distributed clustering (HEED), energy-efficient clustering scheme (EECS), low-energy adaptive clustering hierarchy (LEACH) and energy-based LEACH.
Extracted statement — Method: Distributed
Research field: Science
Title: An energy-efficient distributed unequal clustering protocol for wireless sensor networks
Abstract: Due to the imbalance of energy consumption of nodes in wireless sensor networks (WSNs), some local nodes die prematurely, which causes the network partitions and then shortens the lifetime of the network. The phenomenon is called “hot spot” or “energy hole” problem. For this problem, an energy-aware distributed unequal clustering protocol (EADUC) in multihop heterogeneous WSNs is proposed. Compared with the previous protocols, the cluster heads obtained by EADUC can achieve balanced energy, good distribution, and seamless coverage for all the nodes.Moreover, the complexity of time and control message is low. Simulation experiments show that EADUC can prolong the lifetime of the network significantly.
Extracted statement — Method: Distributed
Research field: Science
Title: An Energy-Efficient Clustering Solution for Wireless Sensor Networks
Abstract: Hot spots in a wireless sensor network emerge as locations under heavy traffic load. Nodes in such areas quickly deplete energy resources, leading to disruption in network services. This problem is common for data collection scenarios in which Cluster Heads (CH) have a heavy burden of gathering and relaying information. The relay load on CHs especially intensifies as the distance to the sink decreases. To balance the traffic load and the energy consumption in the network, the CH role should be rotated among all nodes and the cluster sizes should be carefully determined at different parts of the network. This paper proposes a distributed clustering algorithm, Energy-efficient Clustering (EC), that determines suitable cluster sizes depending on the hop distance to the data sink, while achieving approximate equalization of node lifetimes and reduced energy consumption levels. We additionally propose a simple energy-efficient multihop data collection protocol to evaluate the effectiveness of EC and calculate the end-to-end energy consumption of this protocol; yet EC is suitable for any data collection protocol that focuses on energy conservation. Performance results demonstrate that EC extends network lifetime and achieves energy equalization more effectively than two well-known clustering algorithms, HEED and UCR.
Extracted statement — Method: Distributed
Research field: Science
Title: An Energy-Aware Distributed Unequal Clustering Protocol for Wireless Sensor Networks
Abstract: Due to the imbalance of energy consumption of nodes in wireless sensor networks (WSNs), some local nodes die prematurely, which causes the network partitions and then shortens the lifetime of the network. The phenomenon is called “hot spot” or “energy hole” problem. For this problem, an energy-aware distributed unequal clustering protocol (EADUC) in multihop heterogeneous WSNs is proposed. Compared with the previous protocols, the cluster heads obtained by EADUC can achieve balanced energy, good distribution, and seamless coverage for all the nodes. Moreover, the complexity of time and control message is low. Simulation experiments show that EADUC can prolong the lifetime of the network significantly.
Extracted statement — Method: Distributed
Research field: Science
Title: Chemical Composition of the Essential Oil ofArtemisia herba-albaAsso Grown in Algeria
Abstract: Abstract The essential oil obtained by hydrodistillation from the aerial parts of Artemisia herba-alba Asso growing wild in M'sila-Algeria, was investigated using both capillary GC and GC/MS techniques. The oil yield was 1.02% based on dry weight. Sixty-eight components amounting to 94.7% of the oil were identifed, 33 of them being reported for the frst time in Algerian A. herba-alba oil and 21 of these components have not been previously reported in A. herba-alba oils. The oil contained camphor (19.4%), trans-pinocarveol (16.9%), chrysanthenone (15.8%) and β-thujone (15%) as major components. Monoterpenoids are the main components (86.1%), and the irregular monoterpenes fraction represented a 3.1% yield.
Extracted statement — Plant material status: Dry
Research field: Science
Title: IMPACT OF SEASON AND HARVEST FREQUENCY ON BIOMASS AND ESSENTIAL OIL YIELDS OF ARTEMISIA HERBA-ALBA CULTIVATED IN SOUTHERN TUNISIA
Abstract: <jats:title>SUMMARY</jats:title><jats:p><jats:italic>Artemisia herba-alba</jats:italic> Asso has been successfully cultivated in the Tunisian arid zone. However, information regarding the effects of the harvest frequency on its biomass and essential oil yields is very limited. In this study, the effects of three different frequencies of harvesting the upper half of the <jats:italic>A. herba-alba</jats:italic> plant tuft were compared. The harvest treatments were: harvesting the same individual plants at the flowering stage annually; harvesting the same individual plants at the full vegetative growth stage annually and harvesting the same individual plants every six months. Statistical analyses indicated that all properties studied were affected by the harvest frequency. Essential oil yield, depended both on the dry biomass and its essential oil content, and was significantly higher from plants harvested annually at the flowering stage than the other two treatments. The composition of the β- and α-thujone-rich oils did not vary throughout the experimental period.</jats:p>
Extracted statement — Plant material status: Dry
Research field: Science
Title: Probabilistic Analyses and Algorithms for Three-Level Distribution Systems
Abstract: We consider the problem of integrating inventory control and vehicle routing into a cost-effective strategy for a distribution system consisting of a single outside vendor, a fixed number of warehouses and many geographically dispersed retailers. Each retailer faces a constant, retailer specific, demand rate and inventory holding cost is charged at the retailers and the warehouses. We show that, in an effective strategy which minimizes the asymptotic long run average cost, each warehouse receives fully loaded trucks from the vendor but never holds inventory. That is, each warehouse serves only as a coordinator of the frequency, time and sizes of deliveries to the retailers. This insight is used to construct an inventory control policy and vehicle routing strategy for multi-echelon distribution systems. Computational results are also reported.
Extracted statement — Inventory: Fixed
Research field: Science
Title: GrOWL: A Tool for Visualization and Editing of OWL Ontologies
Abstract: In an effort to optimize visualization and editing of OWL ontologies we have developed GrOWL: a browser and visual editor for OWL that accurately visualizes the underlying DL semantics of OWL ontologies while avoiding the difficulties of the verbose OWL syntax. In this paper, we discuss GrOWL visualization model and the essential visualization techniques implemented in GrOWL.
Extracted statement — System: GrOWL