2,071 research outputs found

    On distributed scheduling in wireless networks exploiting broadcast and network coding

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    In this paper, we consider cross-layer optimization in wireless networks with wireless broadcast advantage, focusing on the problem of distributed scheduling of broadcast links. The wireless broadcast advantage is most useful in multicast scenarios. As such, we include network coding in our design to exploit the throughput gain brought in by network coding for multicasting. We derive a subgradient algorithm for joint rate control, network coding and scheduling, which however requires centralized link scheduling. Under the primary interference model, link scheduling problem is equivalent to a maximum weighted hypergraph matching problem that is NP-complete. To solve the scheduling problem distributedly, locally greedy and randomized approximation algorithms are proposed and shown to have bounded worst-case performance. With random network coding, we obtain a fully distributed cross-layer design. Numerical results show promising throughput gain using the proposed algorithms, and surprisingly, in some cases even with less complexity than cross-layer design without broadcast advantage

    Performance optimization of wireless sensor networks for remote monitoring

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    Wireless sensor networks (WSNs) have gained worldwide attention in recent years because of their great potential for a variety of applications such as hazardous environment exploration, military surveillance, habitat monitoring, seismic sensing, and so on. In this thesis we study the use of WSNs for remote monitoring, where a wireless sensor network is deployed in a remote region for sensing phenomena of interest while its data monitoring center is located in a metropolitan area that is geographically distant from the monitored region. This application scenario poses great challenges since such kind of monitoring is typically large scale and expected to be operational for a prolonged period without human involvement. Also, the long distance between the monitored region and the data monitoring center requires that the sensed data must be transferred by the employment of a third-party communication service, which incurs service costs. Existing methodologies for performance optimization of WSNs base on that both the sensor network and its data monitoring center are co-located, and therefore are no longer applicable to the remote monitoring scenario. Thus, developing new techniques and approaches for severely resource-constrained WSNs is desperately needed to maintain sustainable, unattended remote monitoring with low cost. Specifically, this thesis addresses the key issues and tackles problems in the deployment of WSNs for remote monitoring from the following aspects. To maximize the lifetime of large-scale monitoring, we deal with the energy consumption imbalance issue by exploring multiple sinks. We develop scalable algorithms which determine the optimal number of sinks needed and their locations, thereby dynamically identifying the energy bottlenecks and balancing the data relay workload throughout the network. We conduct experiments and the experimental results demonstrate that the proposed algorithms significantly prolong the network lifetime. To eliminate imbalance of energy consumption among sensor nodes, a complementary strategy is to introduce a mobile sink for data gathering. However, the limited communication time between the mobile sink and nodes results in that only part of sensed data will be collected and the rest will be lost, for which we propose the concept of monitoring quality with the exploration of sensed data correlation among nodes. We devise a heuristic for monitoring quality maximization, which schedules the sink to collect data from selected nodes, and uses the collected data to recover the missing ones. We study the performance of the proposed heuristic and validate its effectiveness in improving the monitoring quality. To strive for the fine trade-off between two performance metrics: throughput and cost, we investigate novel problems of minimizing cost with guaranteed throughput, and maximizing throughput with minimal cost. We develop approximation algorithms which find reliable data routing in the WSN and strategically balance workload on the sinks. We prove that the delivered solutions are fractional of the optimum. We finally conclude our work and discuss potential research topics which derive from the studies of this thesis

    RTXP : A Localized Real-Time Mac-Routing Protocol for Wireless Sensor Networks

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    Protocols developed during the last years for Wireless Sensor Networks (WSNs) are mainly focused on energy efficiency and autonomous mechanisms (e.g. self-organization, self-configuration, etc). Nevertheless, with new WSN applications, appear new QoS requirements such as time constraints. Real-time applications require the packets to be delivered before a known time bound which depends on the application requirements. We particularly focus on applications which consist in alarms sent to the sink node. We propose Real-Time X-layer Protocol (RTXP), a real-time communication protocol. To the best of our knowledge, RTXP is the first MAC and routing real-time communication protocol that is not centralized, but instead relies only on local information. The solution is cross-layer (X-layer) because it allows to control the delays due to MAC and Routing layers interactions. RTXP uses a suited hop-count-based Virtual Coordinate System which allows deterministic medium access and forwarder selection. In this paper we describe the protocol mechanisms. We give theoretical bound on the end-to-end delay and the capacity of the protocol. Intensive simulation results confirm the theoretical predictions and allow to compare with a real-time centralized solution. RTXP is also simulated under harsh radio channel, in this case the radio link introduces probabilistic behavior. Nevertheless, we show that RTXP it performs better than a non-deterministic solution. It thus advocates for the usefulness of designing real-time (deterministic) protocols even for highly unreliable networks such as WSNs

    Delay Tolerant Energy Efficient protocol for Inter-BAN Communication in Mobile Body Area Networks

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    Body Area Networks (BANs) are used in a range of applications. In these networks the sensor nodes attached to human body collect data and send it to controller node which in turn sends to a Base Station (BS) located at a remote location. The controller nodes in a BAN can be replaced easily but when it comes to BANs moving in areas like a war it is hard to replace the batteries frequently. So we need to reduce energy requirement of the nodes to increase the network lifetime. Using mobile sensors is one way to reduce energy and controller nodes can send data to sink easily while performing inter-BAN communication where nodes need to act in a cooperative manner to send data to BS using multi-hop communication. In this paper, we have proposed a new clustering algorithm in which probability of a node to become a Cluster Head (CH) is decided on the basis of its geographical location and residual energy of the node. Simulations results show that the proposed protocol is better than the existing EDDEEC protocol in terms of delay, energy efficiency, reliability and network lifetime.

    Mathematical Models and Algorithms for Network Flow Problems Arising in Wireless Sensor Network Applications

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    We examine multiple variations on two classical network flow problems, the maximum flow and minimum-cost flow problems. These two problems are well-studied within the optimization community, and many models and algorithms have been presented for their solution. Due to the unique characteristics of the problems we consider, existing approaches cannot be directly applied. The problem variations we examine commonly arise in wireless sensor network (WSN) applications. A WSN consists of a set of sensors and collection sinks that gather and analyze environmental conditions. In addition to providing a taxonomy of relevant literature, we present mathematical programming models and algorithms for solving such problems. First, we consider a variation of the maximum flow problem having node-capacity restrictions. As an alternative to solving a single linear programming (LP) model, we present two alternative solution techniques. The first iteratively solves two smaller auxiliary LP models, and the second is a heuristic approach that avoids solving any LP. We also examine a variation of the maximum flow problem having semicontinuous restrictions that requires the flow, if positive, on any path to be greater than or equal to a minimum threshold. To avoid solving a mixed-integer programming (MIP) model, we present a branch-and-price algorithm that significantly improves the computational time required to solve the problem. Finally, we study two dynamic network flow problems that arise in wireless sensor networks under non-simultaneous flow assumptions. We first consider a dynamic maximum flow problem that requires an arc to transmit a minimum amount of flow each time it begins transmission. We present an MIP for solving this problem along with a heuristic algorithm for its solution. Additionally, we study a dynamic minimum-cost flow problem, in which an additional cost is incurred each time an arc begins transmission. In addition to an MIP, we present an exact algorithm that iteratively solves a relaxed version of the MIP until an optimal solution is found

    Design of implicit routing protocols for large scale mobile wireless sensor networks

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    Strathclyde theses - ask staff. Thesis no. : T13189Most developments in wireless sensor networks (WSNs) routing protocols address static network scenarios. Schemes developed to manage mobility in other mobile networking implementations do not translate effectively to WSNs as the system design parameters are markedly different. Thus this research focuses on the issues of mobility and scalability in order to enable the full potential of WSNs to self-organise and co-operate and in so doing, meet the requirements of a rich mix of applications. In the goal of designing efficient, reliable routing protocols for large scale mobile WSN applications, this work lays the foundation by firstly presenting a strong case supported by extensive simulations, for the use of implicit connections. Then two novel implicit routing protocols - Virtual Grid Paging (VGP) and Virtual Zone Registration and Paging (VZRP) - that treat packet routing from node mobility and network scalability viewpoints are designed and analysed. Implicit routing exploits the connection availability and diversity in the underlying network to provide benefits such as fault tolerance, overhead control and improvement in QoS (Quality of Service) such as delay. Analysis and simulation results show that the proposed protocols guarantee significant improvement, delivering a more reliable, more efficient and better network performance compared with alternatives.Most developments in wireless sensor networks (WSNs) routing protocols address static network scenarios. Schemes developed to manage mobility in other mobile networking implementations do not translate effectively to WSNs as the system design parameters are markedly different. Thus this research focuses on the issues of mobility and scalability in order to enable the full potential of WSNs to self-organise and co-operate and in so doing, meet the requirements of a rich mix of applications. In the goal of designing efficient, reliable routing protocols for large scale mobile WSN applications, this work lays the foundation by firstly presenting a strong case supported by extensive simulations, for the use of implicit connections. Then two novel implicit routing protocols - Virtual Grid Paging (VGP) and Virtual Zone Registration and Paging (VZRP) - that treat packet routing from node mobility and network scalability viewpoints are designed and analysed. Implicit routing exploits the connection availability and diversity in the underlying network to provide benefits such as fault tolerance, overhead control and improvement in QoS (Quality of Service) such as delay. Analysis and simulation results show that the proposed protocols guarantee significant improvement, delivering a more reliable, more efficient and better network performance compared with alternatives

    Horizontal trajectory based mobile multi-sink routing in underwater sensor networks

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    Scientific, commercial, exploration, and monitoring applications of underwater sensor networks have drawn the attention of researchers toward the investigation of routing protocols that are robust, scalable, and energy efficient. This has brought significant research in network layer routing protocols. Irrespective of the field of application it is desirable to increase network lifetime by reducing energy consumed by sensor nodes in the network or by balancing energy in the entire network. Energy balancing refers to the uniform distribution of the network’s residual energy such that all nodes remain alive for a long time. It requires uniform energy consumption by each sensor node in the network instead of the same node being involved in every transmission. In this paper, we discuss two routing methods for three-dimensional environments in which the water region under monitor is divided into subregions of equal height and each subregion has a sink. Nodes in the subregion send data to the sink designated for that subregion. The first method called static multi-sink routing uses static sinks and the second method called horizontal trajectory-based mobile multi-sink routing (HT-MMR) uses mobile sinks with a horizontal trajectory. Simulation results show that the proposed HT-MMR reduces average energy consumption and average energy tax by 16.69% and 16.44% respectively. HT-MMR is energy efficient as it enhances network lifetime by 11.11%
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