Towards the fast and robust optimal design of Wireless Body Area Networks

Wireless body area networks are wireless sensor networks whose adoption has recently emerged and spread in important healthcare applications, such as the remote monitoring of health conditions of patients. A major issue associated with the deployment of such networks is represented by energy consumption: in general, the batteries of the sensors cannot be easily replaced and recharged, so containing the usage of energy by a rational design of the network and of the routing is crucial. Another issue is represented by traffic uncertainty: body sensors may produce data at a variable rate that is not exactly known in advance, for example because the generation of data is event-driven. Neglecting traffic uncertainty may lead to wrong design and routing decisions, which may compromise the functionality of the network and have very bad effects on the health of the patients. In order to address these issues, in this work we propose the first robust optimization model for jointly optimizing the topology and the routing in body area networks under traffic uncertainty. Since the problem may result challenging even for a state-of-the-art optimization solver, we propose an original optimization algorithm that exploits suitable linear relaxations to guide a randomized fixing of the variables, supported by an exact large variable neighborhood search. Experiments on realistic instances indicate that our algorithm performs better than a state-of-the-art solver, fast producing solutions associated with improved optimality gaps.Comment: Authors' manuscript version of the paper that was published in Applied Soft Computin

Recognizing and Drawing IC-planar Graphs

IC-planar graphs are those graphs that admit a drawing where no two crossed edges share an end-vertex and each edge is crossed at most once. They are a proper subfamily of the 1-planar graphs. Given an embedded IC-planar graph $G$ with $n$ vertices, we present an $O(n)$-time algorithm that computes a straight-line drawing of $G$ in quadratic area, and an $O(n^3)$-time algorithm that computes a straight-line drawing of $G$ with right-angle crossings in exponential area. Both these area requirements are worst-case optimal. We also show that it is NP-complete to test IC-planarity both in the general case and in the case in which a rotation system is fixed for the input graph. Furthermore, we describe a polynomial-time algorithm to test whether a set of matching edges can be added to a triangulated planar graph such that the resulting graph is IC-planar

CloudJet4BigData: Streamlining Big Data via an Accelerated Socket Interface

Big data needs to feed users with fresh processing results and cloud platforms can be used to speed up big data applications. This paper describes a new data communication protocol (CloudJet) for long distance and large volume big data accessing operations to alleviate the large latencies encountered in sharing big data resources in the clouds. It encapsulates a dynamic multi-stream/multi-path engine at the socket level, which conforms to Portable Operating System Interface (POSIX) and thereby can accelerate any POSIX-compatible applications across IP based networks. It was demonstrated that CloudJet accelerates typical big data applications such as very large database (VLDB), data mining, media streaming and office applications by up to tenfold in real-world tests

Lifetime Improvement in Wireless Sensor Networks via Collaborative Beamforming and Cooperative Transmission

Collaborative beamforming (CB) and cooperative transmission (CT) have recently emerged as communication techniques that can make effective use of collaborative/cooperative nodes to create a virtual multiple-input/multiple-output (MIMO) system. Extending the lifetime of networks composed of battery-operated nodes is a key issue in the design and operation of wireless sensor networks. This paper considers the effects on network lifetime of allowing closely located nodes to use CB/CT to reduce the load or even to avoid packet-forwarding requests to nodes that have critical battery life. First, the effectiveness of CB/CT in improving the signal strength at a faraway destination using energy in nearby nodes is studied. Then, the performance improvement obtained by this technique is analyzed for a special 2D disk case. Further, for general networks in which information-generation rates are fixed, a new routing problem is formulated as a linear programming problem, while for other general networks, the cost for routing is dynamically adjusted according to the amount of energy remaining and the effectiveness of CB/CT. From the analysis and the simulation results, it is seen that the proposed method can reduce the payloads of energy-depleting nodes by about 90% in the special case network considered and improve the lifetimes of general networks by about 10%, compared with existing techniques.Comment: Invited paper to appear in the IEE Proceedings: Microwaves, Antennas and Propagation, Special Issue on Antenna Systems and Propagation for Future Wireless Communication

Edge Routing with Ordered Bundles

Edge bundling reduces the visual clutter in a drawing of a graph by uniting the edges into bundles. We propose a method of edge bundling drawing each edge of a bundle separately as in metro-maps and call our method ordered bundles. To produce aesthetically looking edge routes it minimizes a cost function on the edges. The cost function depends on the ink, required to draw the edges, the edge lengths, widths and separations. The cost also penalizes for too many edges passing through narrow channels by using the constrained Delaunay triangulation. The method avoids unnecessary edge-node and edge-edge crossings. To draw edges with the minimal number of crossings and separately within the same bundle we develop an efficient algorithm solving a variant of the metro-line crossing minimization problem. In general, the method creates clear and smooth edge routes giving an overview of the global graph structure, while still drawing each edge separately and thus enabling local analysis

Semi-automated modeling approaches to route selection in GIS

As an alternative to traditional graphical intuitive approaches (GIA), a semi-automated modeling approach (SMA) can more efficiently identify linear routes by using powerful iterative and automated methods. In this research, two case studies were investigated to examine critical issues relating to the accuracy and effectiveness of raster-defined algorithmic approaches to linear route location. The results illustrate that different shortest-path algorithms do not necessarily result in markedly different linear routes. However, differing results can occur when using different neighboring-cell links in the cell-based route network construction. Cell-based algorithmic approaches in both Arc/Info and IDRISI software generate very similar results which are comparable to linear modeling with greater than eight neighboring-cell links. Given a specific shortest-path algorithm and its route searching technique, the use of a finer spatial resolution only results in a narrower and smoother route corridor. Importantly, cost surface models can be generated to represent differing cumulative environmental \u27costs\u27 or impacts in which different perceptions of environmental cost can be simulated and evaluated.;Three different simulation techniques comprising Ordered Weighted Combination models (OWC), Dynamic Decision Space (DDS), and Gateway-based approaches, were used to address problems associated with concurrent and dynamic changes in multi-objective decision space. These approaches provide efficient and flexible simulation capability within a dynamic and changing decision space. When aggregation data models were used within a Gateway approach the match of resulting routes between GIA and SMA analyses is close. The effectiveness of SMA is greatly limited when confronted by extensive linear and impermeable barriers or where data is sparse. Overall, achieving consensus on environmental cost surface generation and criteria selection is a prerequisite for a successful SMA outcome. It is concluded that SMA has several positive advantages that certainly complement a GIA in linear route siting and spatial decision-making

Nonpoint Source Pollution Control Using a Multi-Objective Optimization Tool for Best Management Practices Selection and Spatial Placement in the Lower Bear River Watershed, Utah

This dissertation presents a set of approaches to help address water quality problems related to total phosphorus loads in water bodies. Water quality degradation is caused by many nonpoint sources such as agricultural runoff, fertilizers applications, and bank erosion. Three studies present methodologies for water quality protection from degradation in watersheds. The first study demonstrates the application of a watershed simulation tool that can quantify flows in the watershed, the amount of released pollutants and identify the areas contributing to the pollutants’ release in the watershed. The second study presents a simple combination tool that can pair potential management practices with the identified nonpoint sources areas to generate cost-effective combinations of management practices for reducing excess phosphorus loading to water bodies. The last study develops an optimization framework that recommends the area optimum sizes that are available for implementing management practices. These studies were applied to real-case problems to reduce excess nutrients within the Lower Bear River Watershed in northern Utah and expected to improve the management of nutrient control plans under the allocated funds

Tramp Ship Scheduling Problem with Berth Allocation Considerations and Time-dependent Constraints

This work presents a model for the Tramp Ship Scheduling problem including berth allocation considerations, motivated by a real case of a shipping company. The aim is to determine the travel schedule for each vessel considering multiple docking and multiple time windows at the berths. This work is innovative due to the consideration of both spatial and temporal attributes during the scheduling process. The resulting model is formulated as a mixed-integer linear programming problem, and a heuristic method to deal with multiple vessel schedules is also presented. Numerical experimentation is performed to highlight the benefits of the proposed approach and the applicability of the heuristic. Conclusions and recommendations for further research are provided.Comment: 16 pages, 3 figures, 5 tables, proceedings paper of Mexican International Conference on Artificial Intelligence (MICAI) 201

Connectivity, Coverage and Placement in Wireless Sensor Networks

Wireless communication between sensors allows the formation of flexible sensor networks, which can be deployed rapidly over wide or inaccessible areas. However, the need to gather data from all sensors in the network imposes constraints on the distances between sensors. This survey describes the state of the art in techniques for determining the minimum density and optimal locations of relay nodes and ordinary sensors to ensure connectivity, subject to various degrees of uncertainty in the locations of the nodes