Sensor Scheduling for Energy-Efficient Target Tracking in Sensor Networks

In this paper we study the problem of tracking an object moving randomly through a network of wireless sensors. Our objective is to devise strategies for scheduling the sensors to optimize the tradeoff between tracking performance and energy consumption. We cast the scheduling problem as a Partially Observable Markov Decision Process (POMDP), where the control actions correspond to the set of sensors to activate at each time step. Using a bottom-up approach, we consider different sensing, motion and cost models with increasing levels of difficulty. At the first level, the sensing regions of the different sensors do not overlap and the target is only observed within the sensing range of an active sensor. Then, we consider sensors with overlapping sensing range such that the tracking error, and hence the actions of the different sensors, are tightly coupled. Finally, we consider scenarios wherein the target locations and sensors' observations assume values on continuous spaces. Exact solutions are generally intractable even for the simplest models due to the dimensionality of the information and action spaces. Hence, we devise approximate solution techniques, and in some cases derive lower bounds on the optimal tradeoff curves. The generated scheduling policies, albeit suboptimal, often provide close-to-optimal energy-tracking tradeoffs

Energy management in communication networks: a journey through modelling and optimization glasses

The widespread proliferation of Internet and wireless applications has produced a significant increase of ICT energy footprint. As a response, in the last five years, significant efforts have been undertaken to include energy-awareness into network management. Several green networking frameworks have been proposed by carefully managing the network routing and the power state of network devices. Even though approaches proposed differ based on network technologies and sleep modes of nodes and interfaces, they all aim at tailoring the active network resources to the varying traffic needs in order to minimize energy consumption. From a modeling point of view, this has several commonalities with classical network design and routing problems, even if with different objectives and in a dynamic context. With most researchers focused on addressing the complex and crucial technological aspects of green networking schemes, there has been so far little attention on understanding the modeling similarities and differences of proposed solutions. This paper fills the gap surveying the literature with optimization modeling glasses, following a tutorial approach that guides through the different components of the models with a unified symbolism. A detailed classification of the previous work based on the modeling issues included is also proposed

Multi-Point Relaying Techniques with OSPF on Ad hoc Networks

International audienceIncorporating multi-hop ad hoc wireless networks in the IP infrastructure is an effort to which a growing community participates. One instance of such activity is the extension of the most widely deployed interior gateway routing protocol on the Internet, OSPF, for operation on MANETs. Such extension allows OSPF to work on heterogeneous networks encompassing both wired and wireless routers, which may self-organize as multi-hop wireless subnetworks, and be mobile. Three solutions have been proposed for this extension, among which two based on techniques derived from multi-point relaying (MPR). This paper analyzes these two approaches and identifies some fundamental discussion items that pertain to adapting OSPF mechanisms to multi-hop wireless networking, before concluding with a proposal for a unique, merged solution based on this analysis

A quantitative comparison of the cost of employing EOR-coupled CCS supplemented with secondary DSF storage for two large CO2 point sources

AbstractThis paper explores the impact of the temporally dynamic demand for CO2 for CCS-coupled EOR by evaluating the variable demand for new (i.e., non-recycled) anthropogenic CO2 within EOR projects and the extent to which EOR-coupled CCS is compatible with the need for baseload CO2 storage options for large anthropogenic point sources. A profile of CO2 demand over an assumed EOR project lifetime is applied across two different storage scenarios to illustrate the differences in cost associated with different EOR-coupled CCS configurations. The first scenario pairs a single EOR field with a DSF used to store any CO2 that is not used to increase oil recovery in the EOR field; the second scenario is designed to minimize storage in the DSF and maximize lower-cost EOR-based storage by bringing multiple EOR projects online over time as the previous project’s CO2 demand declines, making the source’s CO2 available for a subsequent project. Each scenario is evaluated for two facilities, emitting 3 and 6 MtCO2/y. Annual and lifetime average CO2 transport and storage costs are presented, and the impact of added capture and compression costs on overall project economics is examined.The research reported here suggests that the cost of implementing a CCS-coupled EOR project will be more than is typically assumed; in many cases a positive price on CO2 emitted to the atmosphere will be required to motivate deployment of these CO2-based EOR projects, except in the most idealized cases. The reasons for this conclusion are twofold. First, the costs of capitalizing, operating and monitoring a secondary DSF to provide backup storage for CO2 not demanded by the EOR operation can cut sharply into EOR revenues. Second, except in cases where a single firm figures both the CO2 source emissions and the associated EOR recovery on the same balance sheet, the oil production company is not likely to share a significant portion of revenues from the EOR field with the CO2 source. Thus, while EOR-coupled CCS may offer attractive early opportunities, these opportunities are likely only available to a small fraction of the CO2 source fleet in the U.S

Optimal Protection Coordination of Active Distribution Networks Powered by Synchronverters

The integration of distributed generators (DGs) into distribution networks leads to the emergence of active distribution networks (ADNs). These networks have advantages, such as deferring the network upgrade, lower power losses, reduced power generation cost, and lower greenhouse gas emission, DGs are classified due to their interface with the network as inverter-interfaced or synchronous-interfaced. However, DGs integration results in bidirectional power flow, higher fault current levels, deterioration of the protection coordination of the directional overcurrent relays (DOCRs) which are used in ADNs, reduced system stability due to the inverters’ lack of damping. The stability can be enhanced by controlling the inverters to behave as synchronous generators, which are known as synchronverters. In this thesis, a two-stage optimal protection coordination (OPC) scheme is proposed to guarantee reliable protection of ADNs while protecting synchronverters from overcurrent using virtual impedance fault current limiters (VI-FCLs). VI-FCLs provide a cost-effective way to protect synchronverters from overcurrent. The first stage integrates the fault current calculations of synchronverters in the fault analysis to find the parameters of VI-FCLs used to limit the synchronverter’s fault current. In the second stage, the fault current calculations, along with the designed VI-FCLs from the first stage, are employed to determine the optimal relays’ settings to minimize the total operating times for all the DOCR. It is found that fixed VI-FCLs can limit synchronverters’ fault currents but may make the OPC problem infeasible to solve. Thus, an adaptive VI-FCL is proposed to ensure a feasible OPC under various fault conditions, i.e., locations and resistances

Resource Allocation in Survivable WDM Networks Under a Sliding Scheduled Traffic Model

In recent years there has been an increasing number of applications that require periodic use of lightpaths at predefined time intervals, such as database backup and on-line classes. A new traffic model, referred to as the scheduled traffic model, has been proposed to handle such scheduled lightpath demands. In this thesis we present two new integer linear program ( ILP) formulations for the more general sliding scheduled traffic model, where the setup and teardown times may vary within a specified range. We consider both wavelength convertible networks and networks without wavelength conversion capability. Our ILP formulations jointly optimize the problem of scheduling the demands ( in time) and allocating resources for the scheduled lightpaths. Simulation results show that our formulations are able to generate optimal solutions for practical sized networks. For larger networks, we have proposed a fast two-step heuristic to solve the demand scheduling problem and the RWA problem separately

Transiency-driven Resource Management for Cloud Computing Platforms

Modern distributed server applications are hosted on enterprise or cloud data centers that provide computing, storage, and networking capabilities to these applications. These applications are built using the implicit assumption that the underlying servers will be stable and normally available, barring for occasional faults. In many emerging scenarios, however, data centers and clouds only provide transient, rather than continuous, availability of their servers. Transiency in modern distributed systems arises in many contexts, such as green data centers powered using renewable intermittent sources, and cloud platforms that provide lower-cost transient servers which can be unilaterally revoked by the cloud operator. Transient computing resources are increasingly important, and existing fault-tolerance and resource management techniques are inadequate for transient servers because applications typically assume continuous resource availability. This thesis presents research in distributed systems design that treats transiency as a first-class design principle. I show that combining transiency-specific fault-tolerance mechanisms with resource management policies to suit application characteristics and requirements, can yield significant cost and performance benefits. These mechanisms and policies have been implemented and prototyped as part of software systems, which allow a wide range of applications, such as interactive services and distributed data processing, to be deployed on transient servers, and can reduce cloud computing costs by up to 90\%. This thesis makes contributions to four areas of computer systems research: transiency-specific fault-tolerance, resource allocation, abstractions, and resource reclamation. For reducing the impact of transient server revocations, I develop two fault-tolerance techniques that are tailored to transient server characteristics and application requirements. For interactive applications, I build a derivative cloud platform that masks revocations by transparently moving application-state between servers of different types. Similarly, for distributed data processing applications, I investigate the use of application level periodic checkpointing to reduce the performance impact of server revocations. For managing and reducing the risk of server revocations, I investigate the use of server portfolios that allow transient resource allocation to be tailored to application requirements. Finally, I investigate how resource providers (such as cloud platforms) can provide transient resource availability without revocation, by looking into alternative resource reclamation techniques. I develop resource deflation, wherein a server\u27s resources are fractionally reclaimed, allowing the application to continue execution albeit with fewer resources. Resource deflation generalizes revocation, and the deflation mechanisms and cluster-wide policies can yield both high cluster utilization and low application performance degradation

Sixth Goddard Conference on Mass Storage Systems and Technologies Held in Cooperation with the Fifteenth IEEE Symposium on Mass Storage Systems

This document contains copies of those technical papers received in time for publication prior to the Sixth Goddard Conference on Mass Storage Systems and Technologies which is being held in cooperation with the Fifteenth IEEE Symposium on Mass Storage Systems at the University of Maryland-University College Inn and Conference Center March 23-26, 1998. As one of an ongoing series, this Conference continues to provide a forum for discussion of issues relevant to the management of large volumes of data. The Conference encourages all interested organizations to discuss long term mass storage requirements and experiences in fielding solutions. Emphasis is on current and future practical solutions addressing issues in data management, storage systems and media, data acquisition, long term retention of data, and data distribution. This year's discussion topics include architecture, tape optimization, new technology, performance, standards, site reports, vendor solutions. Tutorials will be available on shared file systems, file system backups, data mining, and the dynamics of obsolescence